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Why self-driving isn’t just for cars

The beauty of self-driving cars is that they take you where you want to go while you sit back and enjoy the ride, or use the time to work on other things. Meanwhile, the car’s systems are speaking to each other behind the scenes, ensuring you avoid obstacles, observe all the necessary traffic laws, and take the shortest path to your destination. Connected enterprises are now moving in the same direction. Powered by autonomous technologies, systems and applications speak with each other to manage everyday tasks while employees are left to focus on higher-value work. We are quickly moving towards the era where an organization’s systems are self-driving in their own right. Instead of spending resources managing databases, reconciling sheets, building queries or waiting for data to update, teams will be able to “take their hands of the wheel” and support other lines of business with strategic endeavors. What does this look like in practice? It’s a fair question in these early days of autonomous technology. Here is a sneak peek at the business of the future, including one example of a company that has already adopted autonomous systems to pull ahead of the competition. Optimizing your path Just like traffic is a headache while driving, bottlenecks are the ultimate time-waster for businesses. Whether it’s disjointed processes, a lack of alignment between teams, or simply the need to manually reconcile endless spreadsheets, even the smallest inefficiency can lead to significant costs and time wasted. Especially as more businesses rely on data collection and analysis to inform their operations. Today, the increasingly powerful mix of AI, cloud-based systems, and powerful computing capabilities have made machines capable of taking on tasks that were previously impossible without human involvement. Machine-learning algorithms can make judgment calls, sense people’s emotions, and apply common sense to their decision-making. Meanwhile, businesses operating in the autonomous cloud have live access to data from all the other databases running on the same platform, providing them with more insight to help streamline their operation. In the case of Agea, one of Argentina’s leading media companies, the Oracle Autonomous Data Warehouse has allowed the organization to drastically reduce the burden of hardware and software maintenance. Instead of having to interrupt its operations each time, Agea has left its database maintenance to Oracle, which means its IT and business teams can shift their attention to new business opportunities, by spending more time and resource on actual analysis. Pre-empting roadblocks All self-driving cars use some form of automated GPS to navigate roads. Similarly, autonomous systems will help businesses to navigate unfamiliar territory. Whether they are looking to expand into new markets or launch a new product or service, the autonomous enterprise will make the best possible decisions about how to proceed based on historical data, current activity across the organization, and how the market is likely to evolve. This goes beyond simply learning from the past to make a best-possible guess about the future. It’s about continuously collecting data, analyzing it, and refining the entire business’ path based on real-time conditions. In other words, it’s like having Waze or Google Maps integrated at all levels of decision-making so that you minimize your chance of running into roadblocks. Safety first One of the major selling points of self-driving cars is that they’re expected to be safer. Even if there have been some incidents with autonomous vehicles to date, human error remains the primary cause of automobile accidents. The same goes for businesses. By some estimates, more than half of data breaches in large companies are down to human error. Often, the breaches are not intentional, which makes them even harder to spot or address in time. Machine-learning algorithms embedded in the autonomous enterprise will become increasingly powerful and knowledgeable about how to identify threats, alerting the business of potential issues more quickly even as hackers’ methods become more advanced. These features of autonomous systems are also invaluable from a compliance standpoint, particularly in the age of GDPR and with governments doubling down on data protection regulation. Businesses will only collect more information through more channels, making the job of managing and tracking all this data increasingly complex. No human being can handle the task, and even the need to constantly patch and update systems means companies are playing catch-up rather than pre-empting the threat. Autonomous systems running on the cloud bring all of the organization’s systems and data together onto a central platform, so that information is visible across teams at all times. All of this brings us back to one of the biggest benefits today’s autonomous transformation, which is that with their hands off the wheel of their software, business users can take their eyes off road and look for new avenues for growth. Agility is one of the hallmarks of a successful organization in the digital age, as is the ability to change directions quickly. With autonomous databases ensuring that real time and trustworthy data is available, employees can confidently spend more time exploring alternate routes to differentiation. This final point is crucial. Speed will always be essential in a cutthroat market, but there will only be more companies racing each other to deliver their products and services and win customers’ attention. This focus on being comes at the expense of innovation and differentiation, which is what customers crave. The beauty of the autonomous enterprise is that it will be able to move quickly and confidently, while also being ready at any given moment to take the road less travelled and set itself apart.  

The beauty of self-driving cars is that they take you where you want to go while you sit back and enjoy the ride, or use the time to work on other things. Meanwhile, the car’s systems are speaking to...


How Does the Data Economy Drive the Experience Economy?

The term ‘Experience Economy’ was actually coined way back in 1998. B. Joseph Pine II and James H. Gilmore needed a way to describe the shift from selling products and services to creating memorable events for customers. But it would be twenty years before the Experience Economy really took off. Why? Because people now expect personalised experiences, thanks to the growth of the digital world. And it’s only recently that marketers have gained the data and computing power to deliver them. Just 10 years ago, the success of Spotify, Netflix and other service-based businesses wasn’t possible. These companies haven’t rocketed to success because they offer something new –music and video streaming has been around for years. What they have done is set themselves apart by delivering an experience built entirely around customer understanding. If personalised experiences are about connecting data, then data is the building block of the Experience Economy. Many marketing leaders are gaining an edge over the competition by harnessing data and using it to find new, innovative ways to appeal to their audience.   Personalisation is the new normal Marketers are rethinking the way they measure success. KPIs are shifting from short-term objectives (like reach) to long term goals, like customer satisfaction and retention. Data quality is important too, as the best customer experiences are often built on reliable, real-time information, shared smoothly between different systems. The Economist gives us a good example of this. The publication adopted Oracle Marketing Cloud to shift from mass communication to more tailored, one-to-one interactions. It used data to personalise the customer experience across channels, managing to increase its brand awareness by 64% in the US – and its consideration by 22% in both the US and UK.  Meanwhile, in India, Adidas is using customer data to deliver great cross-channel campaigns. Using Marketing Cloud, the sports heavyweight now has more consistency across its marketing channels, helping it to better engage with audiences no matter the channel they use. The journey is worth the effort These companies are already taking a data-driven approach to thrive in the Experience Economy. But many are just getting started. Plenty of marketers know they need to use data to improve their campaigns, but the volume and variety of data they collect is daunting. Plus they may have old systems and growing pressure to deliver on multiple fronts at the same time. They don’t feel they have the time or capabilities to take advantage of the goldmine they know they’re sitting on. Putting an innovation strategy in place can be an ideal starting point. Those companies that do tend to see a spike in their ability to innovate and delight customers. Our research reveals that 68% of marketing decision-makers say disruptive innovation – including enhancements to the customer experience – plays a significant role in their organisation. And of these, 69% report significant or strong growth. We’ve seen a clear correlation between data-driven approaches and customer success. Of course, that doesn’t mean it’s easy to create an environment where data and innovation work together for better customer experiences. But those businesses that take up the challenge can quickly set themselves apart. Read our report to learn more about how data is fuelling today’s Experience Economy, and see how an innovation strategy can help you thrive in the era of mass personalisation.

The term ‘Experience Economy’ was actually coinedway back in 1998. B. Joseph Pine II and James H. Gilmore needed a way to describe the shift from selling products and services to creating memorable...


The 5 key traits of a future-ready Finance Leader

Finance has always taken advantage of technology to improve productivity and collaboration. But with continuous innovation now driving our economy, the goalposts have moved. Today’s organizations must adopt an agile finance operating model— powered by emerging digital technologies and skillsets. The success of that model depends on 5 keys traits that the Finance Team must possess. When Oracle and the Association of International Certified Professional Accountants (AICPA) decided to follow up our look at the best finance organizations, we already knew that agile finance functions were taking advantage of cloud technologies to improve efficiency; centralize process management and subject matter expertise; make greater use of analytics to contribute insights; and deploy multi-disciplinary teams to partner with decision makers. Talking to both agile finance pioneers and those in less-advanced organizations for the new report, Agile Finance Unleashed, we discovered even deeper links between successful business and digital finance transformation. And the conversations with CFOs successfully delivering operational excellence and strategic influence using digital intelligence led to five conclusions about what makes for effective, future-ready finance leaders. They take a customer-first, holistic approach to organizational change. Rather than focus on optimizing or improving standalone business processes, look at optimizing the end-to-end customer and employee experiences, based on the customer value they will create. One of the starkest differences between leaders and laggards in the Agile Finance Unleashed report was around customers: 83% of Digital Finance Leaders say their organization is quick to meet customers’ fast-changing technology expectations, but this drops to 28% for the non-leaders. Empowerment is critical. The end-state of any transformation should be a workforce that instinctively prioritizes customer experience; and has the tools to deliver that experience using solutions from across the whole organization. This isn’t just about FMCG brands or technology services. Take Kansas City Power & Light. The utility business model is simple, but faced with regulatory evolution and raised customer expectations, it realized it needed to change. Building an integrated customer information system (CIS) allowed the teams there to take a holistic view of each of its 830,000 customers and refine its approach to problem solving, customer support – where teams had previously had to wrestle with more than 20 disparate systems – and efficiency. They focus on platforms, not products. In today’s economy, it’s no longer about products, but experiences and digital ecosystems that bring users and providers together to create shared value. It’s no coincidence that the world’s most valuable companies right now are built around platforms. Apple, for example, established itself through products. But the journey from Mac to iPod to iPhone was really about the development of a customer-oriented ecosystem – a platform that allows the company to sell additional services and complementary products and services. Platforms are a natural extension of a customer-focused approach to change. It’s about optimizing the wider experience, not securing a one-time transaction. For agile finance leaders, that means understanding and analyzing the true value of customers; and being able to spot and evaluate M&A opportunities in complementary business areas for the customer. They use data as a strategic asset. Digital leaders place an economic value on data and look to monetize it versus just managing it. Silicon Valley VC Mary Meeker summed up this priority in her 2019 Internet Trends Report. At the starts of the web era, she says, winning businesses used digital data and insights – not just what they knew about people – to improve customer experiences. Over the past 15 years, winning businesses realized they must use ‘data plumbing tools’ to collect, manage and optimize data to the same end. Agile finance requires that the first two are done better – faster, more cheaply and more thoroughly. But optimizing the use of data and finding insights from the fire hydrant of outputs is now a must. And for true future-ready finance leaders, that also means looking outside the traditional skill-sets in their teams – from awareness of new technologies, to skills in data science and advanced analytics. Worryingly, in the Agile Finance Unleashed report, only one in ten CFOs said their “finance team has the skills it needs to support the organization’s digital ambitions.” They foster a change-ready culture. Adopt an agile approach to change that is iterative, empirical, and continuously improving. Businesses that are highly motivated to change and experiment are the ones that see the greatest success. That’s true even in very traditional, highly ‘physical’ businesses where capital-intensive investment in fixed assets has long been the key differentiator. DP World, for example, is the world’s fourth largest ports operator – not an obvious type of business that would need to embrace agility. But for CEO Sultan Ahmed bin Sulayem, investment to facilitate digital transformation is critical. “Employing cloud applications that can increase efficiency, create new services and support diversification will add value for all our stakeholders and aid our vision to become a digitized global trade enabler,” he says. “In this dynamic digital age, it’s essential that we keep up with our customers’ growing needs. As global trade becomes increasingly digitalized, our stakeholders also require agile tech infrastructure that can integrate quickly and seamlessly.” They secure a top-down, executive mandate. To radically change your culture, you need more than just management buy-in; you need an executive mandate to adopt a customer-first approach to business that permeates every organizational function. Legacy systems and processes stymie change. Future-ready finance is all about delivering a 360-degree view of the organization, but that’s impossible when data is locked in silos, information flows slowly and teams can’t collaborate. The Agile Finance Unleashed report revealed that 37% of CFOs spend more time collecting data than analyzing it, with 59% of large organizations saying that “difficulty extracting data from legacy platforms” is a major challenge.” This cannot change if a team or business unit decides to undertake a transformation project in isolation. That’s one reason why it’s so important that executive leadership doesn’t just support whole-organization digital transformation – it must evangelize it. True commitment to customer-oriented change needs to be driven from the very top – the CEO, but especially the CFO who is usually in the best position to see how the transformation ripples through the business and can both set its objectives and measure its effects. A Digital Finance Leader is one who deploys an agile model that can meet the continuous need for innovation in their organization – and is able to build and support the platforms essential to guide strategic decisions using insightful analysis based on reliable, 360-degree data on customers.  

Finance has always taken advantage of technology to improve productivity and collaboration. But with continuous innovation now driving our economy, the goalposts have moved. Today’s organizations must...


Why Successful Companies are Data Leaders

Research shows that connected data and a successful company are directly related: Those organisations that have seen significant revenue growth (20%+) in their organisation over the last three years are more likely to have completed data protection initiatives, connected systems initiatives, or intelligent automation initiatives, than those organisations that have witnessed a decline in that same time. As we all know, when it comes to connecting systems and therefore data, the buck stops at IT - although functions have their role to play. This insight gives IT the opportunity to correlate the success of their infrastructure and policies directly with the success of a company, thereby widening ITs role and accountability. It’s amazing what you can retrieve from the correct collaboration of data sources when you ask the right questions or join the correct dots so to speak. We produce so much data (and differing types), it’s a wonder we haven’t started ecological campaigns to reduce the data build up within our digital oceans for the good of all - digital data recycling - now, there’s a concept! We saw the rise of Big Data initiatives nearly a decade ago, which formed the precursor to AI and query-based predictive analytics that we know today. Although we create a staggering amount of disparate data, what exactly is generated, what do we really do with it and - more importantly from a business outcome point of view – what should you be focusing on to not just keep up with your business peers pouring good money after bad but to demonstrate value to the business? There are key initiatives that Data Leaders are forging ahead with now and recent analysis from Oracle has produced some very interesting statistics based upon the study of some of the data oceans that businesses have created, and where the Data Leaders and Data Laggards are on this sustainable data initiative for business growth. Highlighted within these statistics are meaningful ROI statistics that are drawn from real respondents of the analysis. Successful enterprises are data leaders: they do things differently and get better results and IT data leaders are 10 times more likely to feel confident in managing systems data than data laggards. Highlighted below are some of the generated statistics that demonstrate Data Leaders against Data Laggards in respect to their ability to manage their digital rivers for 5 areas of data creation: As you can see, the data laggards are simply not coping with the data growth! All roads lead to the IT department’s responsibility when discussing data and the management of, and this will only become more so with key strategic drivers on the board room table requiring more attention than ever to not just be about staying in the game but ahead of it!  This is where the Data Leaders focus is key and where the differentiator lies. If we drill down further look at more detail you can see why with more detailed responses highlighted later and where their priorities are prominent and which paid the most returns in respect to business growth. It’s not often you can relate business growth directly back to technical initiatives which makes the following insights valuable for IT Divisions looking to embark upon their digital strategies. As we all know this responsibility is with the IT Department and any proof points that demonstrate Correct Technical Initiative = Business Growth is welcome. So what are the key takeaways that can be derived from this information? Data Protection/Management/Security/Automation are key drivers for business growth for the leading organisations that have shown major growth over the last 3 years period! Moving more to an Autonomous state of being in respect to your IT estate is a critical capability for delivering complete insight and automating process – and business leaders can see it - 47% of organisations who have seen significant growth have completed intelligent automation initiatives, compared to 23% of those with marginal growth. It’s no surprise that solid analytics with cognitive abilities can demonstrate great returns for your technical investment, but if you link RPA, Data Protection and Management together with robust Security, you have a winning combination of IT services that provide amazing business growth. We all know many of the mainstream IT Strategies around today but they are here for good reason. Oracle have been evangelising about Adaptive Intelligence and Autonomous Databases for some time now and it seems to me that it’s easy to see why. The Autonomous Technologies they have invested heavily in are paying off for data leaders around the globe. I was fortunate enough to hear from Mark Hurd, Oracle CEO, when Mark presented his future vision of business growth with Autonomous products: Self-healing/patching databases that require less administration, less downtime together with rigid security that’s scalable. Organisations who have seen significant growth are twice as likely to have completed intelligent automation initiatives as those with marginal growth. The advantages of employing these initiatives are easy to see but at the time it seemed slightly farfetched, however having seen the statistics here and the strategy presented then, it’s a reality. Oracle, in my opinion, has been the sleeping dragon in the race for technology supremacy, watching, waiting and calculating the correct move to make. However, with the ever-increasing workloads together with the creation of industry data oceans we all have to swim in – doesn’t it make sense to automate, manage and secure effectively to allow for scale whilst requiring less administration, and resources? This does not necessarily mean removing the manpower and staff base from the IT Department, more like working smarter and more efficiently and not managing the huge amounts of data created across IT Systems that will get out of control as the statistics suggest. If you put this together with the recent Microsoft partnership too, there’s a lot of innovation coming out of Oracle and I’m looking forward to seeing further advancements that Oracle have in store.

Research shows that connected data and a successful company are directly related: Those organisations that have seen significant revenue growth (20%+) in their organisation over the last three years...


3 Steps to Connect Customer Experience

Good data makes marketers smile, but managing that data can send a chill down the spine. Many of us see it as complicated, perhaps something that stifles creativity. But it’s also the foundation of a 360-degree customer view. And without that, marketers have little chance of delivering the personalised experiences their audience expects. Customers expect frictionless experiences, on any and all platforms, while businesses need to meet the highest levels of governance and transparency. So an excellent Customer Experience now goes beyond the customer service team. Or the sales team. Or the marketing team. Data has become the domain of every department. And delivering the best customer experience possible depends on it being clean, connected and constantly updated. Step 1: Clean your data Less duplication and disorder in your data means less information to manage and less time spent managing it. Which in turn means marketers can focus on the customer experience itself. But it’s essential for governance too. How can you guarantee customer information is in safe hands if you don’t have sight of it across the business? And how can you ensure proper governance if you can’t see all the data you’re collecting? Honestly, we only expect data privacy fines to grow, so this is an issue that’s better addressed sooner rather than later. This brings us to the main question: how to clean data quickly and effectively. Preparing and cleansing data manually doesn’t really fit the scale and speed you want (and need) in your marketing department. But Artificial Intelligence and Machine Learning could help here. Gartner predicts that ML in particular will take on 40-45% of manual data tasks by 2022. And for many companies, cleaning data will be one of those tasks. Step 2: Connect your data Good customer experiences aren’t one-way, one-off transactions – they obviously haven’t been for some time now. They’re mobile and fluid, as customers interact with companies across platforms as and when they choose. But the number of systems we need to deliver these improved services has steadily grown, leading to silos of data. And those silos can stand in the way of the frictionless experiences customers are looking for. World class brands are responding by centralising their data. An open flow of information between teams can help with building equally seamless experiences for their customers. Take Meliá Hotels. The Spanish hospitality leader recently unveiled a new service, allowing customers to use an electronic bracelet as their room key and a digital wallet across its resorts. And while this service relies on simple Bluetooth technology, it’s the integration of data behind the scenes that makes it all possible. Step 3: Make your data real-time You may have connected your systems and automated data management, but is the data constantly refreshed? You want to learn, but also to adapt and evolve quickly, based on changing needs. And this is as much a mindset as a technical requirement. Most of us want to be more dynamic in our responses to customers. We want to respond quickly to market demands. And that means recognising and reacting to the fact that data is constantly growing and evolving. By enriching our customer profiles with real-time context, we can have better insights and deliver more personalised experiences at the exact moment when they matter most: right now. Each of these elements is made easier by a more intelligent, cloud-based system. It’s one thing to move data to a new infrastructure, but it’s another to use a data warehouse that actively monitors, detects, and repairs itself, to deliver the level of security you really need. In other words, an autonomous system. These allow companies to spend less time managing data, and more time doing what matters most – giving customers what they want. After all, the future of data management shouldn’t be about more admin. Instead, you could work in a more integrated way, and differentiate your business.

Good data makes marketers smile, but managing that data can send a chill down the spine. Many of us see it as complicated, perhaps something that stifles creativity. But it’s also the foundation of a...


From Counting herds to Herding Data?

An evolution of the database, from counting crops to self-driving systems   It was roughly 7000 years ago that Mesopotamians began tracking the yield of their crops, effectively becoming our first data analysts. Today, companies record and manage data in all shapes and sizes, drawing insight from it to work smarter and better serve their customers. The principles have remained the same for millennia, but the rise of AI and autonomous systems have unlocked a new world of opportunity in the zettabytes of information we collect. How did we get here? How did we get from counting crops, to storing huge volumes of information, to self-driving, self-managing systems? Let’s take a trip down database memory lane: 5000 BC – Farmers in Mesopotamia begin to track the size of their herds and record their crop yields, giving rise to early accounting principles and written language. 17th century – John Graunt, widely regarded as the father modern statistics, releases the first European writing on the topic, Natural and Political Observations upon the Bills of Mortality Late 19th century – Herman Hollerith invents the first tabulating machine, used to process data for the 1890 US Census. The machine was subsequently adapted by businesses for accounting and inventory control 1980s – Businesses begin looking for ways to store, track, and understand the data they collect, and begin to analyze the information at their disposal to inform their activities   1990s – Enterprise software becomes powerful enough to support predictive analysis. For the first time, businesses can take a scientific approach to planning and strategizing for the future 2001 – Gartner Analyst Doug Laney outlines the challenges of managing the 3 “Vs” of data – volume, variety and velocity. He argues that all three parameters are expanding, and that simple storage is no longer enough 2008 – Oracle introduces Engineered Systems, giving rise to lightning fast autonomous infrastructure at the same time as companies start to adopt cloud computing on a large scale. Suddenly, IT departments don’t have to hand-build infrastructure piece by piece using disparate solutions from multiple vendors 2012– Artificial Intelligence (AI) enters the mainstream. Companies begin using algorithms to run complex computations on millions of data points in real-time, automating more elements of their operation and changing the way they serve customers 2018 – Understanding that to capitalize on AI, cloud-based systems must be able operate autonomously, Oracle launches the Oracle Autonomous Database, defining a new category of IT. The self-driving, self-securing, and self-repairing system requires no manual intervention. The Future is Autonomous We’ve come a long way from counting crops and cattle. The days of simply storing information have given way to a digital era, where computer intelligence is baked directly into the data we collect from a growing range of sources. The groundwork is now being laid for businesses to become full autonomous, with every system and process able to manage, update, repair and secure itself. Just as cloud computing took the datacenter from CAPEX to OPEX, autonomous systems promise to help users do even more with their data, while putting in less effort and costs. This doesn’t mean people will have no place in the companies of tomorrow. In fact, as our research  suggests, with machines taking on more administrative tasks, employees will be able to dedicate more time and energy to using data strategically, which is where they add the most value. The Oracle Autonomous Database marks just the beginning of our autonomous future. Inspired by rising customer demand, including 5000 trials in the final quarter of FY19, we have now taken a major leap forward with the launch of the Oracle Autonomous Database Dedicated service. Using this service, customers can easily move from manually operated on-premise databases to a fully-autonomous and private database, hosted in the Oracle Cloud.  Join us at our events to learn more, and discover what the future holds for autonomous systems.

An evolution of the database, from counting crops to self-driving systems   It was roughly 7000 years ago that Mesopotamians began tracking the yield of their crops, effectively becoming our first data...


Revealing Tomorrow’s Supply Chain

By 2023, at least half of large global companies will be using advanced analytics, artificial intelligence (AI) and Internet of Things (IoT) in their supply chains. That’s a scary number if you’re not one of them. But to efficiently and smoothly answer demanding customers, those technologies are not only a necessity, they also enable true versatility. Instead of struggling to bridge functions that are seemingly always rigid and disconnected, automation and other technologies are providing connections and coherence so that staff can focus on innovation. But it’s business priorities that are driving adoption of these technologies.In the 1990s, most organizations’ focus was inside-out – making their own logistics more efficient. Now it’s outside-in, to flex around the customer, whether it’s a consumer or a B2B transaction. They want to understand what drives the various segments of their customer base and design supply chains accordingly. That’s not to say the hunt for internal efficiency isn’t still important. Far from it: if organizations want supply chains to be adaptable to changing customer behaviors, they need to move away from rigid, disconnected processes to an agile, connected, automated approach that also drives out cost. These must also integrate with functions such as finance (to give CFO visibility on performance and allow for strategic planning), marketing (to forecast and shape demand), operations and more. This is where an end-to-end supply chain management (SCM) solution comes in. And underpinning its effectiveness should be the cloud. On-premises solutions are much harder to integrate across functions, locations and supply chain partners. They also create more barriers to use of the emerging technologies reshaping transparent, agile and efficient supply chains. Here are three forces that make cloud-based supply chain transformation so compelling right now: Customers, robots and globalization The first is the fact that modern customers have different expectations than they did before the e-commerce era. Whether they’re buying online or ordering in bricks-and-mortar stores, consumers have come to expect they will be able to buy what they want, when they want it, in the quantities they need, no matter how or where the order is placed.  According to Kibo’s 2018 Consumer Trends Report, 40% of shoppers say taking more than two days for delivery would prevent them from making a purchase, while 63% expect delivery within three days as the standard. UPS’s research paints an even tougher picture: 64% of online shoppers it interviewed expect orders before 5pm to qualify for next-day delivery. To serve customers across multiple channels and fulfill orders quickly, supply chains need to be agile enough to change, as well as digitally connected from end-to-end.  For example, if a customer places an order online, the retailer must quickly determine how to fulfill the order. This means locating inventory – which could be in a distribution center or retail store hundreds of miles from the customer – and knowing exactly how picking, packing and shipment will execute so they can tell the customer when it will arrive. Connected applications, such as order management, inventory and logistics, provide that level of visibility and agility. Secondly, automation is changing the game. The first wave of automation dates back 15 years or more, and was about replacing expensive resources with software agents and robots. The current wave is about developing resource that isn’t there – new capabilities that actually transform key processes in the supply chain. We’re still some years away from fully automated delivery trucks and last-mile drones. But cutting edge solutions are already revolutionizing warehouse robotics; and customer chatbots are shifting automation at the front end. It’s reckoned about 85% of companies’ interactions with their customers will be automated eventually. But even in less futuristic settings, automation is taking on manual transaction processes as AI and machine learning become commoditized. For example, warehouse automation enables cost-effective fulfilment of highly variable orders by reducing errors and speeding up the fulfilment process, making personal service at-scale possible. The results could impress even the most demanding CFO. Brazilian footwear retailer Paqueta, for example, reduced inventory levels 25% in one year after rolling out more integrated merchandise planning systems. But to optimize this level of automation, partners up and down the supply chain must be able to communicate in real time – something that on-premises SCM systems struggle to support. There also needs to be a huge focus on developing insight from data – one commodity that supply chains already generate in huge quantities. That data flow will become much bigger as the Internet of Things raises supply chain connectivity to a new level. The third trend affecting supply chains is the need to extend them across geographic locations. Again, while this trend has been visible for some time through globalization and specialization, the constant evolution of external factors and new customer demands makes it ripe for transformation using hyper-connected digital services. And while managing global operations has always been incredibly complex, the finer tolerances of modern supply chains and need for agility is making it more so. Regulatory changes are constant, as is political instability, together with fluctuating market factors such as monetary exchange rates, raw material shortages and rising oil prices. Regulators expect proper customs documentation to be prepared and tariffs to be paid, while customers expect sellers to meet their requirements regardless of unplanned supply chain disruptions. On-premises applications don’t support the necessary ability to dynamically reconfigure processes or achieve comprehensive visibility and granular control of global inventory. They also lack predictive analytics that use technologies like AI to model multiple logistics scenarios, so businesses can effectively adapt to unexpected disruptions. Cloud solutions: Consolidated planning, visibility and control The bottom line is that integrated, end-to-end cloud solutions can make supply chains faster and smarter, as well as more agile. They’re much more resilient and adaptive because planning, visibility, and control are integrated instead of operating in isolation. And cloud makes it easy to scale by adding new users, creating new value chains – and innovating with technologies as they emerge. We’re now starting to see practical applications of blockchain, with for example, CargoSmart  developing intelligent track-and-trace in shipping to slash time spent on paperwork by 65%. IoT adoption is also reaching critical mass. Cloud-based systems and IoT sensor data can create virtual representations of the physical world to track shipments, monitor the condition of sensitive cargo or even check on the quality of baked products rolling off a production line. Crucially, you don’t need to be a data scientist or an IT specialist to exploit these capabilities. Many are embedded in the applications themselves – and with cloud based systems, new reporting capabilities or tools to support faster, better decision-making can be rolled out painlessly. Whether it’s evolving customer demands, the need to explore game-changing automation technology or the hunt for global growth, cloud-based SCM systems have become a compelling solution.  

By 2023, at least half of large global companies will be using advanced analytics, artificial intelligence (AI) and Internet of Things (IoT) in their supply chains. That’s a scary number if you’re not...


You can’t fake it til you make it.

When it comes to crucial Finance data, there is no way to “fake it ‘til you make it”. A bit of swagger might help your sales team land a deal, but it doesn’t get products or services delivered to your customers on time. Accurate information is the bread and butter of a successful organization, but our research reveals companies are still not investing in the tools or skills to manage their data effectively. This lack of confidence in the accuracy, safety, and management of information has ripple effects across every department, impacting their ability to deliver on strategic objectives. Just 34% of Finance professionals believe their data is completely manageable, according to Oracle research, This should be a sobering statistic for any business leader, particularly as data plays a growing role in how their company operates. According to Accenture, 77% of CFOs say it is their responsibility to drive company-wide transformation, and a similar percentage expect they will play a growing role in driving their organization’s digital initiatives. How can they deliver on this expectation when less than half feel confident in their ability to manage data? The imperative to get more strategic with data goes beyond driving growth. According to consulting firm RSM, the UK’s Financial Conduct Authority recorded 819 cyber-crime incidents in 2018, a thousand percent increase from 2017. Even taking into account the added attention governments have dedicated to detecting cyber threats these past years, it’s clear that data security will only become a bigger concern, and that attacks will become more complex. With so much to gain from effective data management, what’s standing in the way for so many organizations? The issue is less down to quantity as it is to quality. Most modern finance systems can handle large volumes of information, but when talking about the deluge of data today, we are referring to the challenge of turning relevant information into valuable insight quickly.   A company-wide data strategy One of the biggest barriers to getting a grip on data is a lack of clarity over who is responsible for managing it in the first place. From Finance, to HR, to Marketing teams, less than half of respondents to Oracle’s survey say they are accountable for their data. In most companies, the task still falls to the IT department. This approach is not only outdated, it is detrimental to a business’s success.   The concept of a company-wide data strategy is still quite new, especially in established organizations that have been operating under a siloed model for decades. As a result, key departments are not accepting responsibility for managing their data, even as it becomes more integral to their daily operations. To catch up with reality, companies need to adopt a common data protocol running across their organization. This is the key to gaining the elusive “single source of truth” that has become so crucial to business success. Shared accountability and an open flow of information between departments will only grow in importance as companies adopt technologies like Artificial Intelligence (AI), Machine Learning, and Blockchain to enhance their services. These innovations are all fuelled by data, and the quality of their output is directly proportional to the quality of information that is fed into them. The same goes for automation and autonomous systems, which are extremely attractive to Finance and Supply Chain leaders who want to reduce their team’s administrative burden and dedicate more time to the supporting the company’s strategic priorities. Autonomous systems have already delivered major improvements in terms of time and cost-savings for a number of business, but underlying each of these success stories is a unified approach to data management and a clear innovation strategy. Bringing structure to innovation It’s worth emphasizing the importance of an innovation strategy. Just as many businesses struggle to bring structure to their data management, they also need more vigour in their approach to innovation. It’s not enough to invest in new technologies and expect improvement; companies need a clear path and processes to innovate successfully, one that is built on the ability to track, measure, and manage data. This is easier said than done, and it would be naïve to say the journey is not without its challenges. But it also pays off for businesses that get the process right. Companies with an innovation strategy in place are more likely to get new products and services out to market successfully. Take Arcadis, one of the world’s leading design and consultancy firms for natural and built assets. The company employs 27,000 people in more than 70 countries and generates €3.3 billion in revenues, but to adapt to evolving needs within its organization, Arcadis realized it needed to streamline its front and back office processes. As part of a wider digital transformation initiative called The Arcadis Way¸ the firm adopted a suite of Oracle Cloud solutions to harmonize its global operation and gain more insight from its data. As Arcadis CIO, Gerard Sans, points out, the company’s aim is to have its 27,000 people working in a systematic way with clients around the world. “That is only possible if we have a uniform and easy-to-manage backbone across our organization,” he says. “The suite of Oracle Cloud services provides us with insight into our data and business performance required to optimize and integrate our critical business processes”. Niall Dore, CFO of Red Group sings a similar tune. For him, getting more value from data comes down to three focus areas: process improvement through machine learning, training teams to extract value from data, and using this information in real-time to make critical business decisions. Crucially, the foundation for all these strategies is a robust approach to data management behind the scenes. The business of tomorrow is built on trust, not just from customers but also internally. Finance leaders need to trust they are making decisions based on accurate information, and that begins by turning data management from a burden into a strategic differentiator.  

When it comes to crucial Finance data, there is no way to “fake it ‘til you make it”. A bit of swagger might help your sales team land a deal, but it doesn’t get products or services delivered to your...


The future is ready, is your CV?

Change is good, but it also makes us anxious. This is especially true when a new technology promises to revolutionize the way we work. We marvel at the possibilities of AI and autonomous systems, but our excitement is tempered by the angst of uncertainty – how will these developments affect our jobs and way of life? Autonomous technologies are not the enemy, they’re just very powerful tools. When used to drive genuine progress, they may bring about the revolution businesses have been asking for. The need to work faster, meet growing demand, and differentiate has always driven companies to enhance their performance with machines. From first farmers who used a mechanical plough, to Richard Arkwright’s invention of the water-powered mill, to Alan Turing’s cracking of the Enigma code, technology has been a powerful ally. And while these innovations have disrupted the job market, new roles and industry segments have been created in the long run, making our society more prosperous as a whole. Today, AI and automation are driving a new transformation. The step change in productivity is unlike anything we’ve ever seen, and the new skills we are developing to manage these technologies are up-levelling the workforce at an incredible pace, creating new forms of employment and changing the dynamic between traditional lines of business.   Man and machine working side-by-side The autonomous enterprise is not devoid of humanity. On the contrary, as our research suggests, it is a place where machines take the robotic elements out of work so employees can operate at the highest level intellectually and emotionally. Consider the following example – a day in the life of an autonomous enterprise employee: Jill, a sales team leader at a major company, arrives at work in the morning. Her emails are sorted in order of priority, while her spam has been moved to the trash folder. Some emails have even been answered automatically, with previously registered responses. That’s at least one hour of admin eliminated. Next, Jill opens a live dashboard of her customers’ details, organized based on her most recent activity with important files proactively highlighted for her attention and suggestions provided for the next best course of action. Rather than digging manually for answers to a customer issue, Jill can simply take on the recommendations provided by the autonomous system. Less time spent on process means more time spent creating value for her customers. Because the data is live, the marketing team has been advised that Jill’s customers are now in a place where they are open to receiving targeted marketing materials on the company’s latest offering, thus supporting Jill’s efforts. While she’s reviewing her customers’ orders, she gets a proactive notification from the system indicating there is a discrepancy between an invoice and the matching payment, with possible explanations for the change and how it could impact the client’s portfolio. Finance has been notified in parallel and have already seen the potential impact on forecasted revenue. If one of Jill’s meetings overrun, the autonomous system proactively attempts to reschedule subsequent appointments based on her availability. Ahead of each commitment, it pulls out recent articles and information that might be of interest to each customer, while also reminding her of important responsibilities like employee reviews. With Jill’s team so busy, the autonomous enterprise takes the liberty of suggesting a bonding session to boost morale, with a couple of dates where her whole team is available. In short, working in an autonomous enterprise means less time spent on administrative tasks, less opportunity for human error as a result of being overworked, and less focus on minutiae. Instead, workers have more time to serve customers, collaborate, and benefit from each other. Change is here As part of this autonomous revolution, the line between man and machine is blurring. Increasingly powerful systems are taking on tasks that were once considered beyond the ability of computers. We now rely on AI and automated systems to predict customer demand, detect people’s emotions, and even drive our cars. This is automation taken to the next level with built-in intelligence. Traditional automation is like a fast-forward button, greatly speeding up processes but not changing them in any way. Users still needed to define how automated tasks worked and intervene each time a parameter changed. With today’s autonomous solutions, processes are not only faster, they are self-improving and self-repairing. Once powered, they will constantly look to work in more efficient ways, while AI algorithms suggest new outcomes that may be more favorable, and that a human mind could not compute alone. Consider the way autonomous robots have transformed warehouse operations. Major ecommerce companies like Alibaba use armies of robots to navigate, retrieve, and deliver products, making it possible to fulfill orders at a previously unheard of pace. The robots operate like a well-oiled machine, avoiding obstacles, finding the fastest route to where they need to be, and turning warehouse management into a nearly autonomous process. A global revolution The rise of autonomous systems is not a niche phenomenon. Last year, Gartner predicted that “autonomous things” would be the top strategic technology trend of 2019. The rate at which countries, and businesses in those countries, embrace autonomous technology will dictate their competitiveness in the years to come. The Economist Intelligence Unit released a ranking of nations based on their readiness to integrate intelligent automation. The 25 countries were assessed based on how well their policy environment is suited to making intelligent automation a reality, and the level of leadership they have shown with regards to digitization to date. The results reveal that autonomous is indeed a global trend, but that even the most advanced countries have work to do when it comes to skills. For automation to have a positive long term effect, education policies and training programs must evolve to ensure the success of future generations in the workforce, in addition to the success of companies that will ultimately employ them. In particular, the Economist Intelligence Unit emphasized the need for continual learning so that people are able to keep up with change. As robots and algorithms take on more routine tasks, we must prepare people to take on more human-oriented roles, which will require adaptability, creativity, and critical thinking over technical abilities.  At Oracle, we are pioneering autonomous technologies for the enterprise. For instance, the Oracle Autonomous Database is able self-patch, self-tune, and protect valuable data with no human intervention. Our broader Cloud Platform Services helps companies to get predictive insights from their data, while driving down operational costs and the risk of human error.

Change is good, but it also makes us anxious. This is especially true when a new technology promises to revolutionize the way we work. We marvel at the possibilities of AI and autonomous systems, but...


Is Finance still playing catch up to Big Data?

The 2008 financial crisis led to a shift in customers’ expectations and relationships to companies. No longer is it enough to sell quality products, these have to be delivered hand in hand with personalised and excellent customer services, everywhere, all the time. Finance and Supply chain offices, being less exposed to those frontline changes, have since been playing catch up to this seismic shift. It’s now time to show that they are equipped with the skills and technology to bring various sets of data together, with the help of automation, to deliver on their role as internal strategic consultant. Alex Doneth Dodds, programme lead at Oracle, says finance can step up its strategic game to match digital transformations in products and marketing. First, it must learn to re-love data, Customer-facing functions have spent a decade dealing with rapid and disruptive change. What journey have the ‘back office’ teams been on? For finance in particular, there has been a fundamental shift beyond managing raw numbers. Collecting, verifying and reporting numbers – often manually – used to be the core role of the finance team. But the complexity and the volume of data that is coming into finance now is growing exponentially and this is making things really difficult for finance leaders. Are some companies are in denial about this growth of complexity of data on the one hand, and inflated customer expectations on the other?  Research suggests only 40% of finance leaders feel ‘quite comfortable’ with the amount of data they’re expected to manage. (Note that only 43% feel that the security they have within their organisation is also adequate. This suggests a degree of complacency given what we know about cyber threats…) Even for a finance team primarily focused on internal, transaction-related data, there are new challenges. The granularity of today’s data breaks a lot of old assumptions about what constitutes ‘good enough’. For finance leaders expected to provide compelling insights on the past, projections of future performance and contributions to growth – particularly around strategic decisions such as M&A – the gap is potentially wider. CFOs without the right support risk falling further behind as these expectations grow. Even on compliance and risk management – also ‘traditional’ finance deliverables – in-the-field-data is getting more complex. For example, IDC predicts that by 2022 digital risk will need to be a standard part of financial reporting. So even the ‘old’ roles are changing to adapt to new sources of data? Today, all that data, that finance insight, is being used to new ends, too – not just to optimise returns, but also shape the behaviour of people and transform culture. It’s not just cost-to-serve for digital versus offline, or even uncovering new potential revenue streams from digital channels; analysis can help leaders embrace disruption with confidence and accelerate innovation. CEOs expect this insight around customer behaviours; they want data-driven advice, not opinions; and they need increasingly accurate projections on future performance. We are working in an era where even the biggest brands have to embrace ‘the pivot’. But if finance is running to stand still on the basic data hygiene tasks, it’s going to struggle to bridge the gap between these critical needs and their capabilities. So if the CEO and the wider leadership team cannot rely on hard data to inform those radical decisions, there’s a problem, right? Agility backed by knowledge creates competitive advantage. Data is fuelling a new dialogue within companies, between companies and their stakeholders – especially customers – and beyond. Ultimately, finance is a language, and using the right language to describe new interactions is a must. Scottish Water – a market-leading supplier in the UK – is a great example. It’s a challenging, highly competitive, industry. So the team there looked at their business model, they looked at what insights do they actually get, and started to focus on articulating potential benefits to the consumer. That work has delivered an 85% drop in complaints and a 21% rise in customer satisfaction – just from using data to better understand what people want. Those customer insights clearly deliver top-line value, then. But even inside the finance team, new approaches powered by AI and cloud are delivering to the bottom line. One trend we’re seeing among the leading finance teams is automation. It’s compelling. Getting the basics delivered via robotic process automation (RPA) allows for a step change in efficiency and means finance staff can focus on delivering business and financial insights. APIs, which are one ingredient for better RPA, are developing into a whole ecosystem, building connections between organisations, standardising data and enhancing the finance function’s ability to deliver against this new promise. And as we create these much broader platforms – systems that are capable of generating and analysing data of every type – we also allow the same kind of analysis to pervade a variety of other functions. Where else can these technologies help companies speed up the strategy to execution time cycle? Supply chain management is an obvious candidate. Today’s supply chains are global, extended, must be flexible yet reliable – and without proper visibility can introduce huge risks into an organisation. Data-driven insights from a properly connected supply chain mean cost savings to boost the bottom line, better risk management and opening up a new strategic markets. So what’s holding up teams that are looking to catch up on exploiting data? One challenge for their leaders is visualising a strategic roadmap, given their need for agility and the effect of uncertainty. It can be hard to develop a fixed idea of the objective when so much is changing. Then legacy technology infrastructure and processes can block adoption of new approaches. If they feel even the early steps are tough because data is stuck in silos, or there’s an interoperability problem between systems, it’s hard to visualise the kind of automated, efficient, open platforms this future works on. Needless to say, there are ways to leapfrog some of the digital transformation challenges – not least by looking at well-established, secure cloud platforms that deliver precisely the kind of secure, flexible approach that’s required today. How will finance and other functions know when they’ve caught up? The ideal is enterprise-wide systems that are interoperable thanks to APIs and cloud availability; that can adapt to different data; and deliver the kind of holistic analytical insights that a single view of big data can bring. ‘Catching up’ means that different teams all operate at the same speed, with a shared view of the data. Then finance leaders can set teams free: automation of routine tasks allows them to focus on value-enhancing questions. When the CFO works in partnership with the CMO, for example, they can bring together different data sources to foster genuine innovation. When the CEO is turning to those finance and supply chain leaders as the first test of strategic decisions – and to generate new strategic directions – they’ll know they’re in good shape. They’ll have truly caught up with expectations that they should be a kind of hyper-informed internal consultant. We apply these same principles inside Oracle, too. Our teams use the same Oracle cloud capabilities as customers – and the kinds of automation that high transaction volumes demand so our finance leaders are able to offer precisely that kind of strategic support. Whether it’s dash-boarding capabilities to visualise real-time data, or applying machine learning to refine the automation of increasingly complex tasks, we know it works.    

The 2008 financial crisis led to a shift in customers’ expectations and relationships to companies. No longer is it enough to sell quality products, these have to be delivered hand in hand with...


Serving the Segment of One

There will be 163 zettabytes of data in the world by 2025 but just 3% of it will be analysed, according to Seagate/IDC. So it seems most of us are still drawing on limited datasets to serve our customers. What could we achieve if we used the vast amount of data at our disposal better? If we fully map audience behaviours and needs, we could move beyond serving groups of customers. And instead, treat customers as individuals. We’re now in the age of the ‘Segment of One’, whether you’re a consumer or a business-facing brand. The days of B2C and B2B are giving way to an era of ‘B2Me’. At a time when customers expect individualised experiences, more and more marketers are trying to understand what makes each person tick, rather than looking for what links groups together. And if we can get that right, it could be the difference between reactive messages and the personal, proactive experiences that allow us to truly engage with our customers. The Shibuya Tourism Association is taking on this challenge already. It provides travellers with information on how best to enjoy the area around Tokyo’s iconic Shibuya crossing. More than five million tourists visit the site each year, taking in the unique spectacle of 1000 people crossing the road at once. But after taking a quick photo, most people leave, skipping the tourist office and missing out on everything else the neighbourhood has to offer. With the Tokyo Olympics just around the corner, the tourist association wanted to change this – and it took a data-driven approach. By installing over 1200 beacons in the streets around Shibuya station, and creating a mobile app, it was possible to pinpoint visitors and draw on data from their smartphones to improve personalisation. The association can now provide visitors with richer recommendations, based on personal interests, where they’re going, and the time of day. It’s these personal moments that matter, in the new experience economy. But getting to this point relies on marketing campaigns being much more efficient and targeted – hardly a simple task, with so many customers and so much data to manage. In fact, dealing with the data can take longer than creating and delivering the customer experiences themselves. That’s why companies like Agea are turning to autonomous technologies to manage their data. Argentina’s largest newspaper is moving from a content-centric approach to a customer-centric one. But it found that the time and cost of managing its analytics infrastructure was standing in the way of success. With Oracle’s Autonomous Data Warehouse, Agea has cut its data management costs by 50%. More importantly, instead of spending valuable time on admin, Agea’s marketing team can focus on drawing insights from its data. Which means more targeted customer experiences, faster.  Reaching a ‘Segment of One’ depends on accurate predictions about what each customer will do next, so we can address their needs at the right time. That means pulling together first, second, and third party data to gain a complete understanding of customers, across channels and devices. And then, with the right end-to-end platform, it’s possible to align the efforts of marketing, sales and services teams. It’s no surprise that today’s fastest growing companies are investing in a more unified approach to data, and getting closer to their audience. Read our report and find out how their investment is paying off.

There will be 163 zettabytes of data in the world by 2025 but just 3% of it will be analysed, according to Seagate/IDC. So it seems most of us are still drawing on limited datasets to serve our...


Why Innovation Needs to Get Personal

Customers share more information than ever with companies. Actually, around 90% of the world’s data was created in the past two years, and most of it’s linked to individuals. And in return for sharing this data, customers want innovative, hyper-personalised experiences. Those businesses hoping to meet these steep expectations are working to first gain control over this data. And then they’re focussing their innovation efforts on people’s real-time needs. Innovation for personalisation Generally speaking, people like brands that make their lives easier. While products and services are important, there’s a lot of choice out there. But if a business can deliver what you want, in real time, with a smooth experience, then they can really stand out. Companies rely on a real-time view of their audience to deliver this. It’s no longer enough to treat social media and email and Point of Sale and any of the other customer channels as different pieces of the puzzle. Instead, we should be connecting our data and systems to develop a complete customer view. The world’s best businesses have focussed their innovation energies on hyper-personalisation. They know that the better they understand their customers, the more they can align their innovation with market demand. Then they can deliver higher quality experiences – and higher returns. Here are just three organisations I’ve seen that have centralised their data to hyper-personalise customer experiences: Foodation is an Italian company that offers casual restaurants across Europe. After building a healthy presence in Italy, the business was ready to expand into new markets. But it needed a single view of its operations to make that happen. Using Oracle Simphony Cloud, Foodation centralised its systems across six brands and integrated all of its digital channels – including mobile payments, mobile ordering, and its app. The result? A more streamlined operation, and better customer experiences than ever. Global fashion retailer Perry Ellis International (PEI) is made up of 21 different brands, each one managing a large international footprint of locations and e-commerce channels. Before, this made it difficult to understand consumer behaviour. Now, PEI uses Oracle Retail Customer Engagement Cloud to bring together data from all of these brands, both in the US and UK. All told, it’s able to use deep insight from more than a million loyalty customers to deliver new levels of personalisation. The Mutua Madrid Open is one of the ATP tour’s top tournaments, delivering an experience that goes well beyond watching world-class tennis. The event has baked hyper-personalisation directly into its mobile app, with a chatbot. Users can instantly find information on players, schedules, results, and guest services, tying the viewing experience with the digital fan experience. The bot can even be used to buy tickets and merchandise. Each one of these companies has set a clear agenda to better use the data at their disposal. And I know that with more integrated data, and a hyper-personalised customer experience, almost any company could reap these rewards.

Customers share more information than ever with companies. Actually, around 90% of the world’s data was created in the past two years, and most of it’s linked to individuals. And in return for sharing...


How HR is leaping ahead by future proofing talent

Organisations have been going through “HR transformation” for over 20 years now. And that’s a good thing, because it means HR is never static and rigid. But it also means that HR is constantly adjusting to external circumstances, reacting to business requirements, and not strategically inputting from a talent perspective into guiding the business. How can we get HR to accelerate past this stage? By addressing the elephant in the room : productivity is the number 1 business priority but talent and culture are at the bottom of the league table, where people are seen as a cost as opposed to an investment By improving what’s holding HR back : data management and labour intensive tasks By future proofing talent: HR would effectively future proof itself “HR leaping ahead…” of anything might be a headline met with scepticism, considering the corporate world’s oft-stated concern surrounding HR’s impact and value creation. One factor in being sceptical about HR, (despite being in its 20th year of transformation), is the productivity “equation” is unanswered. Flatlined growth appears to be more about an over-obsession towards automation/machine development, yet those wiser-of-mind will say this is an under-obsession for the power in people, sometimes in individuals. Jonny Ives’ recent departure from Apple being a point in case: his designs created new product lines and gave the corporation its place in consumer electronics. Paul Polman’s work as CEO of Unilever was more than a vision but it has set a new bar for conscious organisations who are pro-profit and who have ecological and societal delivery to match. So is the continued scepticism about HR well founded? Not with the latest Oracle Research in mind. The research identified that there are some very simple solutions to ensure talent is “future ready” and optimised alongside dynamic, enabling systems and processes.  Which shows less about any more HR oversight needed and more about other business leaders missing this key link between talented people and the improvement of business productivity. If HR is to leap ahead in this area, how can we turn business sceptics into supporters of HR? Simple – Use Data that proves this “talent hypothesis” and showcase it to those who doubt. The research’s headlines for HR to broadcast are: 1. If you want to improve growth, don’t ignore your culture 39% of organisations who have seen significant growth have completed innovation culture initiatives, compared to 20% of those with marginal growth 2. Issues with people are often the barrier holding back growth 27% of decision-makers say the main barrier that stops new products, services and customer experiences from reaching the market is that there is a lack of leadership 3. Businesses whose talent is agile are growing faster 34% of organisations who have seen significant growth have completed agile talent redeployment initiatives, compared to 17% of those with marginal growth 4. The biggest struggle for HR leaders is helping talent be more agile. The gap between desire and reality is huge for HR decision-makers 73% say that talent agility is a priority, but only 30% have achieved this 72% say that giving employees access to the data is much needed, but only 35% have done so This feels like a straightforward business case that should need no further justification. Good work, from talented individuals in their businesses, equates to creative gains and adaptability that delivers competitive advantage and productivity. That talent relies on recognition and needs to be invested in, with flexible working conditions. That talent also needs to be at the tip of the fingers of any HR team who know where it is and how to best grow it. The data shows this will deliver growth and innovation across the organisation.  

Organisations have been going through “HR transformation” for over 20 years now. And that’s a good thing, because it means HR is never static and rigid. But it also means that HR is constantly...


Connect people to change culture

Imagine the day when all the data in your company will be seamlessly connected. You can sit back and relax, right? Wrong. That day is coming, soon, and this technological step-change means HR will have a new challenge to take up: changing the behaviours and culture that such change brings with it. From employee buy-in to skillsets to cultural values, HR’s job is just getting started. According to McKinsey, the time European workers spend using advanced technological skills will increase 41% by 2030. And this is just an average, meaning some will be affected even more. One thing that’s certain is that the way we work now will change, and this will impact company culture. Evolving effectively, with minimal friction from your people, means preparing them for this change. Your business needs every employee to pull in the same direction , as our latest research explores. And the very first step on this road is clear communication. Communicate up front You know that new, connected technologies can help your people to work more efficiently, productively, and happily. But that may not be how they see it. They may worry that more technology means the company has taken a step towards automating their role. Or that greater connectivity is to keep a closer eye on them and their performance. Your organisation is adapting, so your employees will need to adapt too. Getting their buy-in up front could be the difference between them a) taking your hand and walking with you towards a connected future, and b) fighting you every step of the way. HR should stride forward to communicate that your company will become hyper-connected as soon as the decision has been made. Explain why this change is important to the company, and make sure you’re clear on what’s expected of staff to support the new, hyper-connected culture. Set out what will change for them, as well as the benefits they – individually – can experience if the company can make this evolution a success. Skills, mindsets, culture Greater connectivity and new tools require new skills in order to make the most of them. This could mean recruiting additional people, but it will undoubtedly mean training existing employees to help them take full advantage of their connected tools, systems and processes. Ultimately, you’ll be helping them to embrace a new way of working. In fact, by 2022, the World Economic Forum expects that more than half (54%) of all workers will require significant re- or up-skilling. But clear direction and up-skilling are only two sides of a business change tripod. A more connected workplace also needs something far trickier to achieve: new mindsets. Staff will adapt how they work, individually and together. HR leaders will work with heads of department to show the way and prepare teams. But truly accepting and embracing new business models will require a mindset shift, and this can’t be forced. The best chance lies in nurturing a culture that embraces change and the possibilities it brings. And that will need the HR team’s careful stewardship for years to come. Come and visit us at an event close to you to know how HR can power these changes.

Imagine the day when all the data in your company will be seamlessly connected. You can sit back and relax, right? Wrong. That day is coming, soon, and this technological step-change means HR will have...


How CHROs are harnessing data to get ahead

Only 20 per cent of HR professionals believe they can adequately plan for their company’s future talent needs. And yet, an HR survey found that forecasting for headcount is the most important use of data analytics. Why is there such a disconnect? As our research shows, data analytics can help CHROs to anticipate talent needs in a candidate driven market, better track employee fulfilment, and ultimately combine HR insights with business objectives. In other words, HR can study the past, see ‘now’, and get ahead. According to investment bank UBS, global unemployment reached the lowest level for almost 40 years in December 2018. But while record-low unemployment is fantastic news, it means high demand for job candidates. Your best employees are at greater risk than usual of being poached – whether by recruiters, former colleagues, even a well-timed LinkedIn ad. Improving employee satisfaction is the seemingly simple answer to this familiar problem. But it’s far easier said than done. Satisfaction surveys and performance reviews can gather information, but they’re time-consuming and expensive – not to mention the facts that it’s impossible to tell how reliable respondents are being, or that by the time results come in, the issue is often already outdated. But what if CHROs could use insights from existing and real time data to create an environment where employees want to spend their working weeks – a place where they feel fulfilled and motivated? We have the data Every new hire, promotion, raise, review, or departure brings data points, and this information is probably waiting for you in core HR systems. Tools like Oracle Analytics Cloud can use this data – and many other types besides – to reveal trends, help you forecast, and make informed decisions. This could include staff turnover data from your sales team, compared with location, earnings, or promotion information. Mapping this against current execs, you could spot those most likely to leave – and intervene before it’s too late. Over time, you’d be able to understand turnover rates throughout the company, and use insights from predictive analytics to develop plans to improve satisfaction, curb turnover and plug talent leaks. One global logistics company uses analytics to improve the job satisfaction of its delivery drivers. The handheld devices drivers use to accept delivery signatures carry plenty of useful information, and help them find the fastest, most efficient delivery routes. Greater delivery efficiency means the company can increase the number of packages delivered per driver, and this productivity boost leads to some of the highest driver compensation rates in the industry. Happier drivers, less driver turnover. Strategic insights What if we were to take this one step further? You could take your HR analytics and combine with other business areas to reveal new insights. Data from on-boarding, incentive programmes and goal management could inform your company’s strategic decisions. One of the USA’s biggest mobile providers found that SAT scores and college grades are poor predictors of employee success. Instead, experience in sports leadership is a much better forecast. But it only discovered this by analyzing job applications against those employees’ performance data over time. Combining datasets in new ways can be the fastest route to new insights, and forecasted plans that help you to keep the talent you value and spot the talent you need. HR can cement its position as a strategic linchpin of business continuity. And, of course, there’s simply no overstating the potential of motivated, engaged, productive employees.

Only 20 per cent of HR professionals believe they can adequately plan for their company’s future talent needs. And yet, an HR survey found that forecasting for headcount is the most important use...


What HR really does – and could do

What does HR do? From an outside perspective, it’s easy to simplify an incredibly complex function down to ‘they look after the people and the paperwork’. After all, despite being essential to any company, HR professionals have not been in a position where they can elevate their role to shaping business objectives – until now. Connected data and data analytics open up  the opportunity for HR to directly map talent in the world and measure the impact of its recruitment – and other policies – on the business objectives. Here’s how Alex Doneth-Dodds, Programme Lead at Oracle, explained this in a recent conversation. In the HR department, data is produced constantly. From payroll to training programmes, recruitment reports to performance review information – it’s generated and stored in vast quantities. But most HR professionals don’t feel confident with data. According to one of our recent surveys, 27% of our HR respondents are highly confident in the amount of data they have to manage, and only 35% feel highly confident in the security of their data. Why do you think that is? I think it could be because data and analytics are generally still associated with the IT team. Or maybe the commercial analysis that goes on in the finance department. Or perhaps the digital campaign measurement of marketing? The difference with HR data is that it’s focussed on a company’s number one resource: people. And if people are your most valuable resource, then you want the very best people, doing their best work, as productively and happily as they can. In other words, you want market-leading recruitment, training, and performance enablement, as well as job satisfaction. So, what do you usually see in HR departments at top companies? The best HR teams constantly review data and analysis, pulling out insights on everything from talent gaps to educational trends, engagement levels, and workforce dynamics. And by analysing, measuring, and quantifying the ‘human resource’ of a business, it’s possible to look after this asset more intelligently – and build tools that can help. Can you give us a few examples of places where this is already happening? Sure. So, after running some combined analysis of job application and employee performance data, one of the largest mobile providers in the US found that college grades actually aren’t that important for talent selection. Instead, evidence of sports leadership and teamwork is far more important when it comes to predicting future employee success. And the Royal Bank of Canada developed its Embark app to help new employees bridge their pre-joining and post-joining experiences at the company. Now they can connect with their managers, team mates, and HR from the outset, and this helps to set them up as engaged, informed colleagues. Any examples you can think of from outside North America? Absolutely. Lane Crawford is a luxury retailer in Hong Kong, and it uses collaboration and learning software for continuous staff development. Combining this with data analytics, it allows the organisation to track and tweak as needed, and make sure staff get what they need, when they need it. In conclusion, what’s your key takeaway when it comes to data and the HR department? Real business value comes from making successful decisions. Those decisions are based on timely, accurate insights, and those insights are born from data. If HR can embrace this, then it can deliver unparalleled value to the business and become a strategic partner at the same time. Come and visit us at an event close to you to discuss the value data can bring to the HR function.  

What does HR do? From an outside perspective, it’s easy to simplify an incredibly complex function down to ‘they look after the people and the paperwork’. After all, despite being essential to any...


Building greater trust in your data

Yes, you can build better trust in your data —but only if the organization can collect, structure, analyze and protect data in the right ways with the right tools. Modern supply chains integrate a host of related parties (and human error) into knowledge systems, which include business metrics, supplier sustainability performance data, and even intellectual property (IP). This is why systems and data must be built around secure access and verifiable trust. By 2022, cybercrime will cost global business $8 trillion. In the face of stats like these, data security is mission critical. Cloud-based systems offer organisations best-in-class security against hackers and human error. They provide managed access and tiered visibility permissions. Some are also self-patching, minimising security holes to ensuring data and analysis is on the money. Many organisations find solutions to finance security issues in technology. For example, robotic process automation helps lift the load for talent in finance functions and beyond – doing dull-but-crucial jobs with an efficiency and accuracy no human could offer.  An added benefit, AI can develop algorithms to spot exceptions and signs of fraud. Sustainability, diversity, data privacy and supply chain ethics – these kind of metrics now help define customer and employee relationships. Increasingly, they are also subject to regulatory filings. In the UK, for example, most large companies must report on gender pay gap.  Offering employees ‘managed transparency’ on performance might also be beneficial. Businesses need to be able to offer assurances—and data backup—on these non-financial metrics. The next generation of technologies already takes this concept of ‘confident transparency’ even further. Blockchain, for example, provides new ways of offering real-time, highly secure transaction management to create a common and unchangeable record for all parties. Each stakeholder—employee, customer, supplier, partner—has specific interest in a range of new metrics, from the quality of the whistleblower hotline to the provenance of the plastics in packaging. Smart business leaders will take advantage of agile cloud technology designed to help gather this data as effortlessly (and securely) as possible. Check out how other global finance leaders view data security and reliability in our report.

Yes, you can build better trust in your data —but only if the organization can collect, structure, analyze and protect data in the right ways with the right tools. Modern supply chains integrate a...


Finance’s role in a Data breach

I’d had personal experience of what it means to be hacked. And it’s not pleasant. Not only because of the obvious loss of trust and information that a data breach entails, but mostly because there was no contingency planning and the situation took our finance department by surprise. Things have changed since though and we are seeing CFOs to change their mindset and start planning for cybersecurity issues. Why would the role of a CFO be moving in this direction and what are the reasons behind this? One reason that I can explain easily is the rise of cybercrime and the need for robust information security. Cybercrime is lucrative for one reason – money – and who holds the purse strings? I have had first-hand experience in a cybercrime attempt and it wasn’t a pleasant experience, this particular situation turning into complete panic. Sadly, time is not on your side to sit back and run every scenario until you are comfortable with the proposed decision. To make things worse, it is now more than ever before easier to launch an attack with multiple threats as most attacks are conducted under a smoke screen of another event that has been made. Should a CFO understand the risks of a potential data breach? Yes of course, they should! In my opinion, the skills gap between new/innovative and older/experienced staff is a huge chasm to bridge. The CFO now has to understand the concepts of good data security insomuch that they can form a strategy based around potential cyber and ransomware attacks. A ransom/cyber-attack budget and contingency plan needs to have been well thought out and in place, just as an IT Disaster Recovery plan has to be. However, the reality is that any given organisation is more likely to have a data breach than their technology failing. The CFO should be leading the efforts of being prepared for a cyber breach and preparing for the worst – it’s not if it happens but more like when and how severe! It was interesting for me to have these sentiments reinforced whilst at the recent Oracle OpenWorld event in London, where I attended a panel discussion on connected business and finance. This sparked a lively debate where the “old CFO role” was scrutinised further by analysts present, suggesting that education was lacking within organisations to even adopt modern technology principles (E.g AI and Cloud software migrations) let alone cybercrime defence initiatives. Now, the threat of cybercrime extortion is very real. Being prepared for it is not optional, it’s mandatory! I have 2 pieces of advice for any CFO/Finance leader: Work closely with your IT division and work through a scenario where you do indeed get a data breach and ransom demands are made – get a plan in place! Have a budget aside for a) potentially paying a ransom demand and b) additional software and service budget to act as a first line defence. Hopefully if option b is in place you will never use option a. Cybercrime is real, it’s happening every day and it’s getting harder to police. It’s estimated to be lucrative $1.5 Trillion market now and if you don’t believe me, take a look at these statistics but make sure you are sitting down when reading them! For further reading, check out Oracle's report on how business leaders are approaching Data Security.

I’d had personal experience of what it means to be hacked. And it’s not pleasant. Not only because of the obvious loss of trust and information that a data breach entails, but mostly because there was...


A CFO’s perspective on Data Security

CFOs should govern data security, not IT. Why? Because they hold the purse’s strings and are most qualified to plan for risk, in an era where the next cyber-attack is not a question of “If” but “when” and “how often”.   So what is the CFO’s role today, and why should it include data security? The CFO role of today is one of a few that is used to complying with regulations. From the complex accounting standards that took many years to achieve excellence within to equally difficult industry accreditations that are required, so it would make sense that data protection and data security be attached to this role? In my opinion, yes! With complex data privacy and security regulations (GDPR) affecting every element of business data a new role emerged a few years ago – The DPO (The Data Protection Officer). Since May 2018, it’s a requirement for any given company to have one or at least have a nominee for that role. Who would be a good candidate? Of course, I’m going to suggest the CFO. What must a CFO become for a “fit for the future” data secure company? The DPO role is a natural fit for the CFO as the protection of data requires strict principles that apply across the whole company’s data estate (every system that is used to collect data). CRM, Financial, HR, ERP and other data sets now require regulating and safe guarding, with someone who has ultimate responsibility. This cannot be delegated to silo subset divisional heads. Huge fines for non-compliance to GDPR rulings are now in force (Up to €20 million, or 4% annual global turnover – whichever is higher). If you wish to see a comprehensive breakdown of this regulation click here. At the recent Oracle OpenWorld event in London the above statements were also backed up by many conversations regarding the GDPR regulation now in force post May 2018 and the effect on financial data. Not only has the CFO role changed to one of an enabler of budgets for additional data security products and services but also to understand why they are needed. ERP and HR systems have traditionally been under the remit of the CFO so many discussions were had around the emergence of a dual role for the CFO/Finance head for organisations. Couple this statement with the unfortunate reality of increasing threats of cybercrime, shouldn’t the role of DPO belong here? In summary Whichever way you approach data security and potential breaches you must have overall responsibility and accountability and the CFO is a natural fit. Data Security is not just an IT function and it is not just a CISO problem to protect and police. Good governance starts from the top down from any organisation and not just a budget line figure and the CFO has a very important part to play for the current and future strategy for data security.   Check out Oracle’s latest report on security here.

CFOs should govern data security, not IT. Why? Because they hold the purse’s strings and are most qualified to plan for risk, in an era where the next cyber-attack is not a question of “If” but “when”...


There is no fake data

Uncertainty is the new normal. In the era of fake news and unpredictable market changes, there is however one thing you can trust and control: data. Data doesn’t lie, but it needs to be secure, for it to be harnessed by business leaders in decision making.   “Uncertainty is killing growth,” ran the FT headline at the end of December 2018. The hook for its story was a new paper from the IMF and Stanford University that launched a World Uncertainty Index (WUI) – a rough measure of global instability. Uncertainty is neither a recent phenomenon, nor one affected solely by politics. The WUI has been significantly above its long-run average since 2010, reflecting a host of structural problems facing global economies. And for most organisations, ‘disruption’ has been a feature for even longer. There are few industries that haven’t been completely overhauled by technology in the past 20 years. Speed of decision-making and execution in operations, deal-doing and communications now define competitiveness. But as any CFO knows, risk management is double-sided. It requires rapid adaptation and the ability to seize opportunities – often created by the very uncertainty that hampers planning. And it means ensuring the foundations of the business are firm and protected from potential shocks. Either way, decision-makers need to be able to trust what they’re hearing about the business and their markets. Data security is a must – without it, all stakeholders, not just internal decision-makers, will lose faith in the organisation’s ability to either defend its position or find growth. And now the two sides of the risk coin are converging around technologies that enhance enterprise planning. With cloud-based systems, it’s never been easier to gather timely and accurate data across disparate organisations. By weaving in customer and supplier data – including behavioural insights, for example, to help model future trends – decision-makers can fine-tune tactical decisions in a more agile way. Then there’s artificial intelligence. Forget the hype about driverless cars and autonomous drones. AI is already finding its most compelling applications within enterprise decision-making. John Merino, chief accounting officer at FedEx, was interviewed recently for the report Agile Finance Unleashed: The Key Traits of Digital Finance Leaders. And he was clear on what this meant for his team: “The combination… creates a tremendous opportunity to capitalize on some really big efficiency gains in virtually every staff function. The big win for us is to liberate that time and move finance up the value chain in what it delivers to the organisation.” The survey found 46 percent of tech-savvy finance leaders report positive revenue growth, compared with only 29 percent of tech-challenged leaders. Those adopting AI are much more likely to be growing. But only 11 percent of finance leaders had done so – which suggests an opportunity ready to be seized. Put simply, when the world is more uncertain, making sure your own data is trustworthy, timely, properly analysed and actionable is the best way to manage risk on both up- and down-sides. Check out how other business leaders are approaching data in this day and age.

Uncertainty is the new normal. In the era of fake news and unpredictable market changes, there is however one thing you can trust and control: data. Data doesn’t lie, but it needs to be secure, for it...


Finance’s new data mindset

Finance’s job is getting bigger. With this comes greater complexity and a new level of accountability. New areas are emerging where the CFO is no longer just consulted but actually accountable, particularly when it comes to data security and compliance. And that shift means that finance leaders need to embrace a new mindset, where they actively embrace this new environment. You might or not be familiar with the responsibility assignment matrix, with its four categories: responsible, accountable, consulted and informed. In the matrix, tasks are designated to individuals with one of these categories attached to ensure projects and processes run smoothly. All of them apply to a CFO. Globalisation and specialisation have turned coherent ‘walled garden’ organisations into co-ordinators of extended supply chains. Nesting suppliers within suppliers, often in remote networks, brings risk. Being ‘informed’ and ‘consulted’ on this kind of extended organisation is a nerve-wracking proposition. Being ‘accountable’ or ‘responsible’ for it is even tougher. It starts with operational issues and progresses to regulatory and reputational risks that, if anything, have an even greater potential to damage an organisation. How does a CFO report to the board with confidence that, say, their supplier’s supplier conforms to global bribery regulations – or even local labour laws? Technology facilitated the shift towards more diffuse operations and is vital for making better decisions. But it’s also the foundation of regulatory compliance. Oracle customer Marcura is a good example. It co-ordinates maritime services across eight different businesses – mostly around non-standard transactions, which makes data and process robustness even more important. Having a cloud-based ERP helps co-ordinate its different businesses and cater to a diverse global end-user base including ships’ crews, brokers and port authorities. But one of CFO Karsten Gregory’s key considerations for choosing ERP Cloud was its ability to instil trust in all its stakeholders. “Our company is founded on the principles of compliance, independence, transparency and efficiency,” he says. The security of its systems and customers’ data has to come first. For a global business such as Marcura, demonstrating compliance across many different jurisdictions is fundamental to its licence to operate. It has to monitor data to comply with bribery, money laundering and sanctions laws, as well as handling a range of customer interactions. We know the right implementation of cloud systems can enhance security and data robustness. (When security assessment firm KuppingerCole reviewed Oracle Autonomous Data Warehouse Cloud, it concluded that its intelligent automation features massively reduced the potential for human error and malicious attacks.) We know it facilitates more timely and accurate compliance across a range of regulations. But any approach to data has to offer the CFO those RACI elements. If they’re going to be responsible, accountable, consulted and informed – in other words, if they’re going to be confident their business is compliant with both regulations and customer expectations – they need to know that every part of the organisation is aligned, its data is timely and robust, and that it’s properly protected. To find out more about how modern business leaders are thinking and acting with regards to Data security, check out our latest report.

Finance’s job is getting bigger. With this comes greater complexity and a new level of accountability. New areas are emerging where the CFO is no longer just consulted but actually accountable,...


Finance must lead the conversation on data ethics

Finance leaders have always felt responsible for company data, but the spotlight has shifted to protecting people outside the business. Customer and employee data breaches can swing reputations and valuations overnight, making ethical data management a priority across the organisation. We squirm when an invasion of privacy feels personal, even if it doesn’t affect us directly. This is why recent data breaches – from the man who hacked German government officials to companies who mined data from minors – have done more to shape our impression of major institutions than these companies’ legacy or marketing campaigns. The ethics of data-driven business are not just an emotional issue. Lapses in security or in the way data is managed can quickly lead to public outcry, affect customer loyalty, and scare off shareholders in droves, making them a major issue at the boardroom level and across every business function. The challenge is that data security and ethics are (relatively) new concepts for most teams in the organisation. Marketers have been working with customer data for some time, but they are still coming to grips with how to manage all this information. Similarly, HR teams now draw from a range of data streams to help them manage and recruit employees, but these changes have come so quickly that ethics have taken a backseat to progress. Finance teams are the outlier in many respects. For years, they’ve been responsible for managing and protecting some of their company’s most sensitive data. Finance leaders are arguably their company’s greatest data champions, with a unique appreciation for the power of data and the ethical considerations of keeping it safe. Today, they have a responsibility to spread this knowledge across the organisation and turn data ethics into a company-wide conversation. CFOs and their teams are also no strangers to the pressures of competition and the need for innovation. Over the years, they have invested in processes and technologies allowing them to draw insight from data instantly, at any place, and at any time. But given the sensitive nature of this information, they have made this transition conscientiously instead of rushing. It’s a fine balance to strike, but it sets an excellent example for marketers and HR as they look to handle data more responsibly. Our research found that nearly 78% of finance leaders are either highly or moderately confident their company’s approach to data is ethical, but the prevalence of breaches shows that a company’s security approach is only as strong as its weakest link. It’s one thing for customer-facing teams to invest in technologies to protect their data, or for HR to roll-out training programmes on treating it responsibly, but to conquer new territory they will need guidance from finance leaders who have been here before and can help them understand the wider implications of their actions. Want to learn more about the state of data security and ethics in businesses today? Check out our report.

Finance leaders have always felt responsible for company data, but the spotlight has shifted to protecting people outside the business. Customer and employee data breaches can swing reputations and...


Layers of Security

Nature devised a perfect structure to protect the most valuable part of fruits and vegetables. Think about artichokes, onions, and corn—it takes effort to get to the core. Good IT security works in a similar way. Multiple layers of security--including identity management and data-level encryption--help keep sensitive information safe in a breach. This strategy, however, can work only if there’s an easy way to control who can access what data at any point in time. Many IT departments struggle with this elemental task. For large corporations, it’s common to have “millions of user access privileges spread across thousands of IT resources”, as a study by University of Regensburg notes. Companies report “careless employees” and “outdated security controls” as the two vulnerabilities currently exposing them to the most risk, according to EY’s Global Information Security Survey 2018-2019. Cloud-based identity management, “identity as a service”, addresses these risks in several ways: IT managers can move each employee to a single system and offload administration of multiple employee accounts Adaptive and multifactor authentication for both users and administrators provides multiple layers of security Easy and immediate rights revocation for unusual behaviour or termination   Because “human error is a major factor in security breaches”, automating database management in a trusted cloud can dramatically increase security levels, advisory firm KuppingerCole concludes. In an ideal environment, IT administrators offload routine tasks such as updating databases and fixing user accounts. When cloud databases can automate patches and updates, IT staff can focus on responding to suspicious activity flags generated by artificial intelligence (AI). Transformative technologies like AI and blockchain add next-level layers of security and protection. This is the vision for the Global Shipping Business Network, initiated by Hong Kong-based Cargo Smart. By storing necessary information in a cloud database all parties share, the system eliminates the need for printing, sending or faxing documents—along with third-party verifications. CargoSmart’s blockchain solution aims to simplify the shipping documentation process, increase trust, and boost efficiency. Connected through a blockchain documentation platform, the entire shipping ecosystem can reduce disputes, avoid late penalties from customs agencies, expedite documentation turnaround times, and better manage detention and demurrage costs. CargoSmart projects a 65% reduction in the amount of time required to collect, consolidate, and confirm data from multiple parties and to handle shipping data that is repetitive in different documents by leveraging its blockchain shipment documentation solution. Authorized users can see exactly what they need to see, but no more.  Blockchain technology guarantees no one can retroactively edit even a single entry in the shared database. “A peer-to-peer immutable distributed ledger provides near real-time insights. This unprecedented transparency will restore trust in the industry”, notes Steve Siu, CEO of CargoSmart.   To find out more about how IT managers and other business leaders view data security issues, read our report.

Nature devised a perfect structure to protect the most valuable part of fruits and vegetables. Think about artichokes, onions, and corn—it takes effort to get to the core. Good IT security works in a...


Create your own data model

It's a win-win situation in its best sense: Migrating to the cloud, while doing good for society – a German food charity is doing just that. While this may set a precedent for other NGOs, each organisation – whether big or small – must find its own data model and ensure that the asset is always available, trusted, and secure. Organisations have more data than ever at their disposal. That applies to bluechip companies and small organisations alike. Take the example of Tafel Leipzig, a German charity: Founded more than 20 years ago as a small NGO, the organisation today distributes food donations to 15,000 people a month. Their clients in the city of Leipzig include unemployed or homeless people, but also a rising number of low paid workers, single parents, retirees and even students. As the number of people served ballooned, more distribution points were opened up and EU data privacy rules (GDPR) tightened, Tafel Leipzig decided that it was time to give up manually managed Excel sheets. Instead, customer and supplier data was migrated to a more future-proof system: A cloud-based content solution. While the transition helps Tafel Leipzig to fulfil data protection rules, it also boosts their productivity. "This will enable us to serve more people in need and distribute valuable food that would otherwise be wasted," said Werner Wehmer, Chief Executive Officer of Tafel Leipzig. Companies share common goals when dealing with data including data security. If data is lost or stolen, IT assets quickly become liabilities as average cost of data breaches or non compliance keep rising each year and transferring your information system to a cloud helps you to protect sensitive data and critical business processes even better. Still, each business model requires an individual approach to managing data. Whoever tries to take all the data points in the world and imitate your rivals is doomed to fail. There is no one-size-fits-all solution. As Oracle’s research suggests that 80 percent of all enterprise and mission-critical workloads will move to the cloud in 2019, companies must safeguard data by choosing the right technology but also the right data model that works for them. At Tafel Leipzig, an Oracle partner trained volunteers with very basic IT skills to rethink which data must be protected and what should be distributed to whom, as all data moved to the cloud. To ensure the smooth running of food collection, storage, processing and output, data such as addresses, vehicle information or quantities of food has to be accessed by the right people at the right time. Whether you run a charity or a large enterprise, cloud solutions also help you produce trustworthy data and attain meaningful insights from it. You find out who your customers are and what they really care for. As new technologies such as artificial intelligence (AI) and machine learning (ML) are integrated, cloud solutions have become crucial to driving new business and putting your company on a steady path of discovery. The Tafel Leipzig team now has access to client and supplier data from nearly anywhere via mobile devices. The charity also plans to digitally log, visualise and assess the overall throughput of goods to make the most of the donations that fund its operations. Or as CEO Wehmer puts it: "Oracle technology is thus making an important contribution to the common good and to a livable society.” Please read our recent report on Cloud security and ethics here.

It's a win-win situation in its best sense: Migrating to the cloud, while doing good for society – a German food charity is doing just that. While this may set a precedent for other NGOs, each...


All Data is not equal

Different people need and work with different data. Having an understanding of the different datasets that exist across an organisation and the characteristics and quality of the data that could be used to train and run AI systems is key, not just to unlocking the insights and power from data that exists, but also to realising the full potential of the latest data-driven technologies. A machine learning algorithm is in essence a piece of a software code and set of instructions for a computer or machine to follow to achieve a particular result.  It is only when datasets are applied to that algorithm that AI systems can be trained to find patterns, learn from experience and unlock key insights from vast amounts of data. The more data that can be applied, the more it can learn and provide answers. Sounds easy, right? Yet, for those looking to adopt and deploy an AI-driven solution, there are three fundamental questions that must first be answered; what is the business objective you want to solve, is your data in a digital format and ready for AI, and do you trust the quality of the data? Just as with any adoption of digital technologies, there must be a clear business reason for using any technology tool or solution. For example, using complex machine learning to find insights that could have been achieved using tools found in an excel spreadsheet may not be a good use of resources, and could, therefore, put the business’ willingness to invest in AI innovations further down the road. If a clear business objective is identified, the next step is understanding whether the necessary data exists in a digital form and where the datasets needed to train AI systems reside within the organisation. Knowing where the data has come from and its integrity and security during its lifecycle will also be key. Finally, if an organisation is to trust the results generated from an AI system, the quality of the data used to train the system must also be trusted. For example, ensuring biases that may exist in historical or legacy datasets are identified and removed before the data is used to train AI systems is vital. An AI-driven HR system based on historical data could result in hiring recommendations that may lead to a ‘group think’ mentality which could have a long-term effect on an organisation’s market success. Taking the time now to consider the type and format of datasets that may be used to train AI systems, and having the right approach to identify, assess and address bias, so that it does become a case of ‘good data in, good data out’ is the only way any organisation will become  truly AI ready. Read more about our report on Data security here.

Different people need and work with different data. Having an understanding of the different datasets that exist across an organisation and the characteristics and quality of the data that could be...


Data Security is a team effort

Gone are the days when an IT department alone was able to protect a company’s systems. Given the enormous risk, fending off cyber criminals must be of central concern to all employees, from the receptionist to the CEO. But that brings its own risks, which can be curtailed by emerging technologies. Today’s landscape is teeming with an ever-growing number of “attack vectors”,  with the newest being crypto-currency mining – a kind of cyber-attack that grew by an astonishing 4,000 per cent in 2018, according to McAfee. “A successful data breach can destroy both CIOs and the companies they work for”, consultancy KuppingerCole warns. “Database security is becoming the new cybersecurity frontier.” That makes it crucial for IT departments to see Data Security as a team effort. To succeed in protecting their company’s assets, security specialists need to share their expertise and raise awareness for the risks that all employees face in a digital work environment. “It is critical that cyber risk strategy be built and managed from the ground up, embedded in the business mindset, strategy, and policies, not only within the IT architecture and systems design”, consultancy Deloitte points out. “IT and business leaders must collaborate to determine a comprehensive cyber risk strategy.” Managed successfully, the advisors conclude, security can become a competitive advantage and “potentially drive an organization’s market position”. It seems obvious that the way forward is to educate people and control the data flow. Ideally, employees should have access only to information that’s mission-critical to them. And anybody leaving the company should immediately lose all access, of course. However, these seemingly simple issues can quickly become overwhelming when accounts come in the thousands. Cloud services can be an answer to many of these challenges since they allow administrators to centrally monitor and control the flow of information. Solutions like Oracle’s Autonomous Data Warehouse Cloud or Oracle CASB Cloud Services not only encrypt all data for maximum security but also automate a variety of time-consuming tasks, such as patching the database with security updates without downtime. In addition, smart systems can detect anything out of the ordinary with the help of machine learning algorithms, immediately block access and alert administrators. While there may never be absolute security, the right technology choices do make a difference – especially in an era of everyone and everything being connected: by 2030, Cisco predicts, 500 billion devices will be sending and receiving data, communicating among each other but also with corporate systems and companies’ employees. To secure this digital world of tomorrow, human administrators and artificial-intelligence systems will have to work hand-in-hand, with much of the data residing in a trusted, automated cloud environment. Find out more about how IT and other business leaders are approaching data security.

Gone are the days when an IT department alone was able to protect a company’s systems. Given the enormous risk, fending off cyber criminals must be of central concern to all employees, from the...


Treat data like it's a financial asset

Data today is as valuable as money. While investors seek to protect their portfolio from currency fluctuations, IT leaders must aim for the highest possible data quality and security. Treating it like cash under a mattress is not an option. New technology will help to build up trust in cloud solutions. Data, some people say, is the new money. But like bank notes coming out of a cash machine, not all 1s and 0s are of the same quality. While some currencies may lose in value overnight, the dollars in your pocket will most likely be a safe bet. Similarly, IT leaders must strive to transform their data into a "safe haven," something valuable that is always available, trusted and secure. Cloud computing has come a long way. When first-generation clouds emerged, many companies were still reluctant to adopt the new technology as they faced the dilemma of security versus innovation. Instead, they chose to rely on their own IT security infrastructure — like savers stashing cash under the mattress or drawer instead of keeping it in the bank. It’s all about trust. But the technological progress we've seen with the advent of second-generation clouds has helped to boost customers’ confidence. Today, nearly eight in ten businesses are convinced the cloud can boost their security. The latest technology enables highly complex workloads and gives you access to innovations such as autonomous database and artificial intelligence (AI). The fact that nine in ten companies say that at least half of their cloud data is sensitive information is proof of the heightened trust in third party data centres. When LogOn started off a few years ago, it also ran its software via a regional data center as its activities were focused on Germany. In order to scale their services and roll out their voice-based online recruiting system in twelve Western European languages, they have transfered their business to Oracle Bare Metal Cloud Services (Oracle BMC).  Logon’s team, lead by Peter Kolb,  was well aware that running a business in the cloud means shared responsibilities between them and the service provider. As the 2018 Oracle and KPMG Cloud Threat Report suggests, "it is crucial that everyone in the organisation — not just its leaders — is educated about the cloud’s inherent risks and the policies designed to help guard against those risks." It takes two to tango — no matter whether we talk about data quality and security for recruiting software or protecting your financial holdings. From LogOn, meanwhile, there's more to come: "We are currently working on securing the data through the use of blockchain technology," said Kolb. Data quality for sure will be key on that journey. Find out more about how IT and other business leaders are approaching data security.

Data today is as valuable as money. While investors seek to protect their portfolio from currency fluctuations, IT leaders must aim for the highest possible data quality and security. Treating it like...


Why IT worry about data ethics

Data may be invisible, but its effect on your business when something goes wrong is all too tangible. As the team that feels most accountable managing data, IT can teach us a great deal about the power of information and how to approach it more ethically. If a tree falls in the woods and no one is around to hear it, does it make a sound? For years, people have quoted George Berkeley’s adage to distance themselves from problems that felt beyond their responsibility. It is this thinking that has brought us today’s challenges around data privacy and security. IT sits at the center of the organisation’s data management and has a unique understanding of how to collect, handle, and use information responsibly. This sense of accountability also makes IT more attuned to the ethics of managing data – nearly 50% of IT leaders are highly confident in their organisation’s ethical use of data. For comparison, this figure is just 38% for HR leaders. Like data security, data ethics has become a business-critical function, and as with any other business-critical function it requires structure. This is where IT can help, galvanising the organisation to be more conscientious and work with data in an integrated way. This begins with an understanding of who is responsible or accountable for data management and they can contribute, which businesses have struggled with to date. Our research found that only 39% of IT decision-makers feel there is clear ownership and clarity of roles to help them extract insights from data, so there is still some way to go here. According to our joint Threat Report with KPMG, 92% of cyber leaders are concerned their employees aren’t following data security policies. The same report found phishing is still the most common prevalent crack in their defences. This tells us that companies can try to address external threats with new processes and technology, but it will take a greater focus on ethics and responsibility to truly eradicate them. IT has led the way for years, and now it’s time to get the rest of the organisation on-board. Read our report to see where companies are focusing their data management efforts and learn more how IT can lead the charge.

Data may be invisible, but its effect on your business when something goes wrong is all too tangible. As the team that feels most accountable managing data, IT can teach us a great deal about the...


Data security is not my problem

In the event of a data breach, the role of marketing could be arguably the most important. Speed and communication are of critical importance, as minutes could result in millions of dollars lost for your business. To avoid this, marketeers need to thoroughly assess all customer touch points and work with IT to ensure data is collected, analyzed and stored securely at every step.  In doing so, marketeers can mitigate the likelihood of a data breach and increase trust inside and outside the organization. Think a data breach or security attack is the sole responsibility of the IT department? Think again. Data security is everybody’s concern, and it’s important you know what to do when a security breach occurs, whatever your role in the business. For marketing in particular, this area is likely to become more challenging. Consumers are gradually becoming more aware of the impact that digital systems and cloud computing have on their data privacy, potentially making it easier for hackers to access information if it is not locked down properly. This heightened awareness, exacerbated by regular stories of millions more people having their personal details exposed, means marketing leaders need to work even harder to convince their customers they can be trusted with their precious data. A good starting point is to carry out a thorough assessment of all touch points within customer acquisition and retention, ensuring they are free from vulnerabilities and apply the proper levels of data protection. CMOs also need to work closely with their IT counterparts, to check that every step in the data collection, analysis and storage process is secure, minimising the risk of cyber-attack. If the worst does happen and your organisation becomes victim of an attack, marketeers need to focus on damage limitation at the frontline, informing customers and other stakeholders clearly and swiftly about how they might be affected and what the business is doing to improve security going forwards. So all those names, numbers and email addresses you have on file of your business contacts need to be securely stored and managed in exactly the same way you deal with customer data. Consent must be freely given by an individual opting in – the opt-out tick boxes of old are no longer acceptable – and you need to inform customers how you are using their data, how long you plan to retain it for, and if it will be shared. By taking these steps to protect all your customers and contacts, and lock down company data, marketers can help their company avoid embarrassing headlines, steep fines and damaged customer relations. To find out more about business leaders are looking at data security, check out our report here.

In the event of a data breach, the role of marketing could be arguably the most important. Speed and communication are of critical importance, as minutes could result in millions of dollars lost for...


Clean Data before Clever Data

What good is all your data if it can’t be trusted? As marketers start to embrace new technologies, further work is needed to ensure data is accurate and reliable to ensure customer trust and reduce risk. Today’s marketing opportunities are unprecedented. The cloud is driving the move to AI, where data is collected and analysed to better understand customer needs. However, if the data is inaccurate it really can’t be trusted, putting both the organisation and customer at serious risk. Oracle predicts all next generation applications will be AI driven by 2025, including chatbots, which are seen as one of marketing’s big technology wins. Chat about chatbots Chatbots approach the sweetest of marketing’s sweet spots. They meet the needs of customers who expect instant engagement, response and understanding – all without a human in sight. Given the fact that chatbot deployment can see falls in human-intensive contacts of up to 70%, it’s no surprise that Gartner predicts 25% of all customer service operations will integrate chatbots, and customers will manage 85% of their brand interaction without human intervention, by 2020. Sweet indeed – but there’s a sour note too. Whilst people increasingly value chatbots, better understanding is seen as the No 1 area for improvement. And customers will only adopt if the tech works – 73% of respondents to a US survey said one bad experience would see them walk. Which brings us back to where we started – data security, and by extension, data accuracy. Data security is trust The cloud provides infinite possibilities for Marketers to improve CX, open new revenue streams and rapidly deploy creativity at scale. To realise them, any cloud solution must support your business journey – a solution that is comprehensive, open, evolving, integrated – and secure. And remember, the cloud technology toy box will only ever be opened if customers trust what they find inside. Now is the time for Marketing to take responsibility – and seize the power of the cloud. See how our recent report demonstrates that and much more. 

What good is all your data if it can’t be trusted? As marketers start to embrace new technologies, further work is needed to ensure data is accurate and reliable to ensure customer trust and reduce...


Permission to Play

Everyone agrees GDPR has changed the digital marketing paradigm. In the process, it’s also changed the marketing game—providing smart marketers an unprecedented opportunity to shine. While seeking unambiguous and continuous opt-in from customers, marketers have the obligation (and privilege) to take scrupulous care of customer communication. Those that do this well will reap big rewards. From interruption to permission Coined by marketing guru Seth Godin, Permission Marketing relies on consumers agreeing that you can market to them. Instead of interrupting large groups of consumers with broad messages, all over the place, it focusses on specific messages that reach the people who’ve said they want to hear from you. In Godin’s own words, it’s “the privilege (not the right) of delivering anticipated, personal and relevant messages to people who actually want to get them” (Godin, 1999). And the key element GDPR took care of for marketers is ‘anticipated’. By ensuring an ‘opt-in’ approach to customer data, GDPR has made sure we have explicit consent from customers to use their information. It may have been a slightly painful process to make this change, but with our systems adapted and new processes in place, the benefits are already clear: Greater trust – disclosing how we use customer data, up front, gives more reason for consumers to trust us with it. Some may even trust us with more detailed information than before. Economy of spend – data leads to the insights we need to deliver more targeted marketing campaigns, helping us make the most of budgets. Better brand perception – transparency around data and more relevant marketing both help to build more positive brand reputations. Greater focus – with limits on how long a company can hold onto customer data, databases are regularly ‘cleaned up’, with irrelevant or out-of-date contacts removed. So less time spent on disengaged consumers, more time focused on engaged consumers – and converting sales. With 20 years gone since the term Permission Marketing first appeared, the principle isn’t new. But tighter data regulations – specifically GDPR – have surely taken it from a recommended marketing approach to the de facto way of working. France Televisions, France’s number one broadcasting organisation implemented Oracle Blukai to hit both those objectives – significantly improve their marketing ROI but also be compliant with GDPR and the company’s own “Data Friendly” policy. Now that we have consumers’ explicit permission to use their data, we should take care not to squander the opportunities it brings – and that begins with keeping it safe. Thankfully, GDPR put cybersecurity on everyone’s agenda. Find out more about how modern marketers view data security and compliance in our recent report.

Everyone agrees GDPR has changed the digital marketing paradigm. In the process, it’s also changed the marketing game—providing smart marketers an unprecedented opportunity to shine. While seeking...


Your data is your brand value

Every marketer wants to build trust in their brand, because it fuels the business.  But while marketers are increasingly using data to build and measure reputation, they often ignore that in the same way a defective product can undermine their efforts, a data breach can be catastrophic. Data and The Brand Customer data is what makes smart, effective marketing possible. It allows us to reach the right people, at the right time, in the right way. It’s the difference between shouting into the wind and having a persuasive, informed conversation. It allows us to measure satisfaction, engagement and ultimately not only what people are buying and when but also how they perceive our brand. While brand value has many nuanced parts and is scrutinized by marketers, the wider data security is often forgotten. Secure data doesn’t really attract new customers. And data is held by all departments, be it HR or operations or finance.  And when data security is breached, that breach can happen anytime, to any department, to any set of data. We know the fallout can be devastating. Any sign of unsecure data can sway a purchasing decision from you to your competitor, and a breach can shatter the customer trust and the reputation you’ve spent years building. Your business suffers immediately and the brand could suffer long into the future. A dip in revenue can mean more pressure on your marketing team to find new business. But it’s now an uphill struggle. Your brand’s perception has changed, and the memory of that data breach can weigh it down for years to come. Damaged trust means fewer leads, conversions, and sales, making data security an issue for both brand and bottom line. And a challenge that requires collaboration. Mark-IT-ing Many consider data security the IT team’s concern – and from a technical perspective, it is. But we know that as soon as someone says the word ‘customer’, senior heads turn to the marketing department. As marketers, we’re on the front line of customer data. We gather it and then use it to inform campaigns, adjust our plans, and measure success. So how can we lead on customer data security? Set processes – if every team has its own solutions, the processes for using them and keeping the data secure will be different. Just having an agreed set of best practices in place can cut the chances of a data leak, and Non-siloed storage – sales, product, and finance teams store customer data too, likely in their own databases and systems. More storage locations mean more vulnerabilities, so by working with these teams to reviewing all systems, you can help IT to find a secure, central data storage approach. As the voice of the customer within any business, marketers are best placed to be the stewards of their data. But find out more about how all business leaders are facing the challenges posed by security in our recent report.

Every marketer wants to build trust in their brand, because it fuels the business.  But while marketers are increasingly using data to build and measure reputation, they often ignore that in the same...


Marketers embrace the data ethics challenge

If customers are going to trust that brands use their personal data responsibly, marketers first need confidence in their company’s ability to handle this information internally. We outline the crucial role marketing leaders will play in fostering a more ethical approach to data management. Today’s data protection regulation is not intended to punish brands.  Its aim is to make them accountable for the significant power they hold. And if harnessed correctly, it can even be an opportunity for brand reputation.  The crackdown we’ve seen in recent months, including a 50 million euro fine for Google and accusations that streaming services like Amazon Prime are breaking the law, should be a wake-up call for marketers everywhere to put ethics at the forefront of their data strategy.  But is it?  Our research reveals just 39% of marketing decision-makers are highly confident in their organisation’s ethical use of data. Tellingly, just 39% feel fully confident in their ability to manage data securely. Even if we accept that most companies entrust digital security to their IT department (which we shouldn’t) this figure is startlingly low. IT are not the ones interfacing with customers, nor are they drawing on enormous volumes of data to communicate with those customers directly each day.  Before customers and regulators can trust that brands are taking data protection and management seriously, marketing teams need to take responsibility for how within data is handled within their organisation. That doesn’t make them solely responsible for securing customer information, but they do have a central role to play in this joint mission for the entire business.  The need will only become more pressing as marketing automation and AI systems grow in popularity. These technologies have the potential to deliver enormous value for brands and customers alike, but they raise a number of ethical concerns around entrusting algorithms to make decisions about customer data at scale. Here, the combined efforts of IT, marketing and HR will be crucial in rolling out AI in a way that is responsible and serves people’s best interests. Reputation, customer loyalty, and shareholder confidence – all these factors are at risk without an ethical approach to customer data. There is a positive business potential here, in that your brand can be positively impacted and your customer data will be enriched. Learn more about the role marketers will play in addressing these issues in our recent report.

If customers are going to trust that brands use their personal data responsibly, marketers first need confidence in their company’s ability to handle this information internally. We outline the...


Keeping your data clever

Who wouldn’t want to eliminate time-consuming admin tasks in favor of strategic talent management activity? It’s no surprise HR executives are so excited about the promises of AI technology for automation efficiency. Along with the anticipation, though, keep this caveat in mind: AI and automation technologies can deliver if, and only if, they run on a foundation of clean, secure data.   The latest AI-powered cloud systems have a lot to offer HR professionals: • AI-based recruitment is more quicker, more efficient, and eliminates human bias •  AI can identify areas of job dissatisfaction and predict potential for churn •  AI can analyse different types of performance data to personalize training and get the best from employees In the current climate of skills shortages, finding and keeping the right talent drives the competitive edge. If recruitment data can be put in correlation with performance data, organizations can identify the people who will be successful in the long run. Brilliant HR leaders will use AI to support these core tasks as well as free time for more strategic C-level initiatives. But this holy grail of HR AI only exists with guaranteed data security and trustworthy information. Take the example of using AI for CV-screening: AI technology can be ‘trained’—using thousands of relevant applications and CV—to accurately mimic human intelligence and analysis. It’s important the system be trained correctly avoiding any built-in biases against candidates from certain backgrounds, ethnic groups or age bands.  If the data includes any such biases, the AI algorithms will as well. HR leaders need to start with the basics, building intelligent systems based on clean, secure and trustworthy data. If an organization bases employee management decisions on dirty data—different labels for the same role, multiple records for the same employee, missing elements—the value from automation and AI is minimal. What are the basics? • Cleaning out old data is a core part of the process. Companies need to retain employee files for certain lengths of time, but as soon as these are no longer needed for legal purposes, they should be purged. • Identity and access management (IAM) policies should include automatic provisioning and de-provisioning of users. When new cloud applications come online, the same access authorisation process should occur. • The right technology, designed to protect users, enhance data security, and ensure compliance. These will be cloud-based systems offering multi-layered security and including controls to evaluate risks, prevent unauthorised data disclosure and enforce data access controls. • A single source of the employee truth, including access and permissions as roles change and extend, is vital to data security. Smart HR leaders know deploying AI is core to improving people management innovation.  They also know data security and preparation need to come before full AI deployment. By integrating AI as a layer on top of a solid data foundation, they will see the full benefits on offer from artificially intelligent employee management systems. Read more about how today’s HR leaders think about AI and data in our report here.

Who wouldn’t want to eliminate time-consuming admin tasks in favor of strategic talent management activity? It’s no surprise HR executives are so excited about the promises of AI technology for...


AI can only analyse data, not people

Why do you work in HR? Most probably because you are interested in people and their welfare. You’re a people person. AI (Artificial intelligence) will probably become your new best friend in the next couple of years, but AI will never be human. Its limitations need to be understood and taken into account. Oracle’s latest global study "the adaptable business" proves that technology is key to ensure today’s productivity and success, including AI. AI is broadly assumed to be the leading technology. HR needs to get itself into a prime position to keep track of what is top of employees’ wishlist for technology. Plus it is vital that HR professionals use the latest technology like everybody else, so they can provide insights that will help business leaders understand the interdependencies of business and people. One company doing this is insurance firm AXA. AXA is using Oracle's AI-powered HCM application, which offers intelligent features such as smart candidate lists. As a large global company with many decentralised businesses, AXA’s HR team are tasked with managing 157,000 people across 56 countries. By making it quicker to integrate newly acquired businesses into the AXA HR system, and supporting data sharing and analysis locally, regionally or globally – all with the highest level of data security – Oracle HCM is allowing the team to enhance its service to the business. With access to this kind of smart technology, HR staff or line managers can simply ask a chatbot to source specific data points to gain insight into employees’ performance history. A pregnant worker who wants more details about the company maternity leave policy could just grab their mobile and chat to a bot – the AI might even suggest additional actions or activities based on the experiences of others. However, it is important to treat AI as an addition rather than a replacement for HR staff. While AI can be great as part of the recruitment process - attracting talent from a broader range of backgrounds than traditional recruiting processes for example – interviews are still vital to getting a feel for the right candidate. More critically, it is imperative to keep bias out of HR systems. There have been several cases where organisations have relied on AI, and been called out as racist or sexist. According to a study by Massachusetts Institute of Technology, thirty-five percent of images for darker-skinned women faced errors on facial recognition software, compared to only one percent for lighter-skinned males. Google, meanwhile, has decided to omit gender-based pronouns from its Smart Compose Gmail technology, as it cannot find a way to guarantee the software correctly predicts someone’s sex or gender identity, and avoid causing offence. Take the case of the pregnant worker asking the chatbot questions about their upcoming leave – the AI system might be programmed to automatically refer to the father of the baby, in an era where same-sex couples and single parents could just as well be the case. The key for HR staff is to be able to trust the data in front of you, so you can ensure the advice and information being passed to staff and used to form business decisions is accurate. AI can only see the data, not the people behind it; human interpretation is necessary to avoid built-in bias and offence. Find out more about how business leaders are looking at data security by checking our report here.

Why do you work in HR? Most probably because you are interested in people and their welfare. You’re a people person. AI (Artificial intelligence) will probably become your new best friend in the next...


See your staff in a new light

What if you empowered your employees to dictate HR best practices based on how they work best? By using emerging technologies such as AI, HR departments can quickly learn the optimal ways in which their people work, eliminating unnecessary systems and processes. In doing so, organisations can gain a deeper understanding of their people and adopt an urban planning approach to setting up standardized processes that make work easier and more effective. Dictating ‘best practice’ is often unhelpful, as few people want to have a process imposed on them. But the latest technologies (like Artificial Intelligence) can reveal how people work, and suggest changes to help them become more efficient and productive. That’s why – here at Oracle – we predict that by 2025, the productivity gains from AI and emerging technologies could be double what they are now. But what does this evolving approach look like? Our cities offer a compelling parallel. Desire paths and compulsory walkways Through the roads and walkways they build, urban planners try to control the flow of people and traffic around cities. But over time, unplanned pathways emerge. Well-worn shortcuts over patches of grass, and other ‘desire paths’, spring up where people have found their own routes for navigating the city. A similar thing happens within organisations: employees find their own ways of working, no matter the systems and recommended processes they’re given. So instead of imposing a way of working, perhaps we should analyse how it happens currently, and suggest incremental improvements. Instead of fighting the natural flow, AI can draw on everything from sentiment reports to interaction data to help us shape workflows and make them more productive – without ruffling feathers. And all while gaining a richer, more holistic understanding of employees, teams, and the organisation as a whole. Global, agile, informed AXA understands the power of this data. The global insurance giant used to have multiple core HR systems, spread across various business units, in a variety of countries. Working efficiently within the HR function was near impossible, let alone gaining an informed view of how AXA employees worked. But by moving to Oracle’s cloud-based HCM solution, this all changed. Now, this 166,000-strong company has centralized its HR data across 64 countries, sharing it so teams can analyse what they need, when they need. Staff members can manage their own careers, digitally, and standardised processes make work easier and smoother. And HR has a holistic view of the whole organisation, like an urban planner looking down on their city from a helicopter. When you let your people dictate how they want to work, everyone wins! Check out our latest research on how business leaders are approaching data security and compliance.

What if you empowered your employees to dictate HR best practices based on how they work best? By using emerging technologies such as AI, HR departments can quickly learn the optimal ways in which...


HR has become our moral compass for data protection

An ethical approach to data starts with employees. If people don’t manage information responsibly, how can we hope to track it, much less protect it? Education is the key to driving awareness, which is why HR must take the helm in driving this behavioural change across the business. Who would have thought flash drives would become our worst enemy? The convenience of USB sticks and mobile phones has made us more productive, but it has also created a logistical nightmare for businesses that need to track and manage all the data flowing around their organisation. Employees may take data management and security more seriously today, but these risky practices are still prevalent. Consider how companies manage performance reviews. Not long ago, or even still today, data from discussions with employees would be entered in a spreadsheet and shared across the business, with minimal record of who, what, or why it changed hands over time. This approach is or should be no longer acceptable, not just logistically but also from an ethical perspective – employees demand and deserve greater transparency into how their data is being used. Which brings us to the value of training and HR’s crucial role in driving a more conscientious approach to data management. Today, just 35% of HR decision-makers feel fully confident in their organisation’s ability to manage data securely, which is why companies like NatWest have launched data academies to train their employees on the value and power of data they work with each day. Extending this to the wider business, awareness and best-practice are the biggest culprits in the push to handle data ethically: 29% of respondents cited employees’ managing data through mobile devices or social platforms 28% cited a low attention to data confidentiality, and 24% cited outright blindness on how data is supposed be used Reading between the lines, this means companies need better training for their employees on the importance and implications of how they manage data. In essence, HR must act as the moral compass that brings about this change, helping to ensure employees across the business put ethics first when working with data. With the right processes in-place, there’s no reason that ethics and convenience can’t coexist. Encouragingly, 34% of HR leaders have made it a priority to raise awareness around data security threats, and 40% have a data management strategy place. These are major steps forward for a department that in many organisations is still transitioning to a data-driven way of working. There is more work to be done, but with HR serving as a strong moral compass every team in the business will move towards a more considered approach to data management. This greater focus on ethics won’t just help to secure sensitive information. It will also help HR to build a strong employer brand, which will in turn help them attract more data-conscious talent, improve productivity, and foster a more diverse working environment.   Discover how HR departments are contributing to their organisation’s data security in our report.

An ethical approach to data starts with employees. If people don’t manage information responsibly, how can we hope to track it, much less protect it? Education is the key to driving awareness, which...


Your data security is your weakest link

Data security is seen as a drag: it’s complicated; it stifles a marketer’s creativity; and it’s IT’s baby anyway. Sound familiar? The truth is that data security drives every aspect of the technology revolution that is transforming marketing. Marketers need to not just take responsibility, but take control. The idea that data security is boring vanishes once we understand that it’s essential to brand value. The average cost of a data breach is over US$3.8 million ─ with damaged reputation, lost customers and customer acquisition big contributors to the bill. The introduction of GDPR ups the stakes, with a potential €20 million fine. Your data security is intimately linked to your brand value. Any breach and the months spent in building your reputation are gone, forever. Yes, it’s a drag, yes, it seems to stifle creativity, but no, it’s not IT’s problem, it’s marketers problem too, and their suppliers. Time to take responsibility and time to take control. And before we even get to breach, data security encompasses data quality, and bad data will stifle a marketer’s creativity far more than any data protection regulation. One more reason to say that data security isn’t just IT’s concern, it’s Marketing’s. The cloud – hero or villain? The cloud is focusing attention on data security. Mission-critical applications, such as CRM and data analytics are streaming out of in-house datacentres. Oracle predicts that by 2025 80% of these applications will be cloud-based – yet 91% of businesses have security concerns about the shift. The fear seems to be that the cloud is inevitable, but so too is increased risk. The two outcomes are clearly incompatible – so is the cloud hero or villain? Neither, because cloud technology is like any tool, the way you use it is what matters. Cloud can make marketing more efficient, and allow for more creativity. But ultimately, any cloud solution relies on the quality, understanding and engagement that its users have with the data that underpins it. And that data should be secure and used according to legislation and what is ethical. So make no mistake, Marketing must take control, because data security is modern marketing. See how the numbers match up in our recent report on data security.

Data security is seen as a drag: it’s complicated; it stifles a marketer’s creativity; and it’s IT’s baby anyway. Sound familiar? The truth is that data security drives every aspect of the technology...


When HR goes beyond its borders.

People related data needs to be treated with the utmost care and diligence. Rather than seeing recent legislation and rising awareness that as an impediment to great sourcing, HR should rethink their approach and not only do the right thing in the right way but also use the opportunities offered by new technologies to recruit. Data and information about people was a free and open resource in our earlier days of the internet. But increased legislative protection and code (GDPR for one) combined with a more aware and enabled consumer, job seeker and media, has created a tighter, more protective covenant around such information. Doing the right thing and doing things right This leads to a more pronounced duty of care for us all - but particularly for those recruiting and sourcing professionals acting in a widely-accessed, open market - how we search, locate and source potential employees to our organisations. And yet, willingly, we all still placing ourselves, our information and potentially useful insight about us in places that can be searched and used. Incognito we are not We are still leaving data “vapour trails” in places where we are posting, thus sharing and exhibiting behaviours that could match what an employer is looking for. Membership of groups, communities of interest, practice coalitions, learning circles.  Posting and commenting on Medium blogs, creating YouTube playlists and curating information on Scoop.It sites.  Discerning practitioners, those with heightened interest and capability, are likely to be found through these still very open means.  Ethical and genuine methods of connection Recruiters beware; because any fake interest, hijacking of communities and spamming people who post is NOT what’s needed.  Oracle and LinkedIn’s recent affiliation presents a seamless connection between an HRIS and the world’s biggest professional network.  Through this, locating people, creating an intelligence-based view of their capabilities and potential will lead you to their groups, communities, posts, shares and affiliations. Your connection to that potential game-changing employee will come from a place of intelligence, curiosity and belief they may be “the one” and not some cut and paste “carpet bomb” introduction message to those returned from a search query. Emerging technologies And we haven’t even mentioned the Blockchain and its promise of decentralised, secure and undeniable accuracy of information about us.  Our qualifications; work-based accreditations; published journals and articles; evidence-based evaluation of performance and credentials could be validated through this means. When we choose to share our blockchain-validated information, there is the need to be careful with keys, access and sharing of such trusted information; and I suspect none of us are truly aware of the applied processes for this and so are just not ready for that - yet.  In summary Searching, sourcing and using information about people to find that perfect fit for their enterprise may appear somewhat curtailed by data legislation and a more aware public, yet the old adage of getting to know people and using tools to build the intelligence about them, could lead to a stronger more human form of effective hiring.  Relationships built on insight and experiences could be the killer app, alongside high-integrity information that potential hires choose to share with us.  It’s not so much an entirely new game, more a remix of new and old techniques to be the smartest sourcer in town. Check out our latest research on how business leaders are approaching data security and compliance.

People related data needs to be treated with the utmost care and diligence. Rather than seeing recent legislation and rising awareness that as an impediment to great sourcing, HR should rethink their...


Today’s data, tomorrow’s opportunity

By 2025 there will be 163 zettabytes of data – but a only 3% of this data will be analysed according to a Seagate/IDC study. To turn this goldmine of data into actions, the key is looking ahead, not behind. An organisation tackling this task head on is Shibuya Tourism Association, which provides information for the area surrounding the iconic Shibuya Crossing in Tokyo. The crossing, and beyond Over 5 million foreign tourists a year visit this scrambled intersection made infamous in films like Lost in Translation, as they come to photograph the 1000 plus people crossing the road in one go.  But, most come, take their obligatory photos, have a quick bite to eat and move on - only 15 per cent of visitors make it to the tourist information office, barely a 10 minute walk further on.  The result?  The surrounding area often remains a mystery. Wanting to change this, but with limited resources and an ambitious goal of attracting tens of millions more visitors in the run up to and during the forthcoming Tokyo Olympics, the tourist board decided to think differently, and looked to technology for help. Data as the foundation "Data is at the heart of what we are doing,” says Mr. Jungo Kanayama, Chairman of the Shibuya Tourism Association.  “By knowing who is coming into the area, where they are going and what they are doing, we can start to see patterns.  This means we can suggest the right local experiences for them and things to do, both during the day, when people are more interested in sightseeing and shopping and at night, when the focus is more on eating, accommodation and the nightlife in the area. " The power of the smart phone Harnessing the smart phone that comes as standard in most visitors’ pockets, the tourist association created a mobile app and installed a series of 1200+ beacons in the streets around the station to pinpoint visitors as they go past.  At the heart of the system, a smart data platform powered by Oracle Cloud, underpins the beacons and pulls back the information enabling the organisation to start to understand the people visiting, their preferences and the types of promotions that would have most effect.  The solution also lets the tourist association send information to passers-by.  As a result, the association can communicate with visitors, providing the information they are most likely to be interested in, even in advance, by advertising before they even come to the area.  Moving to a hospitality platform Longer term, the intention is to extend this valuable resource to other regional tourist operators via a "Hospitality platform".  Aimed at providing highly value-added services to visiting tourists it would allow different regions and business operators to cooperate and to share and utilize information. “These are exciting times, especially with key sporting events coming up like the Rugby World Cup and Olympics.  With Oracle Cloud, we can provide our visitors with their very own personal guide book.  This means we can be with them at all times, giving them ideas of the wonderful places to explore and information, so they have a reason to stay longer and discover the real Shibuya,” concludes Mr. Kanayama.   Data-driven marketing means you can make more accurate predictions about what your clients will do next, so you can understand not only past trends, but also focus your current and future efforts on where your buyers will be. By combining these techniques, you can build targeted campaigns that reach your customers with the right personalised message, and at the right time, even into the future. Find out more how the Leaders are leveraging Innovation in our report.

By 2025 there will be 163 zettabytes of data – but a only 3% of this data will be analysed according to a Seagate/IDC study. To turn this goldmine of data into actions, the key is looking ahead, not...