Friday Apr 06, 2012

Does your analytic solution tell you what questions to ask?

Analytic solutions exist to answer business questions. Conventional wisdom holds that if you can answer business questions quickly and accurately, you can take better business decisions and therefore achieve better business results and outperform the competition. Most business questions are well understood (read structured) so they are relatively easy to ask and answer. Questions like what were the revenues, cost of goods sold, margins, which regions and products outperformed/underperformed are relatively well understood and as a result most analytics solutions are well equipped to answer such questions.
Things get really interesting when you are looking for answers but you don’t know what questions to ask in the first place? That’s like an explorer looking to make new discoveries by exploration. An example of this scenario is the Center of Disease Control (CDC) in United States trying to find the vaccine for the latest strand of the swine flu virus. The researchers at CDC may try hundreds of options before finally discovering the vaccine. The exploration process is inherently messy and complex. The process is fraught with false starts, one question or a hunch leading to another and the final result may look entirely different from what was envisioned in the beginning. Speed and flexibility is the key; speed so the hundreds of possible options can be explored quickly and flexibility because almost everything about the problem, solutions and the process is unknown. 
Come to think of it, most organizations operate in an increasingly unknown or uncertain environment. Business Leaders have to take decisions based on a largely unknown view of the future. And since the value proposition of analytic solutions is to help the business leaders take better business decisions, for best results, consider adding information exploration and discovery capabilities to your analytic solution. Such exploratory analysis capabilities will help the business leaders perform even better by empowering them to refine their hunches, ask better questions and take better decisions. That’s your analytic system not only answering the questions but also suggesting what questions to ask in the first place.
Today, most leading analytic software vendors offer exploratory analysis products as part of their analytic solutions offerings. So, what characteristics should be top of mind while evaluating the various solutions? The answer is quite simply the same characteristics that are essential for exploration and analysis – speed & flexibility. Speed is required because the system inherently has to be agile to handle hundreds of different scenarios with large volumes of data across large user populations. Exploration happens at the speed of thought so make sure that you system is capable of operating at speed of thought. Flexibility is required because the exploration process from start to finish is full of unknowns; unknown questions, answers and hunches. So, make sure that the system is capable of managing and exploring all relevant data – structured or unstructured like databases, enterprise applications, tweets, social media updates, documents, texts, emails etc. and provides flexible Google like user interface to quickly explore all relevant data.
Getting Started
You can help business leaders become “Decision Masters” by augmenting your analytic solution with information discovery capabilities. For best results make sure that the solution you choose is enterprise class and allows advanced, yet intuitive, exploration and analysis of complex and varied data including structured, semi-structured and unstructured data.  You can learn more about Oracle’s exploratory analysis solutions by clicking here.

Friday Mar 30, 2012

Curious About Oracle's BI and Analytics Strategy?

Normally we use this blog space for discussing our business intelligence and analytic efforts along with our views and perspective on this very fast growing marketplace. However, I can't resist mentioning that we are having a great webcast coming up next week, so please do join Oracle's Mark Hurd and Balaji Yelamanchili as they unveil the latest advances in Oracle's strategy for placing analytics into the hands of every one of your decision makers-so that they can see more, think smarter, and act faster. Register now at http://bit.ly/HpAOJk for the Webcast and Live Chat: Wednesday, April 4, 2012 at 9 a.m. PT, 12 p.m. ET, 10 a.m. GMT.  You don't want to miss this event and thank you very much. 

Consumer Oriented Search In Oracle Endeca Information Discovery - Part 2

As discussed in my last blog posting on this topic, Information Discovery, a core capability of the Oracle Endeca Information Discovery solution enables businesses to search, discover and navigate through a wide variety of big data including structured, unstructured and semi-structured data. With search as a core advanced capabilities of our product it is important to understand some of the key differences and capabilities in the underlying data store of Oracle Endeca Information Discovery and that is our Endeca Server. In the last post on this subject, we talked about Exploratory Search capabilities along with support for cascading relevance. Additional search capabilities in the Endeca Server, which differentiate from simple keyword based "search boxes" in other Information Discovery products also include:

The Endeca Server Supports Set Search. 
The Endeca Server is organized around set retrieval, which means that it looks at groups of results (all the documents that match a search), as well as the relationship of each individual result to the set. Other approaches only compute the relevance of a document by comparing the document to the search query – not by comparing the document to all the others. For example, a search for “U.S.” in another approach might match to the title of a document and get a high ranking. But what if it were a collection of government documents in which “U.S.” appeared in many titles, making that clue less meaningful? A set analysis would reveal this and be used to adjust relevance accordingly.

The Endeca Server Supports Second-Order Relvance.
Unlike simple search interfaces in traditional BI tools, which provide limited relevance ranking, such as a list of results based on key word matching, Endeca enables users to determine the most salient terms to divide up the result. Determining this second-order relevance is the key to providing effective guidance.

Support for Queries and Filters.
Search is the most common query type, but hardly complete, and users need to express a wide range of queries. Oracle Endeca Information Discovery also includes navigation, interactive visualizations, analytics, range filters, geospatial filters, and other query types that are more commonly associated with BI tools. Unlike other approaches, these queries operate across structured, semi-structured and unstructured content stored in the Endeca Server. Furthermore, this set is easily extensible because the core engine allows for pluggable features to be added.
Like a search engine, queries are answered with a results list, ranked to put the most likely matches first. Unlike “black box” relevance solutions, which generalize one strategy for everyone, we believe that optimal relevance strategies vary across domains. Therefore, it provides line-of-business owners with a set of relevance modules that let them tune the best results based on their content.
The Endeca Server query result sets are summarized, which gives users guidance on how to refine and explore further. Summaries include Guided Navigation® (a form of faceted search), maps, charts, graphs, tag clouds, concept clusters, and clarification dialogs. Users don’t explicitly ask for these summaries; Oracle Endeca Information Discovery analytic applications provide the right ones, based on configurable controls and rules. For example, the analytic application might guide a procurement agent filtering for in-stock parts by visualizing the results on a map and calculating their average fulfillment time. Furthermore, the user can interact with summaries and filters without resorting to writing complex SQL queries. The user can simply just click to add filters. Within Oracle Endeca Information Discovery, all parts of the summaries are clickable and searchable.

We are living in a search driven society where business users really seem to enjoy entering information into a search box. We do this everyday as consumers and therefore, we have gotten used to looking for that box. However, the key to getting the right results is to guide that user in a way that provides additional Discovery, beyond what they may have anticipated. This is why these important and advanced features of search inside the Endeca Server have been so important. They have helped to guide our great customers to success. 

Friday Mar 16, 2012

Consumer Oriented Search In Oracle Endeca Information Discovery – Part 1

Information Discovery, a core capability of Oracle Endeca Information Discovery, enables business users to rapidly search, discover and navigate through a wide variety of big data including structured, unstructured and semi-structured data. One of the key capabilities, among many, that differentiate our solution from others in the Information Discovery market is our deep support for search across this growing amount of varied big data. Our method and approach is very different than classic simple keyword search that is found in may information discovery solutions. In this first part of a series on the topic of search, I will walk you through many of the key capabilities that go beyond the simple search box that you might experience in products where search was clearly an afterthought or attempt to catch up to our core capabilities in this area. Lets explore.


The core data management solution of Oracle Endeca Information Discovery is the Endeca Server, a hybrid search-analytical database that his highly scalable and column-oriented in nature. We will talk in more technical detail about the capabilities of the Endeca Server in future blog posts as this post is intended to give you a feel for the deep search capabilities that are an integral part of the Endeca Server.


The Endeca Server provides best-of-breed search features aw well as a new class of features that are the first to be designed around the requirement to bridge structured, semi-structured and unstructured big data. Some of the key features of search include type a heads, automatic alphanumeric spell corrections, positional search, Booleans, wildcarding, natural language, and category search and query classification dialogs. This is just a subset of the advanced search capabilities found in Oracle Endeca Information Discovery.


Search is an important feature that makes it possible for business users to explore on the diverse data sets the Endeca Server can hold at any one time. The search capabilities in the Endeca server differ from other Information Discovery products with simple “search boxes” in the following ways:

The Endeca Server Supports Exploratory Search

Enterprise data frequently requires the user to explore content through an ad hoc dialog, with guidance that helps them succeed. This has implications for how to design search features. Traditional search doesn’t assume a dialog, and so it uses relevance ranking to get its best guess to the top of the results list. It calculates many relevance factors for each query, like word frequency, distance, and meaning, and then reduces those many factors to a single score based on a proprietary “black box” formula. But how can a business users, searching, act on the information that the document is say only 38.1% relevant? In contrast, exploratory search gives users the opportunity to clarify what is relevant to them through refinements and summaries. This approach has received consumer endorsement through popular ecommerce sites where guided navigation across a broad range of products has helped consumers better discover choices that meet their, sometimes undetermined requirements. This same model exists in Oracle Endeca Information Discovery. In fact, the Endeca Server powers many of the most popular e-commerce sites in the world.

The Endeca Server Supports Cascading Relevance.

Traditional approaches of search reduce many relevance weights to a single score. This means that if a result with a good title match gets a similar score to one with an exact phrase match, they’ll appear next to each other in a list. But a user can’t deduce from their score why each got it’s ranking, even though that information could be valuable. Oracle Endeca Information Discovery takes a different approach. The Endeca Server stratifies results by a primary relevance strategy, and then breaks ties within a strata by ordering them with a secondary strategy, and so on. Application managers get the explicit means to compose these strategies based on their knowledge of their own domain. This approach gives both business users and managers a deterministic way to set and understand relevance.


Now that you have an understanding of two of the core search capabilities in Oracle Endeca Information Discovery, our next blog post on this topic will discuss more advanced features including set search, second-order relevance as well as an understanding of faceted search mechanisms that include queries and filters.


 

Saturday Feb 25, 2012

Driving Analytic Advantage

Digital data volumes are increasing tenfold every five years, yet more than 31% of executives say they are not getting the information they need to make important decisions, and 36% say their business units and functional operations are making decisions based on inconsistent information. The resulting “analysis paralysis” is costing the US economy alone over $900 billion per year according to one recent study. Many organizations are turning these challenges into competitive advantage. What are the issues and how can analytics help provide a competitive edge, and drive continuous performance improvement?

Challenges in Managing Business Performance

There are a number of fault lines that interrupt the continuous flow of business processes in the enterprise. The primary focus of ERP, HCM and CRM systems has been to simplify and standardize operational processes. These systems have been very successful over the years but in parallel, analytic systems have been developed to enable you to analyze past performance in areas such as marketing effectiveness, workforce dynamics and customer profitability. Since transaction and analytic systems were created separately, your ability to connect the dots between operational variances and root causes has been elusive.

Furthermore, planning processes have been detached from both operations and analysis. This discontinuity makes it difficult, even impossible for you to achieve a dynamic planning environment where strategic plans cascade to operational plans and forecasts in manufacturing, human resources, finance, sales and marketing. The disconnects between planning, operations and analysis are one of the main challenges of analytic systems, but they also represent one of the biggest opportunities.

While analytics has emerged as a top priority because of its ability to provide deeper insight into business performance, there are obstacles that prevent its full potential from being realized. The proliferation of analytic tools across the organization and the corresponding data silos that exist make it difficult for you to leverage best practices, collaborate across functions and confidently see one version of the truth. People need to have a single, simple way of defining KPI’s so they can quickly align around complete, accurate and timely information and spend their time solving problems instead of gathering and correlating data.

In today’s volatile economic and market environment, analytic requirements change frequently, often exceeding 50% per year. To operate as a competitive organization you must have the capability to adapt to changing business requirements. Static, inflexible systems are a drag on agile business management. You need the ability to quickly visualize the status of performance that’s relevant to your role regardless of location – at your desk, in the factory or on the road – and have the confidence of knowing that you’re seeing current, accurate information.

Evolving from Efficiency to Effectiveness to Transformation

Given these daunting challenges, how do you get started and what's the best strategy for building an analytic roadmap for your company? Oracle believes that there are three major stages in deploying analytics.  First, focus on improving operational efficiency by making insights pervasive and consistent across the organization while lowering total cost of ownership.    Second, analytic initiatives should aim to increase the operational effectiveness of decision makers.  Beyond gaining insight, operational effectiveness is about cascading strategy into operations, and creating more dynamic financial and operational plans that react and respond to a changing environment.

Third and most important, when deployed strategically analytics can be transformative for your company. When linking insights to action, decisions can be optimized and advantage can be created.  By combining unstructured data with data warehouse, new insights and patterns can found.  And through engineered systems new analytic applications can be created with extreme performance advantages.

Efficiency – Doing the Current Things Right

BI Platform Standardization. To create greater operational efficiency you need to standardize on an enterprise platform that can meet the diverse and continuously changing needs of your organization. The Oracle BI Foundation integrates the capabilities of multiple BI tools into a single, unified technology platform that supports the full spectrum of analytic requirements, including reports, dashboards, scorecards, scenario analysis, and ad-hoc query and analysis.

A unique Common Enterprise Information Model centralizes all metrics, calculations and assumptions which provide your users with confidence in the data, because the definitions are consistent regardless of where or how the information is accessed. Your users are insulated from the complexities of traditional BI tools enabling “self-service BI” which minimizes their reliance on IT to generate reports.

Workforces are increasingly mobile and the demand for access ‘on the go’ is exploding due the popularity of the Apple iPad and other tablet devices. In a recent report, Gartner estimates that over the next several years more than 33% of BI information will be consumed on mobile devices. Oracle identified this trend long ago and includes mobile capability in the Oracle BI Foundation. Unlike pure-play mobile BI vendors, Oracle’s solution shares common metadata, common definitions, and common infrastructure across web and mobile devices, meaning that you can see exactly the same information regardless of where you want to go.

Effectiveness – Doing the Right Things

Enterprise Performance Management. Core to improving operational effectiveness is linking strategy with execution. Leading companies have turned to Enterprise Performance Management (EPM) solutions to achieve this objective. Oracle leads this market with the most complete suite of EPM applications that span strategic, financial and operational planning areas.

Customers in all industries use EPM applications to drive agility and alignment into their enterprise planning processes. Annual financial plans are informed by strategic assumptions. These include product, customer, and business unit profitability models that can be created using Oracle’s cost management and profitability application. Through direct integration with ERP systems, baseline plans, forecasts and monthly updates can be informed by up to the minute actual information from the general ledger. Top down and bottoms up approaches can be reconciled and rolling forecasts provide more meaning to variance analysis. Additionally, Oracle has extended our enterprise planning solution to address the specific needs of workforce planning, capital asset planning and project planning. These modular solutions directly integrate with Oracle’s financial planning application to ensure that plans are connected and aligned to support the ongoing operational needs of your company.

Packaged Analytic Applications. Another key attribute of improving operational effectiveness is to challenge conventional wisdom and not build data warehouses from scratch. Although every company has unique reporting and analysis requirements, many can be addressed through packaged analytic applications.

The basic analytic requirements of your finance, HR, sales and procurement teams typically do not vary widely among different companies or industries. For example, finance departments in nearly all private and public sectors need to continuously monitor trends and variances of general ledger accounts, receivables, fixed assets and payable. Oracle is the only vendor that offers a comprehensive family of more than 80 packaged analytic applications for every major business function.

By using Oracle BI Applications, finance professionals have visibility into operating expenses, account balances and purchasing patterns. HR professionals can gain insights into global headcount status, attrition rates and the effectiveness of learning programs. Procurement and Operations professionals can track supplier performance and inventory trends, trade discounts and warranty return costs. In marketing, your managers can monitor the efficacy of promotions and campaigns and make adjustments to maximize success rates. Your sales managers can more effectively forecast revenues and transactions, manage pipeline and track key opportunities. Service teams can optimize call center and depot staffing levels, identify problem areas that need attention, and respond more effectively to customer service call volumes.

All of Oracle’s BI Applications are built on the Oracle BI Foundation, and are pre-integrated with Oracle ERP and CRM applications. Each application features dashboards, metrics, KPI’s and derived calculations based on industry best practices from over 3,000 deployments. Each application can be deployed individually or together, as each module conforms to a common enterprise data model.

Transformation – Doing New Things

Intelligent Business Process. To reach a transformative level you will need to consider a way of linking your planning and analytic systems with the operational systems that run the business on a daily basis. Oracle’s analytic strategy enables you to create an Intelligent Business Process that is connected and continuous.  It supports all three aspects of performance management including shaping strategy through financial and operational planning, taking action to execute the strategy across the business operations and measuring the results to enable fact-based decisions and continuous improvement. 

Delivering on the promise of the Intelligent Business Process requires that analytics be tightly integrated with operational processes. IDC coined the term “Closed Loop Analytics”, describing this type of integration but until recently, the promise has not been fulfilled. Conventional BI platforms can deliver insight in the form of dashboards and reports, but in order to take action based on that insight, you typically need to leave the BI environment and enter some other system. Oracle has introduced an innovative new capability the Oracle BI Foundation that breaks down the traditional walls between analysis and execution by allowing you to initiate actions, such as workflows and notifications, directly from your reports and dashboards. This direct connection of insight with action has also been built into Oracle’s Fusion Applications as a core capability. The compelling result is that your business process is now continuous – you can discover variances, drill to root cause, assess alternatives and initiate action all within the same system – and confidently move forward with the right action at the right time.

Visualization. Linking cause and effect, identifying patterns buried in massive databases has been the purview of statisticians and business analysts. Visualization tools have provided partial solutions but are constrained by data capacity or memory. To overcome these challenges, Oracle developed the industry’s first engineered system which combines analytic software, an in-memory database and hardware platform all built, tested and optimized together. Unlike stand-alone data discovery tools, Oracle Exalytics provided extreme performance and unconstrained visualization allowing users to navigate and explore information at the speed of thought.

Big Data. It’s estimated that 95% of the worlds’ data is unstructured, which is driving the need to store, combine, access and analyze this “big data”. Whether it’s social media activity, web logs, warranty claims, call center activity, movement of assets with RFID tags or sensor data, the need to gain insight on these new sources is growing. Oracle offers the broadest portfolio of solutions to help you acquire, organize analyze this diverse data alongside your existing enterprise to find new insights and capitalize on hidden relationships. The Oracle Big Data Appliance is the first engineered system optimized for acquiring, organizing and loading unstructured data into Oracle Database 11g. Oracle R Enterprise allows you to run existing R applications directly against data stored in Oracle Database 11g.

How Oracle Can Help

To address the complex challenges associated with driving improvement in business performance, Oracle’s analytic strategy enables you to progress from operational efficiency to operational effectiveness to business transformation. This strategy incorporates a powerful and flexible BI Foundation which supports an extensive range of analytic needs, packaged analytic applications based on business best practices, and EPM solutions that link strategy with execution. It lets you access data from all types of sources, consume information when and where you choose, and expand or customize your analytic environment based on business requirements rather than on technology restrictions.

What does it mean? By establishing a reliable and open foundation, you can get information when you want it, visualize results and trends in the right context, and have the confidence of knowing that there is one source of truth. By creating an Intelligent Business Process, you will connect strategy with operations and analysis, and move towards fact-based decisions. This approach is the basis for continuous improvement and for increasing the competitiveness of your organization in a rapidly changing world.

Monday Feb 13, 2012

Expanding Our Business Intelligence Horizons

It is a real pleasure to start blogging here along side my new colleagues from Oracle after going thru the on-boarding process to become a new Oracle employee post the acquisition of Endeca by Oracle announced this past fall. Speaking for our entire team,  we are very excited to be part of the Oracle Business Intelligence product line and team. Its been an amazing adventure. We really appreciate all the support from our customers who have been huge advocate of what has been known as Endeca Latitude and now known as Oracle Endeca Information Discovery.

My goals with my blog posts are to share with you observations, perspectives and insight on the Data Discovery market and technology as well as our product and its capabilities. My style is to have a dialogue, tell a story, dig down into technical topics, use cases and bring you additional insight on the importance of Data Discovery. I hope you will enjoy reading these blog posts as well as others who are contributing to this blog.

If this is your first exposure to Oracle Endeca Information Discovery, you will find the various features and benefits of our product at this landing page on  oracle.com You will also find a data sheet that will walk you thru some of the core elements of our platform. This is a good starting point for getting oriented to our product line.

For my next post, I'll discuss some of the core use cases for Oracle Endeca Information Discovery. In the meantime, thanks again for visiting the blog.

Tuesday Feb 07, 2012

Big Data Analytics – The Journey from Transactions to Interactions

Big Data Defined

Enterprise systems have long been designed around capturing, managing and analyzing business transactions e.g. marketing, sales, support activities etc. However, lately with the evolution of automation and Web 2.0 technologies like blogs, status updates, tweets etc. there has been an explosive growth in the arena of machine and consumer generated data. Defined as “Big Data”, this data is characterized by attributes like volume, variety, velocity and complexity and essentially represents machine and consumer interactions.

Case for Big Data Analysis

Machine and consumer interaction data is forward looking in nature. This data available from sensors, web logs, chats, status updates, tweets etc. is a leading indicator of system and consumer behavior. Therefore this data is the best indicator of consumer’s decision process, intent, sentiments and system performance. Transactions on the other hand are lagging indicators of system or consumer behavior. By definition leading indicators are more speculative and less reliable compared to lagging indicators; however, to predict the future with any confidence a combination of both leading and lagging indicators is required. That’s where the value of big data analysis comes in, by combining system and consumer interactions and transactions, organizations can better predict the consumer decision process, intent sentiments and future system performance leading to revenue growth, lower costs, better profitability and better designed systems.

So, which business areas will benefit via big data analysis? Think of areas where decision-making under uncertainty is required. Areas like new product introduction, risk assessment, fraud detection, advertising and promotional campaigns, demand forecasting, inventory management and capital investments will particularly benefit by having a better read on the future.

 Big Data Analytics Lifecycle

The big data analytics lifecycle includes steps like acquire, organize and analyze. Big data or machine/consumer interaction data is characterized by attributes like volume, velocity and variety and common sources of such data include sensors, web logs, status updates and tweets etc. The analytics process starts with data acquisition. The structure and content of big data can’t be known upfront and is subject to change in-flight so the data acquisition systems have to be designed for flexibility and variability; no predefined data structures, dynamic structures are a norm. The organization step entails moving the data in well defined structures so relationships can be established and the data across sources can be combined to get a complete picture. Finally the analysis step completes the lifecycle by providing rich business insights for revenue growth, lower costs and better profitability. Flexibility being the norm, the analysis systems should be discovery-oriented and explorative as opposed to prescriptive.

Getting Started

Oracle offers the broadest and most integrated portfolio of products to help you acquire and organize these diverse data sources and analyzes them alongside your existing data to find new insights and capitalize on hidden relationships. Learn how Oracle helps you acquire, organize, and analyze your big data by clicking here.

Thursday Nov 17, 2011

Introducing the Industry's First Analytics Machine, Oracle Exalytics

Analytics is all about gaining insights from the data for better decision making. The business press is abuzz with examples of leading organizations across the world using data-driven insights for strategic, financial and operational excellence. A recent study on “data-driven decision making” conducted by researchers at MIT and Wharton provides empirical evidence that “firms that adopt data-driven decision making have output and productivity that is 5-6% higher than the competition”. The potential payoff for firms can range from higher shareholder value to a market leadership position.

However, the vision of delivering fast, interactive, insightful analytics has remained elusive for most organizations. Most enterprise IT organizations continue to struggle to deliver actionable analytics due to time-sensitive, sprawling requirements and ever tightening budgets. The issue is further exasperated by the fact that most enterprise analytics solutions require dealing with a number of hardware, software, storage and networking vendors and precious resources are wasted integrating the hardware and software components to deliver a complete analytical solution.

Oracle Exalytics In-Memory Machine is the world’s first engineered system specifically designed to deliver high performance analysis, modeling and planning. Built using industry-standard hardware, market-leading business intelligence software and in-memory database technology, Oracle Exalytics is an optimized system that delivers answers to all your business questions with unmatched speed, intelligence, simplicity and manageability.

Oracle Exalytics’s unmatched speed, visualizations and scalability delivers extreme performance for existing analytical and enterprise performance management applications and enables a new class of intelligent applications like Yield Management, Revenue Management, Demand Forecasting, Inventory Management, Pricing Optimization, Profitability Management, Rolling Forecast and Virtual Close etc.

Requiring no application redesign, Oracle Exalytics can be deployed in existing IT environments by itself or in conjunction with Oracle Exadata and/or Oracle Exalogic to enable extreme performance and best in class user experience. Based on proven hardware, software and in-memory technology, Oracle Exalytics lowers the total cost of ownership, reduces operational risk and provides unprecedented analytical capability for workgroup, departmental and enterprise wide deployments.


Click here to learn more about Oracle Exalytics.

 

Friday Jul 22, 2011

Data Visualization and Mobile BI

I flew up to the OAUG Connection Point BI & EPM event in Seattle this week to deliver a keynote presentation, and was lucky enough to catch Edgewater/Ranzal consultant Iain Curtain’s awesome presentation on data visualization. The topic has been on my mind lately for several reasons. Now that Oracle is delivering BI capabilities on the iPad, I’m finding that my favorite dashboards are those that spotlight the visuals, and are lighter on the numeric tables. The bright, crisp resolution of the iPad, combined with its’ smaller than a laptop display area, make charts, maps, and pictures especially important for mobile dashboards. Those killer new visualizations that are in the Oracle BI 11g release look fantastic on the iPad! Iain shared some best practice design principles for data visualization, informed by his years of field experience and a few healthy doses of Edward Tufte and Stephen Few.

If you missed the OAUG Connection Point event in Seattle this week, odds are good that you’ll get another chance to catch Iain at the OAUG BI SIG Meeting at Oracle Open World on Sunday, October 1st, or at the next OAUG Connection Point event in November in Atlanta. And if you just can’t wait until fall, Iain has written a short blog on the topic.

Speaking data visualization, Louis Columbus, a longtime friend, industry colleague, and maniacal blogger about all things related to business and tech, tipped me off to comScore Data Mine, a web site that is chock full of visualizations that render a million fascinating factoids about global adoption of technology and other trends. I highly recommend giving it a quick look. You’ll probably end up bookmarking it.

Thursday Jul 14, 2011

Business Intelligence Competency Center

The topic of competency centers and centers of excellence is coming up much more frequently in recent months. Some of the questions that I hear consistently include: How do we define standardized metrics across the organization? What are best practices for implementing and managing a BI system? Where do we start, and what’s the best rollout approach – by department, business unit or region? How can we leverage the knowledge and skills of BI experts in other departments to help us?

Business Intelligence has become a core part of the enterprise IT environment. Most companies and public agencies either have BI, or they are trying to implement it. Selecting and deploying BI tools and applications represent only part of the overall formula for success. The Business Intelligence Competency Center (BICC) draws together the software, people, communication, processes and governance. It can create leverage and increase the ROI of the entire BI program.

People: CXO sponsorship and leadership, and detailed project management are key to driving the visibility and impact of a BICC. People representing stakeholder groups must be fully or partially dedicated to a BICC organization, with their compensation tied to specific outcomes.

Processes: standardizing toolsets and processes will help ensure consistency, lower cost, lower risk and faster implementations. This may mean, for example, that SLA’s are negotiated with constituent groups, that BI Applications are initially deployed with 90% pre-built content, or that LOB’s become responsible for their own reporting and analysis.

Communication: establishing a Competency Center means zeroing in on practices and competencies that everyone can use. It may also mean that some processes and some job content may have to change. Continuous communication about the rationale and the benefits is necessary to get, and to keep everyone informed, aligned and motivated.

Governance: silos of information and software, different and competing interests, friction between business and IT – these are all a part of life in large organizations. Among the roles of the BICC are assessing differing points of view, establishing standards for data format and quality, technology and processes, and enforcing policies and guidelines for user adoption. Governance must have teeth and be backed by management, or people will default back to inefficient silos.

Oracle provides a technology approach to Business Intelligence that supports and enables the concept of a BICC. The Oracle Business Intelligence Foundation is a single platform supporting all types of source systems, applications, analyses and use profiles. Our single enterprise information model is a cross-functional data model that enables people to agree on a single set of metrics. Oracle BI is tightly integrated with Oracle Middleware and Oracle Applications, simplifying deployment and management of the stack.

For some organizations, the hard part about creating a BICC can be defining a centralized structure and bringing about sustainable organization and cultural change that’s needed to support it. The upside is faster deployments, increased collaboration and alignment, lower TCO and risk, and higher ROI across the business. The BICC is a concept whose time has come.

I’d love to hear your experience, successes and challenges in establishing a BICC in your company.

Monday May 16, 2011

The Intelligent Business Process – Closing the Action Loop

Business processes are innately cross-functional, yet enterprise software has evolved in silos. We have reached the point where analytics can access information from multiple sources across the organization and provide a cross-functional view of performance. The question now is, having gained that degree of insight, how do people decide on the best action and then execute that action, within a timeframe that’s short enough to influence quarterly business results?

Business processes are the threads that make up the fabric of an organization. Improving the efficiency of business processes, and the effectiveness of their intersections, is the ultimate goal. BI systems allow people to monitor process through performance metrics. They can also identify variances, direct people to relevant dashboards and reports, and enable them to drill around to understand triggers and root cause. In instances where location is a key factor, extending the data from reports and tables into maps and pictures can help to accelerate insight. Finding the problem is now the easy part; deciding what to do about it and taking confident action can materially affect outcomes, but they are harder to do.

What’s needed is a single software environment that begins with an understanding of the problem, let’s people experiment with different courses of action, and then rapidly executes the desired actions. A decision involves making a selection from a set of alternative choices that may take into account multiple simultaneous factors such as cost, time, supply, demand, competition, discount, etc. To enable business people to evaluate alternatives, they need a powerful analysis tool that’s easy to use, keeps data in context, and allows them to quickly collaborate across functions. Today most people use Excel for analysis and Outlook for collaboration. Together these solutions are inadequate for reaching a clear enterprise decision.

Once the right decision is made, the question then is – how to put it into action? Closing the remaining gap between observation and intervention requires that analytic systems be tightly integrated with transaction systems, so that they operate seamlessly when required. People want to move beyond the state where enterprise software constrains business procedures, towards an environment where systems support their way of operating and enabling an effective execution of business strategy. It means that there must be a logical, consistent connection between the decision that they’ve made, and the action that they take as a result.

If the question is – how can people decide on the best action and then execute, within a timeframe that’s short enough to influence quarterly business results – the answer is that they need an Intelligent Business Process. If the question is – where can they get it? The answer is – the Action Framework, which links analytics with core business applications. Action Framework is one of the key distinguishing capabilities of the Oracle Business Intelligence Foundation.

Monday May 09, 2011

Are you underutilizing your most important corporate asset, data?

It’s a fascinating time to be in the data management business. Pundits are using terms like “oil” and “soil” to describe the business value of data. The Economist magazine in a special report on managing information published in 2010 featured a quote from a computer expert describing the current times as the “industrial revolution of data”. The same report stated “data as becoming the new raw material of business: an economic input almost on a par with capital and labor”. To say data is important to running a business is an understatement, looks like storing, managing and analyzing the data could well be difference between success and failure. Pundits agree that across all the data available in an organization, 20% is structured and 80% unstructured. Structured data refers to the human generated data like orders, leads, support calls etc. which is generally well stored, managed and analyzed. Unstructured data refers to machine generated data like RFID sensors, web logs, application logs, click streams etc. which is loosely stored and infrequently analyzed to drive business decisions. This is not to say that the unstructured data is not analyzed at all, it is generally used to drive technological decisions like improving applications and systems performance. So, in essence, organizations are using only 20% of their data to run the business. Imagine running a business where 80% of your labor or capital is not utilized…how terribly unproductive, yet leading organizations around the world are doing just that day in and day out. Lot of businesses takes comfort in fact that they are really not data oriented business. Conventional wisdom states that structured and unstructured data is definitely relevant to online e-commerce businesses like Google, Facebook, eBay etc. but the unstructured data is of not much use to traditional businesses like manufacturing, utilities, consumer goods etc. Nothing could be further from the truth. So, how can a manufacturing business like automobile manufacturer benefit from analyzing both structured and unstructured data? Automobile buying just like any big ticket item purchase involves the traditional buying steps like need recognisition, information search, and alternative evaluation and purchase decision. The buyers spend a lot of time on the manufacturers or 3rd party information provider websites generating unstructured data around making selections, gaining information and comparing alternatives. This user behavioral data can be constantly analyzed and combined with the structured “compare vehicle” section of the websites to make the comparative selection dynamic and based on user behavior vs. a static list. Similarly, the attitudinal data generated by the customers around a vehicle’s features can be used as an input to improve the vehicle design process. Another example can be around achieving balance between mass customization and mass production with a service like NIKEid. NIKEiD is a service provided by Nike allowing customers to personalize and design their own Nike merchandise. NIKEiD offers online services as well as physical studios in different countries around the world. Mass customization provides personalization but without mass production the cost and lead time is prohibitive. NIKEid can use the unstructured user generated design data to identify the top selling merchandise and sell them as innovatively designed, semi-mass produced items at lower cost, with less lead time and at higher volumes generating better profits. E.g. NIKEiD’s unstructured personalization and design data can be used to identify major trends like demand for “shoes with a smaller carbon footprint” or “green shoes” and can be used to launch a new mass produced product line. These are just a few examples on how data can be used as a strategic asset to drive profitable business performance. In closing, as Rollin Ford, CIO of Wal-mart says “ Every day I wake up and ask, how do I flow, manage and analyze data better?”, data is your most strategic asset which could well be way underutilized. So, it’s time to ask the tough questions and start defining a comprehensive data management strategy, one that includes people, processes and technology and addresses all of your corporate data both structured and unstructured.

Friday Mar 18, 2011

Mobile BI Comes of Age

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