Latest Digital Trends and Business Transformation Stories from the Middle East

You can’t fake it til you make it.

Angela Mazza Teufer
Senior Vice President ERPM WE, ERPM North Install Base

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.

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