Hennen has identified several closely related trends that could play a significant role in the future: elastic cloud computing, the accelerated development of applied mathematics, such as artificial intelligence (AI), and a veritable data explosion. “These three developments – improved mathematics, significantly greater computing power and increasing quantities of data – can be combined to solve bigger and more complex problems. What’s more, you can do so quicker, more accurately and in a more integrated fashion, which will generally lead to better decisions. As global digitization continues to ramp up, it makes sense that more and more businesses strive to get involved and become a data driven company. However, danger lurks in taking a solely technological approach and neglecting the human and organizational aspects of the business.”

You need more than just technology

Hennen agrees that technology often gets people very excited. “They expect a lot from it.” He also emphasizes, though, that state-of-the-art technology adds little value on its own, if no attention is paid to the corresponding business case, strategy, training and required culture shift. “Technology must meet the organization’s need at the specific maturity stage. It should also comply with what people need and want from it, ánd can do with it. We can distinguish four different types of technologies: the technology of visualization and interaction, the technology of applied mathematics, the technology of unlocking data and data centralization and the technology that supports business processes. All four types of technology require a strategic approach. It is often thought that technology works best when it can be standardized but is definitely not always necessary. You can also agree on what you expect from a technology and how it can be integrated with another technology. I do not care whether a data scientist builds a mathematical model in R or Python, as long as the code meets all quality criteria and it leads to the exact same results and improved decision-making.”

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“It is often thought that technology works best when it can be standardized but is definitely not always necessary.”

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Technology is first and foremost about people, says Hennen. “Anyone can proclaim that you need to adopt AI to survive, but there are far fewer people who understand what it actually is and how it can lead to better decisions. AI is useless if your organization does not have the necessary talent. Companies looking to become data driven will make the wrong decisions if they have people with the wrong knowledge at the helm. I still see it happen far too often. You have to approach AI from an economic and a technological angle. That's talent. CxOs today are usually highly experienced, but they usually lack experience in digitization and data driven decision-making. People often think that ‘talent’ revolves around hiring young people who will just go ahead and change the company. Just give them good equipment and cast them as the bright young minds who will transform the organization into a data driven and digital one. It’s undoubtedly a piece of the puzzle, but you’ll also have to think about leadership talent. Who will drive change, who will help propagate the vision and who will inspire young talent? After all, employees will always model their boss’s behavior in the end.”

Implementing innovations

The necessity of becoming a data driven company is closely connected to technological developments. These fast-paced developments constantly lead to new possibilities. Organizations are eager to take full advantage of these opportunities for fear of falling behind. But how can you guarantee a successful rollout throughout the entire organization? According to Hennen, this largely depends on the manner of cooperation within an organization. “Ideally, your organization is capable of innovating, using the tools available to it and experimenting with them. If these experiments work out, your organization will be able to create something that can lead to innovations actually being produced. This final step may sound obvious, but it is often forgotten.” It is something that Hennen sees many organizations struggle with. “If there are 40 departments in your company that are all building Google-like tools, things are bound to go wrong and end up not seeing the light of day at all. Companies should not want to compare themselves to the Google in the first place, because they aren’t Google.

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“If there are 40 departments in your company that are all building Google-like tools, things are bound to go wrong and end up not seeing the light of day at all.”

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You also often see they usually do not have a carefully defined business problem and work on all sorts of odds and ends. Growing into a data driven company therefore requires a central platform from which all those initiatives can be launched, a technological challenge that companies are only now starting to address. Many companies are creating platforms that other organizations can use to run their AI applications, which is something many organizations are still struggling with. Some companies are slightly ahead of the curve, such as Shell, and many companies build their platform themselves. This brings platform maintenance into the equation, which most companies just don’t have the people for. The result is that they’ll start occupying themselves with non-core tasks or neglect the platform altogether, which can have consequences that lead to money down the drain. Many companies will of course have IT specialists, but they should be working on your core profession, rather than figuring out how to keep a platform up and running that you could have purchased elsewhere. It’s best to stick to the old IT adage of buy before reuse before build.” As Hennen puts it: “every man to their trade.”

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“It’s best to stick to the old IT adage of buy before reuse before build.”

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The attraction of data

In addition to technology, organizations are more attracted to data than ever before, and using data has truly taken off. Hennen has seen many organizations haphazardly collect as much data as possible, seeking to get off to a head start. “This is not necessarily a flawed idea, but data are useless if you don’t determine which data you need and what you want to do with them first. Too many companies have started working with data, but do not pay enough attention to organizing it and establishing a central data platform so that they can be easily accessed. These companies have recognized the importance of data but have failed to realize that you need to lay data foundations and make the necessary investments to it. Overall, the developments in data and technology are fairly similar, as these two fields are rather closely connected.

"Data are useless if you don’t determine which data you need and what you want to do with them first.”