If the main question is how best to make the most of your data, you should first of all question your company's strategy, its growth objectives and, increasingly, its constraints, both internal and external, present and future. It is the answers to these questions, which may hold a few surprises in store, that will determine the way forward.
Where do we start with data?
Do public and private organisations know how to work with their data? The landscape is disparate, to say the least. The data ball seems to be all tangled up, it's not easy to find the thread to pull on, and there is a risk of stagnation or, conversely, aborted projects.
Yet there is no longer any doubt. All sectors need to gain a better understanding of their end customers (or the expectations of their constituents), to project their areas of growth over 3 to 5 years and to develop new services, and all this presupposes collecting, processing, analysing and exploiting data.
And because there is no longer any doubt about the value of this approach, companies are trying it out and launching a number of initiatives, not always successful or followed up. It's as if there's something fundamental missing from the thinking process, the essential glue that holds things together.
And the problem arises no matter which way you look at it: equipping yourself with a large number of analysis tools, building a datalake, assembling a team of experienced data scientists, etc., often doesn't lead to the hoped-for results. The datalake remains hopelessly empty, the team of analysts is unable to make itself heard or understood, and IT budgets are strained.
Data-driven or driven by perceived urgency?
Since data is strategic by nature, it should logically mirror corporate strategy. The first surprise is that companies don't always have it. They produce and sell without necessarily planning for the medium and long term. Without a corporate strategy, it is obviously illusory to try and build a data strategy, as the two are intimately linked.
As for those that do, few really take the time to align their data strategy with it. This is quite understandable, having said that. The subject is pre-empted by technologists and is proving to be fairly dry. Not to mention a certain pressure to deliver, which weighs more heavily than you might imagine on the shoulders of managers. Added to all this are public sector initiatives whose relevance may be questionable, such as AI diagnostics aimed at organisations with little or no IT equipment or stifled by their technical debt. There are no bad tools in principle. On the other hand, there are certainly bad timings.
How can I add value to my data?
This is the question that comes up most often in preliminary discussions. But it comes far too early. There are many considerations to be taken into account beforehand. What are we looking for? If the aim is to improve quality (of both products and processes), it makes no sense to study data collection solutions if the data does not exist. However powerful it may be, a CRM like SAP, for example, will never deliver more than it was designed to do.
The point, then, is to question the data that is available. Many organisations assume that they have sufficient data, but this is not often the case. The databases used generally represent very small volumes. And many of them do not provide data that is relevant to the issues raised.
On the other hand, there are those who realise how much gold they have in their hands. But there is still so much to do when there is no strategic alignment. You can have all the sensors you need, and collect all the important data, but still not get the most out of it.
To achieve this, it is not enough to convince the CEO, or just the CIO. Companies that want to create a data-driven strategy must also be able to convince their employees. Because at the end of the day, ensuring the long-term future of an organisation by steering it through data means entrusting its employees with the task of mastering the concepts involved.
Should the business lines contribute to the data strategy?
The short answer is obviously yes. Subjects always emerge from business issues, which is why confining the discussion to executive committees helps to stifle the initiative.
But while companies have been urged for 30 years to break down silos, there is nothing more resilient than the barriers we erect between employees. Yet who needs to understand the concepts of repository and governance? Who needs to put information sharing at the heart of their practice, if not the person who is most often at the origin of it?
The University of Strasbourg is a good example. A Master's degree in Data is open to all students, whatever their faculty. So, Egyptologists rub shoulders with mathematicians, sociologists, lawyers and managers. This shared data base must now give rise to a data hotel, embodying this multiple cross-referencing and this desire to share information, through data analysis laboratories.
It's a very specific form of organisation, as open as possible, which is not really found in companies, despite the democratisation of openspaces. The use of data is an eminently human issue and requires training and support. Otherwise, misunderstood data scientists will continue to work in isolation, and poorly connected data centres will continue to run on empty.
What does the IT sector think?
Every day, IT professionals observe the blurring of lines in which companies are evolving when it comes to data. In fact, there is no real consensus on the subject, given the wide range of specialisms involved. That said, things are beginning to move in the right direction, notably at NUMEUM, one of France's professional associations for the digital industry. By setting up a Data Committee in the Grand Est region (in France), its aim is to raise awareness, mobilise, support and share feedback from useful organisations.
The fact is that businesses will not succeed in their data transformation without effective structuring of the IT sector. They need help in defining their foundation strategy as much as they need expertise in Cloud, storage, databases and security, and at the other end of the spectrum, they need skills in law and even organisational sociology.
This combination of skills is more urgent given that the sole purpose of data in the future will no longer be to help companies identify new areas for growth. Energy shortages, global warming and the very high expectations of the public regarding the efforts we need to make mean that we need to make better use of data right now to find new ways of building resilience.
