Many companies currently behave in exactly the same way: They are looking far and wide for input on their digitization strategies, but their data – the gold treasure on which they already stand – does not capture their attention.
AI: Between hype and uncertainty
There is a hype going on around the globe: artificial intelligence, big data… these are the topics that dominate the front pages of the trade and business press currently. However, there is a great deal of uncertainty within companies.
This was also shown by my small survey conducted recently at the -VDMA- hackathon on predictive maintenance: The participating companies all deal with the topic, but only 5 to 10 percent can already offer specific services and solutions. Everyone wants to do something, but only a few make purposeful progress. What is the reason for this? A key success factor is a clear mandate from the management to deal with these game changers strategically and visionarily – e.g. in the role of a CDO.
In addition, a data strategy is required that is part of the corporate strategy, because when it comes to digitization and data, the existential question is often: How will the company earn its money in ten years? In addition to the management board mandate, a management organization is needed that encompasses all activities, pilots and projects on these topics. Such a “digital hub” as a governance model ensures that the issue is driven forward company-wide.
In addition to this top-down approach, a simultaneous bottom-up approach is crucial to success. Because what is needed is direct access to the processes on the operational level, in which the data is stored.
Three plus one
Whether a digitization project is successful basically always depends on four factors, which are described in the 3+1 rule by Michael Herbst from Unity : The three components technology, service/application, benefit together form a use case (3). This use case will only be successful, if there is also a customer (+1) who can derive a specific benefit from it. In the sense of the bottom-up approach, it is therefore necessary to bring together exactly those persons who together fulfil the 3+1 rule for each data or digitization project.
It is not enough to add a few data analysts to the IT department. If the operational departments are not involved, the project will not be successful. Vice versa, that means: If the individual departments want to use their data, but they lack the right tools, it will not work either.
Another aspect that causes many data projects to fail is that size slows down the entire project. Companies need to realize that right now, the large projects planned for many years are not what is needed today. It is better to learn iteratively at the beginning, quickly try out very specific use cases and prove via Minimum Viable Products (MVP) or a proof of concept, that there is a specfic benefit available to the customer and that the application works in a real process.
Only when checking the box on the items above, the data service can be “industrialized”. As a next step, a process is developed that can be applied to all of the company’s similar use cases. Only at this point, a lot of money can be spent – on technical integration, IT and data security, etc. – but with the certainty that the whole thing delivers added value and will work.
Crucial for survival
Every company sits on a treasure trove of data – simply because it has operational processes. Anyone who uses this data will be able to make a difference in their industry. I even want to go so far as to say that only these companies will survive. Many of the tools needed for artificial intelligence or data analytics are now available free of charge and in high quality via Open Source. Companies should not become dependent on external experts, but rather win them over as innovation partners in order to build up important competencies in the digital revoltution. It’s time to dig for your treasure!