At the end of 2020, Jos Schreurs, partner at Squadra, wrote the article below. This article was part of the newsletter, which you can subscribe to at the bottom of the page!
17-12-2020 – written by Jos Schreurs
In this strange time, in which COVID-19 still has a tight grip on society, it has become clear that digitization has become an inseparable part of and a necessity for our society. Digital Transformation is in the top-3 priority list of all customers I talk to, which is not surprising. What is surprising is that some still limit themselves to a digital-commerce strategy, where others continue the digitization company-wide and see it as an important success factor in the interaction and cooperation with their customers and suppliers.
From conversations I have with customers about the realization of their digital ambitions, it appears that many of the challenges can be categorized as “hassle with data”. Whether it concerns the completeness and correctness of product data on their website, the challenges of merging customer data scattered across departments and systems into an integrated customer view, or to arrive at improved analytics for turnover and spend analyzes and rationalization of the supplier database. The D in the name of CDO does not only stand for “Digital” but also for “Data”, the fuel for the digitization engine.
The data foundation is often insufficient for digital ambitions.
Our quick scans and assessments show that the data foundation in many organizations is often very poor. “For us, data was always seen as part of IT, difficult, complex and quite technical. Moreover, locked up in systems and databases that are managed by IT. However, now we realize that the hassle with data is no longer an IT responsibility and that we as a business must take responsibility for data. Just like we did for eCommerce 10 years ago. A year ago we started a team of data engineers and data scientists, a good step forward. However, this also forces us to face the facts: the data is often not reliable and therefore requires many processing steps. As a result, these people can only spend 20% of their time on real analytical work. Our data foundation is certainly not in order in quite a few places ”.
How?
It sounds great when an advisory report or a strategy plan states that digitization and data analytics are important components for future success. The key question, however, is “how?” Where do you start such a digital journey? Which capabilities do I need to build? Which stakeholders should I involve in this and who claims ownership? What do I have to set up in terms of data-related processes and which tooling do I need? How can I make use of new technologies such as Machine Learning, while my system landscape is still filled with systems that need to be replaced?
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