Now the final line begins as the “100 Days of Data Economy” blog series draws to a close and it’s time for me to summarize the three points that I would all like you to remember. I’ve written quite holistically blogs for business management alone and from a very business-oriented perspective, not so much a technical or data perspective. The idea in all my writings has been that data applies to almost all industries, companies and managers. At the same time as more and more data is being generated around the world, its users are rapidly differentiating themselves from their competitors - data is a completely new non-wearing asset.
First of all, I would like to emphasize the importance of leading although maybe I repeat myself. I’ve described why all of the data utilization needs to start with the business use cases and the easiest ones that are almost immediately possible to implement (so not from the ones that are covering entire globe). In addition, I have often described why competent corporate management has to take responsibility for everything the company does and what can go wrong if it is only run by technical people. All in all, this entity means that as the mechanisms of the data economy and the value creation of data directly or indirectly extend even more to different companies, those who drive it through mechanisms of economy are the ones who benefit the most. In short: if you have a data economy, artificial intelligence, or some other entities that are 100% data-based in your strategy or vision, make sure that top management knows and speaks for it naturally. If you don't, you need start gain the know-how right now.
Secondly, I would like to highlight the dogmatism of the ever-technical debate. There is often talk about the technologies used, the superiority of different technical standards, or who uses Google, who uses Microsoft, and who uses Amazon. These conversations have very little business value. New technologies and technological innovations are emerging with an ever-accelerating speed in the world, and it is very likely that even existing solutions alone can all meet your business needs almost completely. This means that if you manage your business needs correctly, choose technologies (such as low-code / no-code and dual-platform strategy) according to your business needs, avoid technology vendor locks, and try to promote the ability to change at the business level by all means. Before you invite technicians to a discussion, make sure you have a business case and a business needs to be defined.
Thirdly, I want everyone to understand what happens if the structures of information or data and the importance of their continuous management are not understood at the business level. Imagine that you have tens of thousands, millions, or even billions of rows of data in hundreds of storages that are not structurally described, the data cannot be used and it is a major cost for you. In this way, you end up in a situation where the exploitation of the data economy or the real value of the data remains just an imagination for your business. It is an indisputable fact that companies where management does not take part in or take responsibility for the design of data models, even at the highest design level, are left out of the tsunami of the data economy. Unfortunately, many companies do not take this seriously.
Here are briefly the three most important lessons to learn and lift for corporate management for me. I hope you have a good enough understanding of my writings and will be happy to answer any further questions. It’s not meant to scare anyone but if you have a data strategy, do it right!