Many companies understand the value of data. Those companies that also consciously address this are growing exponentially. The speed with which you can achieve this depends on where you are starting from. A start-up can start with a clean slate and immediately start incorporating this principle across its entire organization. Other companies are weighed down by their traditional and analogue business processes and have to move these forward to the digital age at the same time. Data-centricity is a key driver in this shift.
Bram Wauters - Senior Unit Manager Data, AI & Integration
Data as the starting point in the era of post-digital transformation
We are living and working in the post-digital transformation age. This is a time when new needs are constantly being uncovered, to which no solutions exist as yet. Data is a key factor if you want to thrive as a company in this context. In a world where we can no longer fall back on assumptions, you need to be able to fall back on your own facts. A correct reflection of the reality of your business, in the form of data, is the compass you need to keep the ship on course during the present turbulent times. This has once again been shown very clearly, especially during the past year. Even global majors such as Disney felt the need to scale their model in the face of the closure of cinemas and amusement parks. They have invested massive efforts in Disney+, their own streaming service, to ensure a stable flow of income. The speed with which they were able to respond was made possible by the collection and analysis of data and using it to generate useful insights.
Data as a strategic asset
Data is therefore of strategic importance; its management and use deserve the same attention as the other valuable assets within your company. There is a lengthy road to follow before you can fully exploit the value of data. As with Maslow's hierarchy of needs, the factors at the base first need be in place before you can reach the highest level. The bottom layer and the foundation of the pyramid is good data management, to ensure flawless data quality. In addition, you need to set up the right data pipelines to link, organize and access data. Only after that, can the data really be consumed as useful (AI) insights. The value is in the point of the pyramid.
Technology plays an important role in this, but the right data mindset is the key differentiator for success. Cultural challenges – not technological – are the biggest obstacles for data initiatives. Every layer of an organization has to be aware of how to handle data. Every link needs be just right to ensure good data quality. Building this kind of culture requires investment, time and attention.