Data-driven Company
The path to using data strategically: We queried more than 110 international companies about their hurdles on the way to becoming a data-driven company.
85%
of companies think that data and AI have great potential.
25%
of decision-makers surveyed described their companies as data driven.
While most companies are indeed investing in data-driven and AI projects, they often still fail to reap the full potential. Based on our practical experience from over 100 interdisciplinary projects, we have identified five typical barriers that companies face on their path to becoming data driven.
Holistic, ongoing planning and implementation of data and AI projects is critical. If data projects are technology driven rather than business driven, the innovation pipeline is sure to run dry.
Without an operationalisation concept in place, many projects never get beyond the proof-of-concept stage. In other words, even technically feasible solutions do not create any added value in the end.
Failing to integrate solutions into existing tools is by far the most common reason for poor acceptance of AI-based solutions. Other reasons include sceptical attitudes towards AI or users lacking the proper training.
The greatest challenge facing most companies is interdisciplinary collaboration during data projects.
Many companies have the data at their disposal. But the real challenge lies in its quality and in accessing it. In many cases, effective data governance is lacking.