Becoming a data-driven company is more than investing in technology Becoming a data-driven company is more than investing in technology Becoming a data-driven company is more than investing in technology

Becoming more data-driven is one of the key priorities for most organizations today. In the market place we see that truly data-driven organizations are growing faster than the traditional ones. This is leading to serious investments of all organizations to improve their data analytics capability and look for a way to drive value from data analytics. 

However, as a result from the recent survey we conducted in the Dutch market, we see that the vast majority of the organizations within the Netherlands currently still has a relatively low Data & Analytics (D&A) maturity. This is mainly due to the fact that scaling up successfully with data & analytics not only implicates investing in technology, infrastructure and hiring a few data scientists. Becoming a data-driven organization also requires changes in culture, organizational operating model and realizing ‘real’ business value through use cases. These latter topics tend to be very challenging for many organizations.

To be able to structurally drive value from data & analytics, multiple pieces of a complex puzzle need to come together. When developing a data strategy in our experience, a critical success factor for executing and scaling up analytics is connecting the business demand with the Data & Analytics supply. Without this connection, companies run higher risks of slow realization of tangible value, lack of confidence in analytics and higher costs due to delays/re-work. The art is to define and select the right use cases that can deliver value, but at the same time help to further structure and improve the supply side elements to accelerate the realization of future use cases. To support our clients in grasping this we work with the strategic pillar model for a data-driven organization (see below). 

Vision & Ambition: How should data contribute to our long-term strategic business goals (e.g. operational excellence, customer interaction, new products/services, etc.)?

Use cases: Which initiatives should we launch to help realize strategic business goals via data analytics use cases?

Organization & Governance: What target operating model is required to successfully execute and support our data initiatives?

Ecosystems: What are our key partners with whom we need to work together to be able to drive value through data analytics, and how to collaborate on this topic? These can be technology partners, but also for example suppliers/buyers in your value chain.

Architecture & Technology: Which technologies do we need to leverage for a flexible and scalable data platform to support the development and deployment of our data analytics use cases?

People & Culture: How to create a data-driven culture and data literacy across the workforce (with both internal and external resources)?

Trusted data & analytics: How do we build up trust in data, ensure transparency in the algorithms and technology used and realize (ethical) controls for our analytics?

^{KPMG’s strategic pillar model for a data-driven organization.}

Using this model helps organizations to better understand their strong and weak points when it comes to the crucial aspects of data analytics. Providing the right focus on the aspects that are currently your weakest link is vital to be able to make progress. Because the first step to becoming a truly data-driven organization is knowing where you stand and where you want to be. Interested in the detailed survey results? 

Bas Overtoom
Director Data & Analytics
overtoom.bas@kpmg.nl