The 4 key aspects of a successful data strategy

A data strategy requires a culture 

In recognition of Peter Drucker’s adage “culture eats strategy for breakfast,” a corresponding culture is also an essential prerequisite for a successful data strategy. (Corporate) culture encompasses the intangible foundations of an organization’s creative achievements. 

Regarding data culture, for example, the question of how federal structures are designed arises: Does an organization tend to emphasize central responsibility or local responsibility? Do federal levels also correspond to hierarchical levels, i.e. are decisions escalated through management or are competent committees (with decision-making authority), put together differently? How is the decentralized competence of the domains balanced in comparison to centrally provided platforms that are to be used with the shortest possible learning curve for users from the domains, but which have to be operated at considerable expense? 

Moving step by step to the ‘North Star’ 

Companies that are rethinking their data strategy should develop a North Star but then proceed in a very pragmatic way. The North Star represents the desired end state: Do you want to increase efficiency, improve products or services based on insights from existing data or open up new business areas? If the goal of a data strategy and corresponding initiatives is not clear, then the realization is doomed to failure. Only when the direction is clear can practically realizable steps lead to success. 

The organization can be carefully modified, for example, to establish federal governance structures, implement central control of the top ontology layer, and adapt and improve it in interaction with the domains. The domains must be empowered to independently implement data products, with a central definition of the policies that must apply to all, for example with regard to identity and access management. And here, in the creation of a platform — planned or emergent because of only loosely coordinated initiatives to reduce communication overheads — the data strategy approaches the classic IT strategy, particularly concerning cloud architectures.