Data Strategy - You are not alone!
Data Strategy is a team sport and sometimes you are not even the trainer.
Data Strategy is often about change. But sometimes the strategy process shows that you are not alone to decide about the change process. A data, analytics and AI strategy should always consider alignment with business strategy, IT strategy, digitalization strategy (if you have one) and consider current trends in the IT & Data world, depending on you focus and needs. The following image shows an alignment of the formulated vision for data & analytics with different business departments:
"The vision for Data & Analytics is an inspiring, long-term aspiration that defines the organization’s ultimate goal, purpose, and desired future state. It provides clarity to employees and stakeholders about what the organization stands for and the impact it aims to make. A strong vision should be motivating, ambitious, and energizing—guiding and uniting people toward a common future."
Fig. 1: Business alignment of the vision for data & analytics
Crafting a Data & Analytics strategy is always about that you need others. Sometimes you find out, that things important to you and your strategy are not in your responsibility, and you have to go rather into a coordinating or cooperation role to reach your goals.
How it started…
When I started working with a customer, I got the feeling that this initially as SAP Analytics introduced team will face many challenges if they really want to create and execute a data strategy. In an early stage we came to this picture showing or better checking how far they have ambitions to go in these directions. Every element was some steps away from what they did before.
Fig. 2: Challenges in expanding the current role to reach the Data & Analytics vision and goals
How it is going…
When we progressed in the data strategy project, we finalized this picture as follows and clarified the possibilities and responsibility but also the borders of the now Data & Analytics Team. Data strategy can be an organizational change, effecting many areas, people, processes and so on. But some functions can not be changed or integrated and you have to collaborate or cooperate in some ways. For sure you can make a selective data strategy for the area of your current influence, but success will typically be limited.
Fig. 3: Target picture of distributed responsibilities to make data strategy possible
This picture is for sure a work in progress. But for the start it is important to communicate and get people into the boat. You have to find common advantages and drivers to get a better understanding.
Some insights I got on the way:
I see AI rising in different areas in companies. Sometimes a new unit is created e. g. as an independent Center of Excellence for AI (CoE)
Business IT teams like Finance often own some applications like Business Planning or Financial Consolidation
There are many reasons to raise a Public Cloud and if Data & Analytics wants to use it, they are possibly just a subtenant
Digital or Data Academies are often owned by HR departments
The need for Data Governance is often also seen in operational areas first
Data Security can be strongly covered by the CISO, data protection officer or similar departments
Conclusion
You don’t have to own all these topics. You never will. You need to work together in an active way with others in a team approach, to reach the goals of the data strategy. You have to be ready to communicate and activate others. You have to sell your data strategy, show the added value and convince others that it makes sense to engage. Often success depends on your company culture. This is typically why you need CxO sponsorship if things get complicated.
This article is a adapted and extended version of an earlier article on my earlier substack. I promised to relocate the articles but also review the content and update on newer insights.
What departments of functions are the most important for making your Data and AI strategy successful?