Three steps to build a data strategy

I recently wrote an article on why a data strategy is so important to help you meet customer expectations in this digital era - you can read it here. In this blog, I will focus on how to build up a data strategy; where do we start? What do we include and what not? What are the key success factors?

With this article I hope to give you and your organization a brief overview on how to form a data strategy. Additionally, I hope this enables you to take the first step and get started. I look forward to many discussions and additions to this article and developing this to the next level.

Business Goals + Data Maturity form the basis of your data strategy.

Step 1 — “Data only has value when it has a function”

So, where do we start? The answer to this question is very easy. You start with your business goals and your data maturity.

Business Goals. The answer was easy. The thing with easy things is that these things are usually the most difficult things (so many things). Let’s elaborate on this a bit further.

Building a data strategy is difficult because of many reasons, but it basically comes down to two main reasons:

There is no common understanding on the organizational business goals (especially across departments). Do we all understand the famous ‘Strategy 2025’ document? And if so, do we all understand it the same way?

There is no common understanding on how data plays a central role in future businesses and how it will become (or probably already is) of vital importance.

Hence, creating common understanding is where you start. All key stakeholders together (both business and IT leaders) should build a common understanding on the future business they are striving towards and the role data plays in this.

However, they are going to need support.

So, based on buy-in from the board, setup a team and start with in-depth interviews and workshops with all key stakeholders. Let them create this thing called ‘common understanding’ on business goals and the role of data themselves. This is a very valuable approach and will not only result in commonly agreed business goals and the role of data. There is a bycatch: You just planted your first seeds to build a data culture and started your awareness program by creating the first (senior) data ambassadors. This will help during the creation of your data strategy.

Data Maturity. Parallel to the creation of a common understanding on organization business goals and the role of data, you should start measuring (you are becoming more data centric for a reason) your organization’s data maturity. To be able to successfully execute a data strategy, or any strategy for that matter, it is important to know your starting point. A data maturity assessment will give you insights in the current expertise of all data enablers (the data enablers will be discussed in step 2) and forms, together with the business goals, the fundamentals of your data strategy.

Step 2 — “A vision without a strategy remains an illusion”

Now we have a common understanding of the business goals, the role data plays, and our organization’s current data maturity, it is time to focus on the data strategy.

A data strategy is built upon two things:

1. Data Enablers. Elements that enables your organization’s data to improve your business and deliver more value to your customers.
2. Key Success Factors. These do not add immediate value but are nevertheless very important. As the name says, if you skip these there will be no success.

Data Enablers. At BearingPoint we make use of our Data Strategy Model that builds upon six data enablers that are all needed if you are working towards a data centric organization. We see many organizations struggle because their only focus is on data science. However, when you dig deeper there is either not much proper data to analyse or these are ad hoc analysis that don’t necessarily help to reach your organization’s business goals. It’s important to know that all six data enablers are intertwined. An example: If you don’t have a common view on your customer data and don’t have any data quality measurement on the data set, how do you even start to get this 360-view on your customers where everybody is talking about?

BearingPoint’s Data Strategy Model

We believe a data strategy should always be based on those six data enablers. I can almost hear you think: Do we really need to be good at everything? Yes and no. Yes, they are all needed in some extent. No, because it is dependent on your business goals and data maturity where to focus on, what to do now and what to do in the future. Besides, there is the decision on what to do inhouse and what you could outsource to your data or IT partners. But in the end, yes, all six data enablers are needed in your data strategy.

Key Success Factors. If you only focus on the six data enablers you will not make it. There are always the key success factors.

1. Business Ownership. The first one and the most important. If you do not have business ownership, there is no need to continue. For the same reason your strategy should always be in line with business goals, the business should also take ownership in the data strategy to ensure it’s not just IT or the data management department supporting the data strategy. The data strategy is there for the business, not for the sake of having a nice data strategy because “we need to do something with data”.
2. Awareness & Change. Becoming more data centric and having a data strategy will change the existing culture and mindset. So, please take this with you when setting up your data strategy. And please, start with it from day one.
3. Technology. Up to a certain point Excel can manage your information models, create your monthly reports and maintain your data quality dashboards, but if you really want to become more data centric/driven you are definitely going to need supporting tools and technology.
4. Processes. Cross-functional processes are absolutely necessaries, especially when working towards a data centric organization. All employees, from senior executives to junior analysts, need structure and guidance in what they can and cannot do.
5. Tactical and Operational Boards. To guide the transformation, it is also important to form (strategic) boards with data leadership represented. There will be decisions to be made and the governance to take those decisions is better to be organized beforehand. Those boards will allow a smooth and continuously transformation towards a data centric organization.

Even if your data strategy is not perfect in the beginning (which it probably will be), if you take these key success factors into account you have built the system, set everything in place to get started and you will improve along the way. Getting started is a good thing.

Step 3 — Get started!

I hope this article gave you some insights on how we build up a data strategy, how and where we start and what to include. Of course, this is not the only way to build up a data strategy and it also probably is not the best theoretical framework you have ever seen. But it works. It works in practice and I believe that is the most important. It is a pragmatic approach and it really does get you started to build a common understanding of business goals across silos, find the value of data for your organization and build a data vision and roadmap that gives your employees the guidance they have been waiting for. So, please. Just start.

If you find this interesting, please follow me on Medium for more: https://medium.com/@larsvb

Author

Lars van Bussel

Senior Business Consultant

lars.vanbussel@bearingpoint.com