The Why, What and How of Data Strategy

What Do You Recommend? Data strategy is complex, it’s long-term (hopefully) and it needs to be inherently dynamic and flexible to successfully implement. Not surprising then, that answering a question like “what data strategy do you recommend?” isn’t all that easy these days.

Reverse Engineer the Why

I ask my clients to think about why they are looking to implement a data management strategy and ask them to simplify their answer using the most basic language to make sure not to overcomplicate it. Examples of this could include:

–      Bringing all data together in order to generate consensus

–      Understanding more about our existing customers

–      Translating customer insights into relevant marketing messages

Map Out the What

Once you have established your why, it’s a relatively simple process to turn that into use cases and to organise those use cases in terms of priority. In other words, you begin to focus on what are you going to do. The strategic framework should provide a clear vision of what you need to do in order to achieve your goals. It should be dynamic and flexible but should provide yardstick measurement of progress against specific objectives, milestones, and use cases. This project plan is vital to ensure you successfully implement and execute on any given data strategy, regardless of the use cases

Work through the How –  Capital and Operational Expenditure

Once you have your why and your what, and you have begun to think about the strategic framework, you will need to focus on the how. The how revolves around two key elements:

Capital Expenditure – In simple terms, what tools and technologies will you need to execute on your why? Do you need a DMP, an ID resolution solution, a DSP, or all of the above? Do you need something else entirely? Furthermore, what investments in data are you making? Is this a purely 1st party dependent strategy, or will you need to evaluate 2nd and 3rd party data opportunities in the market? What are the processes and the protocols around this, and what are the time and resource considerations?

Operational Expenditure – The creation of an operational infrastructure provides a platform on which you can begin to execute against your strategic framework to achieve success. It is paramount to effective deployment and is in most cases, where major bottlenecks begin to develop. This comes down to the people and the process of continued execution. Do you need a team, if so, what do you intend to invest in building that team? What talent set do you require to be successful, what external and internal resources are available to support the team’s development?

Don’t Procrastinate, Execute

The most important aspect once you have queried your why, established the what and developed on the how is to ensure you actually execute.  Execution cannot be overstated in my view, it is absolutely critical to execute in order to deliver any value through your data strategy. Failure is possible, and in fact likely, don’t be precious about it or paralysed by the prospect of it. Test, learn, iterate and evolve.

The strategic framework is dynamic and flexible in order to account for minor setbacks and these should be balanced against successes.  Marginal gains and incremental value are at the heart of any data strategy, and if you have strong foundations and a clear vision you will differentiate yourself.

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