Oakland Group

How do you develop a data strategy from a data maturity assessment?

A data maturity assessment, whether delivering the new Data Maturity Assessment for Government, or utilising Oakland’s own maturity assessment framework, is a great way to get a grip on your current data capabilities. It can highlight issues and create a case for change; however, it can often leave organisations wondering “what next?”.

Whilst you might have identified areas of low maturity and capability gaps, you will now need to focus on defining and planning the required initiatives to drive the business forward, meet identified business needs and deliver long lasting capability. If you can’t do this, your maturity assessment becomes a wasted exercise. This is where a Data Strategy comes in.

Completing your data discovery

A word of caution: before you jump into the “Define” phase for a future data strategy, is your data discovery complete? From our experience, we see a lot of organisations focus purely on “in the moment” analysis of their current state, without providing key context or clarity on future vision and data capability needs for the organisation.

Contextless maturity scores are not very helpful to a non-technical audience. Have you understood the vision, aims and objectives of your organisation and the required data capability and maturity to meet these? Have you looked at future data capability and maturity needs and set realistic targets for where the organisation needs to be? Have you understood your use cases and capability needs to deliver these?

A data strategy should not be done in isolation. As we often say, it’s not a strategy for data, it’s data for strategy. Higher data maturity, and the required investment to deliver and sustain this, should always be outcome and value focused, driven by a real business need.

Defining your data strategy

Once you’ve completed your discovery work, we can start to define the strategic pillars of the data strategy. What are the 3-5 key changes or themes that define the strategy in response to the vision, objectives, and desired future state and maturity of the organisation.

Key initiatives are defined for each pillar, considering required changes across people, process, technology, and data. It’s at this stage we address desired outcomes and deliverables, the associated benefits and impact on the business and in shifting your data maturity, and the resourcing and enablers for delivery.

From here we begin to design our conceptual operating model, organisational structures, and capability deployment strategies and principles to successfully sustain the data strategy.

Planning for delivery

At this stage you should have a solid, evidence-based case for change, with clearly defined initiatives to deliver required data capability. However, without a pragmatic, actionable plan and business case to support investment, you’ll leave key stakeholder asking, “so what?”. This is where the crucial planning stage comes in.

This begins with your initiative road-mapping, driven by initiative profiling, prioritisation, understanding of key internal and external dependencies, risks, and transition points. Initiative KPIs and success measures should be documented at this stage, whilst setting out the programme and project governance structures.

The data strategy should then be grounded by a solid business case and supporting cost benefit analysis to justify required investment. It’s important that you align benefits to the business problems and needs identified during your data maturity assessment and complete discovery.

If you’re looking for help in delivering a data strategy or data maturity assessment yourself then please drop us a line craig.lambert@weareoakland.com, and why not download our free data strategy guide in the meantime https://weareoakland.com/data-strategy-guide

Craig Lambert is a Senior Consultant here at Oakland, focused on helping organisations with data and digital transformation strategy and implementation, data governance, business case development and target operating model design. Over the past 14 years, Craig has led major transformation programmes in both consulting and industry contexts.