Developing a commercial data strategy

Approach

We began with an analysis of the current situation and engaged in discussions regarding the insurance company's ambitions. Utilising our data strategy model, we first mapped out the organisation's goals and strategy. We aligned organisational goals with departmental objectives to identify areas of alignment and misalignment.

The insurance company aims for customers to have the same personalised experience across all channels of interaction with the organisation. Therefore, we examined which KPIs are used to monitor and drive these goals. Within the organisation, there was a wealth of additional information available. We reviewed existing documentation and compiled an overview of all tools, data sources, and data initiatives. Additionally, we mapped out the stakeholder landscape and engaged with various stakeholders. We also conducted workshops to delve into key themes.

Subsequently, we explored what the insurance company's mission means for data management within the organisation: what role does data play in achieving the goals? How can data contribute to this? This led to the establishment of data ambitions.

An example of such an ambition is their desire to know where the customer is at any given point in their journey. To achieve this, they need to have the right data products such as dashboards, reports, predictive models, and next best action (NBA) models. Furthermore, the available data must be actively used for data-driven decision-making (data activation).

Several enablement factors play a role in using the right data products and achieving data activation. These include technology, data governance, and the right knowledge and skills (capabilities) in the right areas of the organisation (organisational structure), embedded in processes. We analysed the organisation based on all these components of the data strategy model. This provided a comprehensive view of the current situation and allowed us to advise on what was needed to achieve the ambitions.

Result

Our analysis identified four pillars that the insurance company needs to address to bridge the gap between the current and desired situation:

1. Align goals and KPIs effectively

Strategic goals are not fully covered by existing KPIs. Additionally, the hierarchy between different KPIs could be made clearer. To determine how data can contribute to achieving the goals, the goals and KPIs must first be fully aligned.

2. Assign ownership for cross-silo data topics

There are often good initiatives within individual teams that are not implemented more broadly within the organisation. This is because it's unclear who owns cross-silo themes such as personalisation. Ensure there is not only a clear point of contact for the entire strategy but also for specific themes and initiatives that arise from it. This enhances mandate and effectiveness.

3. Promote and consolidate data knowledge and expertise

The ambitions are challenging to realise as long as data expertise is divided across different silos. Establish a central data team that works across silos and ensure this team has all the necessary knowledge and skills.

4. Invest in a data-driven culture

Ensure everyone within the organisation, from management to store personnel, sees the value of data. People need to know where to find relevant data and how to use it in their work. Involve the organisation as much as possible in the process of developing a data-driven mindset and make time for this. A shared vision of the role of data is essential.

Based on these four pillars, the insurance company can now proceed independently. Of course, we are available as a sparring partner for setting up KPI workshops, connecting data sources, or supporting training.

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