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Case study

How we guided a Public Sector Organisation take the right steps in their Data Management Approach

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Many organisations are starting to notice the immense potentials with Artificial Intelligence, Internet of Things, Machine Vision, Machine learning, and other technologies.

A large number of organisations want to deploy these technologies and tend to start with the end result, i.e. hiring AI, IoT, MV or ML specialists or a set of data scientists without necessarily taking into account the readiness of their data.

Yes, of course, organisations don’t have to wait with innovative projects or their digital transformation until they reach a particular level of “data maturity.” However, it is a crucial “must-have” to take up the management from the start in order to avoid the cases of high investments with little rewards.

The Challenge

Data Trust Associates got the chance to take up a client’s data journey right from the start, taking forward every step of the journey in the right order.

This data journey project was started from a business project that was stuck on specific data issues, which our data team were able to get back on the rails.

The approach of carrying out data management in the right order allowed the organisation to get the necessary buy-in and be prepared for any upcoming innovation projects and digital transformation activities.

Furthermore, it made sure they could distinguish which projects would really fit their organisation’s needs and which ones looked great and attractive but weren’t necessarily, bringing a lot of value to the organisation.

Our Approach

… A Burning Platform:

As with many organisations, this client had a project that was stuck with data problems.

“Data was not available (kept in silos), the quality was not okay, and because of the silos, data was too hard to integrate (different structures, different ideas of what the data meant and use).”

Our Team, however, turned this project into an opportunity and fixed the data issues, thus enabling the project to achieve the expected results.

The first step in a data journey is, therefore, to identify one or more projects that face challenges in terms of delivery, cost, effort, and collaboration related to data issues. In other words – find a burning platform.

… Understanding the Organisation’s Readiness and Needs

In terms of data management, we started with understanding what the overall challenges were in the organisation – related to a lack of data management – thereby looking at people, process, organisation & technology readiness.

The business strategy and drivers of the organisation were assessed to help us determine what kind of data management capabilities the organisation needed to realise all their strategic objectives.

The organisation’s challenges and strategic objectives allowed the team to identify the gaps in terms of data management and define some key data principles. These data principles helped the organisation to understand the gaps and what to do about them.

“One such principle was about openness and sharing of data across departments – a great example of what was not adhered to in the project that was stuck (see above).”

… Communication and Organisational Buy-in is the Key.

Still, even with clear data principles, an understanding of the gaps, and a burning platform, it’s not easy to convey to business people so that they can start doing something with data or understanding that some of their business challenges are in fact (hidden) data challenges.

That’s why we created visual storylines, making sure anyone in the organisation could understand how data management could solve some of their problems as well.

With great power comes great responsibility” — Peter Parker.

Data can enable innovation, digital transformation, operational excellence, etc., but comes with great power and responsibility as well. Just think about GDPR and wrong decision-making based on incorrect data and higher costs.

In order to make sure data became part of the organisations’ DNA, we immediately started with defining (and assigning) data stewardship roles and informing/training and coaching people into their new roles.

This helped the assigned people to be more confident, as well as effective in their new roles, while also making sure everyone in the organisation had go-to persons to discuss their (data) challenges.

Having these people assigned in the organisation made sure we could accelerate not only data governance but also the organisation’s data maturity while better overcoming the data management gaps.

… Combining everything into a Data Policy.

Besides the storylines and embedding data roles into the organisation, a data policy was created that allowed everyone in the organisation to understand what was expected from them and why.

Conclusion

Even though it’s crucial these days to get to deliverable fast and continuously innovate, it’s also important to make sure you take the right steps with your data journey and ensure that your data has the right level of readiness and correctness.

Many companies invest in innovative technologies and find out (after 1 or 2 years) that their investments ultimately delivered too little business value.

This unique step-by-step approach led to much wider adoption of data management in the organisation and much better focus on the required data capabilities and priorities in terms of innovation and digital transformation.

Taking the right approach won’t stop an organisation from innovating, but will make sure the outcome is the right and sustainable one for the organisation in the long run.