Post pandemic data governance — has anything changed?
Earlier this year, I was invited by SAS partner Finaps, to participate in their review of innovation-ready practices. The resulting ebook (in Dutch) has been well received by customers eager to be better prepared for the acceleration ahead.
Here, I offer the translation, with additional input for partners and customers attempting to scale innovation.
Refreshing our understanding of data governance
There is no agreed definition of data governance. However, I define it as the organisational framework for establishing and defining the strategy, objectives and policies for business data. In other words, it is the basic principles that the organisation uses for working with data: the why, how and what.
When data governance is good, it makes a measurable contribution to faster, better decision-making. Good governance means that people trust the data, processes are transparent, data are available, the data quality is good and the roles and responsibilities surrounding data are clear. It is therefore a fundamental building block for any work with data — and that means any kind of data-driven decision-making.
The financial sector is generally ahead of other sectors on data governance. This is not surprising when you look at the data intensity and the regulations surrounding the sector, including Solvency, IFRS, and BSBC239. However, the sector cannot afford to rest on its laurels. Data governance is becoming even more important because COVID-19 has increased the pressure on organisations to innovate. Data-driven innovation requires good quality data, and lots of it, available right across the organisation.
However, there is another aspect to consider. In Europe, the General Data Protection Regulation means that businesses have to be able to explain the basis of a decision to a customer. Customers have a right to know what the business knows about them, and how it is making decisions about services such as loans. It is essential that businesses can explain the logic underlying each decision. This means that transparency around data and decisions has become mandatory.
The world of tomorrow…
The analytics process is changing fast. We are seeing a move towards more people working with the same data. Decisions and models are also needed faster. This means that cleaning and organising data is becoming even more important. Nobody wants to spend valuable analytical time on data management processes. Increasingly, these need to be automated.
We are already seeing that more organisations are moving towards a central platform for data and analytics. This supports self-service analytics, because nobody has to pull the data together themselves. Instead, all the data are already together in one place. In future, we will increasingly see this platform kept securely in the cloud.
Perhaps the most crucial move is in organisational culture, though. We must start seeing data as an asset, rather than a by-product of the organisation. We need to start managing data on that basis — and that means that data governance is key.
…starting today
Unfortunately, you cannot simply buy good data governance. You have to design it into your processes, and then work to improve it over time. It will therefore be clear that it is necessary to start now — but how?
The first step is to determine your guiding principles and aims. These are your ‘data beliefs’ and the uses you want to make of the data. This gives you the grounding for your data governance approach. You then need to determine how you are going to implement that.
Like any change process, you need to think about where you want to go — your vision for the future. You then need to consider how you are going to get from where you are now to that vision, via your guiding principles. You need to think about skills and capabilities at people, team and organisational level. You also need to consider how you will communicate the need for change, and how you will avoid or manage resistance and scepticism. Finally, you need to think about some ‘quick wins’, because everyone needs early successes to give some momentum to change.
Your final step is to get started — because even a journey of a thousand miles starts with a single step. In the post-pandemic world, speed has accelerated. Data governance still needs the basic elements in place.
