The power of data is praised by many but only truly exploited by a few. Achieving data maturity, particularly by complex organisations, is difficult, despite how many will tell you they are data driven. There are many reasons for this, but generally legacy and lack of serious investment (and I’m not talking about financials here alone) are the culprits. Governments are the epitome of complex organisations, with tremendous legacy and systemic investment problems, that come and go depending on who is in office.
Every now and then these organisations will try to fix known problems. For governments, this will be in the form of investment plans, strategy announcements and even policy. The problem with governments, as with large organisations is that their attention spans are limited; a lack of immediate and distinct results in politically sensitive areas may cause a loss of momentum. For data, while its potential is hardly questioned, the actions that need to be taken to create a visible dent are a far more difficult pill to swallow. For example, privacy and ethical issues will immediately bubble up in the political discourse, as building a data-driven government means building a data-driven society and all its aspects, including identity, health, benefits and taxes, just to name a few thorny sensitive data topics.
The problem with data is that it cannot be addressed partially. It´s like building a house: you need firm foundations. You might want to build the kitchen first and cook dinner, however a house with just a kitchen and none of the other essentials like a roof, electrics, and plumbing is not going to work, no matter how well you can cook. To address the data problem you need to embrace the complexity of what needs to be done. You need to build the foundations of that house properly, it doesn’t need the luxury fixtures and fittings like a jacuzzi, cinema room or a conservatory
The foundation of data is adequate data management. Along the same lines as the famous slogan from a well-known tyre manufacturer, I’d say that data is nothing without management. Sure, you can have use cases showing how sharing and linking data is great (but we already know that, right?). But unless you establish the principles of how various parts of government consistently do data, it will never be a scalable, replicable solution. In other words, you will not fix the data problem.
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National Data Strategy
The good news is that fixing the foundations of data is exactly what the UK is trying to do, and it is reflected in the National Data Strategy (NDS) in its fourth pillar. The NDS says that “data is not consistently managed, used or shared in a way that facilitates informed decision-making or joint working across government and the wider public sector”, which echoes directly the point I make above. The NDS goes into some detail regarding what needs fixing, including data quality and standardisation, lack of skills and leadership, legacy systems or general lack of alignment. It also commits to a few actions in order to get things on the right path, some of which came from our discussion with colleagues in central government, and which are owned by the Office for National Statistics (ONS). Some examples are
- Setting up a national Data Maturity Model, so that we can understand where each department is on its data journey, track their progress and compare it across government
- Develop the Integrated Data Service, so that data can be shared and analysed securely, using consistent data management practices
- Develop and validate a set of data principles for government, so that we can all set our policies for managed data based on the same foundations
If I had to distil the essence of data management into one word, that word would be “standards”. That word and its variations are mentioned 83 times in the NDS. Standards represent the crux of what it is all about: an agreement regarding how something should be accomplished. And for our purpose, an agreement regarding how to do data.
Data standards come in many forms and sizes from how to format data, to how to describe it, structure it, store it or exchange it. The take home message is this: if we all apply the same standards to our data, it becomes easier to understand. This will make it easier to integrate it with other data, provide quality insights and help make better decisions. Better quality data = better decision making. Which is exactly what government needs.
So there you have it, data is nothing without management, because managing data consistently sets the foundations for data quality. While there is more to good decision making than good data, it is a necessary condition. So if your organisation or your government is working on a strategy to take data seriously, do not forget this simple fact, and invest in data foundations so that you can have a great dinner but you can also move in.
