Paul Jones: Data, Strategy, Innovation

A Data Strategy is a great way to set a clear direction and get the right people on board to sponsor and support the delivery of strategic change.  If you’re trying to do anything strategic with Data, then you’re going to need the support of senior management and are therefore going to need some kind of strategy or articulation of plans to gain their support.  In this article, I present some tips on what a good Data Strategy should contain and then delve into some common mistakes that I’ve seen made when attempting to create a Data Strategy and how to avoid them. Please read my Disclaimer by clicking here. It’s easy to spot a great Data Strategy! I've seen a lot of Data Strategies over the years.  I've even written a few of them. The thing amazes me to this day, is how often the same mistakes are made, across various different types of businesses, of different sizes and different industries; with different aspirations and different organisational make-ups. The good news i...

This is the full version of an article that I originally published as a series of 5 posts, compiled here into one so you can read it all in one go. In this article I present a slightly different and simpler spin on how responsibilities for data work in most organisations, plus a few pointers for things companies can do to make data management roles even more effective. Please read my Disclaimer by clicking here. The wonderful truth: establishing who is responsible for data is easy! It's really common for organisations to struggle with concepts such as "data ownership", "data stewardship", "data custodianship" and the like.  When these ideas are introduced, they are often met with resistance, especially when they are communicated as something "new" that need to be done in addition to people's "day jobs". The great thing is, working out who is responsible for data is extremely simple and is based on the fundamental way that any or...

What Data Management lessons can we learn from the way in which information is being reported about the Covid-19 pandemic?  This post provides some observations and links them to good data management practices. Please read my Disclaimer by clicking here. The Covid-19 pandemic has turned the world upside down.  As the grim reality of this terrible disease started to become apparent, the media jumped into action and started reporting “the numbers”: numbers of cases, numbers of deaths, numbers recovered, numbers of PPE equipment delivered, numbers of care homes affected… the list goes on. Along with these numbers came the comparisons.  Comparisons between countries, between states and regions, between demographic groups and so on.  The increases in deaths were terrifying and the comparisons with other countries did nothing but add to the fear, especially when it started to look like the country “we’re” living in is experiencing more deaths, or when you realise th...

In Part 3 of this series, I explained a bit more about how the answers to the high-level executive questions about data need to be compiled, to enable even more insightful steering of your enterprise data transformation initiative.  In this post, I continue the exploration of the “list-based” approach by explaining how to compile your list of systems. Please read my Disclaimer by clicking here. Why systems? Before going into how to compile your list of systems and how “OK” they are, some people may be wondering – why do you need a list of systems, if you’re trying to manage your data? This may seem obvious to some, but I’ve been challenged on this in the past, so it’s worth addressing up front. The answer is very simple: your systems contain your data.  If you don’t do anything with your systems, you are working in theory land.  You can spend as much time as you like on defining your metadata and agreeing data quality rules and all those lovely, data management...

In Part 2 of this series, I outlined the initial questions that senior management should ask to start to get a sense of the scope and scale of the work, so that they can start playing an effective steering role.  In Part 3, I’ll explain a bit more about how the answers to these high level questions need to be compiled, to enable even more insightful steering of the work.  I’m deliberately keeping this to data, systems and issues at this stage: more on how this approach can be used more widely in future posts.  This is where the “list-based” approach starts… Please read my Disclaimer by clicking here. Answering the executive questions: the list-based approach So, the executive-level questions have been asked.  How do you go about compiling the answers? In simple terms, by creating a set of lists, with clear status, priority and ownership against each item in the lists. This bit requires someone with a bit of data management knowledge to lead, if you want it...

In Part 1 of this series, I introduced the challenge that senior executives often face when trying to get a handle on large-scale data transformation initiatives.  In this post, I’ll outline the questions that senior management should ask to start to get a sense of the scope and scale of the work, so that they can start playing an effective steering role. Please read my Disclaimer by clicking here. The simple steering questions As a senior executive, what do you need to know about your data? This is where you should start: the all-important scoping and status tracking questions. Don’t worry about how your teams will work out the answers – we’ll get to that later.  The important thing for you at this stage is to start with the right questions, because they will help steer the actions of your teams in the right way, to get to the right outcomes. So, I would suggest that some good first questions, at a high level, could be: What data is in scope? How much of the i...

A common challenge for senior executives when sponsoring a large-scale data management initiative, is how to get a handle on just how much work there is to do, how long it will take and how much value it will drive.  In this series of posts, I'll introduce a simple approach to enable senior management to do just that, without needing to become data experts themselves.  I call it the “list-based” approach… Please read my Disclaimer by clicking here. Is it all just too big a problem? With an increasing number of laws and regulations forcing companies to make data management a Board-level priority, providing senior management with the mechanisms to understand the state of their data and enabling them to steer actions to manage it appropriately are imperative. More importantly, it is now increasingly widely recognised that businesses not only run on data, but can use their data to drive massive value.  The ability to leverage new digital services, Artificial Intellige...