Top 3 Data Strategy Mistakes (and How To Avoid Them) – Part 1 of 5
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 series of posts, 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.
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 is, it's also very easy to spot these errors, often within seconds of picking up a Strategy to read. Given how easy it is to identify the common mistakes that are made, it's also easy to avoid them - and this series of posts has been written to help you do just that.
A Data Strategy is just like any other strategy and its structure should therefore cover the same basic things. In its broadest sense, it needs to cover:
The “where are we now” will cover currently known strengths and weaknesses, risks and issues. It may include the findings of audits or gaps in relation to some new aspiration that your organisation has.
The “where do we want to be” is an articulation of a vision for the future. It may use some kind of framework to describe a target state or may build on the organisation’s wider business vision as a way of describing a desired end point.
The “how will we get there” provides a roadmap for achieving the vision. At a minimum, it describes a set of specific actions, behaviours and measures to move in the right direction. Often it will provide some sense of timescales, even if at a high level (such as quarterly milestones).
Beyond the above points, a Data Strategy can take various forms. It may be written as a formal document or as a highly visual presentation. I’ve seen Data Strategies that are relatively brief and those that are many pages long.
Format and structure are less important than the fact that the right questions are answered and that it is presented in a way that enables its audiences to understand what is trying to be achieved and what needs to be done to get there.
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 is, it's also very easy to spot these errors, often within seconds of picking up a Strategy to read. Given how easy it is to identify the common mistakes that are made, it's also easy to avoid them - and this series of posts has been written to help you do just that.
What’s in a Data Strategy?
Before I introduce the most common mistakes, it’s important to have an idea of what a Data Strategy is, in the first place.A Data Strategy is just like any other strategy and its structure should therefore cover the same basic things. In its broadest sense, it needs to cover:
- Where are we now?
- Where do we want to be?
- How will we get there?
The “where are we now” will cover currently known strengths and weaknesses, risks and issues. It may include the findings of audits or gaps in relation to some new aspiration that your organisation has.
The “where do we want to be” is an articulation of a vision for the future. It may use some kind of framework to describe a target state or may build on the organisation’s wider business vision as a way of describing a desired end point.
The “how will we get there” provides a roadmap for achieving the vision. At a minimum, it describes a set of specific actions, behaviours and measures to move in the right direction. Often it will provide some sense of timescales, even if at a high level (such as quarterly milestones).
Beyond the above points, a Data Strategy can take various forms. It may be written as a formal document or as a highly visual presentation. I’ve seen Data Strategies that are relatively brief and those that are many pages long.
Format and structure are less important than the fact that the right questions are answered and that it is presented in a way that enables its audiences to understand what is trying to be achieved and what needs to be done to get there.
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