Writing a data strategy - part two

By Martha Horler   By Martha Horler   - Friday 14 June 2019

In my last article I discussed how to prepare a data strategy, we will now look at a process for writing one for your institution. Every data strategy will be different, and there is no one best way to approach it. Much will depend on what you have learnt while preparing for it, and the direction you think your organisation should be taking in how it uses data. It may help to start your strategy by putting in writing what its objective is – this should be a short statement that simply describes your purpose. This will be key to the rest of your strategy and should be the element you spend time on, getting agreement from your stakeholders.

If a data strategy is something new for your organisation it may help to include a section detailing the context for this, why you are writing one, and what you hope it will achieve. Linking to your organisation’s mission at this point can help show how it relates to the overall strategy and how it can help you get to where you want to be. This can be an important element for getting senior management buy-in, as data is sometimes seen as complicated and confusing, so pointing out how it can contribute to the overall plan can help overcome any resistance.

There are two elements that should be included in a data strategy: the principles you will adhere to, and the components you will develop to achieve it. This isn’t at a detailed planning level, that comes after the strategy, but should show the main areas that will need investment or development if the strategy is to be achieved.

A principle is a value that can be used to guide or evaluate behaviour. You will need these in your data strategy, and they need to be clear enough that people can integrate them into their practices. One example is data quality: what expectations do you have about the quality of your data? Do you expect perfect data (an admirable if unachievable aim), or will it be enough to ensure you meet the requirements of your external reporting needs? Accessibility is another common principle: who should have access to the data, and how will you control this? Will your students be able to access their data on-demand or will there be procedures in place to regulate this?  You do not need a long list of principles, but 5-7 should be enough without introducing too much complication.

The final element you should include is a list of the components you will need to develop or invest in to achieve the objective you have stated.  This might mean indicating any necessary systems development work, or how you will use business intelligence in your organisation. This area will almost certainly require input from your IT team, as they will likely be involved in the development of these components.

One important component that you should consider is the culture of your organisation. Do you have a data-friendly culture? Is your institution organised to make the most of its data assets? Do you have data stewards in place who are confident in their role? Data is widespread, with most people in an organisation using it on a daily basis. They therefore have responsibility for it, and the culture that exists around this needs to be explored in your strategy, and ways to develop it included.

The length of your data strategy is our final consideration. This will be informed by who you expect to read it, how you want it to be used, and whether data is a common topic of discussion in your organisation. As a general rule of thumb, I would say it needs to be long enough to understand, but short enough to remember. Ideally you want people to refer to it in meetings and discussions and be able to put the principles into practice every day. If they can do that, you will be on your way to delivering a successful data strategy.

Martha Horler is a Data & Compliance Manager and a member of the SROC Steering Committee. She has spent over 10 years working in higher education, much of that with data and information systems. She has a particular interest in raising data literacy across higher education, with the aim of making data more accessible to both users and senior managers. Follow her on Twitter @thedatagoddess

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