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Barriers to data fluency

  By Martha Horler   - Thursday 31 October 2019

Back in January, I wrote about data fluency, which is the idea that more people across all organisational functions need to be using, understanding and creating more with the data they have. The need for this seems to only have increased, with data becoming even more of a hot topic in the higher education sector. However, this is not an easy thing to achieve, and there can be a number of barriers to overcome before significant progress can be made.

Report and dashboard proliferation

One report is never enough. For every report that is created, five more are needed to dig further into the topic or see it from another angle. Once a critical mass of reports is reached, you then start to see duplication of reports, either from developers not knowing what already exists, or wanting the same thing only slightly different. How often are reporting teams asked to remove reports? I would hazard a guess that it’s not often – you never know when you might need it, or so the thinking goes. After some time, a new director decides to implement a different reporting system that will make everything much easier, but no one wants to turn off the old one as so many people are using it daily, so now you have two systems.

Dashboards have been a more recent phenomenon, especially now that tools are available that make building them easier for non-technical staff. These also suffer the same fate, with a proliferation of different dashboards for every area, sometimes doing the same job as some of the older reports do. Just with fancier graphics perhaps. Dashboards come with their own set of problems, as many of the tools available now allow a lot of customisation and tinkering with colours, shapes and effects. It can be far too easy to create something that no one can bear to actually look at.

These barriers can be overcome, using a mix of training, careful choice of BI tools, and putting processes in place to prevent the over-proliferation of reports. It can be a hard balance to achieve, and may not be a popular approach, but the rewards are better management of your institutional reporting and hopefully a refocus on what you are trying to use the data for, not how pretty it looks.

Silos and dictatorship

Data silos are present anytime data is taken from one system or application and put into another, something we all do whenever we copy data into a separate spreadsheet. Alternatively, a data silo can be a database that is completely separate from any other data source, even if it aims to represent the same information – the classic example being when you are transferred on a customer service call and having to give them your details all over again as they are using a different system. Having data in different eco-systems creates duplication, waste and frustration.

However, IT departments should be wary of hunting these silos down and just eliminating them. People will often have created them out of a genuine business need, which may not be being met through the mainstream applications. Removing them without understanding why they were created can give users the impression that the IT team believes they are the ones who should dictate how data can be used.

Both of these issues can be mitigated by bringing together both the IT teams and the users of the data to build the systems required by the organisation. Users will usually be the ones that understand how data can drive decisions, ensure compliance with regulations and improve customer service. IT departments can then advise on how best to structure the underlying systems so that all the user’s requirements are met, and in ways that reduce the effects of data silos.

All of these barriers can be overcome with better communication of requirements, monitoring of processes and collaboration between teams – all of which are vital ingredients to achieving data fluency in our organisations.

Martha

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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