Ensuring Good User Adoption
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I wrote a post early last year on user adoption. It is one of the most challenging aspects of BI, and many organziations struggle a great deal with how to address it. The most important thing to do when considering user adoption is timing. As in, don’t think about user adoption after you realize you don’t have any. There needs to be a thoughtful consideration regarding user adoption and all aspects of it. This post will give you some good ideas and a framework for creating a user adoption strategy.
Out of all the things we have ‘discussed’ during this blog series, user adoption may be the most critical, User adoption can make or break your BI program, it drives your ROI and it’s the mechanism for how value gets delivered to the organization. The more users you have, the better information your organization has to make informed decisions. But user adoption can be quite elusive. I admit that it’s the one topic that theoretically I understand but in practice has tripped me up more than once.
Based on my ‘trip-ups’ I have designed the “Trinity of User Adoption” the three things that if you don’t do will jeopardize user adoption. This isn’t an inclusive list, but I believe covers the key problem areas.
1. Trust
If your users don’t trust the data, nothing else you do matters. Trust is related to data quality, data governance, metadata and good communication. It’s really easy to erode trust and nearly impossible to get back. If there is no other reason to create a data governance function, this is it. Your users will abandon your thoughtfully laid out BI system faster than the last lap at a NASCAR race if the data is considered ‘inaccurate’ and be aware that ‘inaccurate’ is not defined by you, but by them.
2. Ease of Use
I have something I call the User Continuum and it helps my customers think about their users in three different categories. The value to that is you are better prepared to design reports and modify the GUI for a variety of different skill sets. This is a big challenge for many BI programs, because our tendency to focus on one user type such as the high end users which isolates the majority of the users – and the opposite is true too.
3. Training
If you think training your users once is enough you should determine how they use the program. If they are logging in once a month, or once a quarter I guarantee you they are not going to remember how to use it. I also find that many organizations think that they don’t have to train because the systems are so user friendly. But that’s not always the case and every user has a different capability set. Unless you know for a fact that all of your users are experts at software usage don’t assume that you can skip training.
