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Avoiding generic dashboards with decision modeling


Sometimes Scott Adams just nails it and late last year I saw this great strip on The Generic Graph. Work with analytics long enough and you see something akin to this – something Mychelle Mollot of Klipfolio called Building a One-size-fits-all Dashboard – one of the 6 mistakes she talks about in this article that she pithily summarizes as the “this sucks for everyone” problem. Mychelle goes on to propose that the solution is not to create a generic dashboard for the broadest possible audience but to create multiple dashboards targeted to specific roles within the organization. I would agree but go further – design dashboards to help specific roles make specific decisions.

Many roles, especially operational roles, have to make many decisions. How they make these decisions, the actions they take as a consequence, are what determine if they will meet their metrics. Displaying their metrics on a dashboard so they can see how well they are doing may be motivating but to actually improve those metrics you will need to help them make better, more profitable decisions. Yet most organizations, most dashboard projects, have never really thought about the decisions made by the people they are trying to help – at least not in any systematic way. In fact, instead of building a dashboard to support decision-making explicitly, most projects begin as Mychelle notes by being “data-centric” – pulling together all the data that might help. This creates a lot of visual confusion  and forces people to jump around multiple tabs or pages looking for the data they need right now to make the decision in front of them.

So how can you fix this problem? Well Mychelle lays out the first two steps:

  1. Figure out who your dashboards need to service
  2. Start with the more junior roles, those with an operational focus

Then move on to the more decision-centric steps:

  1. List the metrics or KPIs they care about
  2. Identify the decisions – the choices – they make that have an impact on these metrics
  3. Model these decisions (using the new Decision Model and Notation standard and a tool like DecisionsFirst Modeler) to understand how they make (or should make) these decisions
    This will give you a sense of the information and knowledge they need as well as how the decision-making breaks down into more granular decisions
  4. Use this model to layout your dashboards, one per decision, looking for opportunities to automate the lower level decisions while you are at it

Decision-centric dashboards really work. Go build some.


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