Building dashboards is cowardly

Blindly building yet another dashboard is an act of cowardice. In today’s application world, dashboards alone don’t rise to the challenge of solving people’s real problems.

As you will read in Logi’s latest State of Embedded Analytics Report, the bad news is dashboards are still the top item on most organizations’ roadmaps. The good news is many organizations are thinking about how they expand the use of embedded analytics to provide better solutions.

End users don’t ask for a dashboard because they really use them. They ask for them out of the need for a safety blanket that gives them the (incorrect) belief they will know everything they need to about their business. The noise of a dashboard can be comforting, but it can cause issues when it’s not truly needed (ask doctors about iatrogenic effects). With a dashboard, there is no assurance that the right information is there in context to make a decision when necessary.

I have worked for large (Microsoft, Waze, KAYAK) and small organizations where access to the right data is key. The benefits of data, when analyzed, are to synthesize information for people to make better decisions. What always resonated best was when information was put in context and could be turned into action towards some purpose or goal. Without that next step, the analysis may as well not exist at all.

Recently, the product world has been focused on understanding what problems people have and how to help solve them. As we find in the “Jobs To Be Done” theory, anywhere there is a solution that is cobbled together, you can find an opportunity.

Exporting a CSV to another system is a ‘cobbled together’ solution. It is a hassle. The people using your application don’t want that. They want to be able to do analysis and make decisions in the same place.

Embedded analytics allows companies to easily integrate analytics information to address the full job that a person needs done.

The question you should be asking yourself when considering embedded analytics for your application is how does your customer differentiate from valuable information to make decisions and ignore the noise? How do they turn information into action towards their end goals?

The competitive moat isn’t broadened by offering more detailed analysis. Distance from your competitors is increased when you give someone an understanding of how to achieve an outcome.

Looking to the future, machine learning will become a high priority for many companies. To be able to leverage it, you must understand the drudgery of a person’s job. First, you need to have the right information alongside the action taking place. And second, you need to understand the hidden relationship between information and the next step.

I hope that you find this report as exciting as I did in understanding how organizations view embedded analytics. What you will find is valuable information for making the case to internal stakeholders and where to look for innovation.

Don’t build yet another dashboard. Instead, help people solve their problems with the right information.

This is the forward I wrote for the Logi’s “2017 State of Embedded Analytics Report: The Fifth Annual Review of Embedded Analytics Trends and Tactics.” It has a lot of great information on the trajectory of the analytics industry and the implementation by organizations. I’ll also be doing a webinar on the topic later in April.

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