Blindly building yet another dashboard is an act of cowardice. In today’s application-driven 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 dashboards because they really use them. They ask for them because they need a safety blanket that gives them the (incorrect) belief that they will know everything 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 contextual information is there 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 benefit of data, when analyzed, is better decision-making. What always resonates best is when information is presented in context and can be turned into action towards some purpose or goal. Without that last 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 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 needs of their end users. When considering embedded analytics for your application, ask yourself this: How does your customer differentiate the valuable information to make decisions and ignore the noise? How do they turn that information into action towards their end goals?
The competitive moat isn’t broadened simply because you offer more detailed analysis. Rather, you increase distance from your competitors when you give someone an understanding of how to achieve an outcome. Looking into the future, we know that 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 as it takes place. And second, you need to understand the hidden relationship between information and the next step.
I hope you find the full State of Embedded Analytics Report as exciting as I did in understanding how organizations view embedded analytics. What you’ll learn is valuable information for making a case to your internal stakeholders and where to look for innovation.
Don’t build yet another dashboard. Instead, help people solve their problems with the right information.
post was originally published on this site