The Last Mile of Business Intelligence (Revisited)

Here’s another re-juice-inated blog post from years ago. Unfortunately, or perhaps fortunately for us, even after almost eight years, we’re still in the last mile. Even today, with Tableau’s huge success and so many data analytics startups, we still see organizations struggle to turn information into insights for their every day decision makers.

Here is Zach’s post from November 2007:


“The last mile” is a term that often is applied in the telecom industry in reference to “the final leg of delivering connectivity from a communications provider to a customer.” It is an expensive and complex step due to the challenge of pushing information from centralized, high capacity channels to many diverse end-points where information is ultimately used.

We think there is a “last mile” problem in business intelligence too. This critical bridge between data warehouses and communication of insights to decision-makers is often weak or missing. Your investments and meticulous efforts to create a central infrastructure can become worthless without effective delivery to end-users. “But how about my reporting interface?” you wonder. That’s a creaky and narrow bridge to rely on for the last mile of business intelligence.

Listening to our clients, we are confident the last mile is a real problem. The ultimate source of this failure is less clear. Here are a few of theories:

1. The engineers who built the data warehouse build the interface. No offense to the talented individuals who can push around, clean, normalize, and integrate data—but they may not be ideally suited to designing a user interface for non-technical users. A designer wouldn’t create charts that look like this (our favorite example of chart-based encryption):

In the worst case, developers are dismissive of user experience. I’ve met with IT folks who felt confident that providing a massive data table would provide a suitable solution for delivering information to users. “Hey, they’re getting their data. Is there a problem?”

2. Reporting is considered the fundamental mechanism for working with data. Here’s a framework we’ve started to consider in thinking through the multiple approaches for getting value from data:

  • Reporting lets you monitor things that are well-understood and relatively predictable.
  • Exporation or analysis helps you understand new processes and erratic and shifting behaviors.
  • Presentation is about communicating insights and understanding, often building on both reporting and analysis.

Many people assume that a reporting tool is sufficient to do in-depth analysis and communicate results. That’s like trying to build a deck with a screwdriver.

3. Poor fundamentals in information display. Despite the efforts of folks like Edward Tufte and Stephen Few, general literacy in this area is still low. Shiny, 3D pie charts are still acceptable, even desirable in some places. Particularly disturbing is the persistence and pervasiveness of this problem in Excel where there still remains some confusion as to why this is bad information display:

You don’t have to go any further than the Dashboard Spy to find examples of the visual muck that is commonplace.