Day Two of Essential Practice Skills for High-Impact Analytics Projects

Analytics & AI / Ramblings

The seminar was an intensive on Structured Problem Solving, which I think is a term created by professor Patrick Noonan. A book may be in the works. I certainly hope so as there was tremendous wisdom and experience packed into these two days. Referring to the slide deck will help, but not the same way a comprehensive book would.

So what is Structured Problem Solving? It is a way to identify the real issue and then methodically move through various steps including research, task identification and communication, ultimately resulting in action. Be sure to keep the end goal in mind. Anyone who loves data understands that looking for other insights “just because” can waste a tremendous amount of time. That extra effort may be interesting but may not be aligned with the immediate needs of the company or customer. We had a great conversation about scope creep—and how that can come from both the requestor and from the team doing the work.

The high-level steps of Structured Problem Solving are:

  • Define the Problem
  • Break Down the Problem
  • Plan the Work
  • Work the Plan
  • Build the Case
  • Tell the Story
  • Start the Change

I have been in charge of software development teams of various size for over 20 years, including internal developers and outsourced teams. During that time, I’ve seen requirements and management styles shift from Waterfall to Agile. SPS is especially enticing to me as the advantages of Agile and iterative methodologies have become so apparent on so many projects. Each one of the steps above is tackled by a team in an iterative process and then refined or worked individually. Every team member understands the big picture, and every team member understands how their part fits into the whole. The final product truly is a gestalt.

Structure Problem Solving is a technique I intend to use both personally and professionally to bring clarity of thought and process to non-trivial tasks.

There were two other major highlights of the day. The first was on data visualization. As the actions should be based on logic and facts, they should be natural conclusions of the research. The question always is how can the data be presented with both the least cognitive load and the most clarity—especially when the results are being presented to non-technical people. Several examples of poorly chosen graphics were studied and better options discussed. Of course, the works of Edward Tufte’s The Visual Display of Quantitative Information and Stephen Kosslyn’s Clear and to the Point: 8 Psychological Principles for Compelling PowerPoint Presentations were referenced and highlighted in many ways.

The second major highlight was the time we spent discussing creativity. Some people in the room had practice with structured creativity while the concept was new to others. I have used Brainstorming and Devil’s Advocate approaches effectively for years. The concepts of Brainsteering and Six Thinking Hats were both new to me. The bottom line: creative insight doesn’t happen accidentally. Creative insight happens within the context of intentionally focused thinking.

This course will definitely change my management style for years to come.