Category Archives: Methodology and "How To"

Now I See It! (The link between visualization and creativity)

We are visual people.  We recall past events by the mental picture we see (or create).  Words are powerful and can be precise, of course, but visual images can often leave very strong and lasting impressions in our minds.

It’s even in the way we describe our understanding of things.  When we say, “I see it!” to describe an idea, this is more than just saying, “I understand what you are saying.”.  We may actually visualize some embodiment of the idea, like someone using the product, walking through a business process, or people faces lighting up as they get their problems resolved.

To be clear, I am not talking about using images or visuals in our presentations or descriptions.  I am quite familiar with business diagrams, process maps, various charts and graphs and other (good and useful) visual tools we have developed over the decades.  These can be helpful, sometimes very helpful (or sometimes not).  Instead, I am talking about the mental work of visualizing something.

So what is the link between visualization and creativity?  In a recent TechCrunch post from Mark Suster, he claims that “all business success relies on creativity”.  He then goes on to describe how he uses visualization to drive creativity.  It’s a long post with one small NSFW element.  It’s also very personal, from a “what has worked for me” approach from Suster.  Other than that, I think it’s a good article.

It’s good because we don’t think much about creativity.  We label something as “creative” and use that terminology post facto, or in preparation of something we do.  But “being creative in something we are doing now” is something that’s relatively difficult if you are out of practice.  So before you draw, write, sort data, open a powerpoint template, even start an outline, maybe we should take a moment and visualize.  Think of what you are asked to do: re-design a business process, look for trends in data, create the world’s most perfect powerpoint page, prepare a weekly report, snuff out competition.  See if visualizing (as described in the TechCrunch post) helps.  It’s free, and it doesn’t have to take a lot of time.  And it gets easier and more productive over time.


2010: Year in Review (by Search Terms)

Welcome to the Business Analytics for a Complex World!  Or in some cases, welcome back!  Many of you are here because you know me, or I have pointed you to a specific post.  Some are clicking through from LinkedIn, facebook, or other hard links.  But many of you are finding this blog through search engines.  Thanks to some nice tools provided by wordpress and statcounter, I know which terms were used to find this blog in 2010.

This is a word cloud of the most popular words used to find this blog.  This first picture is “mostly unfiltered”.  The size of each word reflects the frequency (the number of times) used in a search engine request that someone used to click through to this blog.  (The colors mean nothing in this graphic.)  The only words not included are common English words, like “a”, “the”, “is”, etc.

What stands out?  The word, “business” is quite popular — but that’s to be expected.  There are smatterings of other words that seem to show up: “bubble”, “analytics”, “chart”, etc.

I find such word clouds to be interesting; however, in most cases, it helps to show more than one word cloud, even if it’s based on the same content.  That’s because, I believe, it’s important to help your audience not feel like an idiot.  Let me explain.  Any new graphic, even if it’s “obvious” takes some time to get used to.  With one example, sometimes it’s hard to get used to the new graph.

So, I generated a second graphic:

The second picture is like the first, but I weighted the terms that were used multiple times.  For example, the exact search term “how much oil is leaking” was by far the most popular (several hundred!), so I increased the size of some of those terms.  This does several things to the picture: it starts to show that there are a few “tiers” or “levels” of popular terms.  This helps us to focus on the most popular terms, such as “leaking”, “bubble”, “analytics”, and so on.

Remember that your audience goes through a few phases when they see something like this.  At first, they have to figure out what it is.  Then they have to figure out what it might mean.  You may be very familiar with the underlying topic and “what the graph” means, but please be courteous to your audience… provide a simple guide or step-through.

Error in Aetna’s Model Pricing Model

It’s not often that a model gets front page attention at the Wall Street Journal.  Last Friday, WSJ placed an article on Aetna’s pricing model trouble on the front page of the Marketplace section.  According to the article, Aetna had to pull a request for increasing prices for California policyholders when they discovered “miscalculations” in the monthly premiums.  It’s not clear from the article if there were multiple errors or the magnitude of the errors.  This story comes a few months after another insurer, Wellpoint, received similar press about how external auditors found mathematical errors in their filing.

How can this happen?  You would expect that with something so important, there would be ways to make sure that “model errors” would be caught and fixed BEFORE things get filed and rate increases are announced.  (Approximately 765,000 Wellpoint and Aetna policyholders would have been affected by the “wrong” price increase had the errors not been found.)

I have not worked with either company, but I have seen several kinds of similar mistakes in pricing/cost models.  The fact that many mathematical models have mistakes is not a surprise for those who study how models are built and used.  Ray Panko, whose research focuses on spreadsheet errors, has collected data from several authors that show that 88% of spreadsheets have errors.  Furthermore, Panko has found that 1% of all spreadsheet formulas are in error.  One percent may seem small… until you consider how “big” one mistake can be.  Can you imagine how many formulas must be in Wellpoint or Aetna’s model?

I recall talking to folks at NASA about failure rates for the 10,000 components they may have on a Space Shuttle.  One tenth of one percent failure (0.1%) is still 10 components.  Some components have backups or may be non-essential, but many components are essential to the survival of the crew and the success of the mission.

Think about your last “big model”.  How many errors do you think it has?  Would you be open to letting others audit it?