Analytics: Frequency Distribution & Bell Curves

8 11 2010

A statistical method we often overlook is the distribution curve.  I think most of the time it is dismissed because people get nervous about using statistics if they are uncomfortable with math.  While there are some advanced concepts around using a frequency curve, it can also be used visually as a simple tool to explain results.

A simple stats lesson….

Normal Bell Curve – roughly 68% of the population is within 1 standard deviation (measure of variation) of the average and 95% is within two standard deviations. Below is an example of IQ scores.  The average score is 100 and 68% of the data is between 85 & 115.

While this visualization doesn’t do a tremendous amount for us, this is what we assume when we think of populations, like customers and employees.  And because of our limited statistical training we make a large number of assumptions based on averages.  We love to look at average revenue: average revenue per employee, average revenue per customer, etc.  This thinking also gets us looking into the outliers (that <5% that sits way out to the left or right of the chart).  How much time do you spend on less than 5% of the business?

OK, so back to thinking of this in terms of running a business….

Let’s map out our revenue per customer.  I would be willing to bet it looks something like the following:

If this is the customer revenue distribution, if we use the average number in our analyzes we can quickly generate a number of wrong assumptions.  First and foremost, our typical customer is larger than reality.  It might lead us to think we are serving mid-sized businesses than more likely smaller market customers.  I am also willing to bet our profitability per customer has a similar curve to it.  In this case we are likely spending money on the wrong customers and aligning our better services to a lower profit generating customer (or more likely a profit destroying customer).

Do we need to use it in everything? Of course not, but it might help everyone once in a while to challenge our overuse of the mathematical average to reassess perspectives of our business.  A great place to start is map out the customer base in terms of revenue (profitability is better, but takes a lot longer to do).  It might just lead you to understand your customer (think customer segmentation) better.

Real life example…I was once part of a research project to understand discounting to one side of the outliers (<1% of the business).  The outcome was to focus on reducing discounting to that <1% of the business.  What I argued was to focus on the larger part of the business, where the same efforts would have resulted in millions more in terms of profits.  It was a clear lesson is where to apply process improvement.

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The end of Blockbusters…

23 09 2010

OK, well it is potentially the end of Blockbuster Inc.  This morning Blockbuster filed for chapter 11 protection.  It is a great example of the Risk of being the market leader.  They owned the market, they were on top of the world.  I am sure during their heyday money was being thrown all over the place.

I would love to hear these questions answered:

The trap of leadership is that you often have to wait and see the result.  You are often not allowed to change your business model until it is too late.  If you change it when you probably need to and a loss occurs, then everyone loses their jobs.  The analysts would quickly call out leadership saying that they lost market share because of the business model shift.  Even it is was a great move that would ultimately save the company, our short term focus is entirely too great.

It is also difficult to understand the nature of the perceived threat.  I am sure there were a couple of times when Management said “what do we do about NetFlix and the changes in the market?”  I would guess that 10% market share did not scare anyone, nor 20%.  Yet, at this point there was too much momentum.

As leaders, when do we act?

If we react too soon, we risk looking prone to panic.  We can always explain it easier after the fact.  Our egos, politics in general, and concern about saving face probably drive more decisions than anyone would ever want to admit.

All to often we push harder on marketing and sales to cover shortfalls in market share.  I would be willing to bet that the company spent more time creating sales spiffs and getting creative in terms of finances, than investing in new business models.  What this leads to is a further entrenchment into the business model, a “we can weather this storm” mentality.

I wonder what would have happened if they would have set hard targets in terms of driving action.  What if they would have said “once our market share slips by 10%, I want a meeting where we come up with 5 new business models”.  We are just not trained to think about creating very specific action.

We ponder and delay (then get out and let someone else handle the mess).





Employment Situation November 2009

7 12 2009

On Friday, the BLS released the Employment Situation report.  Everyone jumped on the news that the unemployment rate actually dropped for the first time in months.  While this is a great indicator, the basis for the jump was an increase in temporary help and healthcare jobs.  With Christmas looming,  I fear this is an artificial indicator as this is temporary help for a season that requires more than normal levels of help.  We need a number of industries adding jobs for this report to be positive, until then it is just a little less negative.

We lost 11,000 jobs compared to the 130,000 that Wall Street expected.  Or perhaps we have cut so many jobs the last few months, that we could not find a place to cut anymore.  I am also curious if this isn’t a little manipulated either in timing or impact as the President has been calling for job creation.

What I would really like to see out of Congress and the White House are very specific plans around job creation.  Just like a company saying we want to see 20% growth, yet not laying out the specific marketing, sales, and operational plans to get there it is all just hope.  And hope is not strategy.





Productivity Management

9 07 2009

Performance typically ebbs and flows along a number of fronts.  In the worst cases it declines across multiple areas when it is not managed consistently.  Most productivity initiatives create curves something like below:

Productivity Management

  • At point A – we have identified a performance issue and have created a plan to improve performance.
  • At point B – we have succeeded and typically move on to solve another issue.
  • At point C – we start to see productivity decrease from lack of management and attention.

Unfortunately, most things don’t have pretty economic curves or requires focused thought to create one.  And if we do not create a performance plan we typically see the inflection point at C happen closer to A.  This happens because we have not put a plan in place and/or when we feel some momentium we abandon management of the initiative to fight the next battle.





Going Green

17 06 2009

There are a number of ways companies are “greening.”

  • Some are creating green initiatives and tasks
  • Some are creating green strategic objectives
  • Some are merely applying green make up

In all likelihood, the success will be based upon the level of seriousness and commitment the organization applies.  This is a fad, and leaders will emerge.  Those leaders will reap enormous benefits, the others will be average.

Traditionally, we have talked about 3 business focuses:  Product Leadership, Customer Intimacy, and Operational Excellence.  In each of these cases, you could link “green” strategic objectives, initiatives, and policies into each of these categories.  You could also create a 4th category to trigger discussions about priority and focus of the organization.  A great example here is Patagonia.  They live their commitment to evnironmental stewardship as they understand their clients playground is the environment.

Patagonia Strategy Map

Sample Strategy Map - designed from public documents

During the 2008 Presidential race, Sarah Palin created a great amount of buzz for a number of products.  Patagonia bucked the trend in support of their beliefs:

“Patagonia’s environmental mission greatly differs from Sarah Palin’s,” Patagonia rep Jen Rapp told the WSJ. “Just wearing the clothing of an environmental company does not necessarily make someone an environmentalist.”

  • How committed are you to the success of your green programs?
  • Are you ready to forgo revenue today, for sustainable benefits?
  • Is green an executive agenda, a marketing initiative, or grass roots initiative?




Setting Targets

23 04 2009

Setting targets for Performance Indicators should be well thought through. This should not be an exercise in looking at the historical average (unless that is specifically relevant) and then apply 10% as the desired increase. You will want to review history, but you need to understand the goal. It is also important to define the KPI clearly.

For example, let’s use the retail market’s target of sales to sales last year. Retail has traditionally looked at this on a daily basis, as well as rolled up to the week, month, quarter, and year. I have two primary concerns with this:
  • If the weather was bad, we ran a promotion, or some other contributing factor, we may not know it and are really not comparing apples to apples. Additionally, what if last year was really bad? Beating that number doesn’t do much for us. 
  • If we are reviewing this on a daily basis, we loose institutional knowledge due to the repetition. What if we miss a day? Is there any repercussion? What if we miss three days in a row? What if we miss 10 days out of 14? Were there enough days in there of good performance to hide the fact that a trend is occurring?

What would make more sense to me would be to look at this number as a rolling average, or take the total sales for the last 365 days / 365 on a daily basis. Here we can very quickly identify a positive or negative trend, as we don’t have to look at numbers that swing wildly by the day of the week. Instead of talking about  a couple of bad days, we understand that even though we had a couple of bad days, the overall trend is above the goal. We can also integrate our sales goal and show it relative to the trend line.