2. As we mentioned in the previous activity, if bins of a
histogram are too wide, they may actually hide critical
information that will help you understand what’s going on
with the data. On the other hand, if bins are too narrow, the
histogram becomes too cumbersome and variation may
reflect random behavior and not significant changes.
Monday Histogram
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3. Our mission in this activity is to explore how a poorly
developed histogram can actually hide valuable information
or at best make it difficult to decipher.
We’ll do this by walking through a scenario with a poorly-
constructed histogram and a well-constructed histogram to
illustrate how this might happen.
Monday Histogram
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4. As Chief Financial Officer, your job analyze revenues to make
sure projections and goals have been met and make new
goals for the upcoming year. The 2012 fiscal year just ended.
The revenue goal for your company was $200 million, but
the actual revenue only ended up being $170 million. The
CEO requested that you develop a revenue chart that will
illustrate any patterns, so you create the histogram below.

5. Remember, the bin width of a histogram depends largely on
what you’re trying to analyze. In your case, the CEO asked
you to look for patterns that explain the missed goal.
With a quick look, you determine that with the lower
revenue in Q1, Q2, and Q3, the company was unable to
make the goal of $200 million. However, after taking this
course, you realize that a histogram with only four bins
might not be telling the full story.

6. You decide to create a new histogram, this time one with
twelve bins—which means a 30 day interval between each
bin. This will demonstrate revenue by months rather than by
quarter. The histogram you generate is pictured below. The
story is now much more complex and allows you to look for
patterns much easier than the four bin histogram.

7. After exploring the histogram, you might have noticed that
the months of March and April fell short on revenue, as well
as the months of June, July, and August. What might have
caused this suspicious drops in revenue during these
months?

8. The company holds its annual user’s conference the last
week of March and the first week of April. After analysis of
this possible cause, you determine that many customers
spent money on travel costs to the conference instead of
buying your product. Also, salespersons were heavily
involved in the marketing ramp up before the conference
and in scheduling spots for 2013 after, which means they
had less time to sell in March and April.

9. As for the months of June, July, and August, you checked
PTO records and found that many sales employees took
vacations in the summer months. In addition, many
tradeshows are held during summer months which involve
salespersons as exhibitors. The tradeshows are valuable
marketing venues, but it also means that while exhibiting at
the tradeshows, the salespeople are not on the phones
selling product.

10. The first histogram showing revenue by quarter identified
three quarters falling short of targets; however, just looking
at that the four bins makes it very difficult to pinpoint the
cause of the problem.
The second histogram showing revenue by month was much
more helpful because it keyed you in to dramatically low
revenue months, facts hidden in the first histogram.

11. LETS RECAP!
If bins in a histogram are too wide or too narrow, important
information may be overlooked or misrepresented due to
random variations. It’s important to have accurate bin
numbers and widths to ensure that a histogram is not hiding
an important part of the story.

12. CRITICAL THINKING: What can you do to tell the
difference between a random variation and a
data pattern that could indicate a problem?
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