Volume Decomposition, Part 1: Why Are Sales Up (or Down)?

due-to signpost

Has this happened to you?  Sales of your brand are down vs. the same period last year and management wants to know why.  Sales is saying it’s because there is less advertising this year but Marketing is saying it’s because you’ve lost distribution and the retail price and merchandising are not as competitive.  Another, more pleasant, scenario is that sales are up and Marketing says it’s because of the addition of more advertising this year but Sales says it’s coming from distribution gains and lower pricing.  How do you know what the real answer is?

Since there are many different business drivers that impact sales, the challenge is to estimate how much of the volume change was due to any number of things that were taking place at the same time.  In fact, it is often things that are happening in the store at the point of purchase that have the biggest and most immediate impact on sales.  Fortunately, your IRI/Nielsen database has the data to enable you to look at those retail drivers.  By accounting for as many business drivers as possible, you can get to a decent answer to the question of why sales are up or down.  This post is the first in a series on decomposing a change in volume into its component business drivers.  Future posts will address specific drivers and how to quantify the impact of them on the business.

Due-To Analysis, aka Volume Decomp

An analysis like this is often called a “due-to,” because it tells you how much of the sales change is due to each of the drivers.  It is also known as a volume decomp (short for volume decomposition) or volume bridge (since it bridges the volume from one period to another).  Many of the largest CPG companies have tools from IRI/Nielsen that do this analysis automatically, but smaller companies may not.  Find out if your IRI or Nielsen contract includes a volume decomp tool.  If it doesn’t, it’s usually because of budget constraints but the good news is that you can conduct the analyses described in this and future posts to get to a good approximation of what is driving your business.

First up, what do you want to explain?  See this post about the 3 ways to measure sales – dollars, units and equivalized volume (EQ).  I find it best to use a due-to explain the change in physical volume and not dollar sales.  That way you can show how much a change in pricing affected the physical volume.  You may want to look at the overall dollar impact as well but, for most manufacturers, there are serious operational and cost implications to changes in volume so it’s important to understand and anticipate changes in volume.  If your brand is comprised of multiple sizes, then EQ volume is the best measure to use for this.  And you can also do this analysis for the category or your competition.

Business Drivers and Elasticity

You can think of the business drivers in a due-to as falling into a few different buckets and you have the data needed to address the first 4 buckets right in your IRI/Nielsen database:

  1. Distribution
  2. Pricing
  3. Merchandising
  4. Competition
  5. All Other

Everything else not available in your IRI/Nielsen database that drives the business falls into All Other.  This bucket can have some combination of advertising, consumer promotion, shopper marketing, overall economic conditions, weather and anything else not already mentioned.  You may be able to include some of the All Other drivers in your analysis, if the data is easily available at the right levels of geography and time.

In addition to having data for the drivers, you need an elasticity for each driver.  Think of an elasticity as how much a change in the driver results in a change in volume.  If the elasticity is 1.0, then a 5% increase in the driver results in a 5% increase in volume.  If the elasticity is 0.8, then a 5% increase in the driver results in a 4% increase in volume (0.8 * 5%).  If the elasticity is 1.2, then a 5% increase in the driver results in a 6% increase in volume (1.2 * 5%).  The elasticity is positive if the driver and volume move together or negative if they move in opposite directions and the sign should make sense in real life.  For example, if distribution goes up, volume also goes up so the distribution elasticity will be positive.  Price elasticity, on the other hand, is negative because if price goes up we expect volume to go down.  Elasticities can be determined in different ways and I won’t go into all the analytics behind calculating an elasticity here.  Future posts will talk about where to get or how to estimate the elasticity for each driver.

Due-To Analysis

A due-to starts by looking at changes in volume from one period to another, listing factors that might have driven those changes, and gathering data about how those factors have changed.  It can be presented as a table and/or in graphical form.

The table below shows that Magnificent Muffin volume is up +2.5% vs. year ago in the Total US Food channel and how much each of the drivers themselves have changed over that same period.  With this information compiled, you are ready to work on that last column, the Due-To % chg.

due-to 1

*Due-To % chg = the % change in volume due to that driver.  The sum of the Due-To % chg across all drivers = the % chg vs. year ago for volume.  The Due-To % chg for All Other Drivers is the difference between the % chg vs. year ago for volume and the sum of all the other due-to % chg values.

This type of analysis is often presented in a “waterfall” chart that starts with the year ago volume on the far left, then shows the amount of volume change due to each driver and ends with the volume in the current period.  Negative volume drivers are in red and positive volume drivers are in green.  You can see in this chart that the increase in price and an increase in competitive volume resulted in volume declines, while an increase in distribution and net increase in merchandising across tactics resulted in volume gains for Magnificent Muffins.  All Other drivers also contributed to volume gains – this is where more/better advertising, consumer promotion and/or shopper marketing shows up in the due-to.

due-to waterfall

In the next few posts I’ll talk about how to change the ? in the table into due-to % chg numbers and how to quantify the volume impact of each driver, as depicted in the waterfall chart.

Did you find this article useful?  How do you conduct or present a volume decomp and how is it different than this?  Please share in the comments below.  Subscribe to CPG Data Tip Sheet to get future posts delivered to your email in-box. We publish articles about once a month. We will not share your email address with anyone.

PrintFriendly and PDF

Six Ways To Reduce Your (Inevitable) Data Errors

Data Accuracy

What are the three most important qualities of a great data analyst? 1. They know their data inside and out 2. They draw useful conclusions from their data. 3. They deliver accurate information Robin and I have written many articles … [Continue reading]

How to Be a Great Data Analyst

Better Analyst Insights

Despite the promise of software vendors that their “methodologies extract meaningful and actionable insights from Big Data,” my experience is that no methodology can substitute for the human brain of an astute analyst. Great data analysts are a rare … [Continue reading]

8 Questions To Ask When Combining Multiple Data Sources

combining data sources

One of the advantages of syndicated store data is that it provides you with the most comprehensive retail sales picture you can obtain from a single source. But sometimes you can get greater insight and formulate more powerful arguments by enhancing … [Continue reading]

All About ACV

Store ACV

Earlier this year, we received a frustrated email from a reader. He wrote: “Once and for all, I would like to know exactly what ACV is. You hear several definitions depending on the site you visit. Then I would like to know how to calculate it, what … [Continue reading]