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How to Avoid 10 Awful CPG Analytics | TABS Analytics

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If you’re in the CPG industry, you probably already know that it is in the midst of an historical lull. Growth has been below 2 percent for the past few years, and weaknesses in the market are particularly pronounced for the major CPG manufacturers

Historically, CPG companies have relied on several metrics to evaluate their business growth, identify competitive advantages to exploit and forecast for the future. The major CPG manufacturers spend hundreds of millions of dollars on analytics to get these answers, but most times the results don’t make a significant impact in moving the needle in terms of sales.

Why? CPG companies are using the wrong analytics. Many of the commonly accepted metrics are not effective measures. Worse yet, they can be counterproductive to companies’ growth aspirations.

TABS Analytics CEO and founder Dr. Kurt Jetta recently hosted a webinar that broke down the 10 metrics that are hurting the CPG industry, and explained how to leverage better analytics to get a more accurate picture of your business. Here’s a sneak peek at a few metrics that you’re likely using, but shouldn’t be. 

 Market Share Change

Virtually every CPG company lives or dies on market share analysis. But in reality, this doesn’t offer the best view on the market since your gain would have to come at the expense of another company or brand. Bottom line: It assumes there’s no way to grow the overall category.

Ultimately, market share is contingent on factors that are out of your control – such as industry innovations or offers of hot-selling holiday packages. For example, your business grows by 5 percent, which is well above historical levels. But then a new innovation hits the market, and pushes the overall industry up 10 percent. Looking at market share analysis, your company would have lost share. But, in reality, your sales have grown – which is the ultimate of objective of any company.   

So, by relying on market share data, you may end up taking counterproductive measures to “grow share” instead of focusing on what’s truly important: “growing sales.”

Rather than looking at change in market share, a better way to get a true sense of how your company is doing is to:

  • Identify Benchmark Competitors – This enables you to avoid getting into category definition issues. What you really want to know is if you’re losing opportunities in the market that other similar companies are taking advantage of.
  • Examine Actual and Relative Growth – Look at actual growth (Is my company growing?) and relative growth (Am I growing in comparison to my company’s benchmark competitors?)


Sales Per Million ACV

Often, you don’t look at sales and share in isolation, but using sales per million ACV is a very non-intuitive approach. It’s impossible to project sales using this analytic because there is no context for what “$1 million of ACV” means. Plus, this figure is not adjusted for different item counts in product groups, which flaws the results. For example, some companies may claim to have more sales per million ACV than other brands, but they don’t account for the fact that they have 60 items on a shelf, when the other brand may only have a fraction of that on shelf. 

Sales per million ACV gives you a directionally identical result as the more intuitive “dollars per point of distribution,” which is why it makes more sense to use that metric instead of sales per million ACV.

Instead of sales per million ACV, better approaches include examining:

  • Sales per Point of Distribution – For a single item
  • Sales per Equivalized SKU (aka ACV Weighted SKU) – For multiple items
  • Sales Productivity Index – To compare items

These approaches are grounded in distribution based analytics and are the foundation of being able to understand and grow your business. To learn more about these measures and how to calculate them, please download our TABS Analytics New Metrics Guide - Part 1, below:

New Metrics Guide 

52-Week Sales Change

Dr. Jetta described 52-week sales change as the “lazy man’s approach,” since it’s not truly reflective of recent history, which is the best data to use for predictive analytics.  A full year is a long period, and so much can happen during that time to alter the CPG landscape that this metric isn’t a good way to look at the market overall. And, it dilutes the analysis of innovation. Take, for example, a blockbuster product that has only logged 10 weeks of sales.  The true impact of this product gets washed out when examining sales on a 52-week basis. And it’s particularly bad, too, for products in year two of their lifecycle.

Rather than relying solely on 52-week sales, you will get a clearer picture by doing a momentum chart that examines 52-, 24-, 12- and 4-week results. This approach helps put the 52 weeks in context and can help determine if a product is trending the right way. 52-week sales change can be the first level of analysis, to identify if a product is trending up or down. But you will need to drill down deeper to look at whether the sales are a function of growth in distribution, pricing or philosophy, or a combination of the three. These additional metrics will help explain exactly why velocity is moving in a given direction.

The Remaining 7 Metrics...

These are only a few of the awful analytics that Dr. Jetta discussed during the webinar.  Others included:

  • Average Weekly ACV
  • Percent ACV (Sales) with Display
  • Baseline Units
  • Average Items Per Store
  • SKU Optimization Curves
  • Leakage Tree
  • Consumer Decision Tree

 To learn more about why you should ditch these metrics and how to better measure your business, watch the webinar Awful Analytics: 10 Metrics Hurting the CPG Industry and How to Fix It

 TABS Analytics Fact-Based Selling White Paper