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Why End of Product Lifecycle Management Matters

Early in the Covid pandemic, many leading CPG companies (Kraft Heinz, Mondelez, General Mills, Unilever) took decisive action to reduce SKU counts by 15-25% in order to focus on their winning SKUs.  There are 5 main benefits to potentially be realized (by any company, not just large CPGs) from an end of product lifecycle management process:

  1. Increased margin / lower costs (transport, warehousing, co-manufacturing)
  2. Increased capacity / decreased complexity
  3. Increased available warehouse space / delayed cost of expansion
  4. Decreased write offs of raw material, packaging, ingredients and finished goods
  5. Increased organizational focus due to simplification

In my experience, a basic and well executed end of product lifecycle process will often deliver a 10-25X financial impact relative to the fully loaded cost of personnel time. Structured properly and with the right people attending, the process requires only a few hours per week over a few weeks. This is the epitome of low hanging fruit!

An end of product lifecycle management process should promote holistic conversations about SKU level health and economics that enables both the commercial side (i.e. The BU, Sales, Marketing, Brand Finance) and the cost control side (i.e. Supply Chain) of a company to educate each other. In terms of the “how” I recommend a collaborative approach that first agrees on 4-8 meaningful metrics based on some subset of the following:

  • Volumes (absolute units shipped or net revenue)
  • Velocity (could be market oriented like point-of-sale data, or operational like inventory turns)
  • Growth rate (2-3 year CAGR)
  • Margins (recommend including both absolute $ and percent)
  • Waste (finished goods and/or materials; can also consider multiple echelons of waste)
  • Manufacturing efficiency (units/hour) or complexity (high set up, changeover or cleaning times)
  • Sustainability metrics (carbon footprint, climate risk, energy consumption, water use, waste/pollution)

A relative ranking process helps narrow the focus to only a subset of SKUs. For example, you could flag SKUs that are in the bottom 20-30% relative to other SKUs for the same metric, then only discuss the 15-30% of SKUs that generated the most flags.

For illustrative purposes, here is a summary for a hypothetical company that I expect has ballpark reality values for the several measurements:

SKU Class Volume SKU Count Margin $ Pallet Spaces Waste $
A 70% 20% 80% 55% 15%
B 20% 30% 15% 30% 35%
C 10% 50% 5% 15% 50%


In this example, the company has defined A items as those in the top 70% of volume, B items in the next 20%, and C items the bottom 10%. The percentages could be unit or revenue based, there is no right answer. With that basic classification, I’ve then associated a SKU Count, Margin $, Pallet Spaces and Waste $ to show the often-disproportionate relationships. And if you’re skeptical, I respectfully challenge you to create this table for your company!

SKU Count matters because every SKU has fixed time and efforts associated with it. For even the smallest volume SKU, there is master data maintenance, sourcing negotiations and contracting, manufacturing set up and changeover times, quality assurance and so on. Depending on the nature of the SKU, it may consist of 5 to 50+ other components, including raw materials, ingredients, packaging, and sub-assemblies. SKU Count is a rough measure of complexity, and complexity constrains capacity. More SKUs equals less capacity because more of your line/asset time will be dedicated to set ups, changeovers, and cleanings.

For the SKU Count to Margin Dollars relationship, my illustration is straight Pareto: 20% of SKUs are driving 80% of Margin Dollars. I’ve seen this approximate relationship across many years and business units alike. There are economies of scale and scope with high volume “A” SKUs: they are often produced internally, picked in pallets, and shipped daily on full truckloads to your biggest customers. In contrast, typical “C” SKUs are sole sourced, produced or procured 2-4 times/year, may require more stock transfers, are picked in layers or cases and may have less than 5 customers or ship to points. In short, “C” SKUs lack economies of scale and scope, and for all the aforementioned reasons they are low margin, slow moving, and taking up disproportionate pallet space.

The end of product lifecycle management process recommendations should be finalized with both commercial and supply chain executives at least several months prior to execution. This allows time for customer communications and managing the final purchases of components and production of finished goods. This should minimize costly write off risks. Ideally it is a cross functional team of sales, product management and supply chain planning folks who work together to fine tune each SKU’s discontinuation plan.

It is not necessary to wait for external forces or crises to engage in end of product lifecycle management. Every company should have at least an annual review process, and there is a strong case (i.e. numerous benefits) for supply chain personnel to take the lead in facilitating.
—Jonathan Fleck, St. Onge Company

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