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What’s Wrong with ABC Inventory Classification
eBooks & Briefs
How to Optimize Inventory in the Digital Age
For businesses with complex supply chains and demand uncertainty, service-driven inventory optimization is the better way to optimize inventory in the digital age. Here's why.
Introduction
As many as 75 percent of companies are still trying to use spreadsheets to optimize their inventories. Most still also use ABC Classification, which dates all the way back to 1951. Planners relying on last century’s solutions, however, stand little chance of being able to meet both service level and financial goals in a sustainable way. Global supply and demand is affected by such a staggering range of planning variables nowadays that ABC inventory planning on spreadsheets is akin to using a feather to crack a coconut.
Fortunately, the digital age has ushered in new tools, science, and ways of working, with the common thread of automation. According to a 2019 study by MHI and Deloitte “Elevating Supply Chain Digital Consciousness” inventory optimization (IO) tools, predictive analytics and artificial intelligence (AI) are among seven ‘NextGen’ solutions having the greatest impact on supply chains. Not only can these handle complexity, they actually thrive on it. They enable planners in companies as large as Procter & Gamble down to mid-sized family businesses to optimize inventory across their supply networks while freeing up capacity to engage in creative, personal and value-added tasks.
The most exciting part? Though much more powerful, these solutions are relatively easy to deploy and they empower and liberate supply chain professionals. Humans get to apply their business and market expertise and delegate the onerous, labor-intensive and precise data management and analysis to the machines. This ebook, which draws on hundreds of successful deployments, will introduce you to the new building blocks for optimizing inventory in the digital age so you don’t get left behind. It’s right for you if your supply chain is characterized by:
- Diverse inventory mix needs that don’t mesh well with ABC inventory classification or simple rules of thumb
- A high percentage of long-tail items
- Multiple demand streams, each usually with different service level requirements
- Global, multi-echelon supply and demand networks
- Seasonality, replenishment constraints
- Manufacturing constraints
- Promotional impacts
- New product introductions
Table of Contents
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Service-Driven Inventory Optimization: A Better Approach
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Probability Forecasting: a Primer for Supply Chain Planners
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How Probability Forecasting Drives ServiceDriven Inventory Optimization
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How to Pick the Right IO Tool: 7 Steps from Nucleus Research
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Case Studies
The current generation wants the opportunity to be creative and solve challenging problems. They are not infatuated with the mundane. They want the flexibility to leverage their unique understanding of NextGen supply chains.*
*2019 MHI Annual Industry Report: Elevating Digital Consciousness eBook / How to Optimize Inventory in the Digital Age
Randy Bradley, Assistant Professor of Supply Chain Management, University of Tennessee.
What’s Wrong with ABC Inventory Analysis?
Before we introduce new tools and techniques, let’s confront where we’re going wrong. First stop: ABC inventory analysis. This has been around so long that most planners just assume it’s the only way to segment an SKU portfolio. In fact, it’s not. It’s not even nearly the best way. ABC is a throwback dating back to 1951. Though it has served us well for many years, it hasn’t responded to changing business requirements nor the massive increase in computer power that’s enabled far better ways of solving the problem. This chapter explores why ABC is no longer fit for purpose and introduces the nextgen approach known as service-driven inventory optimization (service-driven IO).
To understand ABC’s shortcomings, first we need to understand the fundamentals. Nearly all traditional inventory management applications calculate safety stock for each individual SKULocation combination. Part of this involves identifying the desired service level percentage for each SKU-Location. Since many companies have hundreds of thousands, or even millions of combinations, it’s impossible to identify a service level for every individual SKU-Location. ABC classification provides one way to simplify an SKU portfolio to make this process more manageable.
A common ABC tool is a 3×3 matrix with the cost value on the Y axis and order-lines on the X axis – a so called “double” ABC classification. The typical way to distribute items across the classes is to put 80% of the cost value in A, 15% in B and 5% in C. You then apply the same 80/15/5 breakdown to the number of order-lines. Since the 80% thresholds for order-lines and cost of sales are hit quickly, there usually end up being only a few A items. Therefore the end result is a matrix that looks like the one below, with a very small share of items classified as AA and the majority classified as CC.
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