Do You Make These Mistakes with Inventory Optimization

Inventory Optimization is a link in your chain that is often misunderstood and misquoted at inventory meetings and sales presentations in many businesses today. Inventory Optimization issues are always easy to find – Buyers, Sales People, and inventory managers of high-volume inventories often complain that there is too much overstocked inventory of slow selling products and not enough of the inventory that is in demand. Sadly, the unnecessary inventory is tying up working capital and taking up much needed storage space. This is a major issue that lowers profits, service attained and customer opinions.

Inventory Optimization with Excel and the ‘Consultant’

So many ask, how do you improve the quality of customer service without storing excessive inventory?
There are a variety of inventory management techniques. However, the most frequently used inventory management technique is “Rule of Thumb” and an Excel spreadsheet. This is when a company hires a professional to analyze sales history, by comparing the older SKUs with the newer SKUs, in turn providing a mathematical prediction as to the appropriate purchase of inventory. However, as the SKU count increases and new products are added to the existing inventory, it becomes difficult to maintain that approach, and it is never accurate.

Demand Forecasting Links to Inventory Optimization

The problem with the aforementioned approach is that it disregards variability. A SKU with a demand of 100 units a week with a standard deviation of 25, cannot be managed the same as a SKU with a demand history of a 100 units a week having a standard deviation of 100. There are very specific demand forecast algorithms for slow and intermittent demand product. Intermittent Demand Products need to be forecasted with an intermittent demand algorithm to achieve higher forecast accuracy. Inventory Optimization needs demand forecast accuracy to effectively determine the amount of inventory to carry and maximize profits, lower operating costs and meet service goals. In large product assortments, slow and intermittent demand products are just part of the potential issues in optimizing inventory. Inventory Optimization is a complicated process but with very profitable rewards.

Why are you using old technology. The truth is more than 85% of the forecasting systems in use today are only using 2 forecast algorithms and a collections of ‘models’. Often software companies claim to have ‘hundreds’ of algorithms when in fact they have only one or two algorithms and several models. Legacy systems often do not have multiple algorithms for intermittent and slow demand product. If you want to get an optimized inventory you need accurate demand forecast. Accurate demand forecast can only be reached with updated, modern demand forecast solutions and fortunately they cost significantly less money.

Learn more about slow and intermittent demand forecasting: Slow and Intermittent Product Demand Forecasting Facts and Myths

A Lot of Moving Data Points to Optimize

With the variability and challenges of large SKU counts, sometimes in the thousands, the answer to proper inventory optimization lies outside any standard spreadsheet software.
A more complex and powerful form of inventory analysis is needed to weight and measure the key data pieces used to optimize inventory:

Acquisition Cost
Carrying Cost
Gross Margin
Vendor Minimum to Ship Constraints
Service Goals

A Modern Way to Make More Money – and it’s Legal

A modern software solution is necessary to calculate large numerical sets of data, while accounting for variability in supply and demand. We use the words ‘modern’ because it is hard to run this many calculations across large data sets with older hardware and remain economical to the business. Modern software that can utilize multi-core processors and large amounts of RAM can quickly calculate the inventory optimization opportunity in your business for significantly less dollars than legacy systems. This will not only restore adequate inventory, but also enhance the level of customer service.

Inventory Optimization is something any business can do better. This is one link in your chain where you can find tools to help you improve quickly. If you need help ‘Tightening this Link in Your Chain’™ or for information on inventory optimization, please Contact Us.

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Stuart D

Stuart Dunkin is a strategic visionary who leads by calling on his broad range of experience as a former retail executive as well as a consultant for top retailers and for the E3/JDA software company. He founded Data Profits to solve a real-world problem plaguing retailers today – the disjointed relationship between supply chain data, people and business goals. He has experienced first-hand the challenges and frustrations that occur when decisions are made based on wrong data, which often leads to the wrong actions being taken with crippling results like overstock, out-of-stock, and increased working capital.
Stuart graduated from Auburn University, with bachelor of science in business administration.