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The 5 Most Expensive Mistakes When Managing Inventory
Stuart Dunkin, Data Profits Inc.

Data ProfitsThere are five mistakes in managing inventory that cost companies millions in lost profits and higher operation costs each year. All five mistakes are based on the forecasting system you use and the processes using the forecast results. Accurate demand forecasting and efficient processes allow you to deliver higher customer service levels, which result in greater sales at reduced operating costs. When demand is forecasted accurately, sales are met in a profitable process that keeps supplier, retailer, and consumer connected and satisfied. Accurate demand forecasting increases customer satisfaction and reduces lost sales. The results reduce the loss of customers to the competition and reduce markdowns thereby improving profitability.

When a company has accurate demand forecasting and sound processes, the flow of products is smoothed through the supply chain - purchases are made in a cost effective manner, finance has a good understanding of cash flow in advance, and logistics services costs can be minimized.

The key benefit to accurate demand forecasting is lowering the amount of inventory held. This excess inventory is safety stock to buffer against inaccurate demand forecast. In a perfect world you would know exactly what would sell each day at each location - you wouldn't need any additional inventory. An accurate demand forecast gets you as close as possible to that perfection delivering all the cost savings associated with lower, accurate inventories.

The dramatic payoffs of accurate demand forecasting can be found in white papers, university studies and press releases. A recent success story describes how a large multi-store retailer installed a forecasting and replenishment solution that netted a 3% same store sales increase in the first 90 days. While that is great news in this tough market, what's really amazing is the same retailer reduced inventories by more than 25% in the same 90 days.

Our hope is that presenting these five mistakes will inspire senior management to review their current forecasting tools, processes and results to find opportunities for improvement.

Mistaking the Differences between Forecast and Plan
Many companies fail to understand forecasting and planning for their uniquely different end goals. Take a minute and review our article last month in which we examine this comparison in detail: Why Planning and Sales Forecasting are Bad for Replenishment. We discuss how forecasting should be a management process, not a piece of software. While you will nod your head in agreement, the truth is most companies treat forecasting as software and the plan as the truth. In fact, a forecast should be the first piece toward building a plan. A plan should be made with knowledge of the forecast to indicate where there are opportunities to grow the business. Many retailers have the forecasting completed by the merchants who pick the products. The result is the merchant or buyer believes every product is a gold mine of opportunity and that sales for most everything will always be rising. This is in reality a plan – the merchants pick the products and plan the business. What is often missing is a solid and accurate forecast on which to build the plan. These two elements, forecast and plan, should be separate and, in fact, have different goals. In reality, many companies will treat the two pieces the same, or worse, discount the forecast in the belief a plan is more accurate.

Do You Send the Correct Data to the Forecast Software?
Complete this sentence: bad data fed into a program delivers ____ results. If you feed the sum of regular, promotional, and closeout sales into forecasting and try to use the result to forecast regular sales, do not expect the results to be accurate. It is just too obvious to ignore and yet 90% of all forecasting apps today make a serious error based on this very premise. A sales forecast methodology uses the aggregation of all demand types to create a forecast. There is a significant difference between sales forecasting and demand forecasting. In reality, most forecasting software being sold today – yes, even some of the biggest software companies – are actually using sales forecasting methods but call it demand forecasting. For more detail read this blog: Differences between Demand Forecasting and Sales Forecasting for Inventory Replenishment.

The key difference is in separating the data being used with the forecast algorithms. With demand forecasting methodologies, sales are broken out into type of demand: regular, promo, lost, and closeout. Each demand type is forecasted separately from the other types of sales. A sales forecast methodology will roll-up all sales types and forecast from the total number. The problem occurs when you attempt to forecast a future event from historical sales without knowledge of events, promotions, lost sales and closeouts that impacted the total sales. Your planning will not be based on demand, rather sales aggregations. For an example, reference our article in the June issue of the RVCF Link: Why Planning and Sales Forecasting are Bad for Replenishment. The difference in demand forecast accuracy is typically 10-25 points.

Forecast Accuracy formula:

Where sales > zero, 1 - [absolute value(sales-forecast)/sales]

Mistake Averages, Excel, and Cubes as Suitable Forecasting Tools
Did you know that most legacy forecasting software used today have only ONE forecast algorithm, a time series. You can employ different methods with a time series and a time series can be multiplicative (seasonal index) or additive (market trend).

The time series forecast has two major weaknesses:

  • New products cannot use a time series
  • Slow and intermittent demand cannot be forecast sufficiently with a time series

At least two major ERP packages use the last 6-8 weeks sales (simple time series algorithm) as the leading indicator for their forecasting - 1980's flashback. A sure sign of failure is found behind the company that isn't willing to change and update to the best available forecasting solutions.

Mistaking Sales Trends for Forecasting Promotions
Technology has enabled forecasting to become more sophisticated and price-wise available to everyone. This means advanced methods of demand forecasting can be used to identify the market response to an event or promotion. While many companies will use a sales forecast methodology and then compare regular sales to a promotional event to calculate promotional lift, there are many factors that are missed with this process. A good demand forecasting solution supports future promotions and events and utilizes input to develop a sound inventory plan. Companies with this forecasting technology can plan and buy inventory for promotions with greater accuracy. If your company uses a forecasting solution that can understand event signals in the demand forecasting calculations, you will be ahead of the competition. The irony is that the idea of event signals included in a data stream to forecast future events and promotions was developed 25 years ago but had to wait for technology and Moore's law to catch up to make them available and inexpensive today.

Mistakes with People, Technology, Visibility and Feedback
In this day of instant information where the customer can know more than the retailer, forecasting becomes the most significant piece to the retail puzzle. If you don't manage the pieces, your competition will do that for you and you lose. We have outlined many ways that forecasting touches your business and some common mistakes.

Some ideas to implement immediately include:

  1. Review a forecast accuracy report by department/location on a weekly basis
  2. Use demand forecast, available inventory and POS to generate a lost sales report
  3. Provide supplier with Dynamic visibility to available inventory, demand forecast, orders, projected orders, and POS

Forecasting is a process, not a software that needs people trained in the analytics. Merchants need some yin and yang to push and pull against the plan to drive the most successful results. A company that doesn't have KPI's, goals, and staff to deliver effective forecasting will cease to be competitive in the marketplace.

Fix These Forecasting Mistakes and Raise Your Profits
Forecasting software today is vastly superior to what was available even five years ago and often costing 50-90% less than legacy applications. With an accurate forecast, you can operate for less and drive better results. The results help grab market share from older companies that continue to resist change and lack a focus on forecasting. Forecasting touches every major component of retail, and bad forecasting rolls up and down the business processes delivering poor performance. Improve your forecast accuracy and you will see improvements roll across the company. Avoid the common and old mistakes we have listed today, improve your forecast accuracy and forecast use to see immediate results on your bottom line.

Join us each month for our short series on forecasting and replenishment. Articles in our continuing series:
1. When is product order point - Safety Stock, Lead-Time, Plan, Just in Time
2. How often should you reorder - Inventory Optimization, Weeks Supply
3. What should be on the PO - Top down based orders (plan), Bottom up based orders (Service Level - Consumer centric)?.

CEO © Data Profits, Inc. 2013 All Rights Reserved.


Stuart Dunkin, CEO of Data Profits Inc, is a strategic visionary who leads by calling on his broad range of experience as a former retail executive, consultant for top retailers, and work for E3/JDA software. Data Profits delivers forecasting, replenishment and collaboration supply chain tools to our customers. Data Profits interviewed over 100 retailers who outlined - the disjointed relationship between supply chain data, people and business goals. This influenced our software designs. Data Profits Software connects people, meets service goals, increases profits and provides a highly visible supply chain across a retail network. The user configurable software installs in less than 30 days at more than 50% less than legacy solutions.

Stuart attended Auburn University for a Bachelor of Science degree in Business Administration. He continued his education at Emory University, pursuing a joint Masters of Divinity and Masters of Business Administration. Stuart writes almost weekly for a popular retail supply chain blog found here. Call Data Profits at (770) 574-4100 or visit their website and subscribe to their blog at http://www.data-profits.com and start to "Tighten the Links in Your ChainTM."

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