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Tag Archives: Lost Sales

Data Profits > Lost Sales

Seasonal Indexes Serve Up Lost Sales and Low Service

Seasonal Indexes Serve Up Lost Sales and Low ServiceSeasonal Indexes are a great tool that can be easily used to manage inventory and improve replenishment, allocations and new product releases. Seasonal Indexes used correctly result in sales growth and fewer out-of-stocks. Hello,Captain Obvious. The unfortunate truth is many of you fail to use seasonal indexes where you should today. The small group that does use seasonal indexes often fails to adjust the indexes when calendar events happen in different business fiscal weeks this year compared to the year the index was created. Last, Seasonal Indexes fail when you use the wrong math formula to create the seasonal index or you or your software use the wrong demand sales data to build the seasonal index. The results from these issues are out-of-stocks, lost sales and mis-spent inventory dollars. Read More

Little Known Leverage Strategies for Lost Sales Reductions – Part 3

 

drought-strategies-to-successLeverage Your Lost Sales Data to Grow Profits

The key to successful Demand Driven retail is leveraging the right data in the right places. Lost Sales data has a lot of leverage that, when ignored, can be your demise; however, those that successfully measure and leverage Lost Sales data will see sales and profit gains. Our Lost Sales blog today outlines how lost sales data can be used to improve inventory optimization and highlights how all the pieces are interconnected. We also dive into the differences between lost opportunity and lost sales, the differences and impacts between the two, and close with some sobering statistics from Lost Sales data collected from the industry.

Our first blog on Lost Sales highlighted the staggering impact of Lost Sales in most businesses today. We outlined some of the methods used to calculate lost sales, and why these methods do not deliver value. Our second Lost Sales blog reviewed how lost sales can add value to demand forecasting and improve the accuracy and value for the service attained calculation.
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Truth, Lies, and Strategies for Lost Sales – Part 2

Truth, Lies, and Strategies for Lost Sales - Part 2

Why Lost Sales are Ignored

Our last blog highlighted the staggering impact of Lost Sales in most businesses. We outlined some of the methods used to calculate lost sales, and why these methods do not deliver value. We touched on in-stock and Service Attained as two measures that in the past were acceptable inventory ROI measures but, in the market place today, these methods are dated and focus retail in the wrong direction.

With the advancement of inexpensive hardware, we can calculate a very accurate demand forecast across any block of products in our assortment and measure the business at any individual (or group of) product / locations. We can easily track available inventory for any product/location at a moment’s notice. This makes calculating lost sales a simple calculation: sum demand for the days where available inventory <=0. Today, we will review how lost sales impact demand forecasting, service attained, and inventory optimization.
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The 7 Most Frightening Lost Sales Facts – Part 1

The 7 Most Frightening Lost Sales Facts - Part 1

Companies Miss the Staggering Impact of their Lost Sales

Most companies are totally blind to the amount of lost sales they accumulate each year. Without a Lost Sales measure, a company loses significant opportunities to the competition in the forms of repeat business and gross margin dollars. The real impact of lost sales is often further hidden by the false securities of in-stock reports and service level measures that are based on fill rate.

How often do you review a lost sales report? Do you know how the lost sales are calculated and if they are accurate? Most legacy systems lack a true measure of ‘Lost Sales’ for the many reasons listed above. Many companies miss out due to the age of legacy software (often more than 5 years). The hardware cost to run product/location data even 5 years ago would prevent most companies from buying software that needed mega expensive hardware. Legacy software left out these types of calculations as the customer market that could afford to pay for mainframe hardware was extremely small.
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