Keeping Shelves Stocked

One of the greatest challenges that both consumer goods manufacturers and retailers face is keeping the shelves stocked. This month, CGT sits down with Doug Percy, President and CEO of Blue Agave Software, to discuss the causes of out-of-stocks and how manufacturers and retailers can work together to ensure consumer satisfaction.

 

 

The last mile of the retail value chain is where sales are won or lost -- and replenishment really addresses this last mile. Over the past several years, organizations have focused resources to make their supply chains more responsive to consumer demand, especially improving their forecasting and planning capabilities. Yet, out-of-stocks and other retail execution issues are still a common occurrence. With the unpredictability of consumer demand, organizations are realizing that forecasts and plans are simply not enough; constant, daily adjustments must be made to keep shelves stocked, avoid costly excesses and meet retailer requirements. Many consumer goods suppliers are beginning to make significant investments in the replenishment area.

 

A demand-driven approach to replenishment bridges the gap between an organization's supply chain operations and what's happening at the store. Replenishment professionals are the folks on the front line, evaluating the demand signal against information from their supply chain, to ensure that store-level consumer demand is being met. This requires a timely understanding of what's happening at the store, and the ability to quickly and efficiently act when problems arise.

 

We have found that many organizations are starting to add headcount to specifically address the replenishment area, since in many cases, the replenishment responsibility for multiple retailers has been shouldered by as few as one or two people. But to achieve the huge ROI that demand-driven replenishment can deliver, these professionals will need to be armed with tools designed for very specific needs.

 

 

Replenishment teams have long recognized the value of consumer demand data --usually POS data and more recently RFID data. But up until very recently, the only tools available to manage and analyze this data were sales analysis and reporting tools. These tools were designed to analyze large volumes of data and provide aggregated, retrospective information about past sales trends. These capabilities are sufficient for sales teams as they formulate plans and promotions, however, replenishment teams require more proactive, daily, store-level data to do their job effectively.

 

Weekly, aggregated, demand data can mask what is actually happening at the shelf. For example, an in-stock percentage measured once a week on a Friday will hide the fact that over the weekend, certain SKUs consistently stock-out until Tuesday when an order arrives. We worked with one supplier that had a 98.5 percent in-stock percentage with its top retailer, but when we analyzed its demand data at the daily level, we found out-of-stocks that were costing the organization more than $14 million a year in that one retail channel.

 

Another huge issue we've seen is the problem of stores not scanning. A point of sale (POS) system will show on-hand inventory and demand for the product, yet nothing is selling. Often, this can be the result of shrink, product not making it out from the backroom or just an incorrect replenishment setting in the system. Only store-level data will reveal problems like this, guiding merchandising teams or store managers to investigate and make adjustments before sales are lost.

 

Replenishment is a unique process that requires unique solutions, ones that facilitate timely, proactive decisions based on accurate, store/SKU-level data. As more retailers require their suppliers to manage at the store-level, store-level replenishment activity takes on an even greater importance. We've been finding that it is the power users of sales analysis and reporting tools that now recognize the need for a dedicated replenishment solution and are beginning to allocate the budget dollars.

 

 

Retail out-of-stocks can occur for a number of reasons. The Wharton School of Business recently reported on one study which found that the root causes of 72 percent of out-of-stocks were store-related -- higher-than-expected demand, shrink, store stocking problems or even incorrect settings within a retailer's POS system. Sometimes, however, the cause can be traced back to an organization's own supply chain -- for example, late shipments or cancelled orders.

 

It's important to understand why an out-of-stock occurred in order to take the most appropriate action. First, you need to know if the cause is on the supply side or the demand side, since each will require a different response. For example, if an out-of-stock occurred because production cancelled an order, then adjusting the store-level forecast won't adequately address the problem. If, however, out-of-stocks consistently occur because of higherthan- expected demand, then the forecast does need adjustment -- simply creating more orders will not address the underlying cause and will only serve to cause more out-of-stocks in the future. This is why the use of daily data is so important; it quickly senses the issue and enables a proactive response, often early enough to prevent out-of-stocks.

 

It's a lot of information to juggle, but it is becoming increasingly necessary to do so -- not just to formulate an appropriate response, but because Wal- Mart, as an example, has begun to require a determination of root cause before accepting any new orders or changes. One of our customers estimated that it could take them several hours to determine the root cause of just one out-of-stock in order to meet the mandate. This is why we automated the analysis process -- following the supplier's best practices -- we present the root causes of its out-of-stocks and potential out-of-stocks automatically, even grouping them by like cause for more efficient response.

 

 

Part of the reason why many retailers haven't made this data available is that suppliers simply weren't in a position to use it. Up until recently, the technology just wasn't available to manage the large volume of granular data that daily data generates. It's an investment for retailers to make this information available, but it is one that will pay off with fewer out-of-stocks and inventory reductions as suppliers start using solutions that leverage daily data to drive replenishment decisions.

 

Exception management technology automates the rapid analysis of the whole volume of daily data, to pinpoint the highest priority replenishment issues each day. The reality is that replenishment teams don't need to take action on every store, every SKU, every day; they really only need to focus on the out-of-tolerance conditions that, if left unaddressed, will result in empty shelves or excess inventory. Exception management technology illuminates these "needles in a haystack," guiding replenishment teams to quickly take action only when required. This type of technology allows them to spend their time doing their job instead of spending the better part of the day looking for problems.

 

Out-of-stocks cost retailers and their suppliers a significant amount of money; the Grocery Manufacturers of America estimates that the industrywide impact is $6 billion a year. In analyzing the data of several leading consumer goods suppliers, we found that if anything, this number is low. For one top supplier alone, we found almost $16 million a year in out-of-stocks --many of them preventable with early insight gleaned from daily data. Even a conservative estimate of the revenue that can be captured by eliminating a portion of these out-of-stocks makes a compelling case for daily data availability and utilization. CG