Best Practice Demand Sensing
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Why Is Demand Sensing Suddenly On the Hot Seat?
During the past several years, consumer goods suppliers have made substantial investments in their own supply chains, improving forecasting, order management, transportation management, and warehouse management. Yet, out-of-stocks—and other retail execution issues—still plague the industry. The Grocery Manufacturers of America estimates that out-of-stocks are a $6 billion problem annually, industry-wide. At the same time, retailers are dramatically reducing the amount of in-network inventory they are willing to carry, which only exacerbates the out-of-stock problem. A recent study by the Wharton School of Business found that 72% of the root causes of out-of-stocks could be found in the store. It is clear that suppliers and retailers must address the last mile of the retail chain. To do so, many organizations are now focusing renewed efforts on improving replenishment. The most innovative are tapping consumer demand signals to drive timely replenishment decisions.
Demand-driven ( see also: Creating Demand Driven Operations )replenishment moves organizations away from a dependence on forecasts based on retrospective data and enables them to become responsive to what is actually occurring—or predicted to occur—at the store. The increased availability of consumer demand data, in the form of retailer-provided point-of-sale (POS) and RFID data, enables many suppliers to understand, predict, and respond to consumer demand for every store, every SKU, every day. In other words, these organizations can find and respond to forecast errors, shipment issues, store anomalies, and POS system anomalies before they result in out-of-stocks, excesses, and customer dissatisfaction.
What’s in it for Your Organization?
Simply put, a demand-driven approach to replenishment will dramatically reduce out-of-stocks while driving excess inventory out of the supply chain, both of which lead to superior customer satisfaction. Following are several real-world examples of the benefits that leading suppliers are realizing. Preventing Out-of-Stocks
A $1 billion supplier to Wal-Mart was losing more than $14 million a year in out-of-stocks, despite a 98.5% in-stock rate. Because the in-stock rate was based on aggregated, weekly numbers, the seemingly satisfactory metric was masking true problems at the shelf that cost both the retailer and the supplier. By initiating a demand-driven replenishment strategy that automated the analysis of daily point-of-sale data at the most granular SKU/store levels, this supplier was able to understand exactly what was happening at the store in order to consistently prevent out-of-stocks.
Responding to Store Anomalies
Another leading consumer goods supplier had a shrink problem, which was compounded by the latency of notification that items were missing from the shelf. This resulted in several days of no sales even though the retailer’s POS system showed inventory and demand. By taking a demand-driven replenishment approach, this supplier was able to immediately pinpoint which stores weren’t scanning, and alert their merchandising teams to investigate specific items and problem locations. Within the first year, this client was able to capture several million dollars that otherwise would have been lost.
Identifying Root Cause
Meeting its largest retailer’s new requirements had become a burden to a third client, a $3 billion supplier to Wal-Mart. Two-tier had been a challenge, especially with retailer-mandated inventory reductions. Now this supplier was being asked to determine root cause of out-of-stocks before the retailer accepted any changes to the replenishment and forecast settings. While many of its fellow suppliers faced the daunting and time-consuming task of logging into multiple systems to find the evidence for every out-of-stock, this supplier was able to turn to its demand-driven replenishment system already in place. The system was already configured to identify this supplier’s replenishment issues based on its own business rules. A few adjustments to the parameters enabled the same rules to automate the determination of root causes as well. The fact-based analysis and evidence for change could be automatically attached to communications
All of these companies benefited greatly from taking a demand-driven approach to their replenishment. This white paper will examine five key approaches that these companies employed to achieve their results.
Key #1: Analyze Every Store, Every SKU, Every Day
As retailers make more and more consumer demand data available to their suppliers, their expectations of what suppliers will do with this data increases. Larger retailers provide their suppliers with daily POS and inventory data at a store/SKU level of granularity. As more retailers and suppliers adopt RFID, the volume and granularity of consumer demand information only increases. The most innovative suppliers will use this valuable insight into real-time consumer demand to drive effective and profitable replenishment decisions. The most value is derived from this data, however, when it is used at the granularity with which it is provided to the supplier.
The first supplier in the previous examples provides a striking model of what can happen when organizations do not analyze daily demand data. A high in-stock rate can often mask what is truly happening every day for specific SKUs on specific shelves.
With the volume of data generated by the retail channel on a daily basis, many suppliers find themselves overwhelmed—even with the processes they have developed in an attempt to manage the data. Many suppliers will download daily retailer-provided POS data, but because of the effort involved, will do so only once a week. After it is downloaded, each day’s data is put into a separate spreadsheet or report. At this point, replenishment teams will then scour these reports, searching for problems that are impacting sales—a process that could take all week. If a stock-out occurs on a Monday, this information often does not even get downloaded until the Sunday after; it may be days later before the stock-out is found. With the additional time it takes to transport orders from the distribution center to the store, how many days will the shelf sit empty?
It is impossible to effectively manage the volume of data now available to suppliers using manual processes, thus necessitating the processing power of newly-available technology. Intelligent replenishment solutions will apply an organization’s business practices or rules to automate the access and analysis of the full volume of consumer demand data, including POS and RFID, on a daily basis. These business rules can focus the data analysis on finding replenishment issues, presenting them to the appropriate decision-makers, and then guiding a timely response. More than just automating a tedious task, replenishment solutions weigh many factors in their analyses, providing early and predictive insight into replenishment issues—which gives users more options to respond.
If an item is stocked-out on Monday, the system will tell the replenishment team on a Monday. What’s even more valuable, a replenishment solution can tell the team on Monday that an item will be stocked-out next week—based on current supply and demand—and what actions the team can take to pre-empt the empty shelf.
Key #2: Manage by Exception
Even with an automated analysis solution, a replenishment team will still find itself buried in daily demand data. With hundreds of SKUs moving through thousands of retail locations every day, the amount of data quickly adds up. The reality is that replenishment teams do not 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. With an exception management system in place, these “needles in a haystack” are identified, organized, and prioritized, guiding the replenishment team to quickly take action only when required.
Attention to exceptions is necessary because forecasts alone are not sufficient to drive effective replenishment. According to AMR Research, even the best forecasts are incorrect, on average, 27% of the time. Retailer-provided store/SKU forecasts have even worse accuracy, yet many retailers are requiring that their suppliers manage store-level inventory to these forecasts. So much can impact sales in the short-cycle, especially at the granular store/item level—from the unpredictability of store-level consumer demand to constantly changing retail conditions, even changes in the weather. It is crucial that organizations quickly understand and respond to what is actually occurring, not just what is forecasted to occur.
All replenishment professionals can readily describe the exceptions that matter to them most: stock-outs, excesses, stores not scanning, incorrect retailer replenishment settings, late/missing orders. By focusing and responding to these crucial issues, replenishment teams are able to capture revenue that would otherwise be lost. For most organizations, this incremental revenue adds up to millions of dollars annually for both the supplier and the retailer. An automated exception management system will not only identify these issues (or potential issues), but will also determine root cause—whether it’s on the supply or demand side—and guide an appropriate and timely response. This type of system automates the tedious, freeing up replenishment professionals to focus on proactively solving problems, rather than searching for them.
Key #3: Integrate All Relevant Data
If an item is stocked-out, there are several potential reasons why: some of these might include higher-than-expected demand, cancelled orders, incorrect replenishment settings, or late orders. And the root cause of why an out-of-stock occurred will impact the action the replenishment team takes to resolve it. For example, a replenishment team may respond to higher-than-expected demand by expediting additional orders for the short-term, and adjusting the store-level forecast as a longer-term resolution. If, however, the shelf is stocked-out because a shipment was late, the replenishment team may opt to take no action if the truck is already on the way.
Consumer demand data, in the form of POS and RFID, certainly provides many of the details about replenishment issues and why they occurred, but it cannot be the sole source of information. Information about why an issue occurred is usually scattered throughout various enterprise systems—including ERP, order management, and transportation management systems—and it is important to use this contextual information to understand why an issue occurred and how best to resolve it.
An effective replenishment system will seamlessly bring this information together in one place, providing replenishment professionals with the relevant information and analysis they need to make the best decisions. Too often, replenishment teams find themselves spending a lot of time logging into these various systems and running reports to first find issues, then logging in again to determine the reasons why the issues occurred, and then going back again to figure out what action to take. Using a replenishment system that automates these tedious tasks makes the best use of a replenishment professional’s time, creating far more time and opportunities to concentrate on decisions that improve revenue and service.
Key #4: Use Predictive and Early Insight Technology
Most out-of-stocks do not just happen. They are the result of something unexpected occurring either to demand or supply. Many stock-outs are predictable and can be avoided by acting on the early clues gleaned from an organization’s supply chain and order management systems, forecasts, total pipeline supply, and actual consumer demand. Predictive technologies are built to rapidly analyze all of this available data and provide short-cycle insight into replenishment issues that will occur over the next several days, giving teams more options to respond before revenue is lost. Predictive technology is not traditional sales forecasting; rather it is similar to short-term weather forecasting. Seven-day weather forecasts will look at the previous days’ temperatures, the weather in the west, and fronts moving through the region to predict the next day’s precipitation and high/low temperatures. In much the same way, predictive technology will rapidly analyze relevant short-cycle factors to present replenishment issues that will occur over the next several days.
Take, for example, an out-of-stock that is the result of higher-than-expected demand. A predictive replenishment system can weigh the store-level forecast for the next several days against actual consumer demand for recent days and orders currently in the pipeline to determine if an out-of-stock will occur within the next two weeks. If expected orders will fulfill demand, then no action may be necessary. If, however, anticipated demand will exceed the anticipated supply, then the system will alert users to the potential out-of-stock and illuminate the future impact in the days ahead. Having this predictive insight is especially useful in the early days of a promotion or new product introduction; two selling periods where it is most critical to keep shelves stocked during specific windows of time.
On the supply side, an out-of-stock may occur because of orders cancelled by production. Not all cancelled orders will result in stock-outs, but some may. Predictive technology can weigh a cancelled order against actual consumer demand and forecasts to provide an early indication when an out-of-stock will occur unless other compensatory actions are taken.
In both of these examples, with the advanced notice that predictive technology provides, a replenishment team can take several actions to pre-empt the out-of-stock, including placing additional orders, expediting orders, diverting inventory, or adjusting the forecast. A replenishment solution can weigh all of the factors, determine root cause, and guide users through the most optimal course of action. All of this can dramatically reduce the time that shelves sit empty.
Key #5: Use a Solution Designed to Meet the Unique Requirements of Replenishing the Shelf
The replenishment area faces challenges that require a unique solution. In the line of fire on a daily basis, replenishment professionals must keep their retailers’ shelves stocked, without the luxury of the inventory levels they were once able to maintain. Replenishment teams, therefore, must have access to timely information coupled with the ability to quickly and appropriately respond to constant changes in consumer demand—before out-of-stocks and excesses occur. Sales analysis and reporting tools were simply not designed for these tasks. Sales tools were built to deliver information—replenishment solutions are built for action. Sales tools are built to analyze trends and changes in large amounts of data. They do this by storing large amounts of data in a repository and providing the user with pre-defined reports, drill-down capabilities, and ad hoc tools for searching and mining the data. Sales tools are architected in this way because the user does not know, at the outset, the relevant data to analyze. As a result, replenishment teams still find themselves drowning in data with these tools, spending far too much time looking for replenishment issues—time they could use to make revenue-impacting decisions.
Dedicated replenishment solutions, on the other hand, are built to deliver relevant information and guide timely action. They automate the rapid analysis of large volumes of demand data, for the purpose of identifying and presenting only the specific issues that will impact replenishment. These issues are grouped, prioritized, and presented to the user along with an automatic determination of root cause and several options to respond. Replenishment solutions will guide users, step-by-step, through the most optimal response to replenishment issues, based on the current business conditions and the organization’s best practices. Users quickly understand the situation and can then respond directly from the system, collaborating with team members and their retailers as necessary. In addition, the issues, the root causes, and the actions taken to respond are tracked for ongoing continuous improvement within the organization and with the retailer.
Conclusion
Replenishment will always remain a critical area of focus for consumer goods suppliers and retailers, for the simple reason that they can’t sell products that aren’t on the shelf. The replenishment area addresses the last mile in the retail value chain. Taking a demand-driven approach ensures that supply and demand align as closely as possible, compensating for forecasts that are often incorrect without incurring excess inventory. By employing the Five Keys discussed here, suppliers are better equipped to meet both their retailers’ requirements and end-user consumer demand.
