As a little kid growing up in former (and erstwhile happy) Yugoslavia and watching my elders, day in, day out, downing dozens of strong Turkish coffees with their neighbors and relatives (while discussing sports, weather, world politics, and the neighborhood gossip) I would sometimes naively ask for a sip of coffee. The deterring line (a bogey-man tale) from my folks would be that “kids that drink coffee end up with a tail on their rear side.”

A few decades later (being currently admittedly addicted to Starbucks triple-shot espresso drinks), it appears that modern supply chains suffer from long tails, albeit not due to anyone’s premature coffee consumption. That (and much more) was the enlightening conclusion of the recent Webcast entitled “Long Tails and Optimizing Inventories” conducted jointly by AMR Research, ToolsGroup, and Supply Chain Digest.

The recorded Webcast, which took place a few months ago and was reportedly well attended (several hundred listeners) can still be replayed here. There is also a related elaborate white paper from ToolsGroup entitled “Mastering the Long Tail of Demand.”

According to Lora Cecere, a Research Director of Consumer Products at AMR Research, the current “anatomic” supply chain business problem stems from the fact that products are continually proliferating. For instance, there has been a 15 percent increase in consumer products over the past three years.

Thus, over 16 percent of orders in the consumer products sector have a “stock-out” (whereby the customer is turned down and possibly lost in the long run). Most of these stock-outs are associated with a new product introduction (NPI) or promotional campaigns.

In addition to proliferating products, other trends that are driving companies to long tails are the following: the need for more frequent replenishment control (and thus more granular forecasting), adding replenishment locations closer to the end customer, and trying to deliver 98 to 99 percent service levels.

As an illustration, to go back to the coffee theme from the beginning of the post, imagine Starbucks Coffee or Peet’s Coffee & Tea companies trying to handle all of the possible coffee beans and tea flavors (beside other short-lived and seasonal merchandize) across the multi-echelon supply chains (central and regional warehouses) and hundreds of retail outlets. Indeed, what are the chances of over-stocking some and under-stocking the other stock keeping units (SKUs)? Quite large, indeed.

To make things worse, coffee retailers would not be the worst example of long tails, since the above-mentioned Webcast has pointed out some other businesses (like automotive aftermarket part distributors) that attribute even 98 percent of all SKUs to slow-moving items that contribute to over 60 percent of revenues.

Yet, 82 percent of organizations still measure the weighted mean absolute percentage error (WMAPE), which is an appropriate key performance indicator (KPI) for a small number of items with high volumes and high demand forecast predictability (that form the “head” of the supply chain). But this metrics largely masks the forecast accuracy of slow-moving products that have low volumes and low demand forecast predictability (and that form the ever-longer “tail” of supply chains).

Where Does the Tail Start?

To be more precise, from a supply chain perspective, the tail starts there where demand becomes lumpy, and this lumpiness is measured relative to the Replenishment Control Frequency (RCF). Increasing RCF lengthens the tail. Namely, when a company controls replenishment weekly, the tail starts at SKUs with 0.7 line-orders per week, whereas in case of controlling replenishment daily the tail starts at SKUs with 0.7 line-orders per day (the 0.7 line-orders per RCF means a 50 percent probability of zero demand, or half the chance that this particular SKU will not be sold in this time period).

Confused, overwhelmed, embarrassed and whatnot yet? I guess so, but please do not feel badly about your lack of knowledge on the matter! In fact, only a few companies have processes in place to manage this product complexity. According to AMR Research, only 26 percent of supply chain companies engage in an important cost-to-serve analysis that calculates the profitability of products, customers and routes to market to give a fact-based focus for decision making — on service mix and operational changes — for each customer.

In a nutshell, slow-moving products are increasing and important (as new products and promotions) to growth strategies. Traditional advanced planning & scheduling (APS) and enterprise resource planning (ERP) deterministic (formulaic) approaches are not designed to properly forecast slow-moving products. Stochastic or probabilistic methods are much more appropriate here.

Not All Slow-Moving Products are Create Equal

Last but not least, all slow-moving products are not created equal, which requires new levels of focus and management. Based on the products’ importance and cost-to-serve, AMR Research has created a slow-moving product framework with four differing strategies below:

1. “Buffer” — for products low in importance with low cost to serve;
2. “Rationalize” — for items low in importance and with high cost to serve;
3. “Maximize” — for products with high importance and low inventory carrying cost; and
4. “Focus” — for items with high importance and high cost to serve.

As a little kid growing up in former (and erstwhile happy) Yugoslavia and watching my elders, day in, day out, downing dozens of strong Turkish coffees with their neighbors and relatives (while discussing sports, weather, world politics, and the neighborhood gossip) I would sometimes naively ask for a sip of coffee. The deterring line (a bogey-man tale) from my folks would be that “kids that drink coffee end up with a tail on their rear side.”

A few decades later (being currently admittedly addicted to Starbucks triple-shot espresso drinks), it appears that modern supply chains suffer from long tails, albeit not due to anyone’s premature coffee consumption. That (and much more) was the enlightening conclusion of the recent Webcast entitled “Long Tails and Optimizing Inventories” conducted jointly by AMR Research, ToolsGroup, and Supply Chain Digest.

The recorded Webcast, which took place a few months ago and was reportedly well attended (several hundred listeners) can still be replayed here. There is also a related elaborate white paper from ToolsGroup entitled “Mastering the Long Tail of Demand.”

According to Lora Cecere, a Research Director of Consumer Products at AMR Research, the current “anatomic” supply chain business problem stems from the fact that products are continually proliferating. For instance, there has been a 15 percent increase in consumer products over the past three years.

Thus, over 16 percent of orders in the consumer products sector have a “stock-out” (whereby the customer is turned down and possibly lost in the long run). Most of these stock-outs are associated with a new product introduction (NPI) or promotional campaigns.

In addition to proliferating products, other trends that are driving companies to long tails are the following: the need for more frequent replenishment control (and thus more granular forecasting), adding replenishment locations closer to the end customer, and trying to deliver 98 to 99 percent service levels.

As an illustration, to go back to the coffee theme from the beginning of the post, imagine Starbucks Coffee or Peet’s Coffee & Tea companies trying to handle all of the possible coffee beans and tea flavors (beside other short-lived and seasonal merchandize) across the multi-echelon supply chains (central and regional warehouses) and hundreds of retail outlets. Indeed, what are the chances of over-stocking some and under-stocking the other stock keeping units (SKUs)? Quite large, indeed.

To make things worse, coffee retailers would not be the worst example of long tails, since the above-mentioned Webcast has pointed out some other businesses (like automotive aftermarket part distributors) that attribute even 98 percent of all SKUs to slow-moving items that contribute to over 60 percent of revenues.

Yet, 82 percent of organizations still measure the weighted mean absolute percentage error (WMAPE), which is an appropriate key performance indicator (KPI) for a small number of items with high volumes and high demand forecast predictability (that form the “head” of the supply chain). But this metrics largely masks the forecast accuracy of slow-moving products that have low volumes and low demand forecast predictability (and that form the ever-longer “tail” of supply chains).

Where Does the Tail Start?

To be more precise, from a supply chain perspective, the tail starts there where demand becomes lumpy, and this lumpiness is measured relative to the Replenishment Control Frequency (RCF). Increasing RCF lengthens the tail. Namely, when a company controls replenishment weekly, the tail starts at SKUs with 0.7 line-orders per week, whereas in case of controlling replenishment daily the tail starts at SKUs with 0.7 line-orders per day (the 0.7 line-orders per RCF means a 50 percent probability of zero demand, or half the chance that this particular SKU will not be sold in this time period).

Confused, overwhelmed, embarrassed and whatnot yet? I guess so, but please do not feel badly about your lack of knowledge on the matter! In fact, only a few companies have processes in place to manage this product complexity. According to AMR Research, only 26 percent of supply chain companies engage in an important cost-to-serve analysis that calculates the profitability of products, customers and routes to market to give a fact-based focus for decision making — on service mix and operational changes — for each customer.

In a nutshell, slow-moving products are increasing and important (as new products and promotions) to growth strategies. Traditional advanced planning & scheduling (APS) and enterprise resource planning (ERP) deterministic (formulaic) approaches are not designed to properly forecast slow-moving products. Stochastic or probabilistic methods are much more appropriate here.

Not All Slow-Moving Products are Create Equal

Last but not least, all slow-moving products are not created equal, which requires new levels of focus and management. Based on the products’ importance and cost-to-serve, AMR Research has created a slow-moving product framework with four differing strategies below:

1. “Buffer” — for products low in importance with low cost to serve;
2. “Rationalize” — for items low in importance and with high cost to serve;
3. “Maximize” — for products with high importance and low inventory carrying cost; and
4. “Focus” — for items with high importance and high cost to serve.