Executive Briefings

How Much Inventory Do You Really Need?

Inventory is evil. Inventory is essential. The two statements aren't necessarily contradictory. Not if companies can figure out a way to determine the absolute minimum amount of stock needed to keep customers happy, while maintaining a tight lid on costs.

How Much Inventory Do You Really Need?

There's a more sophisticated way of expressing the problem: the science of theoretical minimum inventories. It's essentially a new gloss on an old problem, but it promises to help supply chains draw closer to the goal of zero waste in their operations. Think of it as applying Lean manufacturing principles to the information flow that governs inventory levels.

An academic effort to explore the science is underway. It's being spearheaded by supply-chain software vendor One Network Enterprises, in cooperation with the University of North Texas (UNT). One Network is funding the research, which is intended to "determine the theoretical minimum inventories in any supply chain ecosystem, presuming all information latency is eliminated, while asset availability and performance are optimized."

That, of course, is a bold presumption, given the glaring lack of efficiency in the way that information moves through most global supply chains. Still, the initiative could turn out to yield valuable insights, provided researchers can get their arms around the issue of "informational lead time" - in other words, how quickly critical data is conveyed to all of the trading partners in a supply-chain "ecosystem." Long lead times have been shown to be a major reason why companies find themselves suffering from low inventory turns and unacceptably high "safety" stocks.

According to Richard Dean, chief marketing officer with One Network, it all started when company founder and chief executive officer Greg Brady approached UNT's faculty about working on a problem that would identify the various levers that drive minimum inventories.

In a sense, the subject is an outgrowth of the familiar just-in-time production and inventory strategy. JIT has taken some blows in recent years, with manufacturers forced to build buffer stock back into their supply chains to guard against unanticipated disasters, and offset the effects of longer supply lines caused by outsourcing to Asia. It's still a valid concept, though, and a noble goal to pursue. Perhaps the theory of theoretical minimum inventories can inject it with new life.

Of course, information latency is everywhere in the supply chain, lurking wherever there's a link between partners or even the departments of a single company. David Nowicki, associate professor of logistics at UNT, says the new project can help to shine a light on the problem. In particular, it can draw a direct correlation between delays in information transmittal and the financial performance of a company. Science becomes everyday reality, when you can remove five days of inventory because you were able to speed up the flow of your data.

Companies might think they're doing multi-echelon JIT, but they're often stymied by the failure of all parties to share critical intelligence on a timely basis. Never mind the often-stated belief that information replaces inventory. Many companies have yet to translate that bromide into reality. "There's a tremendous amount of waste," says UNT assistant professor of logistics Wesley Randall. "We can actually [generate] a number showing the cost of latency."

It all boils down to looking at key supply-chain processes "and saying how much wealth you are leaving on the table," says Randall.

First step is for a consumer products manufacturer to calculate how long it's taking to transform raw materials into finished product, and get it into the hands of the customer. The researchers then break down that map into its various elements, and determine how long the entire process should actually be. They deploy a framework that figures the average variability of elements such as demand, lead time and data conveyance. In the end, they should be able to show a company an optimal number for a specific class of SKUs.

It's important that the conclusion not be influenced by the prejudices or assumptions of the manufacturer, Randall says. As inspiration, he cites The Structure of Scientific Revolutions, Thomas S. Kuhn's landmark 1962 work on what drives major advances in science. The answer isn't always slow, steady progress - it's sudden leaps in thought. The theory of theoretical minimums, he says, "allows you to look at the world differently."

Overselling? Perhaps. But organizations do have a tendency to insist that the traditional way of doing things is the only way. If a new way of thinking comes along, causing them to reevaluate every aspect of their supply chain, why not go with it? And if talking to supply-chain managers doesn't work, "I'd have the conversation with shareholders," says Randall.

In any case, he says, "the model isn't forcing you to adapt to its business processes. It's forcing you to map your supply chain and understand what your drivers are."

One caveat: there's no single number that applies to all companies. (Where have we heard that before?) On the contrary, it will depend on the characteristics of each product and manufacturer. Fast-moving goods with steady demand require a different approach than those with less predictable patterns of consumption. But the researchers are convinced that their work can create a model that comes closer than ever to a perfect world of physical distribution driven by zero information latency - and they're currently putting it to the test with a select number of manufacturers. "We were able to demonstrate that it's utterly possible," says Dean.

And utterly necessary, if the UNT researchers are to be believed. "If you don't do this, somebody else will," says Randall. "One of your competitors is going to figure this out, and they're going to crush you."

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Keywords: supply chain, supply chain management, supply management, inventory management, inventory control, global logistics, logistics management, supply chain planning, retail supply chain, supply chain risk management, logistics management: Inventory Planning & Optimization

There's a more sophisticated way of expressing the problem: the science of theoretical minimum inventories. It's essentially a new gloss on an old problem, but it promises to help supply chains draw closer to the goal of zero waste in their operations. Think of it as applying Lean manufacturing principles to the information flow that governs inventory levels.

An academic effort to explore the science is underway. It's being spearheaded by supply-chain software vendor One Network Enterprises, in cooperation with the University of North Texas (UNT). One Network is funding the research, which is intended to "determine the theoretical minimum inventories in any supply chain ecosystem, presuming all information latency is eliminated, while asset availability and performance are optimized."

That, of course, is a bold presumption, given the glaring lack of efficiency in the way that information moves through most global supply chains. Still, the initiative could turn out to yield valuable insights, provided researchers can get their arms around the issue of "informational lead time" - in other words, how quickly critical data is conveyed to all of the trading partners in a supply-chain "ecosystem." Long lead times have been shown to be a major reason why companies find themselves suffering from low inventory turns and unacceptably high "safety" stocks.

According to Richard Dean, chief marketing officer with One Network, it all started when company founder and chief executive officer Greg Brady approached UNT's faculty about working on a problem that would identify the various levers that drive minimum inventories.

In a sense, the subject is an outgrowth of the familiar just-in-time production and inventory strategy. JIT has taken some blows in recent years, with manufacturers forced to build buffer stock back into their supply chains to guard against unanticipated disasters, and offset the effects of longer supply lines caused by outsourcing to Asia. It's still a valid concept, though, and a noble goal to pursue. Perhaps the theory of theoretical minimum inventories can inject it with new life.

Of course, information latency is everywhere in the supply chain, lurking wherever there's a link between partners or even the departments of a single company. David Nowicki, associate professor of logistics at UNT, says the new project can help to shine a light on the problem. In particular, it can draw a direct correlation between delays in information transmittal and the financial performance of a company. Science becomes everyday reality, when you can remove five days of inventory because you were able to speed up the flow of your data.

Companies might think they're doing multi-echelon JIT, but they're often stymied by the failure of all parties to share critical intelligence on a timely basis. Never mind the often-stated belief that information replaces inventory. Many companies have yet to translate that bromide into reality. "There's a tremendous amount of waste," says UNT assistant professor of logistics Wesley Randall. "We can actually [generate] a number showing the cost of latency."

It all boils down to looking at key supply-chain processes "and saying how much wealth you are leaving on the table," says Randall.

First step is for a consumer products manufacturer to calculate how long it's taking to transform raw materials into finished product, and get it into the hands of the customer. The researchers then break down that map into its various elements, and determine how long the entire process should actually be. They deploy a framework that figures the average variability of elements such as demand, lead time and data conveyance. In the end, they should be able to show a company an optimal number for a specific class of SKUs.

It's important that the conclusion not be influenced by the prejudices or assumptions of the manufacturer, Randall says. As inspiration, he cites The Structure of Scientific Revolutions, Thomas S. Kuhn's landmark 1962 work on what drives major advances in science. The answer isn't always slow, steady progress - it's sudden leaps in thought. The theory of theoretical minimums, he says, "allows you to look at the world differently."

Overselling? Perhaps. But organizations do have a tendency to insist that the traditional way of doing things is the only way. If a new way of thinking comes along, causing them to reevaluate every aspect of their supply chain, why not go with it? And if talking to supply-chain managers doesn't work, "I'd have the conversation with shareholders," says Randall.

In any case, he says, "the model isn't forcing you to adapt to its business processes. It's forcing you to map your supply chain and understand what your drivers are."

One caveat: there's no single number that applies to all companies. (Where have we heard that before?) On the contrary, it will depend on the characteristics of each product and manufacturer. Fast-moving goods with steady demand require a different approach than those with less predictable patterns of consumption. But the researchers are convinced that their work can create a model that comes closer than ever to a perfect world of physical distribution driven by zero information latency - and they're currently putting it to the test with a select number of manufacturers. "We were able to demonstrate that it's utterly possible," says Dean.

And utterly necessary, if the UNT researchers are to be believed. "If you don't do this, somebody else will," says Randall. "One of your competitors is going to figure this out, and they're going to crush you."

Comment on This Article


Keywords: supply chain, supply chain management, supply management, inventory management, inventory control, global logistics, logistics management, supply chain planning, retail supply chain, supply chain risk management, logistics management: Inventory Planning & Optimization

How Much Inventory Do You Really Need?