Executive Briefings

Rethinking the Concept of Supply-Chain Optimization

Before companies can apply state-of-the-art technology to that crucial exercise, they need to redefine exactly what it is they are trying to optimize. It's not just about cost and time.

Sometimes the path to innovation lies in finding a new meaning for an old word.

Take "optimization." That's been the goal of supply-chain managers for decades. But what exactly have they been seeking to optimize? Most have centered their efforts on cutting cost and time, says Katharine Frase, vice president of industry solutions and emerging business with IBM Research. That narrow view misses some critical, if intangible elements of a modern, best-in-class supply chain.

"In the past," says Frase, "people tended to view supply-chain optimization a bit one-dimensionally. They wanted to do routing of trucks, or logistics in the warehouse, or the attributes of vendor management. That was all very important, but it tended to be a bit piecemeal."

It's not a question of tossing out traditional metrics, she says. Companies still need to keep a close watch on supply-chain costs, while minimizing the time it takes to get product to market. But they ought to be taking other considerations into account as well, as part of a much broader view of global supply chains.

Chief among them is a company's carbon footprint or total energy bill. A focus on this aspect of operations might raise the cost of moving goods, yet yield big advantages in other areas, such as brand image. For example, a food company might want to use more locally grown produce in its supply chain, to position itself as a "green" organization. Implementing that policy while attempting to hold down costs involves a delicate balance, where one key metric has to give way to another. The trick, says Frase, lies in coming up with a formula that's ultimately most beneficial to the supplier.

Other elements to take into account include the impact of weather, as it impacts both product flow and customer demand. Often a high-level optimization strategy must be set aside to address the needs of the moment. A sudden snowstorm, for example, might motivate a retailer to increase its supply of snow shovels. Agile providers need to make "on-the-fly" decisions about where and how they can obtain more product at a moment's notice.

The Importance of Brand
Public image can trump top-line considerations in areas that go beyond environmental responsibility. A chain of bakeries might be focused on minimizing the amount of bread it has left over at the end of each day. In the process, though, it angers late shoppers who can't find product on the shelves. A smart retailer might up its inventories to please customers, then burnish its image by giving away any leftover loaves to charity. In the end, it reaps a double advantage that wouldn't have been possible with an approach based purely on cost.

Modern-day supply chains need to be viewed in the context of "ecosystems," says Frase. She uses the term to describe a web of supply-chain partners that do not always relate to one another in a linear or serial fashion. Moving up and down the supply chain from a consumer-products company, one encounters a plethora of suppliers and distributors, all of whom must be taken into account when optimizing critical business processes. Companies need to visualize this entire universe of participants in real time, Frase says.

Information technology systems that help to achieve this ambitious goal are still in development. IBM's own offering pulls data from a number of sources, including point of sale, logistics operations and enterprise resource planning (ERP) systems, to help make sense of the total picture. "By pooling that data outside of everybody's silos, you can get to functions that weren't available before," says Frase. "You're allowing the system to extract approved forms of data so that other people can see it."

Central to this new concept of inventory optimization is the use of "what-if" scenarios to review all possible options, prior to putting the best one into play. Another IBM Research initiative, this one out of its offices in Zurich, employs this technique. Called AXIO, it draws on years of historical sales data in order to determine optimum stocking levels in a variety of situations. IBM is using the tool in-house, as well as deploying it on behalf of customers such as BMW and several European "do-it-yourself" retailers.

The traditional approach has been to fashion inventory policies at a relatively high level, says Ulrich Schimpel, manager of inventory analytics with IBM Research in Zurich. What such systems haven't done is reach down to the execution level, where the realities of everyday business can play havoc with a carefully thought-out operational plan. "The normal theory that you see in textbooks about supply-chain optimization ... is not sufficient," Schimpel says. "You have to take into account a lot of restrictions."

The Spare Parts Dilemma
The gap between theory and practice is especially wide in spare parts fulfillment. Demand in that area can be highly erratic, notes Eleni Pratsini, manager of IBM Research's Mathematics and Computational Sciences Department. In the end, she says, what really matters is service level, but to maximize that metric companies might need to depart from traditional assumptions in economic order quantity (EOQ) theory.

Under a contract with IBM Global Services in Germany, automaker BMW is using AXIO to support its IT platform for spare parts delivery. Known as ATLAS, for Advanced Parts Logistics in After Sales, the system operates out of a central warehouse in Dingolfing, Germany. It manages more than 270,000 parts and accessories from some 1,900 suppliers. A pilot version of AXIO reduced BMW's U.S. parts stocks by 10 percent, according to IBM.

"The big idea" behind AXIO is the notion that "the world is getting more and more connected," says Schimpel. Companies don't lack for data and the necessary sensors to track supply-chain performance. They can devise any number of forecasts using complex algorithms and simulations. What they must be able to do is filter that massive amount of information into a coherent picture that conforms to reality. Outside influences that are beyond the control of supply-chain managers, such the buzz of social networks and shifts in weather patterns, must be married with hard data to create an accurate picture.

IBM works closely with clients to encompass the necessary information. Weather is a critical element in forecasting replenishment of flowers, Schimpel notes. And a few sunny days can increase consumer purchases of products such as gardening appliances.

Social networks are wielding a growing influence over sales. They can drive both positive and negative trends. Schimpel cites the case of a fashion merchandiser that was rumored on the internet to be scraping its inventories of unsold clothes. True or false, the chatter threatened to cause a dip in sales, although the company was able to react quickly.

Without loading up their warehouses with excessive buffer stock, companies have to respond to the situation at hand. As always, Schimpel says, the goal is a 100-percent service level, regardless of time of year or special circumstances.

Simulations are the virtual laboratory in which companies can try out numerous scenarios based on many internal and external factors. Schimpel says the exercise can reveal relationships between elements that weren't visible before. Armed with that intelligence, they can come up with "a good, risk-minimal, profitable solution."

Resource Link:
IBM Research, http://www.watson.ibm.com/index.shtml

Sometimes the path to innovation lies in finding a new meaning for an old word.

Take "optimization." That's been the goal of supply-chain managers for decades. But what exactly have they been seeking to optimize? Most have centered their efforts on cutting cost and time, says Katharine Frase, vice president of industry solutions and emerging business with IBM Research. That narrow view misses some critical, if intangible elements of a modern, best-in-class supply chain.

"In the past," says Frase, "people tended to view supply-chain optimization a bit one-dimensionally. They wanted to do routing of trucks, or logistics in the warehouse, or the attributes of vendor management. That was all very important, but it tended to be a bit piecemeal."

It's not a question of tossing out traditional metrics, she says. Companies still need to keep a close watch on supply-chain costs, while minimizing the time it takes to get product to market. But they ought to be taking other considerations into account as well, as part of a much broader view of global supply chains.

Chief among them is a company's carbon footprint or total energy bill. A focus on this aspect of operations might raise the cost of moving goods, yet yield big advantages in other areas, such as brand image. For example, a food company might want to use more locally grown produce in its supply chain, to position itself as a "green" organization. Implementing that policy while attempting to hold down costs involves a delicate balance, where one key metric has to give way to another. The trick, says Frase, lies in coming up with a formula that's ultimately most beneficial to the supplier.

Other elements to take into account include the impact of weather, as it impacts both product flow and customer demand. Often a high-level optimization strategy must be set aside to address the needs of the moment. A sudden snowstorm, for example, might motivate a retailer to increase its supply of snow shovels. Agile providers need to make "on-the-fly" decisions about where and how they can obtain more product at a moment's notice.

The Importance of Brand
Public image can trump top-line considerations in areas that go beyond environmental responsibility. A chain of bakeries might be focused on minimizing the amount of bread it has left over at the end of each day. In the process, though, it angers late shoppers who can't find product on the shelves. A smart retailer might up its inventories to please customers, then burnish its image by giving away any leftover loaves to charity. In the end, it reaps a double advantage that wouldn't have been possible with an approach based purely on cost.

Modern-day supply chains need to be viewed in the context of "ecosystems," says Frase. She uses the term to describe a web of supply-chain partners that do not always relate to one another in a linear or serial fashion. Moving up and down the supply chain from a consumer-products company, one encounters a plethora of suppliers and distributors, all of whom must be taken into account when optimizing critical business processes. Companies need to visualize this entire universe of participants in real time, Frase says.

Information technology systems that help to achieve this ambitious goal are still in development. IBM's own offering pulls data from a number of sources, including point of sale, logistics operations and enterprise resource planning (ERP) systems, to help make sense of the total picture. "By pooling that data outside of everybody's silos, you can get to functions that weren't available before," says Frase. "You're allowing the system to extract approved forms of data so that other people can see it."

Central to this new concept of inventory optimization is the use of "what-if" scenarios to review all possible options, prior to putting the best one into play. Another IBM Research initiative, this one out of its offices in Zurich, employs this technique. Called AXIO, it draws on years of historical sales data in order to determine optimum stocking levels in a variety of situations. IBM is using the tool in-house, as well as deploying it on behalf of customers such as BMW and several European "do-it-yourself" retailers.

The traditional approach has been to fashion inventory policies at a relatively high level, says Ulrich Schimpel, manager of inventory analytics with IBM Research in Zurich. What such systems haven't done is reach down to the execution level, where the realities of everyday business can play havoc with a carefully thought-out operational plan. "The normal theory that you see in textbooks about supply-chain optimization ... is not sufficient," Schimpel says. "You have to take into account a lot of restrictions."

The Spare Parts Dilemma
The gap between theory and practice is especially wide in spare parts fulfillment. Demand in that area can be highly erratic, notes Eleni Pratsini, manager of IBM Research's Mathematics and Computational Sciences Department. In the end, she says, what really matters is service level, but to maximize that metric companies might need to depart from traditional assumptions in economic order quantity (EOQ) theory.

Under a contract with IBM Global Services in Germany, automaker BMW is using AXIO to support its IT platform for spare parts delivery. Known as ATLAS, for Advanced Parts Logistics in After Sales, the system operates out of a central warehouse in Dingolfing, Germany. It manages more than 270,000 parts and accessories from some 1,900 suppliers. A pilot version of AXIO reduced BMW's U.S. parts stocks by 10 percent, according to IBM.

"The big idea" behind AXIO is the notion that "the world is getting more and more connected," says Schimpel. Companies don't lack for data and the necessary sensors to track supply-chain performance. They can devise any number of forecasts using complex algorithms and simulations. What they must be able to do is filter that massive amount of information into a coherent picture that conforms to reality. Outside influences that are beyond the control of supply-chain managers, such the buzz of social networks and shifts in weather patterns, must be married with hard data to create an accurate picture.

IBM works closely with clients to encompass the necessary information. Weather is a critical element in forecasting replenishment of flowers, Schimpel notes. And a few sunny days can increase consumer purchases of products such as gardening appliances.

Social networks are wielding a growing influence over sales. They can drive both positive and negative trends. Schimpel cites the case of a fashion merchandiser that was rumored on the internet to be scraping its inventories of unsold clothes. True or false, the chatter threatened to cause a dip in sales, although the company was able to react quickly.

Without loading up their warehouses with excessive buffer stock, companies have to respond to the situation at hand. As always, Schimpel says, the goal is a 100-percent service level, regardless of time of year or special circumstances.

Simulations are the virtual laboratory in which companies can try out numerous scenarios based on many internal and external factors. Schimpel says the exercise can reveal relationships between elements that weren't visible before. Armed with that intelligence, they can come up with "a good, risk-minimal, profitable solution."

Resource Link:
IBM Research, http://www.watson.ibm.com/index.shtml