Regardless of the economic environment (and sentiments), I always think of the opportunity within the aftermarket service and support as a profitable, high-margin and customer-captive business, and yet, still underserved. General Electric (GE) would be the proverbial example of a company that has focused on aftermarket opportunities, going so far as to call itself a “services” company as opposed to a “products” company.
GE indeed, starting with Jack Welch’s long chief executive officer (CEO) tenure, has been widely reported to have significantly increased both its total revenue and profitability by focusing on services opportunities in addition to developing world-class products.
The manufacturing corporate giant has certainly proven the value of serving the product aftermarket, which has recently been purported in a quantifiable manner by many pundits as a high margin business. For instance, AMR Research reported recently that businesses earn 45 percent of gross profits from the aftermarket, yet it is only 24 percent of their revenues, while a recent article in Harvard Business Review claims that we all spend US$1 trillion every year on assets we already own.
A related software category term was mentioned in TEC’s 2003 article titled Service Lifecycle Management - Tapping into the Value of the Product Aftermarket. Namely, Service Lifecycle Management (SLM) is a business initiative focused on servicing a company’s products, and the customers that bought them, after the product has been sold. Simply put, SLM focuses on making more money from the product after the initial sale. But it is more than that — it is also a way to become a strategic part of the customer’s business after the sale is completed.
In another Harvard Business Review article titled Winning in the Aftermarket from May 2006, MCA Solutions’ co-founders, Dr. Morris Cohen and Dr. Vipul Agrawal, shared their insights on opportunities to increase corporate profitability through better management of the service business. The “Six Steps for Managing Service Networks” outlined therein explain how all service-oriented companies (not to be confused with “service-oriented architecture [SOA]”!) can take advantage of these opportunities.
Industry leaders like Cisco Systems have reportedly been leveraging MCA’s Service Planning and Optimization (SPO™) suite [evaluate this product] to do just that, and have benefited from reduced service parts inventory, improved service levels and greater profit.
Servigistics, one of the leaders in the nascent SLM software category, refers to it as “strategic service management”, which entails service parts planning & optimization, service labor planning & scheduling and service parts pricing. The focus of today’s blog post is the realm of service parts planning & optimization.
TEC’s 2006 article titled Enterprises May Be Overlooking Profits from After-sales Service concurs with this particular opportunity. Namely, if service parts (including their availability and pricing) and service personnel management are well managed, manufacturers can significantly improve their profits from service operations. This will in turn lead to significant overall profit margins.
This brings us again to MCA Solutions, a privately held company headquartered in Philadelphia, Pennsylvania, the United States (US). Besides Servigistics, MCA Solutions has become a “usual suspect” in most big-ticket service parts planning and optimization evaluations.
The above-mentioned MCA’s award-winning SPO software suite has helped a number of aerospace and defense (A&D), high-tech and capital equipment companies of all sizes transform their service supply chains into bottom-line business drivers, by reducing (excess and obsolete) inventory, lowering support costs and improving service levels to maximize customer satisfaction. These, in turn, often result with higher revenue and increased equipment availability.
Outside the service parts planning & optimization market, the “MCA” name can be confused for a record label, museum of contemporary art, and whatnot, but the company’s brand recognition in its target market needs not much bolstering. Virtually anyone dealing with service parts planning and optimization knows that MCA stands for Morris Cohen & Associates.
Dr. Morris Cohen is the Matsushita (Panasonic) professor of manufacturing and logistics at the Wharton School of the University of Pennsylvania, and co-director of Wharton’s Fishman-Davidson Center for Operations Management. Dr. Cohen has spent three decades researching, planning, and designing advanced value chain systems and working with customers such as IBM, Cisco, Applied Materials, Intel, General Motors, and the United States (US) Navy.
In 1999, he co-founded MCA Solutions to bring the intellectual capital of service value chain optimization from the classroom into the technology marketplace (i.e., the real world). Another MCA co-founder, Dr. Agrawal, was a student of Dr. Cohen’s at Wharton before becoming assistant professor in the operations management department at the Stern School of Business at New York University. Today, Dr. Cohen serves as chairman of MCA’s board, while Dr. Agrawal is MCA’s executive vice president of products.
The mere concept of inventory optimization sounds quite simple: one has to balance the risk of stockouts (i.e., missed sales opportunities translated into poor customer service) with the (often hefty) investment (and tied up capital and cash) in inventory (safety stocks). This becomes sort of a “damned if you do, damned if you don’t” situation.
But the situation becomes much more complicated when one has to take into consideration multi-echelon distribution channels that entail hundreds or thousands of possible part locations worldwide, and even hundred thousand parts/stock-keeping units (SKU’s). The multi-echelon term refers to the supply chain hierarchy that spreads from the top upstream inventory point (e.g., a central distribution center [DC]) downstream several layers to the farthest node in the service chain (e.g., a regional warehouse or even a field service van).
It is thus a small wonder that MCA (and virtually every other optimization peer vendor) stems from the academia and its software’s concept is based on rocket science-like planning & optimization algorithms. In 2001, MCA released the first commercially available software for multi-echelon inventory planning for service parts.
As I have learned thus far from talking to the likes of MCA and Servigistics, these vendors remain quite cautious (if not outright secretive) about mentioning client’s names (especially if the client is involved in the product co-development) and about discussing their planning algorithms at a deeper level (not that many ordinary folks would understand these either, but, hey, the competition might listen in!).
Indeed, the planning and optimization models that these vendors tout can really be too overwhelming and hard to comprehend for ordinary mortals. For instance, in a single location with typical service parts, there can be deployed a few different methods of inventory planning, such as:
* Each part location is planned separately;
* With a so-called demand accommodation approach (mastered by Servigistics), which determines what parts to stock, then calculates demand satisfaction levels, to finally segment parts and locations into these different fulfillment (customer service) levels; and
* Overall optimization (arguably mastered by both MCA and Servigistics), as to achieve an overall desired service level across selected parts and locations.
Reportedly, the optimization approach can result in inventory about 30-40 percent lower than individual part location and 20 to 30 percent lower than the demand accommodation approach with much less planning and labor.
Warning: each prospective customer should check well which of these models would be the most appropriate for their business and ask the vendors to simulate real-life scenarios to them with germane data. Another warning: even then the recommended results from these packages might initially seem counterintuitive, with the rationale being difficult to explain. Nonetheless, MCA’s very first customer (I suspect it is Cisco) still successfully uses MCA SPO to manage a multi-billion dollar service parts inventory base, with 250,000 active parts across over a thousand service parts locations over several echelons.
Moreover, in some industries like aerospace & defense (A&D), stockouts are often prohibitively costly (i.e., planes are grounded due to missing critical parts), while, on the other hand, a mission-critical spare part can cost an arm-and-a-leg. There, the whopping investment in safety stocks has to be balanced rather against the risk of the part failure.
To that end, in 2003, MCA partnered with a well-known aerospace company to develop the first commercial software for planning based on service parts availability. Availability-based planning means that the system looks at the availability of all of the critical parts to support a piece of a complex equipment (installation), as opposed to independently planning for fulfillment rates of individual parts and locations.
With the same customer, MCA introduced software that managed multi-indentured and multi-echelon spare parts forecasting and planning, which was needed to support stringent “performance-based logistics (PBL)” programs that have been mandated by the US Department of Defense (DoD).
In 2004, MCA introduced risk-based tactical planning which takes a probabilistic approach to forecasting and applies it to the management and prioritization of service (work) orders. By prioritizing based on the risk of stockouts (i.e., the part’s criticality vs. its cost and the lead time to replenish it), the system ensures that supply is used optimally to meet spare parts service objectives, thus increasing service performance while making the planner more productive, too.
For more details on these principles see TEC’s earlier article titled Lucrative but ‘Risky’ Aftermarket Business—Service and Replacement Parts SCM. Also, TEC, with a courtesy of ChainLink Research, has featured Dr. Cohen’s article along similar lines entitled Service Supply Chain Strategies to Increase Corporate Profitability.
GE indeed, starting with Jack Welch’s long chief executive officer (CEO) tenure, has been widely reported to have significantly increased both its total revenue and profitability by focusing on services opportunities in addition to developing world-class products.
The manufacturing corporate giant has certainly proven the value of serving the product aftermarket, which has recently been purported in a quantifiable manner by many pundits as a high margin business. For instance, AMR Research reported recently that businesses earn 45 percent of gross profits from the aftermarket, yet it is only 24 percent of their revenues, while a recent article in Harvard Business Review claims that we all spend US$1 trillion every year on assets we already own.
A related software category term was mentioned in TEC’s 2003 article titled Service Lifecycle Management - Tapping into the Value of the Product Aftermarket. Namely, Service Lifecycle Management (SLM) is a business initiative focused on servicing a company’s products, and the customers that bought them, after the product has been sold. Simply put, SLM focuses on making more money from the product after the initial sale. But it is more than that — it is also a way to become a strategic part of the customer’s business after the sale is completed.
In another Harvard Business Review article titled Winning in the Aftermarket from May 2006, MCA Solutions’ co-founders, Dr. Morris Cohen and Dr. Vipul Agrawal, shared their insights on opportunities to increase corporate profitability through better management of the service business. The “Six Steps for Managing Service Networks” outlined therein explain how all service-oriented companies (not to be confused with “service-oriented architecture [SOA]”!) can take advantage of these opportunities.
Industry leaders like Cisco Systems have reportedly been leveraging MCA’s Service Planning and Optimization (SPO™) suite [evaluate this product] to do just that, and have benefited from reduced service parts inventory, improved service levels and greater profit.
Servigistics, one of the leaders in the nascent SLM software category, refers to it as “strategic service management”, which entails service parts planning & optimization, service labor planning & scheduling and service parts pricing. The focus of today’s blog post is the realm of service parts planning & optimization.
TEC’s 2006 article titled Enterprises May Be Overlooking Profits from After-sales Service concurs with this particular opportunity. Namely, if service parts (including their availability and pricing) and service personnel management are well managed, manufacturers can significantly improve their profits from service operations. This will in turn lead to significant overall profit margins.
This brings us again to MCA Solutions, a privately held company headquartered in Philadelphia, Pennsylvania, the United States (US). Besides Servigistics, MCA Solutions has become a “usual suspect” in most big-ticket service parts planning and optimization evaluations.
The above-mentioned MCA’s award-winning SPO software suite has helped a number of aerospace and defense (A&D), high-tech and capital equipment companies of all sizes transform their service supply chains into bottom-line business drivers, by reducing (excess and obsolete) inventory, lowering support costs and improving service levels to maximize customer satisfaction. These, in turn, often result with higher revenue and increased equipment availability.
Outside the service parts planning & optimization market, the “MCA” name can be confused for a record label, museum of contemporary art, and whatnot, but the company’s brand recognition in its target market needs not much bolstering. Virtually anyone dealing with service parts planning and optimization knows that MCA stands for Morris Cohen & Associates.
Dr. Morris Cohen is the Matsushita (Panasonic) professor of manufacturing and logistics at the Wharton School of the University of Pennsylvania, and co-director of Wharton’s Fishman-Davidson Center for Operations Management. Dr. Cohen has spent three decades researching, planning, and designing advanced value chain systems and working with customers such as IBM, Cisco, Applied Materials, Intel, General Motors, and the United States (US) Navy.
In 1999, he co-founded MCA Solutions to bring the intellectual capital of service value chain optimization from the classroom into the technology marketplace (i.e., the real world). Another MCA co-founder, Dr. Agrawal, was a student of Dr. Cohen’s at Wharton before becoming assistant professor in the operations management department at the Stern School of Business at New York University. Today, Dr. Cohen serves as chairman of MCA’s board, while Dr. Agrawal is MCA’s executive vice president of products.
The mere concept of inventory optimization sounds quite simple: one has to balance the risk of stockouts (i.e., missed sales opportunities translated into poor customer service) with the (often hefty) investment (and tied up capital and cash) in inventory (safety stocks). This becomes sort of a “damned if you do, damned if you don’t” situation.
But the situation becomes much more complicated when one has to take into consideration multi-echelon distribution channels that entail hundreds or thousands of possible part locations worldwide, and even hundred thousand parts/stock-keeping units (SKU’s). The multi-echelon term refers to the supply chain hierarchy that spreads from the top upstream inventory point (e.g., a central distribution center [DC]) downstream several layers to the farthest node in the service chain (e.g., a regional warehouse or even a field service van).
It is thus a small wonder that MCA (and virtually every other optimization peer vendor) stems from the academia and its software’s concept is based on rocket science-like planning & optimization algorithms. In 2001, MCA released the first commercially available software for multi-echelon inventory planning for service parts.
As I have learned thus far from talking to the likes of MCA and Servigistics, these vendors remain quite cautious (if not outright secretive) about mentioning client’s names (especially if the client is involved in the product co-development) and about discussing their planning algorithms at a deeper level (not that many ordinary folks would understand these either, but, hey, the competition might listen in!).
Indeed, the planning and optimization models that these vendors tout can really be too overwhelming and hard to comprehend for ordinary mortals. For instance, in a single location with typical service parts, there can be deployed a few different methods of inventory planning, such as:
* Each part location is planned separately;
* With a so-called demand accommodation approach (mastered by Servigistics), which determines what parts to stock, then calculates demand satisfaction levels, to finally segment parts and locations into these different fulfillment (customer service) levels; and
* Overall optimization (arguably mastered by both MCA and Servigistics), as to achieve an overall desired service level across selected parts and locations.
Reportedly, the optimization approach can result in inventory about 30-40 percent lower than individual part location and 20 to 30 percent lower than the demand accommodation approach with much less planning and labor.
Warning: each prospective customer should check well which of these models would be the most appropriate for their business and ask the vendors to simulate real-life scenarios to them with germane data. Another warning: even then the recommended results from these packages might initially seem counterintuitive, with the rationale being difficult to explain. Nonetheless, MCA’s very first customer (I suspect it is Cisco) still successfully uses MCA SPO to manage a multi-billion dollar service parts inventory base, with 250,000 active parts across over a thousand service parts locations over several echelons.
Moreover, in some industries like aerospace & defense (A&D), stockouts are often prohibitively costly (i.e., planes are grounded due to missing critical parts), while, on the other hand, a mission-critical spare part can cost an arm-and-a-leg. There, the whopping investment in safety stocks has to be balanced rather against the risk of the part failure.
To that end, in 2003, MCA partnered with a well-known aerospace company to develop the first commercial software for planning based on service parts availability. Availability-based planning means that the system looks at the availability of all of the critical parts to support a piece of a complex equipment (installation), as opposed to independently planning for fulfillment rates of individual parts and locations.
With the same customer, MCA introduced software that managed multi-indentured and multi-echelon spare parts forecasting and planning, which was needed to support stringent “performance-based logistics (PBL)” programs that have been mandated by the US Department of Defense (DoD).
In 2004, MCA introduced risk-based tactical planning which takes a probabilistic approach to forecasting and applies it to the management and prioritization of service (work) orders. By prioritizing based on the risk of stockouts (i.e., the part’s criticality vs. its cost and the lead time to replenish it), the system ensures that supply is used optimally to meet spare parts service objectives, thus increasing service performance while making the planner more productive, too.
For more details on these principles see TEC’s earlier article titled Lucrative but ‘Risky’ Aftermarket Business—Service and Replacement Parts SCM. Also, TEC, with a courtesy of ChainLink Research, has featured Dr. Cohen’s article along similar lines entitled Service Supply Chain Strategies to Increase Corporate Profitability.
