Moving a Slow-Clockspeed Business into the Fast Lane:
Strategic Sourcing Lessons from Value Chain Redesign in the Automotive Industry
Charles H. Fine (corresponding author)
Professor of Management
Sloan School of Management,
MIT Room E53-390
50 Memorial Drive
Cambridge, MA 02142
Manager, Strategy Development Group,
Mail Code 483-720-210
777 Joslyn Ave
General Motors Corporation
Pontiac, MI 48340-2925
Pittiglio, Rabin, Todd & McGrath, Inc.,
Vice President, Planning
General Motors of Europe
Submitted to Sloan Management Review
Moving a Slow-Clockspeed Business into the Fast Lane:
Strategic Sourcing Lessons from Value Chain Redesign in the Automotive Industry
Charles Fine,1 Roger Vardan2, Robert Pethick,3 Jamal El-Hout,4
Most companies, whether focused primarily on manufacturing or services,
frequently face the need to consider changes in the composition of their supply chains.
Few companies, however, undertake with any frequency, the task of comprehensive
assessment of the entire value chain that serves the end consumers. This paper
presents a strategic sourcing decision model developed in the process of a complete
value chain analysis done for the General Motors Powertrain (GMPT) organization. This
decision model was been applied across many activities – from traditional casting and
machining of metal for automotive engines and transmissions to the development of
software that encodes the latest algorithms for improved vehicle performance and
emissions control. The model has also proved valuable for assessing strategic alliances
– both with traditional supply chain partners as well as with long-time competitors. As
well, it has proved its worth at companies far removed from the relatively slow-
clockspeed, manufacturing-intensive automotive industry. This paper describes the
analysis process, the decision model, and the resulting improved process for value chain
strategy at GMPT. The value analysis process emphasizes the need to balance
quantitative financial considerations with less-easily quantifiable strategic issues. This
model not only provided key decision support for value chain strategy, but also formed
the foundation of a fast-response capability to emergent and disruptive strategic
challenges. We describe why such a capability is of critical importance not only to
companies such as General Motors, buy also to companies in very fast clockspeed
industries such as on-line music and entertainment.
Professor of Management, Sloan School of Management, MIT
Manager , Strategy Development Group, General Motors Powertrain
Director, Pittiglio, Rabin, Todd & McGrath, Inc.,
Vice President, Planning, General Motors of Europe
Arvin Mueller, Group Vice-President of GM Powertrain from 1997 through 2001,
comments on the Value Chain Strategy and its role in the strategic governance of GM’s
global powertrain operations:
Without a structured process for value chain strategy and formation, dealing with a
rapidly changing business model in a huge, complex, and global industry provides only a
A systems approach to value chain strategy led to a partitioning of “Knowledge Assets”
and “Supply Capabilities” within the vast business of engineering and manufacturing
engines, transmissions, and control systems for the world’s largest automotive
company. Application of consistent criteria to each partition enabled a formulation of the
“ideal” value chain configuration – a target toward which GMPT can migrate. With this
ideal configuration in hand, partnership or supply synergies can now be pursued with
value creation as a crafted intent—not a hope.
The Value Chain Strategy developed by this team--and the execution thereof--has given
us the capability to anticipate and adapt more quickly than our competitors. I thank them
for a job well done!”
Moving a Slow-Clockspeed Business into the Fast Lane:
Strategy Lessons from Value Chain Redesign in the Automotive Industry
Charles Fine, Roger Vardan, Robert Pethick, Jamal El-Hout,
When one thinks about case studies of innovative value chain management, it is common and
useful to look at the exploits fast-clockspeed industries and organizations – what are sometimes
called the “fruit flies” of our economy. The dynamic evolution of these organizations, the upstart
new ventures or the aggressive electronics giants, can teach a great deal about industry and
value chain dynamics.5 With rapidly shifting supply chains and high-clockspeed technologies,
these firms often provide useful lessons for responding to cutting-edge strategic challenges.
However, these “new economy” players are not the only ones facing dramatic and sweeping
changes throughout their value chains. Stimulated by the creation of a global integrated
organization for powertrain (engine, transmission, and controls) engineering and manufacturing
at General Motors under the leadership of Arvin Mueller, a team of managers and analysts was
created to perform a sweeping analysis of value chain strategy for the General Motors
Powertrain organization (GMPT). A key finding: Insights into the nature of value chain design
and corporate strategy -- for both fast- and slow- clockspeed firms -- can still arise from the
midst of a traditional “old economy” firm.
To present the strategic value chain framework developed and implemented, this paper is
organized as follows: Section 1 provides the background for the project and the setting at the
General Motors Powertrain organization. Section 2 presents the overall framework of the model
developed and applied at GMPT. Section 3 provides details on the components of the strategic
value chain analysis model developed and deployed. Section 4 illustrates the application of the
strategic value assessment model at GMPT. Section 5 provides a decision framework for
applying the model. Section 6 includes concluding remarks on organizational capability and
1. Project and Setting Background
GM Powertrain (GMPT) is the world’s largest manufacturer of automotive engines and
transmissions. Responsible for the design and manufacture of powertrains for General Motors
(as well for, among others, BMW, Volvo and Rolls Royce), the 76,000 employees of GM
Powertrain produce approximately 7.5 million engines and 6.5 million transmissions annually.
As global organization, GMPT has over 35 manufacturing facilities spread across North
America, South America, Europe and Asia as well as engineering and administrative centers to
govern these activities. In addition to its significant automotive business, GMPT is also the
largest supplier of engines to the marine industry, with over 80% market share in the North
American marine segments it competes in. If considered as a separate entity, GMPT would
itself be a Fortune 100 Company.
See, e.g., Clockspeed, by Charles H. Fine, Perseus Books, 1999.
The powertrain provides the defining characteristic of a modern vehicle: automatic propulsion.
From a cost perspective, the powertrain is the most expensive system in the vehicle and the
most asset-intensive in its production. From a technology standpoint, it is the most complex
system in the vehicle. From a regulatory standpoint, the powertrain is highly constrained with
respect to its fuel economy and tailpipe emissions. Furthermore, the powertrain plays a key role
in determining consumer perceptions of vehicle character. Many consumers consider the
powertrain to be the “heart of the vehicle;” its features are of great consequence to vehicle
performance and they often play a very significant role in consumers’ vehicle purchase
Structurally, GMPT is a classic example of the “old” economy: asset-intensive, highly vertically
integrated, and a manufacturer of products that require a large and highly skilled industrial labor
force. Yet, the automotive industry and its powertrain segment seem to be undergoing a phase
of horizontalization. That is, despite significant industry consolidation at the OEM level, many of
the consolidated OEM giants are increasing their outsourcing and reducing their degree of
In addition, after nearly 100 years of relative technological stability with the internal combustion
engine platform, the auto industry is facing the onset of new and potentially disruptive hybrid-
electric and fuel cell propulsion technologies. These technological innovations have significant,
long-term implications for the GMPT portfolio.6
In short, as the GMPT Value Chain Strategy was undertaken, the organization faced a complex
and bewildering array of challenges, changes and uncertainties. The project undertaken,
however, boiled these issues down to four key questions that the GMPT leadership wanted the
Value Chain Strategy to answer:
• Where in GMPT is value being created and what activities are not adding to overall
• What areas of the business should remain in-house versus being outsourced?
• Where should GMPT be making investments? How can these be leveraged?
• How can the organization optimize the GMPT Value Chain to govern its destiny
through mutual benefit among existing and emerging Alliance partners?
The work described here was motivated by a need to address these questions.
2. The GMPT Value Chain Strategy Framework
The overall objective of the Value Chain Strategy project was to examine from scratch the
strategy for the GMPT organization. A key sub-objective was to make strategic assessments of
important value chain elements.
A first step in the analysis was to characterize the GMPT value chain. How should it be
represented? What were its constituent parts? As Figure 1 shows, three dimensions were used
to categorize value chain elements: products (e.g., L4, V6, V8), subsystems (e.g., block, valve
See, e.g, Metcalf, Sara Susanne, A System Dynamics Exploration of Future Automotive Propulsion
Regimes, MS Thesis, Sloan School of Management, MIT, 2001.
train, controller), and process elements (e.g., design, assembly, test). As examples,
engineering of the block for a certain V8 engine is one process element in the value chain,
assembly of the valvetrain for a V6 is another, and test of the electronic controller for an in-line
four cylinder engine (I4) is a third. More generally, any cell in the grid portrayed in Figure 1 is a
value chain element for which GMPT should develop a strategic posture, i.e., insource,
outsource, alliance, etc.
Categorizing Value Chain Elements
L4 V6 V8 V8
The representation in Figure 1 can usefully be called the subsystem value chain because it
captures all the subsystems that make up GMPT products. Another approach is to focus
primarily on the product value chain and the customers and consumers of powertrains. This
paper addresses primarily the work done on the subsystem value chain; work on the product
value chain at GMPT is ongoing.
To value elements in the chain, one first needs a measure of value. Traditional methods
seemed incomplete for the task. For example, Economic Value Added (EVA) analysis provides
a quantitative financial value for elements in the value chain. Developing such an analysis and
an accompanying financial model requires a significant amount of time and effort. However,
there is a well-established body of knowledge to draw upon to complete this analysis.7 Our
project objectives required a framework that would extend beyond merely financial assessment.
The resulting framework we developed comprises a quantitative, financial component, utilizing
traditional EVA analysis, and a qualitative, strategic component, representing the decision
model innovations presented here.
Combining Strategic & Economic Assessments
See, e.g., EVA: The Real Key to Creating Wealth by Al Ehrbar, Wiley, John & Sons, October 1998, or
EVA and Value-Based Management: A Practical Guide to Implementation, S. David Young, Stephen F.
O'Byrne, McGraw-Hill Professional Book Group, September 2000.
Figure 2 Competitive Cost (Economic)
Figure 2 illustrates the framework that we developed and applied to each value chain element.
Each element is passed through a strategic assessment and an economic assessment to
produce recommendations regarding Sourcing, Investment, Architecture and Alliance Insights.
Before moving into a more detailed discussion of each of the “arms” of the framework, consider
the outputs of the framework in more detail:
• Sourcing: Identifying elements of the business that either need to be migrated more to the
supplier base or, alternately, more insourced within GMPT.
• Investment: Identifying specific areas and activities of strategic importance where further
investment would result in creating or maintaining additional value and/or competitive
advantage in the future.
• Architecture: Identifying potential areas where modularization of previously integral
component interfaces would make sense from an overall value chain perspective, often to
support ease of outsourcing and development of a competitive supply base. Alternately,
identifying modular value chain elements that could productively and profitably be integrated
into a single integrated component.
• Alliance Insights: Identifying areas or activities that benefit from present or future strategic
To do a strategic assessment of value chain elements, we used as a starting point the
make/buy decision model presented in Clockspeed, by Charles H. Fine.8 Following this work,
the GMPT Value Chain model identifies two broad categories of assets: knowledge assets and
supply assets. In the GMPT context, knowledge assets are primarily those related to design
and engineering of powertrain products (engines, transmissions, and their subsystems) and
process engineering for powertrain manufacturing systems. Supply assets consist primarily of
the manufacturing capacity at GM and suppliers to provide the volumes of product required.
These two asset domains are not all encompassing. However, conceptually, these two domains
broadly represent important asset classes for value chain design consideration. Conceptually,
the objective of the project was to define a “target” value chain configuration based on the
strategic and economic analysis.
Economic Value Framework
As mentioned above, the decision model has two principal components, to assess respectively
the economic and strategic aspects of sourcing strategy. As described in the literature, EVA is
calculated by combining two distinct financial streams: Income and Capital Costs. The Income
stream generates the Net Operating Profit After Taxes (NOPAT) using Revenues, Cost of
Goods Sold and Tax charges. Given that GMPT is a cost center and that its automobile
engines are consumed internally and not typically sold at market prices an open market,
computing the revenue side of EVA proved somewhat challenging. However, the powertrain
revenue stream was approximated by examining the differences in manufacturers’ suggested
vehicle “sticker prices” charged for purchasing different engines in GM vehicles, to estimate the
economic value of different engines in various segments.
The second component of the EVA equation analyzes the type of return on capital generated in
relation to an industry benchmark. Its computation involves identifying the Capital Charge by
multiplying net assets by the Weighted Average Cost of Capital (in the case of the Automotive
industry this WACC was assumed to be approximately 9.5%). Positive Economic Value is
created when NOPAT exceeds the Capital Charge.
In a pure application of EVA, this is a fairly straightforward computation. However, to apply the
model to understand how EVA for a given element would change as a function of procurement
strategy, a ∆ EVA approach (which starts with a baseline EVA) was used. Quantities for ∆EVA
were calculated as the differences between various value chain options compared with the
status quo, using estimates of the cost of procuring products, components and supply chain
activities (such as Machining, Assembly, Product Engineering, etc) from other
The starting point for this model was the material in Chapter 9 of Clockspeed, by Charles H. Fine,
Perseus Books, 1999. The work there, in turn, builds on an MIT Sloan School Masters thesis, A Strategic
Sourcing Model for Concurrent Product, Process, and Supply-Chain Design,
by Paul M. Gutwald and the article, "Is the Make-Buy Decision Process a Core Competence?" by Charles
Fine and Daniel Whitney, in Moreno Muffatto and Kulwant Pawar (eds.), Logistics in the Information Age,
Servizi Grafici Editoriali, Padova, Italy, 1999, pp. 31-63. The latter is also available at
Many sourcing decision approaches simply stop with such a financial analysis. However, a
large number of strategic issues are not captured easily or at all with such an approach.
Therefore, a complementary qualitative, strategic assessment may significantly improve the
overall assessment and decision process.
3. Strategic Value Framework: Assessing Five Dimensions
The strategic value assessment tool developed for this project utilizes five criteria (Figure 6) for
considering the strategic impact of sourcing alternatives. For each element of the value chain,
the model assess five dimensions: (1) Customer Importance (how does the sourcing decision
affect customer preferences), (2) Technology Clockspeed (how rapidly is the underlying
technology for this value chain element changing), (3) Competitive Position (how does the firm
stack up to its competition in achieving cost, quality, technology, etc. on this value chain
element), (4) Supply Base Capability (how deep and capable is the outside supply base for
outsourcing this value chain element), and (5) Architectural Relationship (how integral or
modular is this value chain element to the overall product, service, or system of which it is a
component). These five criteria are considered sequentially, as described below.
As will be described below, for each element of the value chain to be assessed the model is
intended to be used qualitatively and prescriptively to analyze sourcing decisions as follows: (1)
The more important the source to the customer, the more important the sourcing decision. (2)
The faster the technology clockspeed, the more risky it is to be fully dependent on an outside
supplier. (3) The stronger one’s own competitive position in designing or making the value
chain element, the more desirable it is to insource it. (4) The more capable the supply base (in
number of viable suppliers and their technological competency) the safer to outsource. (5) The
more integral the value chain element to the overall system, the more risky to be fully dependent
on an outside supplier.
Before going into the details of the model, we provide two brief illustrations, the first on a famous
outsourcing decision: the choice by IBM to outsource to Intel the manufacture of the
microprocessor for its first personal computer.
Assessment Dimension Strategic Assessment for PC microprocessor
Customer Importance Microprocessor source was irrelevant to the customer
(What was relevant (at first) was IBM’s name
on the computer)
Technology Clockspeed Very fast (measured ironically, eventually by Moore’s law)
Competitive Position IBM was the world largest semiconductor manufacturer
Supply Base Capability Intel and AMD were the only qualified suppliers
Architectural Relationship Microprocessor was fairly modular to the rest of the PC
(except, famously, to Microsoft’s DOS;
hence the Wintel colossus)
IBM reasoned correctly that the customers would not care whether the computer’s brains were
made by IBM or not, so on this dimension, outsourcing the microprocessor was a reasonable
choice to consider, even though as a corporation, IBM had as much capability in semiconductor
manufacturing as any firm. However, since semiconductor technology clockspeeds were so
fast, a supplier who got a lead proved tough to dislodge. Combine this with the small supply
base and the risk goes up. Add in the failure to recognize that the modular architecture
combined with an independent Wintel supply base created extremely low barriers to entry for
clone makers such and Compaq and Dell, and we gain some insight into one of the most
significant sourcing decisions of all time, as measured by its impact on the market values of the
firms involved. Our primary intention here is not to second-guess past sourcing decisions
however. Rather, we hope to present a model to aid in future strategic sourcing decisions.
Even more briefly, consider the following additional example of a consumer products
company (say Proctor & Gamble or Unilever) assessing whether it should insource or outsource
the manufacture of one of its branded products (say shampoo). With respect to Customer
Importance, investment in brand image is quite important, but few, if any, shampoo customers
are likely to know or care what company actually mixes the ingredients and bottles the
shampoo. Further the Technology Clockspeed on shampoo mixing and bottling is very slow.
Third, because the processes are well known, it is unlikely that any firm has a large competitive
advantage in, say, the cost of mixing and bottling its shampoo. Fourth, there are quite a few
companies that can serve as suppliers for shampoo mixing and bottling. Finally, the production
of shampoo is quite modular to its design and to the development of its brand image. We are
left to conclude that there is not a strong strategic case to be made for consumer products
companies to own and operate their shampoo factories. Nevertheless, one often observes
vertical integration in this kind of situation, partly due to history and organizational inertia. For
companies that wish to take a fresh look at these kinds of issues, we believe the model
described here provides a practical, yet comprehensive approach.
Strategic Sourcing Assessment requires
evaluation of five key criteria
Customer High customer importance and fast clockspeed means more
Fast Competitive position is critical for
Medium assessing value of outsourcing
Supply Base Capability must None
be present for successful Few Possible Decisions
outsourcing Many (Knowledge & Supply):
Degree of modularity affects Modular
significantly the ease and risk of Partial Outsource
Exercising the Model: Begin with Customer Importance
To describe the model in more detail, we relate here the process of its development and use in
the General Motors Powertain organization. For engines and transmissions, customer
preferences can be estimated in part by observing buying behaviors. That is, one can tabulate
how frequently customers choose a gasoline engine over a diesel or a manual transmission
over an automatic. However, to uncover subsystem level preferences and biases, surrogate
measures are often needed, in part because consumers do not have direct preferences on
subsystems such as engine blocks, valve trains, exhaust systems, etc. Instead, one must elicit
customers’ tastes on performance characteristics such as fuel economy, acceleration,
emissions, and quietness (noise, vibration, and harshness), and then relate those to powertrain
subsystems and value chain process elements.
As an example, consider two different customer classes (pickup truck buyers and minivan
drivers) and two different engine subsystems (the starter motor and the engine controls logic
algorithms). In the pickup truck segment, there are loyal GMC and Chevrolet customers who
buy GM products for the superior acceleration and smoothness of their engines. For such
buyers, knowing that the control systems are designed by GM engineers, generation after
generation, can be important to continued customer loyalty and to the vehicle purchase
decision. Such buyers may care little however, about whether GM designs or builds the starter
motors, which have little, if any effect, on driving characteristics. Minivan drivers, on the other
hand, expect reliability from their engines, but typically pay much more attention to the layout of
the vehicle’s interior space than to any engine characteristics and may not care what parts of
the engine are designed by GM.
To implement the Customer Importance component of the model, the GMPT value chain team
conducted workshops with GMPT Engineering and Manufacturing staffs to relate engine and
transmission subsystems to various performance characteristics perceivable by customers. To
complement this, GMPT launched the corporation’s first-ever customer clinics and statistical
model aimed solely at capturing customer preferences about powertrains. The resulting model
yields significant insights for helping the GMPT designers and managers understand consumer
trade-offs and the key drivers of consumer preference in various segments.
In the words of one GMPT executive: “I care about this variable because I want to know what
investments I will get paid for.” That is, the data from the Customer Importance variable aids in
understanding what product characteristics the customer will pay a premium for. For an
organization whose annual investments in products, processes, capacity, and technology are
typically measured in the billions of dollars, the model provides a critical new source of data to
help direct these investments and related sourcing decisions.
The second criterion in our Strategic Assessment Framework is Technology Clockspeed.9 The
clockspeed construct assesses the rate at which underlying technologies of a product or system
are changing. This criterion is important because value chain elements with fast clockspeeds
are more prone to experience rapid innovations and are more likely to require ongoing
knowledge investments to maintain technological competency.
As an illustration, consider the Cylinder Block, which has relatively stable underlying process
technologies (e.g., aluminum casting), compared with the Controller, which is the computerized
“brain” of the engine, and has underlying technologies (e.g., semiconductors, algorithms) that
change quite rapidly.
Elements with fast Technology Clockspeeds typically require higher levels of investment to
maintain technical competency. In contrast, even though the Cylinder Block is a crucial element
of the Engine, the relatively slow pace of underlying technological change makes the core
knowledge more common and less likely to be subject to innovations that could result in loss of
competitive advantage if it were to be outsourced. Furthermore, once dependent on a supplier
for a fast clockspeed technology, it can be very difficult and/or costly to regain capability in the
technology should that become desirable or necessary.
A company’s relative competitive position for developing and/or producing some element of the
value chain is another important factor to consider in formulating sourcing strategy. The reason
for this is straightforward: areas of relative competitive advantage are potential sources of
strategic advantage, especially when they are in areas of high customer importance and with
relatively fast technology clockspeeds. By contrast, areas of relative competitive weakness
could be candidates for outsourcing, since the weakness may not be able to be overcome
without significant investment, if at all.
Of course, the data collected for this dimension of the project is highly confidential, so we use a
hypothetical example to illustrate further. Consider, for example, how this factor might be
assessed differentially by General Motors and Toyota. Imagine for some component, that GM
assessed that its competitive position in manufacturing cost were average. That is,
benchmarking studies showed that total manufacturing cost at GM was about equal to the
industry average for that component. In such a case, GM might assess that such a component
might benefit from outsourcing if a lower cost could be obtained from an outside supplier. GM
would therefore consider this component as a candidate for outsourcing based on this criterion.
Suppose for example, in contrast, that for the same component, Toyota were to assess that its
internal manufacturing costs were the lowest in the industry. In this case, even though GM and
Toyota might assess Customer Importance and Technology Clockspeed identically, they might
come to different conclusions on outsourcing based on Competitive Position. In particular, GM
might reasonably choose to search for a lower cost external supplier whereas Toyota would not.
See C. H. Fine, Clockspeed, Perseus Books, 1999.
The relative strength of the supply base for any given value chain element is also an important
factor in our Strategic Value framework. The strength and size of the supply base provides
perspective on the relative leverage that the supply base might have if a given value chain
element is outsourced. For example, if some value chain element were outsourced where only
one supplier existed, the supplier might have considerable leverage versus the OEM. On the
other hand, where an extensive supply base exists, the key capabilities are more likely to be
judged as commodities and not necessarily a source of strategic value.
As an example, consider the sourcing strategy that GMPT might consider for the casting of
engine blocks. As mentioned, the engine block casting process is not a value chain component
that is high in the customer’s consciousness. As well the clockspeed is relatively slow, so we
might consider this process as not particularly strategic. Yet, GM, as well as most of the world’s
large automotive OEM’s are largely vertically integrated in engine block casting. One reason for
this is a dearth of suppliers able to take on the volume of casting GM might like to outsource.
That is the supply base capability is low. More specifically, GM casts many million engine
blocks each year, as does each of Ford, Toyota, DaimlerChrysler, Volkswagen, and
Renault/Nissan. With all the major manufacturers vertically integrated to a significant degree,
no large capable suppliers have arisen, so the supply base capability, for the volumes needed
by the large OEMs, is low. If any one of these firms chose to spin off its casting plants as an
independent entity, that would create a large independent supplier, but only one such supplier
might leave the OEM in the type of situation IBM found itself in with Intel: dependent on a single
supplier with little leverage on price. As a result, developing a capable supply base where there
is none can be a difficult task.
The Architectural Relationship between the value chain element in question and the product,
service, or system in which it is embedded represents the fifth and final dimension of our
Strategic Value Framework. Following Ulrich,10 we think of product architecture as the scheme
by which the function of a product is allocated to its constituent components. Ulrich
distinguishes between integral and modular product architectures, where integral architectures
exhibit close coupling among the elements of the product. In contrast, a modular architecture
features separation among a system’s constituent parts, where standard interfaces make the
exchange of parts relatively simple. We find it useful to make this assessment along a
continuum from highly integral to highly modular.
To a significant degree, an automobile engine is a fairly integral system. One certainly cannot
build one from off-the shelf parts as can be done with a stereo system or a bicycle, for example.
On the other hand, although the design of the many subsystems is fairly integrated, once the
design is complete, the manufacture of many subsystems is modular from the manufacture of
others. As a result, following Fine and Whitney,11 we found it useful to assess separately the
Karl Ulrich, “The Role of Product Architecture in the Manufacturing Firm,” Research Policy 24 (1995):
"Is the Make-Buy Decision Process a Core Competence?" by Charles Fine and Daniel Whitney, in
Moreno Muffatto and Kulwant Pawar (eds.), Logistics in the Information Age, Servizi Grafici Editoriali,
knowledge elements (e,.g., design and engineering) of the value chain and the capacity or
supply elements (e.g., the manufacture) of the value chain.
4. Model Illustration and Implementation
As we developed our framework, we continually tried to collect data to quantify the concepts.
As mentioned, a major customer preference assessment project was launched to collect data
for the Customer Importance component of the model. For data on Technology Clockspeed
and Architectural Relationship, dozens of engineers were interviewed and their assessments
tabulated. For the Supply Base Capability and Competitive Position components, we
interviewed experts in procurement, financial analysis, benchmarking, etc. In total, over 100
executives, product engineers, manufacturing engineers, financial analysts, planners, and
purchasing agents contributed their knowledge. The project team systematically documented
this large knowledge base. In the first use of the model we developed a database of each of the
five criteria (and the underlying rationale behind each rating) for over 20 Engine Subsystems, 20
Transmission Subsystems, as well as various supply chain elements for both Engineering and
Padova, Italy, 1999, pp. 31-63. The paper is also available at
Table 1: Case Example: Exhaust System Engineering
As an example of the approach, consider the analysis for the Powertrain Exhaust subsystem
(Also, see Figure 4 below).
• Subsystem – Powertrain Exhaust
• Components – Catalytic converter, Air Injection Reaction system, O2 sensors, etc.
• Customer Importance – High. The performance of this subsystem impacts the emissions of
the vehicle, which is important to many customers. The Exhaust system also has a high
impact on acceleration due to the converter’s key role in regulating exhaust back-pressure.
• Technology clockspeed – Fast. Key driver is the sensor technology, which is evolving
rapidly. Stringent government regulations and use of precious metals requires GMPT to
maintain a continual focus on improving the performance of this subsystem.
• Competitive position – Parity. The OEMs have different strategies for the cost and
performance of this subsystem, but overall all OEMs have similar capability.
• Supplier Capability – None. Although there are suppliers capable of component design,
there are currently no suppliers that are capable of developing the entire subsystem.
• Architecture – Modular. The powertrain exhaust system is somewhat modular because the
same converter can be used in multiple vehicle applications. The packaging constraints
may drive changes in the design of the down pipes and bolting schemes from vehicle to
• Strategic Value Chain Assessment – High Strategic Value; Likely Insourcing
Table 1 provides some of the details on the strategic value analysis performed for the Exhaust
System Engineering sourcing decision. The economic data is proprietary and not included.
At a broader level, some of the highlights of the strategic Value Chain analysis for the entire
• Enhance / Maintain capability to determine the Architecture of the Engine, Transmission and
Controls as this is a highly strategic activity.
• Maintain Process Expertise for Product / Process Development & Supplier Management.
• Maintain “Final Assembly & Test” of Engines and Transmissions within GMPT as it is a
highly strategic activity.
• Increase Reliance on Suppliers for design of lower strategic importance subsystems &
• Develop a capable supply base for lower strategic subsystems and components.
The performance of the Exhaust subsystem impacts the emissions of the
vehicle, which is important to the customers. This system also has a
high impact on acceleration due to the converter’s key role in
Customer regulating exhaust backpressure
Key driver is the sensor technology, which is relatively fast
changing. Stringent government regulations and use of
precious metals requires GMPT to maintain a continual focus
Technology Clockspeed on improving the performance of this subsystem.
The OEMs have different strategies for the cost
Competitive and performance of this subsystem, but
Competitive overall all OEMs have similar capability.
Although there are suppliers capable
of component design, there are
currently no suppliers that are Capable Suppliers
capable of developing the entire None
The powertrain exhaust system is somewhat
modular because the same converter can Value Chain Strategy
be used in multiple vehicle applications. Architecture Outcome
Modular Insource All
The packaging constraints may drive
changes in the design of the down pipes
and bolting schemes from vehicle to vehicle.
5. Decision Framework: Analysis, Options, Assessment, Decision
The Strategic Value Framework described above should be considered as an analysis tool. It
does not actually recommend a course of action. Thus the value framework has to be
embedded in a decision framework which includes (1) value analysis (economic and strategic),
(2) development of strategic options, (3) assessment of the generated options, and then (4) the
making of a decision.
The implementation of the remaining steps in this process for specific subsystems is proprietary
to General Motors and therefore not appropriate for this article. However, some broad
comments about the process follow.
The economic and strategic value analysis enabled us to classify key elements of the value
chain in a matrix shown in Figure 4. This classification scheme categorized value chain
elements as having (1) both high economic and strategic value (likely insourcing candidates),
(2) both bow economic and strategic value (likely outsourcing candidates), (3) high economic,
but low strategic value (internal cash cow or spinoff candidate), and (4) high strategic, but low
economic value (“strategic” investment or financial “problem”). Once categorized, we compared
the existing sourcing posture for each element with the “desired” position. In many cases, those
elements that our value analysis recommended outsourcing were already outsourced and
conversely. However, we did find some elements that were not aligned. These were the ones
that received additional attention to generate alternatives to the existing posture. These
alternatives were then assessed, followed by decisions and actions.
These alternatives broadly fall into the following categories:
• Partial Outsource
• Partial Insource
• Spin Off
• Outsource to existing suppliers
• Develop Suppliers and Outsource
Synthesizing Strategic & Economic Elements
Use for higher
Strategic - High
Strategic - High Economic - High
Economic - Low
6. Organizational Capability and Internet Applications
Strategic - Low
Figure 5 Strategic - Low
Low High 17
Economic - High
Economic - Low (negative) Medium (positive)
Economic Value Added
We have presented a model for strategic value chain analysis based on work at the General
Motors Powertrain organization. However, during the course of this work, we became aware of
how such a project can create an organizational capability for fast response to industry value
chain dynamics. Specifically, when the first phase of our project was almost complete, General
Motors announced a major alliance with Fiat, Italy’s leading vehicle manufacturer. At the time of
the first announcement, not all of the details of the relationship had been settled and Arvin
Mueller, GM’s Group Vice President and General Manager of GMPT was asked to make
recommendations on how to structure the powertrain portion of the GM/Fiat alliance. Building
on the value chain analyses that our project team had developed, we were able to make specific
recommendations that influenced the alliance structure in the powertrain domain. A year later,
the powertrain portion of the alliance was being viewed by the automotive press as successful
and particularly “savvy.”12
Of course, in a relatively slow-clockspeed environment like automotive powertrains, the need for
rapid response value chain analysis arises relatively rarely. However, in a very fast clockspeed
environment, the need for what we call a “Value Chain SWAT Capability” is arguably much
greater.13 To illustrate this, consider the gyrations in the music industry since the explosion of
MP3 file sharing built on the peer-to-peer sharing software distributed widely by Napster.
Napster displaced the distribution segment of the music industry’s value chain, which happens
to be the stage in the chain where most of the revenue is traditionally collected, only after
significant investment has been sunk by large music companies in upstream value stages.
Although Napster was started by a 19-year-old “hobbyist,” it’s control was bought by capitalists
once the subscriber count exceeded ten million or so. The Recording Industry Association of
America (RIAA), which represents large music companies (the property rights holders of a large
fraction of commercially recorded music), quickly deemed Napster as “Public Enemy Number
One,” and successfully applied a legal strategy to have the courts shut Napster down.
At best the RIAA might be judged as having displayed brilliant legal tactics, but
extremely myopic strategic vision. As widely predicted, Napster’s demise has lead to a
multitude of websites devoted to free music file sharing.14 There are now even websites
devoted solely to keeping track of the many music file sharing sites in existence.15 Many of
these sites are undoubtably run by capitalists, who might respond predictably to legal or
financial incentives. However, some of these sites seem to be run by music lovers (or freedom
lovers) who might be more aptly described as anarchists. Some of these website operators
seem to be more interested in seeing music widely available for free than they are in financial
remuneration. As a result, the upcoming war between the RIAA and the anarchists is likely to
be very different from the one with Napster. Anarchists are hard to find and harder to hit. By
destroying Napster rather than finding a way to coopt or control it, the RIAA has made its value
chain infinitely more difficult to control.
Had the RIAA done a deeper (and timely) value chain analysis, they may have
concluded that a partnership with Napster (who had a huge following and huge market share for
music file sharing) represented their best chance to preserve any degree of control over the
“Looking More Savvy than Sentimental: A Year after Rejecting Merger, Fiat’s Silencing Critics,” Jeff
Israely, The Boston Globe 06/23/2001 Page: C1 Section: Business
In police work, SWAT stands for Special Weapons and Tactics. SWAT teams are rapid response
teams that are trained to react to difficult and unanticipated urgent matters. We think the analogy fits well
“Revenge of the file-sharing masses!” http://www.salon.com, July 20, 2001, by Scott Rosenberg.
See, e.g., http://www.zeropaid.com.
future of on-line music-distribution. The window of opportunity for creating such a deal was very
short, however. The anarchists were already hard at work refining their user interfaces to the
point where generations X, Y, and Z would forever abandon the concept of paying for music.
More than ever, companies in fast-clockspeed environments need a strong capability for
continuous assessment of their entire end-to-end (E2E) supply and distribution chains. When
disruptions occur, value chain SWAT teams must rapidly assess which parts of the chain are
vulnerable, which parts are defensible, which alliances are palatable, and which threats are
deadly. Such skills were clearly lacking at the RIAA and at Napster. The RIAA chose to shoot
its potential partners, while giving valuable development time to its truly deadly foes.
Napster, however, was also at a loss to define a viable business model, although its
large collection of eyeballs (or ear drums) would surely have fetched a decent price when its
peak matched the internet market’s peak. One Napster executive allegedly suggested to an
already-agitated RIAA official that the only profit model available to the RIAA might be selling T-
shirts on the Napster website, further inflaming the passions against Napster arrogance. But
Napster, too, had a limited opportunity window to cut a deal with the RIAA before losing its ear
drums to the anarchists or losing its business license in the courts.
Whether the music distribution industry will save itself from the anarchists (or even
profitably postpone its demise) continues to be a fascinating case study in internet-driven
disruption. But the deeper lesson is learning what capabilities are required by companies to
survive such now-commonplace cosmic disruptions driven by the internet. No one can predict
what industry will next be disrupted by what teenage hobbyist. And strikingly, the capabilities of
teenagers to disrupt industries is probably only growing with each passing year of Internet
Our conclusion: In any business where digital content is of any importance, managers
ought not sleep well until the value chain SWAT team is armed and ready.
The authors would like to thank Mr. Arvin Mueller for conceiving the GMPT Value Chain project
and, more importantly, for leading it with his active involvement and his strategic insights. The
authors also acknowledge the valuable contributions of Mr. Cuneyt Oge of PRTM, Messrs. Gary
Blair and Alan Kennedy of GMPT, as well as the members of the GMPT Strategy Development
Group and the PRTM team.