For more than a decade, companies have been told to compete on capabilities. But this advice can take companies only so far. For capabilities to make a difference in business performance, ultimately they must be distinctive—combined selectively to create an unassailable formula for satisfying customers.
By Tim Breene, Narendra P. Mulani and Paul F. Nunes Outlook Journal, June 2005
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For years, top executives have been advised to compete on capabilities. More specifically, they have been given two options. Option one: view capabilities as the bases of core competencies, areas of specialized expertise that companies create through organizational focus over time. Option two: view business capabilities as the processes that are central to the execution of the company's strategy.
But while the arguments used to support these two approaches to capability development are compelling,
they tend to break down in practice. Management discussions centered
on capabilities as the embodiment
of strategy in action, for example, can often be reduced to the observation that what is needed is "a good strategy well executed"—which won't come as news to most executives. And core competence arguments begin to crumble when a fixation
on capabilities excellence causes a company to lose sight of the broader market, leaving it to become the best buggy-whip maker in an increasingly automotive world.
The danger at the heart of both these admonitions is that the unwary company could mistakenly assume that lasting business success comes from achieving world-class excellence
in one or more processes. In fact, observation has shown us that in practice, conventional process excellence often fails companies as a means to achieve high performance. One need only look at the airline and wireless communications industries, where although there are more than a few companies with exceptional process capability—nearly flawless flight operations, for example, or superior wireless network management—profitable enterprises are hard to find.
By studying high-performance businesses within their competitor sets and across industries, Accenture has gained insights into what makes capabilities truly distinctive, and why distinctive capabilities are critical to lasting competitive advantage. We are also starting to see how high performers successfully create and manage the unique sets of business processes and resources that underpin their distinctive capabilities. Five key attributes make the difference.
No one attribute can give a company a distinctive capability. Together, however, these five consistently make the difference between business practices that are good but unexceptional, and those that make a real and lasting difference in company performance. An examination of each of the five elements of a distinctive capability reveals how companies actually build them, and what other companies must do to find their own path to achieving them.
Companies with distinctive
capabilities… 1…define customer-centric algorithms for value creation.
All companies recognize the need
to serve customers well. But how can a company achieve that essential goal in a way that gives it a sustainable competitive advantage? A high performer relies on an algorithm that charts the path from process to profit.
A business algorithm is a formula for doing business, either at the enterprise or business unit level,
that translates a big idea regarding customer needs into a specific set
of connected business processes and resources that cost-effectively satisfy those needs. The result is significant value for customers and shareholders.
There are two crucial elements to creating a successful algorithm. The first is deep insight into what consumers truly value (or will value) in an offering category, and an understanding of the marketing capabilities—for example, building the branded
experience—necessary to create and sustain demand.¹ The second is originality in identifying the most profitable configuration of resources to deliver the promised value. Such
originality can come only from deep knowledge and mastery of a range
of capabilities, from finance to supply chain to human performance.²
Consider Dell, which went beyond
a simple telephone model, and later an Internet model, of selling personal computers and electronics.
The company recognized that in addition to the cost savings it
captured by not having its own retail stores and not selling through traditional retail channels, it could use the time the customer was
willing to wait for home delivery
to postpone actually assembling
the PC until after it was ordered. This enabled Dell to reduce costs and prices even more. The com-bination of these two distinct processes gave Dell a business algorithm that has made it the
No. 1 seller of PCs today.
One leading auto insurer formulated its algorithm after recogniz-ing that what many customers value in auto insurance—and the main factor in customer retention—is fast claims payment. The company leveraged new technologies
to link a number of processes so that most customers receive the settlement check on the spot, immediately after the claims adjustor has inspected the damage, and not weeks later. Result: dramatic business growth and an actual reduction in the ratio of costs to claims.
Creating a successful algorithm
is never easy. It requires deep insight into customers' current
and future needs, and it demands the creative use of resources to manage the costs of delivering exceptional value. Yet the high
performers we've observed all understand, across a wide range
of employee levels, the unique value-creation process that enables them to make money—and that
is, in essence, the formula for
their success. 2…align their capital deployment with these algorithms.
The key to making a distinctive capability work is ensuring that capital deployment is disproportionately targeted to the underlying business algorithm. At a minimum, this means each component process has the financial backing it needs
to be successful.
This kind of commitment can
be substantial. One retailer, for example, is estimated to have
spent $500 million in the early 1990s to create the infrastructure needed for its algorithm's linchpin supply chain capability, a critical process in its business algorithm.
A major implication of this insight into how high performers fund processes is that annual budgeting versus zero-based budgeting can lead to the misappropriation of funds to areas that, as the core processes in the algorithm change over time, no longer create substantial value.
Core processes in high performers not only get adequate financial support. They also tend to receive the greatest focus on human capital, from management on down to line employees. "Hero" functions—the ones whose people always seem to get the most credit for a business' success—are therefore often the same as the core processes of the algorithm.
A CEO's provenance is often a strong sign of where a company's key algorithm processes are located. Another is the differentiated way
a company treats the employees within key processes. Accenture research shows that high performers often devote special resources, including performance improvement efforts, to such employees.³
Their generous funding of key processes does not mean that high performers ignore cost management. Indeed, the high performers we've observed are fanatical about asset efficiency, and they use asset innovation as a key component in their algorithms. The companies seek advantage not just from high margins but, wherever possible, from a high return on net assets, creating a low-cost structure that can sustain a first mover in the face of copycat competitors.
Today's low-cost carriers in the
airline industry, for example, have innovated to create greater returns from both their fixed assets and their workforces—a powerful one-two punch of capabilities. First, these companies invested in a uniform fleet of aircraft, usually Boeing 737s, eliminating the increased maintenance and operating costs associated with a mixed fleet. Next, they make the most of their human capital by having employees work in multiple roles: They not only assist passengers in-flight but also clean the cabin and, upon landing, frequently serve as additional gate agents. Together, these reduced asset costs help these carriers maintain their powerful low-cost, high-customer-value position against
the major carriers.
It is important to note that while high performers seek a substantial return on assets, they are extremely careful not to go too far and embrace capital deployment models that are highly productive in theory but that cannot or do not support
a successful algorithm. UK-based retail hypermarket Tesco, for example, maintained its Internet home shopping and delivery service with a model of picking and packing groceries inside its stores; its competitors built ostensibly more asset-efficient warehouse operations
to support their models. Result: Tesco has managed a very successful online grocery business while some other online grocery operators have struggled to succeed.
Tesco management also recognized that if store employees were to select the groceries for delivery,
the selection process had to be
very efficient. This prompted the company to design a system in which employees use computer-assisted carts that determine the most efficient path to walk within each store and that allow up to
six orders to be filled simultaneously. (For more on high performance in the retail hypermarket industry, see “Consuming Passions.")
3…concentrate their operational integration efforts on the core processes of these algorithms. Operational integration has been both an operations nirvana and a business buzzword for some time, but it is also an important part of what makes the capabilities of a high performer distinctive. While many companies struggle to integrate all of their processes, building ever larger interconnected webs of information sharing (usually with mixed results), high performers focus their integration efforts. They make a substantial investment in integrating only what truly matters to their business algorithm—they don't try to connect everything to everything else.
  Creating the right integration in the snack food business is a good example. One company's value algorithm is focused on freshness, so speed from its kitchens to store shelves is critical. The company achieves this goal through a direct store delivery model that tightly couples production with delivery systems; it also uses delivery employees as sales personnel.
The system makes the consumer happy by putting fresh products
on the shelves and by limiting
out-of-stocks, while also making the company's profit equation
work better. By increasing the speed to the shelf, the company dramatically improves the return
on its production and delivery assets, and nearly eliminates
warehousing costs. Even better,
its model is one competitors have found hard to duplicate.
 Though it is counterintuitive,
to make an algorithm work, some
of the individual parts must deliberately not be optimized. For
example, Spanish clothing retailer Zara creates spare capacity in its production and distribution
systems to meet "velocity goals," which benchmark the speed at which new items are delivered to stores. One way it does this is by producing and shipping goods
in small batches, a seemingly
inefficient way of operating.
However, the company knows
that maintaining velocity is
more important to its overall
business success than achieving incremental cost reductions in
certain operating assets.
One global manufacturer of consumer goods sacrificed optimal product innovation to stay true
to its business algorithm. For example, to avoid disrupting its continuous flow production model, the company modified one new item to make it less complicated
to manufacture—despite the fact that testing revealed this would make customers like the product less. The company recognized
its success does not depend on product innovation; instead,
its business algorithm is based
on delivering high volumes at
the low prices such volume
enables, which, in turn, keeps demand high.
4…continuously improve the algorithm's performance through stretch goals and fast learning loops.
If a company is to succeed in today's highly competitive marketplace, its business algorithms require continuous improvement. The company must quickly move along the learning curve, increasing barriers to competition, improving cost structures, and enhancing the fit of its offerings to customer needs by effectively capturing and acting on customer insights.
High performers achieve this first
by continually setting stretch goals for their organizations, especially for the core processes of their value algorithm, and then by employing fast learning loops—auxiliary processes that quickly transform insights about how to improve into actions that result in improvement. This enables them to achieve what we call "stretch learning"—the ability to gain the knowledge necessary to improve not just incrementally but dramatically.
High performers understand that management cannot dictate the solutions that allow them to achieve true stretch goals. To encourage stretch learning, goals must appear unattainable. Meeting those "impossible" goals can then occur through rapid and creative collaboration involving employees of all levels, outside experts and business partners. Because reaching stretch
goals is about more than simply increasing labor, the goals are
sufficiently aggressive only when they force employees to work smarter, not harder.
An important lesson about stretch goals comes from carmaker Toyota Motor Corporation, long famous
for its continuous improvement activities. Three years ago, its
North American parts operation launched a key change initiative, named Stretch Goals, through
which it sought to save $100 million in distribution costs, to remove $100 million of inventory costs
and to improve customer satisfaction by 50 percent—all at the same time. Management realized that each individual stretch goal could be easily met if other parts of the operation were allowed to suffer—for example, inventory could be reduced if backorders were allowed to rise, at the cost of customer satisfaction. To avoid the pointless frustration of simply squeezing one end of a balloon, Toyota successfully paired its stretch goals—for example, reducing packaging costs and damage—to make real progress. Recently, the company celebrated having only narrowly missed making all three goals.
High performers base their fast learning loops on better measurement processes. UnitedHealth Group, for example, recently created a database that collects information about hospital and physician activities and then links it to evidence-based performance standards. The company uses this database, the largest of
its kind in the healthcare industry,
to evaluate all the components of patient care teams over time and
to rapidly adjust their behavior
to improve care. (For more on the value-creating use of data, see
"From Data to Decision.")
Another reason high performers are able to achieve stretch learning is that they better understand their progress along individual learning curves; just as important, they are better able to move on to new learning curves as the current one flattens—but before
it bottoms out completely. One soft drink manufacturer achieves this by effectively designing new performance improvement programs each time it notices that its measured productivity improvement is slowing, effectively creating a continuous series of step-change improvements in productivity.
5…maintain a balance between evolutionary and revolutionary change as capabilities and algorithms are inevitably adapted. Distinctive capabilities must be dynamic, because at their heart they rely on customer insight, which requires them to be responsive to ever-changing customer needs. Beyond that they must also respond to the demands of environmental change and technology disruption.
High performers are particularly good at both adjusting their algorithm and redefining it when circumstances require them to. The secret for high performers appears
to be in achieving the right balance—knowing when an algorithm must evolve and when change must be more revolutionary. We have seen many companies fail because they gave up on an algorithm too soon; we have seen just as many fail because they held onto an algorithm too long.
One thing high performers do to maintain this right balance is to move quickly and continuously to acquire the new capabilities needed to adapt their algorithm to changing market conditions. One company that has done this successfully is packaged goods manufacturer Kellogg Company. The company recognized that more and more, today's consumers are buying food at convenience stores, fast-food outlets, club stores and other locations beyond supermarkets and grocery stores. It also recognized the need to ensure that sales were not exposed by having only a small number
of key retail buyers. To increase
the variety of its sales outlets, the company purchased Keebler, whose products are widely available in vending machines. Now Kellogg's Nutri-Grain bars, Pop-Tarts and even single-serving cereal bowls
are available at many more places, increasing the consumer reach and market share of these products, while simultaneously avoiding
relying too much on key retailers.
Another way high performers successfully preserve their algorithm
is by refreshing its component capabilities when the algorithm
is faltering but not yet failing.
Consider Domino's Pizza. Rapidly
growing labor costs due to high attrition have increasingly challenged the staffing component
of its successful algorithm of fast, affordable delivered pizza.
Knowing that its emphasis on
selling low-priced pizza precludes increasing wages across the board for its more than 135,000 hourly employees, the company set out
to reduce attrition—at the time running at 158 percent per year—and to recoup the damaging associated costs, estimated at $2,500 per lost employee. By investing in more selective hiring, better training and greater incentive-based compensation for its managers, the company has been able to reduce its attrition to 107 percent per year, bringing
its cost structure back in line and preserving the viability of its successful algorithm.
These are just a few of the many considerations managers have in creating and sustaining distinctive capabilities, and this is but an early and brief synopsis of what we
are learning. But those companies
that can begin to incorporate, or improve, these elements in their
current business activities are well on their way to creating a high-performance business and earning their own marks of distinction.  About the Authors Tim Breene is Accenture's group
chief executive of the Management Consulting capability group and the company's chief strategy officer. He
is also a member of the company's Executive Leadership Team, and he chairs Accenture's Innovation Council. Since joining Accenture in 1995, Mr. Breene has held a number of senior positions, including managing partner
of Accenture Strategic Services and managing partner of the company's global service lines. Mr. Breene is
based in Boston.
Narendra P. Mulani, a partner
in the Accenture Supply Chain Management service line, is the head
of the North American Supply Chain Management practice and the global Consumer and Industrial Supply Chain Management practice. Mr. Mulani, whose industry experience includes electronics and consumer goods, focuses on various aspects of supply chain implementation, such as strategy and execution, as well as on trade
promotion planning and new-product forecasting. He is based in Chicago.
Paul F. Nunes is an executive research fellow at the Accenture Institute for High Performance Business in Wellesley, Massachusetts, where he directs studies of business and marketing strategy. In addition to his frequent contributions to Outlook, his work has appeared regularly in Harvard Business Review as well as in numerous other publications. His most recent book is Mass Affluence: Seven New Rules of Marketing to Today's Consumers (Harvard Business School Press, 2004).
¹ For more on marketing mastery, see "The Best and the Rest," Outlook, October 2004.
² For more on achieving mastery in these capabilities, see "State of the Art," "A Seat at the Table" and "Disturbing the System," Outlook, June 2004, as well as "Supply Chain and the Bottom Line," Outlook, February 2004.
³ “The Mysterious Art and Science of Knowledge-Worker Performance," by Thomas H. Davenport, Robert J. Thomas and Susan Cantrell, Sloan Management Review, Vol. 44, No. 1, Fall 2002.
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