Getting those offerings to the consumer in a way that optimizes value

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  • The Full-Potential Gap
  • Value-Exchange Optimization
  • Closing the Gap
  • Positioning Strategy.
  • Investment Management Processes.
  • Operational Processes.
  • Organizational Alignment.
  • How do you provide value to consumers?
  • How can a company ensure that their offerings deliver customer value?
  • How do we increase the value of our customers?
  • What are the four ways to give customer value?

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Achieving the full profit potential of each customer relationship should be the fundamental goal of every business. The logic is as simple as it is compelling: Profits from customer relationships are the lifeblood of all businesses. And, at the most basic level, these profits can be increased in only three ways. The first is to acquire new customers—to increase the number of people who use a product or service. The second is to enhance the profitability of existing customers—to motivate people to engage in behaviors that generate higher returns. The third is to extend the duration of customer relationships—to maintain those enhanced behaviors for a longer time. Yet the implicit business models that drive decisions in most large companies today do not focus on achieving this full profit potential. Why? Because those models were forged before such a focus was possible.

At several junctures since the industrial era, advances in technology and increasing access to information have fostered the development of new management models. With the emergence of the industrial era in the mid-1800s, for example, companies began to adopt a productivity model. Technological innovation in manufacturing, along with the creation of regional and national distribution channels, enabled organizations to mass-produce products for customers beyond their local markets. As a result, a company’s profitability began to depend on the scale of its operations: its ability to achieve cost-effective production and distribution. Under this model, managers focused on costs and capacity.

By the late 1960s and early 1970s, however, with the rebuilding of postwar commercial infrastructure and the emergence of global competition, capacity began to outstrip demand. It became necessary to compete for customer cash flows by adopting a competitive business model. Using industry and market-share data available for the first time, companies discovered a strong correlation between market-share leadership and profitability. Many managers thus began to focus on achieving the leading market-share positions in their industries.

In the mid-1980s, as the business environment continued to evolve, the quality model was born. Companies started to exploit new capabilities for collecting and using information to compete on the quality of their products and services. Using new continuous-process-improvement techniques, they identified and reduced the costs of rework, inefficiency, and waste. Companies also began to examine the costs incurred by suppliers and customers in an effort to reduce overall systems costs and increase customer satisfaction. Across a range of industries, organizations successfully applying the quality model showed how superior financial performance could be achieved despite inferior market-share positions.

In each era, the prevailing business models accurately depicted the relevant drivers of profitability. But the capabilities necessary to focus directly on maximizing profitability from customer relationships were simply not in place. Today, using the information and technology tools currently available, companies can link their investments in customer relationships directly to the returns those customers generate. For example, companies can more easily identify the customers that have the highest profit-improvement potential, use databases to understand the specific needs of those subsegments, and take advantage of flexible manufacturing and delivery to provide cost-effective offerings tailored to each subsegment—offerings such as product features, price discounts, service arrangements, and purchase warranties. They can integrate and orient every function toward maximizing customer profitability. In other words, companies can now optimize what we call the value exchange: the relationship between the financial investment a company makes in particular customer relationships and the return that customers generate by the specific way they choose to respond to the company’s offering.

Value exchange as a concept is not new. Early adopters of each preceeding management model earned superior returns because they were, in fact, improving the value exchanges with their target customers. Those improvements, however, were only by-products of efforts to increase productivity, create product differentiation, or achieve higher quality. Adopting value exchange as a direct focus—operating a company under a value-exchange model—is only now possible.

Companies that embrace the principles of value exchange are operating on an entirely new playing field.

Companies embracing the principles of value exchange are operating on an entirely new playing field. These organizations don’t evaluate their performance based on comparisons with last year’s figures or with their competitors. They don’t focus their time and money on abstract metrics such as market share, quality indices, or customer satisfaction. And they don’t use the power of information technology simply to turbocharge their marketing functions. Instead, they define their target customer base, quantify the current and the full-potential value of these relationships, and commit the entire company to closing the gap between the two.

The Full-Potential Gap

Even using conservative estimates, the gap between most companies’ current and full-potential performance is enormous. Think back to the three ways companies increase the profitability of customer relationships, and consider the following questions:

The gap between most companies’ current performance and their full-potential performance is enormous.

1. What percentage of your target customers do you currently have? How many could you have?

2. How do your customers currently behave? What if they exhibited the ideal behavior profile (for instance, bought all lines, used them exclusively, and paid full price)?

3. How long on average do your customers remain with the company? What if they remained customers for life?

Work done by a leading Canadian grocery store chain provides a case in point. Recently, in order to understand and quantify its full-potential gap, the company analyzed the economics of the customer base of a typical store. (The store operates in an area with around 15,000 households, generates annual revenues of $25 million, and realizes an operating profit margin of 2%.)

First, the company segmented the customer base surrounding the store into three categories: primary shoppers (those who give the store 80% or more of their grocery business); secondary shoppers (those who spend more than 10% but less than 50% of their grocery budget at the store); and nonshoppers. The analysis showed that the store’s primary and secondary shoppers represented less than one-half of the shoppers in the store’s trade area.

Second, the company calculated the impact on the store’s profitability of small improvements in the behavior profiles of existing customers. Given the fixed cost structure of a grocery store, the contribution margin from each additional dollar spent by a customer can earn ten times the store’s net profit margin. Thus, the company found that even small improvements in any one of many customer behaviors led to very significant profitability gains. Expanding the customer base by 2% with primary shoppers, for example, would increase the store’s profitability by more than 45%. Converting just 200 secondary customers into primary customers would increase profitability by more than 20%. Selling one more produce item to every customer would increase profitability by more than 40%. Persuading every customer to substitute two store-brand items for two national-brand items each time they visited the store would increase profitability by 55%. Obviously, generating several of these behaviors in combination would dramatically increase the profitability of the store’s existing customer relationships.

Third, the company examined the average duration of its customer relationships. The research suggested an annual defection rate in excess of 20%, implying an expected duration of less than five years. Reducing this annual defection rate to 10% would increase the expected duration to ten years.

The analysis showed that each of these three key profit drivers independently represented a major opportunity for profit improvement. Multiplied together, however, even small improvements in all three areas would mean enormous increases in store profitability. For example, expanding the customer base by 2% with new primary customers and substituting two store brand items for two national brand items for each customer visit and reducing the customer defection rate by 5% would increase the future gross profits by nearly 300%.

Rather than focusing directly on these opportunities, though, the company, like most other organizations, had been paying attention to more traditional objectives, such as productivity, market share, and quality. As a result, it had overlooked the possibility of closing this full-potential gap by optimizing customer value exchanges. Although secondary shoppers, for example, had the potential to generate much more revenue, the company’s investment in those relationships—which included its hours of operation, efforts to keep the store clean, and coupon discounts—was obviously not sufficient to entice these customers to shop more exclusively at the store. In the same way, the company was not offering optimal exchanges to its infrequent shoppers or to prospective customers.

A similar analysis across a range of businesses will reveal the same findings: Companies serve a fraction of their available target customers; the behaviors of existing customers are not close to ideal; and a surprising number of customer relationships do not last nearly as long as they could. The full-potential gap in most companies is usually enormous because the value exchanges are less than optimal.

Value-Exchange Optimization

A handful of pioneers across a range of industries have begun to exploit the profit potential of value-exchange optimization. Take First USA, a financial services company based in Dallas, Texas. First USA is one of the country’s fastest-growing issuers of Visa and MasterCard. Since its founding a decade ago, the company has grown at more than 40% per year. It has now amassed more than $12 billion in total receivables, ranking fifth in the industry. Using the power of information technology, the company has figured out how to focus on hundreds of different target customer segments simultaneously—with offerings that are carefully tailored to each segment’s individual needs and potential returns. First USA currently extends more than 750 different credit card offers. Each presents a different combination of variables: the annual interest rate, the annual fee, the credit limit, and add-on features such as collision insurance. Customers no longer pay for or receive benefits that they don’t value—the company investment in each relationship is carefully designed through disciplined testing to generate the optimal value exchange.

Union Pacific is an equally compelling example. The company has applied the principles of value exchange to the railroad business by creating cross-functional teams and making them responsible for designing service offerings for larger customers. These teams analyze the full-potential gap for each customer; they understand which changes in customer behavior will improve returns. Furthermore, they have the authority to act. No element of an offering—the number of rail cars, train schedules, rates, or transit times—is sacred. The teams use any of these variables as needed to maximize the long-term value of relationships with customers that have the potential to generate high returns.

Value-exchange optimization is possible in any kind of company, although its implementation must be approached differently depending on a given company’s situation. Grocery retailing provides a good example of an industry beginning to use emerging data and technology to close the full-potential gap. Many grocers are encouraging customers to present an identification card at check-out in order to track and analyze their behaviors. Over time, as managers identify customer segments with different behavior profiles, they can create special offerings targeted to create profit-enhancing behavior changes in high-potential segments. For example, primary shoppers who buy large amounts of food items but no health and beauty aids (HBA) might be given a packet of computer-generated coupons, printed specifically for them, offering 30% discounts on store-brand HBA items. By industry norms, the offer is radical: A 30% discount equals the product’s entire gross margin. But the investment is sound. If it stimulates even small increases in the customer’s ongoing HBA purchases, it can generate significant increases in the value of the relationship.

Thanks to advances in database systems and mapping technology, grocery stores also can now identify high-potential customers that they are not serving and thus invest in value exchanges designed to win their business. For years, grocers used crude data on numbers-of-households-served to measure market share. Today market share is becoming less relevant as stores can more closely analyze their own customer prospects. For instance, grocers can record the license plates of cars parked in the parking lots of rival stores. They can then feed that information into a commercially available database that links license plates with street addresses, zip codes, and even finer-grained information on geography—right down to a portion of a specific block on a particular side of the street. A computer program generates easy-to-read, color-coded neighborhood maps that depict individual households and their shopping patterns.

As a result, grocers can devise offerings to win new customers almost on a street-by-street basis. Today households that a grocer has targeted as high-potential customers (based on an analysis of income, family size, and proximity to the store) are sometimes offered a cash or free-product incentive worth up to $75 for visiting a store. Again, offers like this one may seem radical in an industry with minimal marketing budgets and a net profit margin of only a few percentage points: When one includes the cost of the market research and the communications efforts needed to find and reach these customers, the real cost of the enhanced offer is actually more than $100 per new shopper acquired. Yet this investment makes enormous sense when one considers that a new relationship with a typical household can increase store profitability by more than $500 per year. Even if only a portion of the households receiving this offer remains with the store, these acquisition investments pay significant returns.

The precise terms of the value exchanges designed by these innovators are not important. What is important is the principle they validate. Rather than trying to improve performance by focusing on subjective indices such as customer satisfaction and quality, these companies are designing explicit exchanges based on the hard-nosed economics of actual customer behavior.

An important clarification: Examples such as First USA, Union Pacific, and the grocer do not necessarily imply a one-to-one future in which companies must design a unique offering for every single possible customer. Companies that learn to maximize their value exchanges figure out the appropriate numbers and types of customer segments for their organizations’ situation. They only go after additional segments if the potential profit increase is sufficient to justify the added investment. These companies also identify the optimal degree of variation in a given offer by carefully assessing the returns earned on each new exchange, including the hidden costs of increased complexity. In some companies, value-exchange optimization may result in fewer segments and offerings. Rather than tailoring for the sake of tailoring, the focus is on finding the degree of segmentation and offer variation that maximizes profitability.

Closing the Gap

Closing the full-potential gap requires more than simply taking a marketing function designed around an outdated business model and turbocharging it with information and technology. It means designing and installing an entirely new business system based on value exchange. That, in turn, means rethinking four basic elements common to all business models: positioning strategy, investment management, operational processes, and organizational alignment. Let’s examine how value-exchange innovators are approaching each of these four areas.

Positioning Strategy.

A company cannot begin to optimize its value exchanges without clear answers to these questions: What need is the company trying to serve? Who is in the target customer universe? What is the ideal customer behavior profile? How large is the full-potential gap? Does the company have the elements of the core offerings necessary to achieve that full potential?

Many companies rely on imprecise concepts such as “industries” or “available market” to define the customers they intend to serve. In order to define and understand full-potential performance, however, a company must specify and analyze target customer segments in far greater detail. Such analysis goes beyond understanding who buys what to understanding the full range of behaviors that have an impact on profitability. The company must examine behaviors such as share of use (the percent of a customer’s total budget for an item or service that the customer spends with the company); costs of service (such as credit, warranty, and customer service); price paid (level of discounting and incentives); and referrals (whether or not the customer has referred other customers to the business). Once the company has defined this ideal behavior profile, it can calculate the full potential of its target customers and prospect universe. Using this economic analysis, senior managers can identify the segments with the highest profit potential. Then they can turn their attention to figuring out the needs that must be met in order to achieve the full profit potential of these segments.

Once a company has defined the ideal behavior profile, it can calculate the full potential of its target customers and prospect universe.

Armed with this information, the company must then be able to provide the kinds of offerings it needs to optimize the value exchanges with each high-potential segment. A high-cost grocer, for example, cannot expect to achieve full-potential performance until it can offer competitively priced products, no matter how powerful its insights are into the full-potential-behavior profiles of target customer segments. Implementation of the model, therefore, must begin with a clear positioning strategy that defines both the full-potential opportunities (target customers, needs, behaviors, and values) and the investments (core-offering elements and infrastructure) required to achieve this potential.

Even though Taco Bell is not in an industry in which companies can afford to gather data on individual customers, the approach that management used to reposition this division of PepsiCo provides a classic illustration of the principles of value exchange. Until the late 1980s, Taco Bell had a generic mass-market orientation. Fast food has historically meant convenient, inexpensive, reasonably satisfying meals and snacks. So, like many other such organizations, Taco Bell had defined its target market only by broad demographic and psychographic categories: high-frequency fast-food users (HFFFUs) mostly between the ages of 13 and 24. Acting on a belief that adding new items to its menu was the way to appeal to this wide range of consumers had made Taco Bell’s operational systems increasingly complex.

In the late 1980s, president and CEO John Martin decided to conduct a more refined study of Taco Bell’s customer base. Within the previously defined broad HFFFU market, Taco Bell identified three key segments—people who visit Taco Bell at least once a week, people who visit as little as once a month, and people who never patronize Taco Bell because they don’t like Mexican food.

Of these three segments, two distinct groups emerged as high-potential customers: penny pinchers—18 to 24 year olds who use Taco Bell frequently but narrowly, spending a limited amount for lunch and buying an average of three to four products from the lowest-priced offerings; and speed freaks—generally harried, two-income couples or parents concerned with quick service and ease of use along with the taste and quality of the food, who visit Taco Bell less frequently than the penny pinchers and also use it narrowly. Speed freaks generally purchase higher-priced menu items than penny pinchers; they are less concerned with price than they are with convenience.

Taco Bell managers found that these two groups of HFFFUs represented more than 70% of the company’s volume even though they made up less than 30% of the customer base. Based on that discovery, the company decided to reorient Taco Bell and focus explicitly on leveraging those relationships. In other words, Taco Bell repositioned its entire organization, down to redefining its business concept and reengineering its core processes, to provide what the speed freaks and penny pinchers wanted.

Using its new understanding of the needs of these segments, the company created the FACT concept (fast food Fast, orders Accurate, in a Clean environment, at the right Temperature) and streamlined its menu. To attract speed freaks, Taco Bell initiated a major speed-of-service program that transformed the entire production model from an on-demand approach to an inventory-based approach. This initiative resulted in a 54% increase in peak-hour capacity and a 71% reduction in waiting times. To attract new target customers and provide easier access for existing customers, the company also de-emphasized store-based production capabilities and invested in the necessary multiple (and flexible) channels of distribution. For example, it began to use kiosks, carts, and counters in addition to the traditional restaurants as points of access. As a result, Taco Bell established a presence in such locations as college cafeterias, malls, airports, and gas stations. To attract penny pinchers, the company shifted its core menu offerings from higher-priced items to 59-cent, 79-cent, and 99-cent items, reducing its prices in 1988 to 25% below what they had been in 1982.

Taco Bell’s repositioning efforts were extremely successful. Sales increased from $1.6 billion in 1988 to $3.9 billion in 1993. Earnings rose from $82 million in 1988 to $253 million in 1993. In 1994, the company’s sales totaled $4.5 billion and earnings topped $273 million. Today the challenge for Taco Bell continues to be one of closing the full-potential gap with existing customers while at the same time attempting to attract new high-potential segments. The company’s new Border Light menu line, for example, is aimed at attracting a new customer segment interested in more healthful foods.

Investment Management Processes.

Once the broad positioning strategy is set and the core value-exchange elements are in place, the next challenge is to design an investment process for optimizing the value exchanges. This step raises new questions: How do you identify the subsegments with the least optimized exchanges? What process should be used to design, test, and improve continuously the value exchanges required to close the full-potential gap?

Every company today has an implicit process in place for configuring customer value exchanges: Each customer receives a certain level and type of investment and generates a corresponding return. However, most senior managers have never explicitly studied these exchanges or the mechanism that drives their design. What’s more, the process is invariably difficult to document. It is a by-product of a variety of ad-hoc programs and procedures designed for other purposes that have built up over decades. Furthermore, the people who design the exchanges are generally spread across functional silos that seldom communicate or coordinate; they work individually to maximize the efficiency of their functions rather than collaboratively to optimize the overall design or improve the delivery of the exchanges.

Companies today must begin to use a disciplined, cross-functional process to configure the offerings required by their target customers. Given an ever-changing competitive environment, such a process is the only way to manage the enormous number of trade-offs and revisions required to achieve optimal value exchanges continuously.

AT&T’s new approach to optimizing its value exchanges with residential long-distance-service prospects offers a compelling example of a company making the shift to a disciplined investment process. Before the 1990s, AT&T spent hundreds of millions of dollars per year trying to attract prospects to use its residential long-distance service. But, because AT&T lacked the systems and data needed to segment prospective customers and customize offerings, most prospects received similar offerings (such as a discount offer, a message, or communication materials) regardless of their specific needs or annual revenue. Working across marketing, finance, legal, field operations, data processing, and advertising departments also made it slow and difficult to design and field a variety of offerings. Furthermore, AT&T, like many companies, lacked the necessary infrastructure (for instance, the database, application tools, and costing systems) to use hard-headed economic analysis to understand and improve their prospect relationship investments. As a result, AT&T sent out millions of pieces of largely undifferentiated direct mail solicitations several times a year urging prospects to switch carriers. As in most efforts to change customer behavior, less than 5% of the time and money invested resulted in prospect conversion.

Over the past four years, however, AT&T has transformed both the offerings it designs for residential prospects and the way it interacts with prospects. The company’s prospect solicitations are no longer simply onetime transactions that are evaluated as independent events. Instead, AT&T employs highly refined subsegment investment strategies.

AT&T’s solicitations aren’t onetime transactions treated as independent events but are refined subsegment investment strategies.

Today, for example, AT&T managers supplement available market data with predictive models to determine which prospect segments and corresponding value exchanges are likely to produce the greatest return on investment. Then, for each high-priority segment, the company identifies the reasons why a prospect might not sign on with AT&T’s residential service, selects those prospects that are most likely to leave a competitor’s service and sign on with AT&T, and designs—via disciplined testing—offers that will entice those prospects to AT&T for the least possible investment. AT&T now designs and delivers hundreds of tailored prospect offerings. And the process doesn’t stop there. Say, for example, that a high-potential customer has recently left AT&T’s service. Cross-functional teams now preplan a series of up to seven phone and mail communications with varying messages and incentives. The first step in the strategy is to send the defector a letter offering a basic incentive to switch back. If the prospect does not accept the offer, the company will call offering a larger incentive. If the prospect still does not accept, AT&T will ask a few basic questions about the service currently used. AT&T will then record the new information and use it to tailor different value exchanges designed to overcome the barriers in each different customer subsegment. The return on investment of each exchange is determined by carefully forecasting the economic potential of the particular prospect relationship against the total cost of the investment strategy that is necessary to win the prospect back.

AT&T also carefully analyzes the yield loss on each prospect’s value exchange; that is, it calculates the percentage of prospects who do not accept a revised exchange. It then calls these prospects and conducts interviews to identify the reasons for the ineffective exchange. Through this contact, more information about the prospect is entered into the database to be analyzed and used later to design a more effective exchange earning a higher return on investment. For example, when AT&T found that Hispanic prospects did not respond well to offers communicated in English, the company tested and identified higher ROI strategies using Spanish-speaking telephone representatives and literature printed in Spanish. By making sure that the information it obtains through these efforts is not lost—that is, by creating a feedback loop so that the company learns from each encounter with a prospect—AT&T can continuously improve its value exchanges. It can also continuously refine the allocation of its investment among hundreds of unique customer-prospect segments. Rather than being established up front, the precise number and type of customer segments that merit separate treatment become by-products of this continuous improvement process.

Targeting Hispanic prospects, AT&T identified higher ROI strategies using Spanish-speaking telephone representatives.

The end result? Armed with its new competency, AT&T’s prospect investments have become profoundly more productive. The company attracts seven times as many customers as it did in 1990. In 1994 alone, it saw a net gain of more than 1.2 million accounts while reducing the cost-per-acquisition by more than $3. Moreover, 50% (versus 5% in 1990) of the dollars invested in attracting prospects now perform; that is, they persuade the prospect customers to sign on.

Value-exchange optimization is much more than state-of-the-art marketing. It is a cross-functionally integrated learning process. Investments in application tools, database technologies, and management systems supporting this process were not cobbled together. They were custom-designed and integrated to create a proprietary capability.

Operational Processes.

Identifying the optimal value exchanges alone is not sufficient. A company must be able to deliver them efficiently and effectively to the customer. This next step raises a number of key questions: What overall configuration of processes is needed to deliver optimal value exchanges? How must individual processes be engineered to connect with this overall delivery capability? How can a company manage the trade-offs between adding value exchange and the costs of operational complexity?

Most companies strive to design world-class operational processes and then figure out the kinds of value exchanges that they are able to deliver. But in order to achieve full-potential performance, companies must reverse those actions. They must begin by identifying the optimal value exchanges and then work backwards to design the kinds of processes needed to deliver them. By allocating costs carefully, companies can ensure that any additional cost of increased operational complexity is justified by increased relationship profitability.

Consider how one U.S. airline is beginning to align its core operational processes to permit coordinated cross-functional value-exchange delivery. Providing the value exchange necessary to get the full potential of a high-potential customer—say, a frequent flier who flies on several airlines—requires a coordinated effort among core airline functions. Eventually, functions including marketing, reservations, airport, inflight, baggage handling, and travel agent services must all be coordinated to provide the customer with the optimal exchange. Consider how this airline approached the first phase of the redesign, although it is only partly through the transition. It reengineered its reservation center processes to reduce costs and at the same time contribute to the development of a cross-functional set of exchange capabilities.

Prior to the reengineering effort, an average call in a typical reservation center cost more than $3 to handle. Because the centers received about 80 million calls per year, total costs ran to about $250 million, with labor costs accounting for more than 80% of that total. Only one call in ten resulted in a booking; that is, only 10% of the callers made a reservation to buy a ticket at a later time. Only 70% of callers making bookings actually followed through and bought tickets through the airline. Many callers, in fact, ended up buying their tickets through a travel agent—sometimes on the airline they originally called for information and sometimes on a rival airline. Therefore, on each call, there was only a 7% chance of selling a $150 ticket, making the average call worth about $10 in revenue. Obviously, even small changes in customer behavior had significant profit implications. If the reservation agent could get the caller to make a booking, the expected value of the initial call would increase tenfold. And, if the agent were also able to sell the ticket while on the phone, the expected value would increase by another 40%.

The airline decided that a process-redesign effort concentrating on cost reduction alone was not the answer. In fact, in many centers, previous cost-cutting efforts had contributed to reduced returns. Fewer staff-people were available to answer a growing number of inquiries, which caused customer dissatisfaction because of delays in service. Furthermore, agents found it difficult to stay on top of the increasingly complex fare structures, restrictions, and routes, limiting their ability to offer customers the kinds of solutions that would bring both buyer and seller high value.

In the initial redesign, the company focused on improving its ability to tailor the level and type of investment in each reservation-center caller in order to maximize the likely return. The company found, for example, that about half the customers calling the centers were interested in making reservations; they were potential revenue generators. The other half already had reservations and wanted information on such things as seat assignments, food, and flight requirements; they were not revenue generators. To distinguish between the two groups, the company installed a system so that callers could choose by pressing numbers on their touch-tone phones to indicate whether they wanted reservations or information. In that way, they would be segmented automatically. They could then be sorted into different treatment streams according to their potential value.

The airline next divided its reservation agents into two groups: the sales group and the service group. It gave each group specific goals related to the kinds of customers they handled. In this way, the agents would deal with only one broad type of customer situation, thereby developing an expertise at fielding a certain kind of call. For example, the company developed scripts for the sales group to ensure that the agents provided the optimal offering to the customer based on the profile that appeared when the caller came on the line. The agents then underwent training using the customized scripts in order to increase their effectiveness. Because these calls are of high value, the company could relax its call-time standards and allow the agents to spend more time on a particular call.

In the initial piloting of the reengineered process, the company achieved dramatic profit improvements. It increased revenue-generating calls by 100% and the average revenue on these calls by 50%. At the same time, the company cut the average cost per call by 35%. Multiplied together, achieving these three goals produced more than a 400% increase in reservation-center profit contribution: an improvement that was orders of magnitude greater than the amount that would have been obtained under a pure cost-reduction approach.

Under the value-exchange model, operational excellence becomes the ability to deliver the targeted value exchange efficiently and effectively. The transition to an integrated set of value-exchange-delivery processes must be approached in a coordinated but phased manner. With a clear overall vision of the desired goal, short-term process-reengineering efforts can have a potentially large impact.

Organizational Alignment.

In most corporate change programs, it is easier to design new operating processes and technology tools than to foster the appropriate attitudes and behaviors in the people who are necessary to make them work. How can a company motivate employees at every level to embrace the skills and attitudes necessary to meet the requirements of these new value-exchange optimization and delivery processes?

The challenge of realigning employee behavior closely parallels the challenge of achieving full-potential customer behaviors. Not surprisingly, the key to effective organizational alignment is to apply the same value-exchange principles.

The challenge of realigning employee behavior closely parallels the challenge of realigning customer behavior.

Managers in most organizations today do not think about managing employees in full-potential terms. Indeed, most top-level managers cannot answer full-potential questions when the objects of inquiry are their employees rather than their customers: What percentage of my workforce is made up of “target” (in other words, high-potential) employees? What is their ideal behavior profile? How close are they to that profile? How close are employees to the ideal tenure?

We believe that the employee full-potential gap in most organizations is as significant as the customer full-potential gap. Consider a recent study in the Journal of Applied Psychology, which examined productivity differences between the top 1% of all performers across a range of organizations and average performers in these same organizations (John E. Hunter, et. al., “Individual Differences in Output Variability as a Function of Job Complexity,” Volume 75, 1990). For low-complexity jobs (frontline workers in a fast-food restaurant), top-level performers were 50% more productive than average performers. For medium-complexity jobs (production workers in a high-tech factory), top-level performers were 85% more productive than average performers. For high-complexity jobs (an associate in an investment bank), top-level performers were 125% more productive than average performers. The gap between top-level performers and those in the bottom 1% was even more striking. For low-complexity jobs, top-level performers were 300% more productive than bottom-level performers. For medium-complexity jobs, top-level performers were 1,200% more productive than bottom-level performers. For high-complexity jobs, the differences were so profound they were unmeasurable.

Companies are ill-prepared to close such a gap. How many companies can identify with precision the core processes and related employee skills and behaviors needed to design and deliver the required customer value exchanges? How many companies explicitly identify the barriers to achieving full-potential employee behaviors and then devise “offerings” (such as pay, training, and promotion) to overcome those barriers? How many companies “segment” their workforce so that they can focus investment on motivating the kinds of behavior changes that will yield the highest returns?

Most human resource systems are profoundly incapable of addressing such critical questions. Like their customer counterparts, existing HR processes are ineffective and inefficient because they invest in employee relationships with one-size-fits-all offerings rather than with tailored value exchanges that recognize the fundamentally different behavior profiles, needs, motivations, and aspirations of their employees.

Human resource processes invest in employee relationships with uniform offerings instead of tailored value exchanges.

Federal Express offers a good example of how one company is applying value-exchange principles to align employees as it implements a broad customer value-exchange-optimization process. Several years ago, Federal Express won the Baldrige Award and also received a Marketing Hall of Fame Award from the American Marketing Association. But despite these honors, the company did not sit on its laurels; it set out to improve further its customer-relationship management capabilities.

Federal Express recognized that its customer value exchanges were being designed and delivered by many different people who did not communicate with one another: Direct mail efforts came from the marketing staff; a pricing group set prices; field sales staff made their calls; customer service representatives answered the phone; and the finance department handled credit and collections. After in-market pilot tests showed that installing a customer value-exchange process could significantly increase profits, the company began a phased implementation.

First, FedEx created a team made up of representatives from across the relevant functional groups. The team had the job of defining the value-exchange-optimization process that could be used to manage customer segments. This, in turn, required identifying specific work tasks and associated roles and responsibilities. The team also identified the technology tools that would be needed to enable this operational work flow. Finally, it divided the FedEx customer base into more than a dozen initial target segments that could be managed by dedicated segment teams.

At that point, FedEx knew exactly what kind of employee behaviors it needed to operate the new process. So, the company proceeded to identify the employee value exchanges necessary to engender those behaviors. To start, FedEx assessed its employees’ competencies against the new process requirements. Then it developed a specific investment strategy designed to align the teams fully around the requisite new behaviors. The investments took a variety of forms, but they were all conceived and executed in an integrated fashion. FedEx created new job descriptions consistent with the newly defined work flows. It established new performance metrics, performance evaluation systems, and recognition and reward mechanisms. It defined new career paths. It recruited individuals from the outside as necessary to fill positions requiring new specialized skills. The company also invested in comprehensive skills training to ensure a high level of segment team proficiency. For example, a new segment-analyst position was created to support the financial management of the segment investment programs. These analysts underwent an intensive five-day training program to ensure that they had the necessary technical skills and essential understanding of their process-specific tasks. Because market tests had proven that millions of dollars could hinge on employee effectiveness, FedEx management viewed the HR initiatives not as costs but as investments with very high and measurable returns.

Today the cross-functional teams are demonstrating the behaviors necessary to implement this crucial process and working with high levels of proficiency, commitment, and morale.

Redesigning any one element of a business system poses real challenges; tackling four elements represents a fundamental transformation. But through careful phased planning and an understanding of relevant leading practices, many companies have successfully navigated historic transformations with low risk and high returns.

In industry after industry, the opportunity today is just as clear. It is now possible for companies to focus directly on achieving the full potential of customer relationships. Doing so will require executives to abandon outdated management models. But, as with prior shifts in management thinking, those who act early will reap disproportionate rewards.

A version of this article appeared in the September–October 1995 issue of Harvard Business Review.

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