Atypically Early Customer Research

About four years before introducing the Cayenne and Panamera, Porsche conducted initial research, including high-level telephone surveys with potential customers in its most important markets.

Porsche's surveys confirmed what the company hoped they would: Customers would view a Porsche SUV and family sedan to be in keeping with the brand's image, and they wouldn't detract from its reputation for building leading sports cars. Just as important, the customer surveys provided detailed input that Porsche used to fine-tune each concept. For example, the Panamera's potential customers wanted a full-size sedan with plenty of trunk space, but with 100 percent Porsche (sportiness) DNA.

The customer surveys also helped Porsche find the proper price positioning for the two cars—that is, the price range, not the exact price point. For the Cayenne, the survey told Porsche it could charge a significant premium over other SUVs. For the Panamera, Porsche learned it could position the car at the upper luxury segment level (e.g. Mercedes S-Class) and thus significantly above the Mercedes CLS level (a four-door Mercedes coupe about the size of the Panamera, but with a 15 percent lower price than the S-Class). This was welcome news.

Finally, each survey gave Porsche important initial insights into both cars' market potentials and key segments. For example, many people liked the Porsche brand and would love owning a 911 sports car, but they couldn't afford it as an additional, just-for-fun car. But with the Cayenne or Panamera, a Porsche fan's everyday family car could be a Porsche. Moreover, Porsche 911 owners would not have to drive another brand's cars for family errands; they could make every vehicle in their garage a Porsche.

But Porsche is also a brand that polarizes consumers. From its surveys, Porsche found it had a customer segment that would never buy an SUV or sedan from Porsche, no matter how great the vehicle. With this information, Porsche had an initial quantitative sense of the market potential for Cayenne and Panamera. The survey data became crucial inputs to each vehicle's first business case.

Deciding Which Features Should Be In or Out

With initial research showing Porsche had real opportunities with an SUV and a four-door family sedan, the next step was to determine exactly what had to be in those vehicles. The company knows designing a viable vehicle means giving customers the features they want, not what Porsche wants. For Cayenne and Panamera, it conducted extensive value analysis (as discussed in Chapter 4) to determine the features for each car.

Porsche did its value analysis in so-called “car clinics” in exhibition halls, where it rented competitors' cars and presented them alongside the new Porsche models. It then invited potential customers to evaluate the vehicles.

Of course, part of what Porsche asked these potential customers about was their willingness to pay (WTP) for the cars. This, too, went above and beyond the industry's typical customer research. Most automakers only gather customer perceptions, asking such questions as, “Do you like the car overall, the front, the interior?” or “How do you like this feature?” and “Would you be interested to buy?” But they typically don't take the next crucial step and ask the WTP questions (as we explored in Chapter 4).

This information was indispensable to Porsche. It gave the firm specific price ranges for the Cayenne and Panamera. And by gauging customers' reactions to each proposed feature, the company had the data to make sure each car's design and product configuration were on target.

No feature is sacrosanct at Porsche; even the smallest features are carefully considered. For example, Porsche initially thought small hidden cup holders in the Panamera dashboard would be sufficient. But the research showed customers wanted much more. Managers decided to not only include the dashboard cup holders, but also to invest in an expensive redesign of the middle console to do full justice to what customers said they valued, wanted, and were willing to pay for.

A crucial design and product configuration decision for Porsche was to determine which features should not go into the Cayenne and Panamera. Here again, Porsche breaks from the pack. At many other automakers, arguments abound over why certain features shouldn't be added to a car. At Porsche, the burden of proof is always on why a feature should be included. Porsche puts every feature on trial. The argument that “everybody else does it in this segment” does not fly.

A key step in this process is deciding which features will be standard equipment and which will be options. What matters most is customers' value and WTP for each and every feature. If nearly all customers have a relatively high WTP for a certain feature, Porsche makes it standard in the vehicle. If only some customers will pay, Porsche makes it an option.

Porsche conducts this rigorous analysis on every one of its new car models. Consequently, its cars have some of the longest option lists of any automaker. But Porsche also makes more money from those options than most rivals do. And by turning so many features into options, the company avoids building an overloaded, overpriced base product.

At Porsche, the process of deciding which features are in or out is long and sometimes cumbersome. However, it enables the company to avoid costly feature mistakes that rivals make.

Creating a “Living” Business Case with True Price Optimization

For the Cayenne and Panamera, Porsche's business case included a market simulation model of the entire relevant market for the vehicles. Each business case showcased Porsche's customer WTP data, value analysis of features, and price elasticity. All of this was based on detailed research in the United States, Europe, Asia-Pacific, and all available market data (market size, sales volume of competitors, and so on).

Using its market simulation model, Porsche had a firm idea of consumer demand for the cars at each price point. (That should sound familiar; it's the price elasticity/demand curve we explored in Chapter 8.)

In this exercise, Porsche did not consider the Cayenne's impact in isolation. It also looked at the product's effect on the company as a whole: additional revenue, profit, and related factors. Porsche carefully analyzed whether new products would cannibalize sales of other Porsche cars. It only approved new products if they increased Porsche's total revenue. In the cases of the Cayenne and the Panamera, the company found cannibalization would be relatively low.

That holistic approach is rare in the auto industry, a business in which the number of car models has exploded since the 1990s—even though every market but China has shown little growth. The lineups of the major automakers are extensive. As such, Porsche's competitors are weighted down with car models that cannibalize sales of their other models. But for Porsche, adding new products that don't boost overall revenue is, as they say in Germany, verboten.

Porsche's business cases for the Cayenne and Panamera are living, continually updated documents. The company even revisits a business case after a vehicle's launch to check the accuracy of the sales forecast and capture lessons for the next new-product development process.

Appealing to the Early Adopters: Porsche's Skimming Strategy

From its customer research, Porsche knew its new SUV and family sedan would stir high interest. Potential customers had told Porsche they had a high WTP for both the new cars; they saw real value in them. Therefore, for the Cayenne and later the Panamera, Porsche initially came to market with only the premium eight-cylinder engine models. The company waited a year before rolling out less expensive six-cylinder models.

That allowed Porsche to skim the cream of its market segment—the customers who wanted to be the first on their block to own a sporty SUV or family sedan from Porsche. Those customers had to buy the higher-priced (and higher-margin) models, even if they didn't value an eight-cylinder engine.

Porsche's C-Suite Task: Planting New-Product Monetization into the Company's DNA

Porsche's top managers, right up to the CEO and the board, drove the “design the product around the price” innovation approach. Through their conversations and their actions, Porsche's C-suite has infused the principle into the company's DNA.

The company has long referred to its DNA as “The Porsche Principle.” This broader guiding philosophy is to “always get the most out of everything…to translate performance into speed—and success—in the most intelligent way possible.” But to make monetizing innovation part of that philosophy, Porsche's top executives knew they constantly had to lead by example.

How did they do that? When the firm's product developers started the Cayenne project, the C-suite rented and test drove rivals' cars to gain firsthand knowledge about their road performance.

In its car clinics, focus groups, and other research activities, Porsche's top executives eagerly spoke to participants to gather feedback. They also intensively watched focus group videos and returned to the product development teams with specific questions. These actions sent an inarguable message to the teams: This exercise is important.

That kind of top-level interest and support, for customer research on a new car's value and customers' WTP for it, is rare among the world's automakers—and we know most of them. Top management also made sure that all relevant functions—sales, marketing, product, strategy, after sales, market intelligence, finance, controlling etc.—were represented in the new product team. With that approach, all monetization aspects were evaluated holistically, if possible in a quantitative way. Decisions which would only support sub-goals of specific functions but contradict the overall Porsche goal were avoided.

Finally, the teams had to present the monetization strategies for the new Cayenne and Panamera to the full board. That, too, created a very clear message to Porsche's product development teams—the board recognized the importance of the new Cayenne and Panamera and their monetization strategies. Needless to say, it also helped the teams get the time and money necessary to design and price those products right.

And right they were: By 2014, Porsche was selling more than twice as many nonsports cars (about 135,000 Cayennes, Panameras, and a newer SUV called the Macan) as the sports cars and roadsters it's been identified with for nearly 70 years.

Porsche is a study in how a company can transform itself through disciplined innovation. It succeeded by making bigger, bolder new product decisions based on painstaking upfront work on exactly what customers needed, valued, and were willing to pay for.

Designing Products Based on the “Members First Principle”

From day one, LinkedIn held an unwavering focus on delivering value to members. The benefits of this focus are evident in the company's success. Here are but a few examples of products that have fueled LinkedIn's fortunes, starting with a product that allows members to send private e-mails through the LinkedIn platform.

Instituting a Rigorous Monetization Process

So how has LinkedIn gone from zero to $3 billion in revenue in a dozen years? The answer is nicely summed up by Andrew Freed, the head of Talent Solutions Marketing: “LinkedIn has put in place a rigorous process for monetizing innovation and has embedded that into the core philosophy and approach to bringing products to market.”

Josh Gold, LinkedIn's global head of pricing strategy, describes how the company's new process works for monetizing innovations this way:

At LinkedIn we typically use a multi-step, iterative process to test new concepts with customers. As our confidence in the product's potential increases, we invest more time and energy into optimizing our go-to-market monetization strategy.

More specifically the typical process steps are as follows:

• Hypothesis development: Innovation teams start with identifying the white space. They ask questions like “Where can we create and deliver differentiated value?” and “Which markets are underserved?”
• Internal refinement: A cross-functional group of internal experts comes together to refine and pressure test the hypotheses. These discussions bring together teams like marketing, sales, pricing, and product design.
• Initial customer validation: The team then starts validating product-market fit, perceived value, and WTP with target markets. Methods used include value trade-offs, ideal package (i.e. product configuration) creation, unaided WTP, and purchase probability (as outlined in Chapter 4). This typically occurs prior to writing any code.
• The gut-check: The concept must then pass an internal “smell test.” The team typically pitches the product concept to LinkedIn sales reps—the people at the firm who are closest to customers. If both customers and the LinkedIn's sales team give the concept a thumbs-up, the product team has the green light to start developing it.
• Building a precise model: After this stage, typically a larger scale quantitative study is commissioned to get more precise inputs (on product configuration, price models, and of course the WTP), in order to build a robust business case (as outlined in Chapter 9). Such findings are constantly fed to the product teams so that things are moving lock, stock, and barrel.
• Paid pilots: Instead of giving the product to beta-testers for free, LinkedIn typically goes to market and sells the beta version of the product. Why? It provides another layer of validation for the monetizing potential of the new service based on the value delivered. In the words of Josh Gold, “Our beta users have skin in the game by actually paying for the pilot tests.” And there is a clear impact of having skin in the game: It generates better concept-testing feedback from the testers. It also allows LinkedIn to fine-tune the price levels prior to a full go-to-market launch.

In summary, what LinkedIn has is an extremely collaborative, parallelized approach with an extraordinary amount of rigor to monetization and commercialization. This robust process speaks volumes to LinkedIn's unwavering focus on providing value and identifying the monetization potential of that value long before that product comes to market. This is typically how LinkedIn designs the product around the value and the price.

Looking Ahead

Over the recent years, the firm has brought several new promising products to market. One such product is Elevate, launched in 2015. Products such as Elevate are crucial to LinkedIn's further evolution as an invaluable online tool to help employees progress in their careers, and employers find the people they need. Like Andrew Freed said, embedding the monetization process into the core philosophy and approach to bringing products to market at LinkedIn is the key to its continued success.

The Limitations of the Old Innovation Process

At the time Drews took over the firm's R&D, its longstanding product development process typically began with a bunch of engineers brainstorming in a whiteboard-filled conference room. As Drews says, it was emblematic of the so-called “fuzzy front end” of innovation—when a new product is often a nebulous concept.

The primary input for product development came from Dräger Safety salespeople. From their rounds with customers, they came back to R&D with customer suggestions and complaints. However, used as customer research for product development purposes, such feedback had severe limitations. First, it was anecdotal and thus might not broadly represent the customer base. Second, it reflected needs the customers could articulate and thus left out their unarticulated desires. Third, it was gathered in an unstructured way, which made it hard to know the relative importance of any customer suggestion. Finally, it was filtered through the eyes of the sales force and thus wasn't direct from the horse's mouth.

For those reasons, while it was valuable, the sales force's input couldn't drive product development, Drews believed.

There was one other not-so-tiny flaw in using the sales force as the firm's market research team: The sales team would come to R&D and say the price of a proposed new product had to go down and the performance had to go up at the same time. Not a big surprise. No salesperson wants price to be a customer objection. However, if the price had to go down, that meant the firm's production cost had to drop as well, otherwise the price reduction would pinch margins.

Competitors' products were another input to new product designs. When competitors added features to their own products, Dräger Safety salespeople lobbied hard to match the features.

The scene at Dräger Safety provided the perfect recipe for a feature shock. Nobody rigorously examined the value each feature delivered to customers. The firm's entire product definition process was unstructured—in part because customers were treated as one segment and because Dräger had no systematic way to prioritize their needs.

As a result, Dräger Safety created too many products overloaded with features and overengineered to deliver those features. That led to lots of overpromising on customer delivery dates because the company's feature-laden products were a bear to manufacture.

The messy product development process created internal havoc as well. Frequent changes to product specifications delayed schedules, which deeply frustrated the R&D team. On top of that, the sales force applied constant pressure to reduce prices, which in turn forced Dräger Safety engineers to change their designs in order to trim manufacturing costs.

In short, the fuzzy front end of innovation led to overengineered, one-size-fits-all product specifications, scope creep (in which the list of features kept growing), an unclear selling story, and mediocre product margins.

Bringing Innovation to the Innovation Process

When Drews became global head of R&D in 2000, he said “enough” to the old product development process. He forced R&D to flip it: Start with the true voice of the customer, not the internal view.

“Thinking about how to monetize a product during the front end of innovation gives a firm a very good chance that it can come up with something great,” Drews says. Without it, he believes, firms are likely to create an average or losing product that tries to do too many things. “A powerful innovation approach is to find out both the articulated and unarticulated needs of the customer,” he says. The unarticulated needs can lead to the biggest innovations, Drews says. “The key is to understand how much value your innovation provides customers in solving their problem.”

At Drews's insistence, Dräger Safety reversed its innovation process. It began with engineers and others from the new product team going out in the field and observing customers. The X-zone 5000 gas detector started this way, with Drews himself observing customers who drilled for oil and gas and firms that deal with sewage. “You really want to understand how people are dealing with your equipment,” he says.

For example, Drews and other Dräger Safety employees went to such dark places as pipelines and parts of Hamburg's sewage canals to talk to the workers who spend 80 to 90 percent of their job time underground. The Dräger Safety crew asked them for pointed advice on how to improve the firm's products. They spoke with workers who monitored manholes and operated underground in sewage canal pipes. These workers, called testers, must continually sample the air from canals to detect toxic or combustible gases.

The interviews found the testers had two main problems. First, pedestrians often accidently kicked the gas detectors into a canal because they didn't see them. Second, when it rained, a tester had to stay out in the rain rather than work from a truck, because the detector's visual alarm wasn't bright enough and the audio alarm wasn't loud enough.

Dräger Safety's new X-zone 5000 portable gas detector addressed both issues. Resembling a mini R2-D2 from the Star Wars movies, the small, three-legged device stands 20 inches high and 12 inches wide and weighs in at 15 to 22 pounds, depending on the size of the battery. The $4,300 product provided big process cost savings for customers, despite commanding a price premium of 35 percent above its next-best competitor.

The X-zone 5000 became a huge hit. Product sales were 250 percent higher than expected, margins proved far above average, and the company won a German safety award for the product.

So what led to the X-zone 5000's roaring success? Dräger Safety had shown the concept of X-zone 5000 to customers before engineers even started to develop it. Customers loved how the X-zone 5000 addressed their biggest pain points, with its distinct visual appearance and improved alarms.

The new innovation process produced another benefit, one that went beyond creating an on-target product: pre-selling the new product long before it was available. “By doing such voice-of-the-customer research, you can ‘test-sell’ your product even though you haven't even started the product development process yet,” Drews says. “Then, when the customer asks when he can have it, you know you created a very powerful product idea.”

A company will have far more confidence that its product development investment will pay off. “With this kind of upfront customer feedback, it is much easier for top management to approve significant funding for a new product,” Drews says.

Institutionalizing the Innovation Monetization Process

After it saw the big financial return on the X-zone 5000 and several other successful pilot cases, Dräger Safety decided it had to institutionalize this new product development approach for every new product idea. The new process (called CPM, for Customer Process Monitoring) begins before a new product is designed. The research and value analysis part of CPM has five phases:

1. Defining where to focus the target market in terms of geographic region, application, and industries. Dräger Safety concentrates on its most important industries and chooses product features largely on the basis of what those markets require.
2. Identifying key decision makers and influencers. In Dräger Safety's case, it's almost always a customer's buying center—a group consisting of a safety engineer, procurement professional, and a technical or plant manager. Each person has different requirements and degrees of influence on the buying decision.
3. Launching qualitative research to observe and interview customers in their environments. In this phase, the company gathers invaluable data on how customers will use the product. The firm also identifies unarticulated and articulated needs (as we discussed in Chapter 4), especially those that lead to “wow” features.
4. Conducting a quantitative survey. While the qualitative research provides a wellspring of feedback on relevant features, the quantitative survey assesses customers' WTP in absolute terms, and relative to competitors' offerings. The company uses conjoint analysis and other techniques. From this research, Dräger Safety identifies needs-based segments, customer groups with homogeneous requirements, values, and WTP. For example, for the X-zone 5000 research, sewage customers said a watertight housing was very important and they were willing to pay for it. In contrast, petrochemicals customers showed less interest and almost no WTP for that feature.
5. Assessing competitive products. Before it establishes the value proposition and selling story of a new product, the firm spends considerable time to understand the strengths and weaknesses of competing products. “Your product cannot and does not have to be better than competitors' products in every function,” says Drews. “You must pick your battles so that your product is stronger than competitors' products in key functions for your target segments.”

As a result of its CPM process, Dräger Safety's new-product plans are no longer ruled by anecdotal evidence from salespeople about the importance of certain features. The company has learned that many proposed product features are of little interest to customers, and thus they have little willingness to pay for them. This was a revelation to Dräger Safety's R&D team. Knowing which features customers don't care about and won't pay for has helped the team to significantly reduce the cost of new products.

With all this information, Dräger Safety then created a full-fledged product concept. Features that differentiate a product and generate value for customers (especially those “wow” features) pass the test; they're baked into the product concept. Costly and unimportant features fail the test, and they are omitted.

Because Dräger Safety is vitally interested in meeting the often varying needs of different segments, it creates variations of each product. This was the case with the X-zone 5000 gas detector. For example, the sewage market version of the product came in a more expensive, watertight case.

Creating Winning Sales and Marketing Messages

After Dräger Safety creates a robust product concept, its next monetization task is to create the all-important messages for marketing and sales campaigns. The first job here is creating selling stories—narratives that articulate the product's value to each influencer and decision maker in the purchasing process. But before it starts printing marketing and sales collateral—indeed, even before it starts developing the product itself—Dräger Safety gauges customer reactions to its selling stories.

You may be thinking, how can you ask customers about a new product that you haven't yet developed? How can customers react to something they can't see? Dräger Safety creates simple presentations that show key product benefits—exactly what customers get if they purchase the device. These presentations vary by customer role. For example, the purchasing function gets a presentation on the benefits it cares about. The safety engineers get a presentation on what matters to them, and so on.

These selling stories generate important conversations with customers—conversations that give Dräger Safety a much finer sense of how much customers want the product and what they'd shell out for it. All these conversations happen before a single product is put through the manufacturing process. In fact, they take place even before Dräger Safety's product design professionals start the engineering process. These conversations are critical because it is far better to “fail early”—to learn what customers do and don't value—before kicking off product development.

Only when Dräger Safety gets an overall positive market reaction to a new product concept will it launch into its product development process. That gives the R&D team a clear mandate and much higher confidence in the product specs.

Since it added CPM to the beginning of its product development process, Dräger Safety hasn't had to change product specifications in the product development phase—and if they had to change, it was tweaks rather than drastic modifications Drews says. This is the design the product around the price paradigm at its best.

Embedding Monetization into Dräger's Innovation DNA

Dräger Safety's version of monetizing innovation—of creating products around a price—has taken firm hold. The CPM work that started with the X-zone 5000 product remains an integral part of the firm's innovation process.

So how exactly did Drews bring CPM into the organization and make it stick? Launching successful pilot tests was a key element. While he headed R&D, Drews collaborated with his counterpart in marketing to develop the CPM process and institute it in a few pilot projects. The X-zone 5000 was one of them. Another pilot test, for a new “alcotest” product—shorthand for an alcohol breath-detecting device—became a major success as well. Sales of an entirely new generation of alcotest product were 10 times higher than the version it replaced. And the new product's profit margins were significantly greater than prior ones.

These pilots proved to be very successful. They convinced Dräger Safety of the power of its CPM innovation process. Before long, the company couldn't imagine doing R&D any other way. Now all relevant Dräger Safety innovations must move through the CPM process. Each new idea is presented to the firm's product portfolio board (which includes C-level managers), and the board makes the ultimate project decision: a yes or a no. Major projects that have not gone through the CPM process are not approved.

To make the CPM process stick in the organization, Drews and his peers from the marketing department hired people to run the new CPM group. The CPM managers were made part of the marketing/product management function. In doing so, Drews and his marketing colleagues made a bold move to bridge the gap between R&D and marketing and demonstrate that the entire product development process had to shift from inside-out to outside-in thinking, rooted in customer desires.

As a result, Dräger Safety's product development projects are now spearheaded by CPM managers from marketing/product management. For Dräger Safety, outside-in thinking has become part of its innovation DNA.

But while such organizational and process changes are important to making a CPM process stick, they aren't the most critical ones, Drews believes. Changing culture and strategy are more important—and more difficult. In culture, a corporate DNA of “product first, customer second” is, in Drews words, a “huge animal” to address. In such companies, a CPM-like process is hard to accept at first because executives fondly remember times in the 1970s and 1980s when product development delivered big wins. When asked to institute a process like CPM today, executives will say, “Our old approach to product development worked before; why would it be different now?”

Companies can be equally resistant to the strategic changes that a CPM approach forces on management: a crystal-clear focus on key market segments. In developing a new product, the CPM approach requires management to decide which customer segments to emphasize over other segments. Sales-driven companies can perceive this as heresy; focus and priorities will limit sales opportunities, so goes the impression. That, of course, is a wrong perception. (See Chapter 5.)

These mindset, cultural, and strategic changes can only be driven from the top of an organization. That's the way Drews did it when he ran R&D at Dräger Safety, and later when he became CEO. But, he adds, the changes must also be driven by executives in R&D, product management, and marketing—the business functions critical to product innovation.

“Creating a CPM type of process is relatively simple,” Drews sums up. “But deploying it and making sure it stays in place for every new product can be like climbing the Mount Everest.”

Uber Designed Its Innovation around the Price

There are two levers to Uber's pricing strategy—the dynamic piece and penetration pricing. Let's look at both of these closely.

Part One: The Dynamic Piece

What accounts for Uber's success? Fans of the service will point to the app, which allows you to know exactly when you'll be picked up, track your driver's progress, estimate your fare, and pay automatically with a pre-loaded credit card. All of these are great features, but no matter how amazing Uber's app may be, no matter how clean the vehicles or magical the customer experience, none of that counts when a would-be rider sees the dreaded words, no cars available.

According to Bill Gurley, an early investor and current Uber board member, that was one of the company's biggest challenges.

Even among the all-star team of Uber insiders, Gurley stands apart. On Forbes’ Midas List, dubbed “The World's Smartest Tech Investors,” Gurley has also served on the boards of GrubHub, Zillow, NextDoor, and OpenTable among several others. His blog, Above the Crowd, is a must-read for the growth capital community. And before he became famous, he was the lead analyst for the IPO of a little-known company at that time, Amazon.

Early on, according to Gurley, Uber had discovered that they were dealing with a highly price-sensitive crowd. “It became very obvious very early in the company that the elasticity was off the charts,” Gurley says in a conversation he had with us.⁸

The key insight was that this did not just apply to the riders. It applied to the drivers as well.

Faced with a shortage of drivers to pick up weekend bar patrons just after last call, Uber “messed around with incentives,” says Gurley. The results were surprisingly strong. By offering additional money, they were able to “move supply off the edge” and get more drivers picking up Bostonians at 2 a.m.

The company could have attacked the car availability problem by forcing drivers to sign up for quotas, as some firms do. They could have insisted on regular hours, graveyard shifts, and forced scheduling. Instead, they solved it in the most elegant way possible: with a monetization model.

This is what Gurley refers to as the “dynamic piece,” also known as Uber's surge pricing. Today, in times of peak demand, the company charges customers more for a ride than during non-peak times. In Chapter 7, we discussed this approach under the name “dynamic pricing,” one of the key monetization models powering many successful businesses.

In effect, Uber's platform has a customer pay the driver more during high-demand periods, so that the driver is willing to brave the elements—or skip their own New Year's Eve party—to give the customer a ride. If Uber had not implemented the dynamic pricing model, the alternative would have been to leave numerous customers in the lurch, complaining about availability and reliability. Such customer dissatisfaction would have severely hurt adoption. Instead, the dynamic model intentionally reduces demand and at the same time increases supply in order to maximize availability and reliability.

This model creates a platform where supply is controlled not by the company but by the independent contractors. And it works brilliantly. “I still find it the most fascinating piece of Uber, because we do no scheduling whatsoever,” says Gurley. “We do millions of drives a day and we never tell a driver when to go to work.”

Part Two: Penetration Pricing

If Uber's drivers are price sensitive, its riders are doubly so. This meant that despite early positioning that framed Uber as a luxury brand—the company's original slogan was “Everyone's Private Driver”—Uber could not charge luxury prices.

In some ways, their customers' low willingness to pay forced the company's hand. “I would argue that it is tautological that you need to be the low cost provider when you have such high price elasticity,” Gurley said. “Otherwise another person can come under you and take massive share because the consumer is telling you that price matters.”

In order to get prices as low as possible, Uber knew it would have to cut down on its drivers' idle time. “Surge pricing plays a huge factor there,” says Gurley. “It tells people when to be where.”

As they get accustomed to the system, a driver's utilization rate, which is the percentage of time they actually have a customer in the car, picks up. Drivers and riders naturally find their fit in the company's highly-efficient marketplace.

As utilization rates increase, Uber can drive the cost down even more, generating what Gurley calls the “Uber virtuous cycle.”

The company's key insight was that this pricing strategy—“pricing low on purpose,” in Gurley's words—was critical to gain large market share with customers. “It is a longer-term game, because with lower margins you've got to get much bigger. But it was the right play,” says Gurley. As discussed in Chapter 8, penetration pricing is a bigger (and riskier) commitment since with pricing low you operate at razor thin margins and you need to get much bigger fast. Few companies get it right; Uber was one of them.

More importantly, the price low strategy opened the door to a much larger consumer base. Having made it “a company mission” to push the price ever lower, Gurley says, “suddenly you can reach a market that is 20 times larger than what you would have had had you not messed with price.”

In a famous blog post, Gurley wrote that Uber's skeptics did not fully “consider the impact of price on demand.” He asked, “What if someone could run a more convenient, safer service at a much lower price and with much higher availability? You would end up with dramatically more rides—and that is exactly what is happening.” He then pointed to the multiple markets critics had not considered, from public transportation to rental cars.

Even walking is not immune: If you open up Google Maps for certain destinations, you will be shown an Uber price as an alternative to taking a stroll—a brilliant way to pose the question, “How much is your time worth?” Gurley told us that this is all part of the overall corporate approach to pricing. “The lower I can get the price point, the more types of scenarios I can get the customer to think of this as an alternative to whatever the substitute was—public transport, renting a car, borrowing a car, owning a car, etc.”

Loose Crystals for the Fashion and Jewelry Sectors

Swarovski's loose crystals business customers largely are fashion and jewelry companies, ranging from midpriced brands like Victoria's Secret to luxury brands like Jean-Paul Gaultier. With more than 100,000 products in its active catalog, Swarovski can provide crystals of pretty much any type, color, size, cut, and form imaginable.

Swarovski launches new collections of stones twice a year. With 100,000 products and new ones added every year, it is impossible for Swarovski to research exhaustively what customers would pay for the new offerings on its drawing boards. So what can Swarovski do to know whether its products will appeal to consumers, its ultimate customers, in the fickle world of fashion?

The company needed an effective and systematic way to get customer feedback on the value of its products early in its product development process. But rather than doing customer research product by product, in 2013 it began conducting extensive research and analysis to identify the product criteria or features that increased customer WTP. In other words, the company was hunting for the drivers of customer value. Swarovski's goal was to come up with a systematic monetization and price-setting process, one that would capture both business customer and consumer WTP, taking into account the complexity of the company's huge product portfolio.

Swarovski surveyed customers in more than 20 countries around the world. According to Kargruber, the company's product managers retrieved two huge insights after analyzing the data. One was that certain customer segments were willing to pay five to six times more for crystal products with sophisticated cuts rather than traditional ones. Stated our way, cut complexity was a major driver of customer WTP. The second revelation was that WTP increased with a crystal's brilliance. And as a crystal's brilliance increases with cut complexity, making a crystal brilliant through a sophisticated cut was potentially a very profitable endeavor.

To put its WTP data and drivers of customer interest into a pricing system that product developers could use, the company came up with five price tiers. Each one varied by the degree to which a crystal delivered the core customer benefits of brilliance and sophistication achieved by a complex cut. Products in each tier had the same prices, even though they were different in such aspects as form and color, as consumer WTP did not vary very much for those factors. To make the price-tier approach more comprehensible to customers, each category was given an appropriate name (from lower to higher price positioning): Essential, Classic, Advanced, Sophisticated, and Outstanding Crystals. The price span from the lowest to the highest tier was 650 percent.

With a price-tier system based on customer value, Swarovski could now make crucial design and pricing decisions early in a new product's development. And because it followed the philosophy of “design the product around the price,” designers could start their work knowing the price range they were dealing with and what would drive customer value.

This was highly beneficial to Swarovski, Kargruber explains, because designers could now create new products to appeal to each price layer. The company must have products for all of them. Behind each category are one or more target segments; Swarovski wants to address all of them. The price-tier system also helps steer the firm's product development process according to market size. For larger segments, Swarovski needs more new products.

Another big benefit of the price-tier system is that the sales force now can easily explain the rationale of Swarovski's pricing to its jewelry and apparel manufacturing customers. There are only five price tiers—not dozens, as in the past—and the most expensive products are the most innovative and complex. Customers now understand why one product's price is so much more than another's, and that reduces price resistance.

Before it instituted the new process, Swarovski based its prices on “internal gut feeling,” Kargruber explains, not customer value. The result was that many of the company's prices were wrong, and salespeople had to correct for that in their negotiations with their B2B customers, which sometimes led to steep discounts for some products. Today, that no longer happens. The sales force can now focus on its core task: selling.

Kargruber says the new process helps product managers make new-product pricing decisions more quickly, easily, and accurately. “And more important, the redesigned new product monetization process helped to bring up our margins significantly, which was the key goal of that initiative,” he states.

Boosting New Product Success for Customized Solutions

The Customized Solutions unit that develops custom crystals for businesses also has adopted the “design the product around the price” approach to product development. Custom Solutions is a growing revenue source for the firm. Mobile phone makers like Samsung want cases festooned with Swarovski crystals to stand out from the plastic-cover crowd; furniture manufacturers are spiffing up their lamps, chairs, and other items with fancy crystals to catch the eyes of consumers in cavernous furniture stores.

Each of these products is customized for each manufacturer. The cases that Samsung's mobile phones will get are not what another mobile phone maker gets.

But the Swarovski crystals that create an attractive phone case or lamp are only part of what's necessary to entice consumers to buy them. Swarovski not only sells a customized product, it also sells the customized packaging, marketing and branding, promotion, and sales consulting that are crucial for these companies to create consumer demand. Swarovski is selling a differentiating solution.

Here, too, Swarovski has learned it must discern consumer trends and spot drivers to make its products more attractive. Understanding consumer needs, and what they'll pay for products that meet those needs, is still critical. Without this information, Swarovski would have no idea what Samsung's customers would be willing to pay for a Swarovski-embellished smartphone case, and therefore what Samsung will be willing to pay Swarovski for its customized crystals. But the Custom Solutions group knows the answer to this question because (in contrast to the loose-crystal unit) it conducts more detailed end-consumer research. Consequently, the firm knows the crystal designs that consumers covet and what they'll pay for them.

To optimize profits, it knows which consumer segments to pursue over others. For example, with mobile phone cases, Swarovski has found consumers across different markets will pay an unbelievable 120 percent more for a crystal-embellished case. That helps Swarovski convince mobile phone companies that the value of its case goes far beyond its manufacturing costs, and that having the Swarovski logo, designs, and crystals on their cases will command a significant premium in the marketplace.

That knowledge enables Swarovski to move off the cost-plus discussions on pricing that manufacturers try to pursue. Swarovski can show manufacturers how much additional profit they can make with Swarovski crystals attached to their products, even if Swarovski takes a greater share of that profit than it would have on a cost-plus margin basis.

The 120 percent premium consumers will pay for Swarovski smartphone cases varies greatly for other products, from as little as 30 percent to several hundred percent. Swarovski's data has focused the Custom Solutions group's strategy on products whose customer segments have a higher WTP for them.

What's more, knowing consumers are willing to spend much more for products embellished with crystals from Swarovski, the firm even manages to monetize their brand and logo. Because Swarovski has such a strong brand, firms with weaker brands have been seeking Swarovski out. They are willing to pay for the spillover effect from having a Swarovski logo on their products.

Having nurtured and buffed a brand known for innovation and excellence for more than a century, Swarovski is now in a position to help companies without strong brands increase their own cachet. But this requires Swarovski to remain a top-of-mind crystal brand in the eyes of consumers and the businesses that resell its products. And that, in turn, means Swarovski must continue doing the research that shows why and how much consumers are willing to pay for its crystals and the products they brighten.

The Next Steps in Swarovski's Monetization Journey

It's been two years since Swarovski began adopting these approaches to monetizing innovation. Kargruber believes it will take the firm another one to two years to complete the journey. “You can't underestimate how long it takes to change a firm's product development approaches, especially to change the mindsets people bring to the innovation process,” he explains. “It is not just a process change; it's a very different way of thinking.”

Making these difficult changes cannot be ad hoc; the effort must be structured. Swarovski installed a pricing board of three people to guide and push the change process, including the heads of marketing, sales, and the controller. The board's mandate is to give clear direction, resolve conflicts, monitor the monetization progress, and make necessary corrections to the process. It meets six times a year and has proven to be effective in moving Swarovski from a “price the product” to a “design the product around the price” approach.

For the more operational monetization support, Kargruber has created a pricing office with two full-time employees based in the marketing organization. They report to him and help innovation teams apply the new monetization approaches.

With a “design the product around the price” innovation monetization process, executives on a pricing board to steer it, and support from Kargruber's group, Swarovski crystals are glittering even more brightly in the marketplace. “In hindsight, we should have done this even earlier,” Kargruber says. Nonetheless, the company is quickly making up for lost time.

First Up: Determining Whether Customers Would Pay

Siroker sought out his former Google colleague, Koomen, to investigate the commercial viability of the product. But instead of diving headlong into development, as many Silicon Valley companies would, they started having the WTP talk with potential customers.

“We had a strong belief many companies would find our technology valuable,” said Siroker in a conversation he had with us.¹⁷ “But we didn't really know just how many and whether they would pay for it. We also needed to find out exactly what benefits drove customer value and how much each customer segment would be willing to pay for different levels of value.”

At the time, A/B testing was in its infancy, and Optimizely had no products to sell. But when Siroker presented his idea to e-commerce companies, they instantly recognized its value. They also expressed a high WTP, which was no surprise. If more customers engaged with their website, they were more likely to spend more time on the site, and therefore they would make more purchases more often. In other words, Optimizely's customers could generate incremental revenue by using the Optimizely software product.

Siroker and Koomen set out to create a world-class but easy-to-use online service on which businesses could run experiments about their websites and make informed decisions about how to change them. They worked with Stanford statisticians to develop a new, powerful, accurate statistical framework for A/B testing that would remove the guesswork from declaring a test successful and statistically significant. Siroker and Koomen set up shop in downtown San Francisco, near a swarm of other web companies.

Still, with no commercial competitors, how would Optimizely price its platform? To buy the Optimizely testing product, what capabilities would customers need? To answer these questions, Siroker and Koomen created a monetization task force, a team with members from product, marketing, sales, and finance. Their job was to determine which features were and were not important (the product configuration considerations) and the best monetization model. Should it be fee per transaction? A subscription service? Freemium? They also looked at pricing strategies and how much they could charge.

From their conversations with potential customers, the monetization team identified clusters, or segments, of the market according to the value they desired from different feature sets. With that information, they created packages (i.e. product configurations) that varied by value (features offered) and price. These packages, they believed, would satisfy companies across all sizes. They also defined the minimum set of features for the “freemium” product, and they outlined a clear and compelling land-and-expand strategy that would convert free users to paid users over time.

But the Optimizely monetization team was still missing a core ingredient: a revenue model that would be a win for both the firm and its customers. In other words, they needed a winning monetization model. So they set out to create one.

Understanding How to Charge

To the Optimizely monetization team, the question of how to charge was, in many ways, more important than how much to charge. The more a customer uses the product, the more benefits the customer derives. Consequently, the team wanted to base the monetization model on usage. Use it more, pay more for it.

But that model would be a bit unusual in the software industry (at least back in 2010). When the team looked at the software market, it found most SaaS companies priced their offerings on a per-user basis. Per-user pricing made sense, they believed, if customers got more value as more of their employees used the software—a network effect. However, the Optimizely monetization team felt per-user pricing had no relationship to their software's value. Of course, they were right. The number of employees in a company using Optimizely's service had no bearing on whether that company generated business value from the software. If Optimizely had charged on a SaaS per-user model, and only the few employees who worked on it were monetized, Optimizely would have left a lot of money on the table. They would have produced a classic minivation.

In addition, the monetization team also worried that customers would not be able to predict how many people would use the software. This would likely slow down the purchase decision.

After weighing these factors, the monetization team decided to charge according to the number of monthly unique visitors (MUVs) bucketed into an experiment. This metric was more in line with the value of Optimizely's product. It also enabled smaller companies with lower site traffic to afford Optimizely. As their use of the software grew, they would get more value from it and thus be in a better position to pay more as their website traffic grew. That's a win-win. Larger companies tended to have larger MUVs and already were in a good position to pay Optimizely a price commensurate with the value they gained from the product.

The MUVs model also enabled Optimizely to increase revenue from customers over time. The more tests a customer conducted, the more value it received from Optimizely, and the more it would pay in return for getting greater value. In addition, as a customer's web traffic grew, it had to spend more to maintain the same level of testing.

The MUVs pricing model also simplified Optimizely's sales process, since customers only needed to know their monthly site traffic (not how many users might use the software)—a measure they invariably knew. (If they didn't, it was doubtful Optimizely could help them. After all, it was software, not a magic wand.) The MUVs pricing model is exactly analogous to the Michelin monetization model described in Chapter 7: charging by the miles truckers drove the tires, not per tire.

Expanding the Product Portfolio

In 2014, Optimizely began gauging customer interest in a new product, Personalization, to help companies tailor their web experiences for customers in real time. The product lets customers tailor their website based on demographic and behavioral data on each web visitor. For example, a customer who purchased a backyard barbecue on the last site visit could be shown grill covers, sauces, and grilling tools. This kind of personalization creates customer loyalty, increases engagement, and can greatly increase the chances that a visitor will buy more on the site.

To validate whether customers valued their product and how much they would pay for it, Optimizely talked to a representative set of customers and prospects around the world. The answer to the first question was a loud and clear “yes!”

Optimizely then used the techniques mentioned in Figure 4.3 in Chapter 4 (including most–least and build-your-own) to break down a list of 15 product benefits/features into leaders, fillers, and killers. With this information, the Personalization product team created a good/better/best package that tied the products to the right segments. But from a product portfolio standpoint, the team was left with two fundamental questions:

1. Should they bundle the Personalization offering with the Testing offering?
2. How should they charge for the Personalization product? Should its pricing be different than Testing's pricing?

To Bundle or Not to Bundle

To answer the first question, Optimizely took a closer look at each core market segment, breaking each into three groups:

1. Current Testing customers who might also value Personalization
2. Prospects who might want to purchase Testing and Personalization in a bundle
3. Prospects who only would want Personalization

Selling Personalization to existing Testing customers was a no-brainer, since it would be a natural extension to the software they already owned. For example, a retailer who is an existing customer and has tested several campaigns might want to personalize its home page for shoppers based on the test results (e.g., customize the web page based on current weather conditions in their region, or the consumer's purchasing history). But since Optimizely's current customers already subscribed to the Testing product, bundling the two offerings didn't help Optimizely answer the question of whether they should do it.

When the Optimizely team talked to prospects who hadn't purchased Testing, or Personalization, it learned their needs could be substantially different for the two products. One reason was that each product was not necessarily needed by the prospect organization at the same time. Most companies preferred to sequence the purchase of the products.

To further complicate matters, there was no clear consensus among the prospects on whether a prospect should buy Testing before Personalization or vice versa. A small segment clearly needed both products, but not so many to warrant bundling the two.

Everything pointed to keeping Personalization a stand-alone product, but under the same optimization experience platform that Optimizely was building. When customers used the products together, they needed to be seamlessly integrated, but one should be able to work without the other.

Optimizely chose this route: Customers who wanted both products could choose from the good/better/best options of Personalization and Testing (that is, mix and match between the products). This also allowed advanced users of the Testing product to purchase a basic package of Personalization to get started. As the customer advanced on the learning curve, retrieving increasing benefits (from advanced packages) would be possible.

Had Optimizely not validated the go-to-market approach (including value and price) with customers before it developed the offerings, it might have bundled them, trying to sell the two products together since this was the easiest thing to do from a product standpoint. At best, that would have created a minivation. We have seen many SaaS companies go down this path and then try to take a step back after the bundle's sales fall short of expectations. Optimizely's laser focus on having the customer conversations early in the product development process steered it to the (shall we say it?) optimal outcome.

Deciding How to Charge for the Personalization Product

With its Personalization product strategy in hand, the next step for Optimizely was deciding how to charge for it. Should it use the same metric it used for the Testing product, MUV? Using the same metric would keep things simple for both Optimizely and its customers because both products would have the same monetization model. However, Optimizely learned from its validation with customers and prospects that the usage of Personalization is likely very different than Testing. While Testing would be used periodically and for a specific experiment, Personalization would be used at all times for all site visitors; it was always on. Personalization only works when it's constant and universal. Jill would not like it if the site were personalized on one visit and not on another, and why personalize for Jane and not Jack? Given that dynamic, customers would resist tying the price of Personalization to how much they used it.

After hearing this feedback, Optimizely chose a different pricing metric for Personalization: total site traffic. This metric was in line with how customers planned to use Personalization and get value from it. By measuring the value of each product differently, Optimizely could better defend the value of each. This, again, was a win-win for Optimizely and its customers.

The moral of the Optimizely story is that there is no one right answer for monetizing a suite of products. Had Optimizely kept its monetization model the same for the two products, it might have created a suboptimal outcome. By designing each product separately around the value and the price, Optimizely and its products have been a huge market success.

With 400 employees, the firm has continued to grow rapidly. It expanded its headquarters in San Francisco and opened five others in the United States, Europe, and Asia-Pacific.

Looking ahead, Optimizely has positioned its products as a website customer experience optimization platform, on which the company will add future Optimizely products. But before it launches those new products, the firm won't have to guess how many customers will want them and how much they'll pay. You can bet it will know.

Adopting a New Approach to Sizing up Opportunities

Top management at the firm realized they had to get better at picking winners, so they welcomed the “customer value–driven new product” approach. In this industry, customers include the physicians who prescribe drugs, the entities that typically pay for them (government and healthcare insurers), and, of course, patients themselves. All those influencers and decision makers on the drug-purchasing decision had to be considered in advance of the firm committing big dollars to developing a therapy. Shifting to this approach would require cultural and organizational changes that would ultimately take company management more than five years to complete.

First the executives had to sell the approach internally. One of the earliest internal presentations on the journey laid out three critical changes for the company to make.

Change #1: Listen to the Country Teams to Get the Insights on Market Access and Price Potential

The drug development division at headquarters started listening to its teams in the country markets and engaged them in the product development process. No one at a pharmaceutical company is closer to patients, physicians, and payers than the local teams consisting of medical, marketing, and market access specialists. Drug developers needed their input to assess a new compound's viability.

In the best case, the local teams serve as surrogates for customer input when primary research is prohibitively expensive. This has another benefit: It enables the country teams to assess early in product development which unmet customer needs a new product may be able to address—pending confirmation by clinical trials—rather than hearing about it from headquarters close to product launch.

When local teams provide customer insights, they feel committed to embracing the candidate product and prepare future customers wherever they are allowed to (note: Talking with customers about forthcoming new treatments is strictly regulated). In effect, the company created a tight and transparent information loop between its local market teams and the central decision makers. The final step was the creation of an internal information system for tracking and repeat utilization of earlier gathered information.

Change #2: Determine a Product's Clinical and Economic Value Much Earlier in the Process

The testing of a medical compound goes through several phases before it gains regulatory approval and listing on the reimbursement schemes of insurance companies or governments. The most critical and costly clinical trials take place in Phase III. The supporters of the company's new value optimization process argued that if they better understood a drug's clinical, humanistic, and economic value to patients, payers, and physicians by the end of Phase II, they could send fewer compounds into Phase III and provide them with more resources.

For this reason, the company focused most of its process changes on the early stages of product development. Its task forces created new process steps that gathered input from customer surveys.

But the task forces were realistic about the magnitude of short-term process changes that could be adopted. They decided not to try to foist major all-or-nothing change on the drug development process. That risked spawning heated arguments and alienating key team members.

Instead, the task forces urged noticeable changes in drug development but with minimal friction. Rather than trying to get product developers to strictly adhere to a new process, it was more important to communicate the ideas behind the process. What if few teams followed every new step? Not a problem. The way the task forces explained the new process conveyed what the teams needed to do differently, and why: Broader market insights gathered by the end of Phase II greatly increased the chances that the products with the highest customer value potential made it to Phase III trials.

Change #3: Increase Cooperation between Clinical Development, Marketing, and Market Access to Encourage Constructive Challenges

The company's clinical development and marketing groups once operated separately, while market access barely existed. Clinical development tested and shaped a product, and then marketing launched it. The new organizational alignment still called for several groups, but their tasks had to be closely intertwined. Marketing focused on the prescriber customer, medical on the patient and physician specialists, and market access on the payer customer needs. In that context, health-outcomes could develop the evidence for the economic value of the product, while the clinical research teams developed the clinical value of the product.

Cooperation between clinical development and market access professionals became much more extensive under the new model, each group keeping of course their own tasks and responsibilities. Clinical researchers had to improve their understanding of payer data requirements—the proof payers require to evaluate the drug and decide on price, reimbursement coverage, and market access. The market access staff had to get better at articulating, in a way that researchers could understand, what payers were looking for to optimize the likelihood of successful negotiations in the countries between the company and payers. Such enhanced mutual understanding would allow the researchers to adjust their clinical trials and other product development activities in a focused and timely manner.

The new process linked the teams looking at the economic value of new drugs with the teams looking at their clinical value versus competing therapies (in other words, value differentiation). This is essential to shifting product development to the model we are embracing.

Senior management approval and ongoing support helped the pharma giant reap the benefits of its new innovation monetization process. They gave the green light to the first change: moving value analyses to the front end of the product development process. That gave the task forces the license to prepare a global rollout, which the top management then approved.

Impact: Lower Risk, Higher Upside

What was the result of these changes? The pharmaceutical company actually lowered its risks by placing bigger bets. It did so by killing more products in early development than it previously had the courage—or evidence—to stop. Over time, the pharma company placed fewer but much larger bets rather than continuing to support all compounds appearing to have some clinical benefit. This goes against conventional wisdom, which says that a company mitigates its risk by launching more products and counting on the gains from a few winners to overcompensate for the larger number of less successful products.

The company's “customer value–driven new product” approach supports the opposing argument: Concentrating more dollars in fewer products is actually less of a commercial risk than spreading the risk across a large number of products or compounds. Why is this the case? Having a much more incisive understanding of the market and a drug's commercial prospects reduces risk significantly. With better tailored data about the clinical and economic value of a new drug, the company was able to develop a better view of whom to target with the treatment, how much to charge, and how to quickly get to market. This allowed the company to make much better decisions about how much money to allocate for Product A versus Products B and C. Having a deeper understanding of a few high-potential products is far better than a superficial understanding of many products.

The broader lesson is that in innovation, less is more. Having a deeper and more specific knowledge about fewer products is superior to knowing only general information about a multitude of new offerings.

The trials the pharma company needed to conduct to gather additional information can indeed be more expensive, risky, and time consuming. This is contrary to how R&D people are normally measured. When a pharmaceutical R&D team fights internally for R&D dollars, it doesn't want longer and more expensive trials. R&D people prefer their standard key performance indicators (KPIs), which are based on how fast they complete a trial and the number of positive outcomes (that is, the number of products that hit the minimum bar to get regulatory approval).

In the company's new system, new products must meet financial minimums, not just clinical or regulatory ones. By changing incentives for its research teams, the company encouraged them to embrace the process and to understand that the payer-rationalized trial design would make the entire company more successful in view of the increased likelihood of clinical and commercial success at and after launch.

Impact: Less Promising Candidates Killed Earlier

Since shifting its product development process, the company has stopped several products not because of clinical issues but because of poor market prospects: not enough differentiation against the standard treatment, lack of added value in the eyes of key payers, and so on. Today, senior managers are much more critical before they give the green light to taking a candidate drug into Phase III of clinical development. It has become clear that weaker candidates need to be dropped even earlier in order to clear the path for the better candidates that deserve the resources.

At first, all this was a culture shock for the pharma company because it used to define new product success as approval from the U.S. Food and Drug Administration, the European Medicines Agency, or their counterparts in other geographies. In the new system, it is okay if a candidate drug does not reach the approval stage—if the team identified this risk early enough and had the courage to pull the plug with convincing arguments.

This experience shows that long-established companies whose pipeline products require scientific breakthroughs can make the shift from an internally focused R&D approach toward an outside-in customer value–driven approach that strengthens the collaboration between the multiple areas of expertise.

In fact, for all companies with major R&D investments, the outside-in customer value–driven approach will help identify the losers earlier, allowing the company to commit and invest in the winning candidate drugs while boosting the business in the longer run.

This is, however, easier said than done. It requires full commitment from the top and will take several years to implement.