Can innovation be disciplined without killing it?

Yes, by implementing innovation as an end-to-end idea-to-cash process and systematizing support for problem solving. By Vinod Baya, Bo Parker, and Christopher Wasden

Edison’s light bulb, Google Search, and the Apple iPod—many people would describe these hallmark inventions as examples of rare talent in action or the products of uniquely innovative companies. But to attribute them to “magical genius” not available to others lets everyone else off the hook with an easy excuse not to be innovative: “How could we possibly expect this type of rare talent or unique capability in our company?”

Is rare insight only the domain of the extremely brilliant? Is radical innovation conceived in a single, stunning act of invention and delivered as an entirely new offering? No. Innovation is a process. It is a process that taps into genius, but it need not be the accidental province of the madly brilliant, as these hallmark inventions illustrate. Even some of the most celebrated inventions don’t quite fit the eureka moment stereotype.

Specifically, a disciplined problem-solving process in materials science led to the light bulb. Applying a ranking principle from one domain to another led to more satisfactory Web search results. Several incremental improvements to existing technologies and the vision to combine them led to Apple iPod and to iTunes, which together became the radical commercial innovation.

The common element in these examples: the enterprise could not move from idea to cash or business value because of some problem the inventors encountered. Solving the problem moved the process forward. And solving problems typically involves a disciplined approach, pattern matching, or a combination of these.

This issue of the Technology Forecast explores how organizations can develop, manage, and continually improve an end-to-end process, supported by technology, in which innovations are more likely to be discovered, better assessed, and better converted into profits—what PwC calls the idea-to-cash process.

This article examines the importance of a problem-solving approach in the end-to-end innovation process. The second article examines the software available to organize, manage, and systematize the problem-solving approach. And the third article offers insight into how CIOs can use the IT infrastructure to support more disciplined idea-to-cash processes.

Hallmark examples shatter the innovation myth

There’s no getting around it. Innovation is hard. It is one of the rare business activities that does not benefit from economies of scale. That is, large businesses are no better at it than small ones—and, in fact, are often worse. But the notion that brilliant individuals, using mysterious methods, create all the radical innovations is a myth. Implicit in the myth is the idea that innovation is beyond the reach of process improvement and discipline, and is impervious to management influence (other than management throwing more money at research and development [R&D]). But consider three hallmark examples:

• Edison’s light bulb—Thomas Edison didn’t arrive at the solution of tungsten filaments in a vacuum through once-in-a-lifetime insight. The basics of making a light bulb were known: pass electricity through a filament in a vacuum. The problem was the filaments he had tried did not last long. Edison’s genius was dedicating scores of engineers to systematically testing thousands of materials as filaments. Eventually, they discovered tungsten lasted longest. Edison brought the idea to cash through a disciplined process to solving a problem.
• Google’s Web search algorithm— Larry Page, co-founder of Google, was using the Alta Vista search engine to find e-commerce Web sites and encountered the problem of search results being plentiful but of limited value because they were not ranked by relevance. He connected two patterns: the importance of the web of links among Internet sites, and the way academics use journal citation counts to measure the importance of articles. Then, using the number of links among pages to determine which are seen first, he transformed Internet search. Page did it intuitively, but connecting two patterns from dissimilar domains can be used as a formal process to accelerate invention.
• Apple iPod—Apple released the iPod in 2000 to middling success, despite its creative combination of many smaller inventions resulting in an elegant portable music player. The problem: the digital music ecosystem was in chaos. Songs illegally ripped and shared on the Internet often were mixed with malware, there was no single place to buy tracks legally, and moving music between multiple sources and the iPod presented complex challenges. Apple soon made one additional, incremental invention to unlock the vast commercial success latent in MP3 players: iTunes as a safe, legal, and user-friendly way to get music to the device. Neither iPod nor iTunes by itself was radical innovation, but together they changed the game.

There are lessons here that all leadership teams need to take to heart.

“While innovation can be groundbreaking, it is more often the incremental improvements of existing technologies and methods—the sum of many small but constant changes that over time can transform the way a company or an industry does business,” says Jon Bidwell, chief innovation officer of Chubb, for whom the end-to-end innovation process goes from idea to marketable products.

Innovation is high on the agendas of CEOs in virtually any industry. In the past, they might have focused on growing market share to drive growth. Now, they increasingly are focusing on innovation in new products and services. (See Figure 1.)

And they’re confident their innovations will succeed: 78 percent expect their development efforts to generate “significant” new revenue opportunities over the next three years. It won’t be easy. But they are making changes at all levels of their organizations to make sure they can take advantage of incremental innovations, as well as breakthroughs.

As Bidwell understands, it is time to discard the stereotypes of innovation, radical or otherwise, and treat it for what it is: an enterprise business process that can and should be better understood, redesigned, improved, and measured to improve performance. The rest of this article examines how.

Problem solving: Core to how innovation happens

A substantial body of research explores how intuitive innovators think and how their thinking patterns can be incorporated in the problem-solving steps that lead to innovation.¹² The literature usually refers to this approach as “structured problem solving.” Two broad themes emerge:

• Problem solving is core to innovation. Problems are what inspire innovators to look for answers. Problems often surface as tensions—loss of market share, decline in profitability, dissatisfied customers, and others. Natural innovators are good at defining the problems; they often see problems that others do not. “[Apple CEO Steve Jobs] will reject something that no one will see as a problem,” former Apple CEO John Sculley has said.³ Jobs has a knack for seeing problems—in a user interface or business model, for example—that the rest of the industry does not see.
• Almost all innovation involves the application of a known solution to a problem or part of a problem from one domain to a new problem in a different domain. Bill Hessler, an innovation expert, describes how nozzles designed for decorating cakes were used to solve a problem in designing gas turbine nozzles. (See the interview with Bill Hessler on page 22.) There are many other examples. Open collaboration, as a source of ideas that address design problems, succeeds because it exposes the design challenge to a large number of people from different knowledge domains. This increases the likelihood that someone will intuit what the problem has in common with a problem—and a solution—outside the domain.

The combination of these two themes reveals how enterprises can recast invention⁴ challenges into problem-solving tasks. Thinking about the invention challenge as problem solving—and using patterns and principles that already exist—greatly simplifies the invention task and transforms it into a process of knowledge search and pattern recognition. In the transformed invention task, process orientation and information technology will play a bigger role.

This problem-solving approach typically involves four steps, listed here and illustrated in Figure 2.

1. Understand and specify the precise functional problem that needs to be solved—anything from a deep materials-science issue to a business model challenge. For example, despite the existence of many search engines, Page understood and focused specifically on the problem of relevance in search results.
2. Abstract the specific problem to a general principle so it can be mapped to a generic version of the problem. Rather than seeing the problem of poor search results as unique to the Web, Page saw it as a general ranking problem, which he then mapped to other domains.
3. Identify generic solutions to the generic problem to generate candidate solutions or approaches to the specific problem. This activity often means a creative mix and match of partial solutions to parts of the problem. The domain of academic literature and how it ranks the popularity of research led to the insight that Web links could serve a similar purpose.
4. Translate the generic solutions into specific solutions to the specific problem and thereby invent a new approach. In Google’s case, this was the page rank algorithm.

Without a system or discipline, such problem solving is experienced as serendipitous or ad hoc. If an organization can discipline serendipity to make it happen more often, with more people, to yield more productive outcomes, then the organization would have higher innovation performance.

Enterprises often hire a consulting organization to tap disciplined processes and problem-solving methodologies. Some consulting organizations, such as IDEO and Jump Associates, accept the challenge of delivering the innovation for enterprises largely on an outsourcing basis. They combine techniques such as brainstorming, design thinking, and prototyping to bring discipline in their processes. Other consulting organizations, such as PwC, Doblin (a member of Monitor Group), and others, deliver services designed to change internal processes so that future innovations can be generated by the enterprise itself.

TRIZ⁵ is another example of a methodology that uses the principle shown in Figure 2 to systematize innovation. “What the intuitive innovator does subconsciously, TRIZ brings to the conscious level,” says Peter Hanik, president of Pretium Innovation.

Hanik offers an example of how powerful this principle’s search and application process can be. Ice storms have been capsizing fishing boats for centuries, despite many efforts to design boats less susceptible to flipping over after heavy ice collects on the decks. Not until a principle of energy transfer was applied to the problem did it occur to anyone that the temperature of the sea was high enough to melt the ice. It is now standard practice to pump seawater onto the decks of fishing boats to avoid capsizing in icy conditions. For a brief look at TRIZ, see the conversation with Peter Hanik in the sidebar on page 11.

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Hessler, who has used TRIZ, says, “It frames all innovation as a search for existing solutions in different industries or contexts. In other words, your problem has already been solved and you just don’t know it.”

If this approach to problem solving, invention, and innovation is so powerful, so well specified, and so developed, where has it been all this time? One challenge is that most enterprises view innovative problem solving as a siloed activity, limited to the R&D and product development departments. A recent survey by Harvard Business Review Analytic Services found less than a quarter of senior management has high satisfaction with R&D outcomes and processes. (See Figure 3.) Clearly, if enterprises start to look at innovation as an end-to-end process, they could improve their innovation performance. This means marketing, product management, sales, customer support, strategy, IT, and even human resources need to incorporate creative problem solving in their daily jobs—supported by a disciplined and technologically advanced infrastructure.

Innovation is an end-to-end process

Innovation is value-creating novelty. It must be new, but it must also create value for the business. “The key is to leverage our capability at all levels within the organization and to increase the speed and scope of idea generation and transformation into marketable products that result in new business value,” Bidwell says. Unless an innovative idea for a product, service, or business model is carried through to the customer, it will fail to generate cash or other value for the enterprise. It is therefore a process, rather than an activity.

The rise of open collaboration at companies such as Procter & Gamble, Cisco, and General Electric Company⁶ has begun to create awareness of innovation as a process that starts with ideas. Many companies are making good use of their customers, suppliers, and Web-based “suggestion boxes” to broaden the source of ideas for enhancements to existing products or entirely new products.

About 40 percent of global CEOs expect the majority of innovation in the future to be co-developed with partners outside the organization, according to PwC’s 14th Annual Global CEO Survey. (See Figure 4.)

In the journey of innovation, ideas—whether incremental or radical—are just the beginning and they need to move from discovery to impact on the business. Figure 5 shows this idea-to-cash life cycle as PwC constructs it. Managing a set of ideas beyond discovery through logical stage gates of incubation, acceleration, and scaling are the execution steps upon which most companies stumble.

The following summarizes the key activities in each phase:

• Discovery phase—The primary purpose is the exploration, identification, ideation, screening, and selection of ideas to determine feasibility and create a proof of concept. A key problem is to generate a constant flow of ideas. Driven by open innovation paradigms, the sources of ideas increasingly include customers, suppliers, partners, and other external organizations or individuals. This open model has become a best practice among innovation leaders.
• Incubation phase—This phase eliminates technical risk by creating working prototypes and pilots and explores additional ideas regarding the value proposition among buyers, users, and beneficiaries. Companies that do not address problems in this phase are unlikely to advance innovations beyond discovery. The prototypes and pilots provide the basis for conducting additional product and market research to develop a robust business plan for the innovations needed to advance to the acceleration phase.
• Acceleration phase—This phase eliminates the initial commercial risk by demonstrating that there is a meaningful market among various segments. As such, this phase requires a large commitment of resources and time. In this phase, problems related to commercialization of a product, process, or service are solved. The team applies more formal structures and practices to ensure greater discipline, yet remains flexible enough to exercise agility in adapting the product, process, or service to the market’s needs.
• Scale phase—In this phase, the primary problem to address or the risk to manage is the size of the market opportunity. The result of the acceleration phase is now fully established as a core product or service offering.

Challenges and risks facing an innovation don’t stop if their nature changes during different phases of the life cycle. All great ideas sourced in the discovery phase will encounter numerous execution challenges in all phases, or problems that need solutions, for which structured problem solving can deliver dramatically better results.

It is also important to note that only a fraction of ideas move through the full life cycle—not all ideas can overcome all challenges and risks encountered during their development. As few as one in a hundred seemingly great ideas may eventually succeed and become a commercial offering. Built into disciplined problem solving are mechanisms to drop ideas when core problems have been exhaustively examined for solutions, which should be done as early as possible in the life cycle. This approach is often referred to as a fail fast strategy, so that only the most promising ideas move forward. Organizations also learn from failure. Fast, frequent, frugal failure decreases the learning cycle time and allows organizations to come up with better ideas faster in the future.

“If you want to come up with 10 or 20 ideas or directions for your company, you need a structured approach that thoroughly scans the range of possible solutions from many different domains,” Hessler observes.

An end-to-end innovation process “is important, because ultimately innovation’s success is not idea generation; it’s a lot of pick-and-spade work,” says Patrick Sullivan, chief architect of Chubb. “I liken it to building a road. It is one thing to draw a line and say that’s where we want the road to be. It’s another thing to get all the equipment and people, blast the passes through the mountains, level all the stuff out, grade it, surface it, and everything else. Organizations fall down in this, because the execution is really hard.”

Enterprises should treat innovation as an end-to-end process from idea to cash, and each problem faced in this process as an opportunity to invent a solution that moves the process forward. In many cases, the problem/invention challenge identifies and clarifies the real opportunities for sustainable competitive advantage.

Business process support for thinking is on the rise

If innovation has been so important, why hasn’t it been addressed as an end-to-end process to be optimized before now?

The history of process improvements, particularly those associated with the use of IT to implement best practices and to establish managed, end-to-end processes, starts with activities focused on managing behavior to common standards. Behavior-dominated business processes are primarily activities that require limited thinking, problem solving, or creativity. Some examples include accounting for a purchase, keeping track of how employees spend their time, and noting the details of an item being put into inventory. These are detailed, data-capture-oriented activities.

Over time, the focus of enterprise performance improvements grew to include activities that require more thinking, more knowledge, and direct support to enable staff to reach more informed conclusions. One example is the establishment of enterprise-wide standards and processes for measuring employee performance, providing coaching, and deciding compensation and promotions. Many IT vendors now offer applications that introduce end-to-end management of the performance appraisal process while those who know and work with the staff retain the role of evaluation and assessment.

The trend is clear. As Figure 6 shows, the target of enterprise performance improvements to end-to-end processes is steadily moving in the direction of more thinking. Innovation has been a challenge for the enterprise, in part, because it requires far more thinking, analyzing, knowledge leverage, and creativity, with much less scripted behavior. Now, enterprise applications are beginning to deliver more subtle support for semantically rich business activities such as idea management, problem solving, and invention—all keys to successful innovation. “Innovation is a social activity, and until software became social, it was impossible to really try and automate the innovation process,” says Matthew Greeley, CEO of Brightidea.

In part because of its high requirement for analysis, creativity, and social interaction, innovation has not been seen as a broadly connected collection of enterprise activities subject to process discipline or re-invention. Just as beliefs about performance management evolved and are now included in human capital management (HCM) applications, innovation increasingly is understood as being more than creative insight occurring at unpredictable times from inspired individuals.

The changes companies need to make to their siloed approaches to innovation may be jarring to some. But enterprise-wide transformation always ruffles feathers and faces initial resistance. That’s why the best organizations plot a collaborative, strategic program of change to maximize their chances of success.

Because enterprise transformations have occurred in the past, pattern matching suggests ways to succeed in the innovation domain. For example, when organizations transform siloed, disconnected, suboptimal processes into seamless, responsive, and efficient end-to-end enterprise processes, they focus on four deliverables: common nomenclatures, digitization of interfaces, a technology-enabled new process, and continuous monitoring and improvement. The article, “The strategic CIO’s new role in innovation,” on page 44 explores these in more depth.

Barriers to innovation

What keeps good ideas from moving to cash and bad ideas from dying a quick death? It depends on how the enterprise executes on the idea.

Developing a good understanding of the end-to-end process shown in Figure 5 is a key first step. To jump from discovery to scaling without going through incubation and acceleration results in suboptimal outcomes. It is like trying to go from infancy to adulthood while bypassing childhood and adolescence. You’re not ready for it. Managing ideas to cash is also fraught with other challenges. The biggest factors in poor innovation execution within the life cycle include the following:

• Selecting the wrong ideas to develop—Companies often have poor connections between idea sourcing and company strategy. They forgo ideas that should be developed, and they overinvest in ideas that are off strategy. An end-to-end process approach addresses this scenario by defining a “reverse funnel” that translates the business strategy into ideas through “innovation challenges.” These requests direct creative thinking in useful ways at the beginning of the idea-to-cash process and guide those people making decisions about which ideas to develop further. A related issue is supporting for too long new ideas that are failures and not having the discipline to kill bad ideas.
• Transferring ownership of the idea too soon—The people (staff or collaborators) who originate an idea are usually the most passionate believers in it. But ideas don’t represent fully detailed product or service descriptions. Even the best ideas go through a series of specification and design challenges from their earliest stages through prototyping and market entry. At some point the idea originators usually become less involved in its development—for example, if it requires deep engineering analysis. But the early days of specification are also open to challenges. Separating the idea from the idea generators too soon can lead to great ideas being killed by status quo inertia, a lack of creative energy and tension, and misunderstanding.
• Failing to solve design problems— As ideas flow through the process, they encounter many issues. Edison’s original light bulb was a good idea facing a fatal design problem. Invention is, in fact, solving the problems good ideas face by using and creating knowledge—in Edison’s case, discovering that tungsten would burn in a vacuum for many hours. This is the crucial thinking part of the innovation process, and most companies do little to enhance it. The most innovative companies use advanced information technologies to augment problem solving by treating it as a knowledge engagement, interaction, and growth challenge.
• Failing to design for scale—Many great ideas are successful as one-offs, and companies can find a few customers willing to pay a premium for the new product or service. Truly transformative ideas often face additional design challenges to drive out cost to address the much bigger, price-sensitive part of the market. Progress is subject to knowledge engagement enhancements to the innovation process, described in more detail in the next section.

Any serious effort to transform enterprise innovation must address all of these challenges. The effort must introduce meaningful metrics and adopt a continuous improvement ethic. The good news is that idea management systems are now mature enterprise applications capable of addressing the key life-cycle challenges of idea selection, idea management and handoff, and innovation metrics. (See the article, “Powering the innovation life cycle,” on page 26.)

Problem solving: A special form of knowledge management

Applications are becoming available that help manage the complexity and learning issues associated with structured problem solving. They do this by addressing the two biggest mental challenges facing anyone trying to adopt structured problem solving:

• Translating a specific problem into an abstracted, generic version that maps to a generic principle is difficult. It requires a creative step and the ability to recall the many principles that define the problem/ solution universe. The best software allows problem solvers to define their issue in relatively specific terminology, and it returns candidate solutions from multiple domains. This approach transforms the mental process into something closer to a pattern recognition task rather than a recall task. As all software designers know, and as psychological science informs us, humans are much better at recognizing patterns than at remembering a lot of specific detail.
• Having access to as large a body of relevant problem/solution knowledge as possible is a major challenge. Software that captures semantically meaningful functional descriptions of problems and solutions addresses this challenge. Invention Machine’s Goldfire software does this by semantically analyzing inputs to the company’s knowledge base—patents, proprietary functional specifications, and so on—and queries by users, using the problem/solution principles as metadata.

Applications that support structured problem solving can also be understood as digital interfaces in a business process that today is mostly analog or human based. As problems are encountered and solved, by your enterprise or others, the flow of knowledge is added to the palette of potential solutions available to the enterprise digitally. No people need to assess, classify, or otherwise intervene.

Conclusion

Today, structured innovation methods and the software that supports them typically remain isolated in R&D. Yet enterprises have awakened to the need to seek ideas not just from staff in product design and engineering but also those in customer-facing, manufacturing process, business strategy, and partner management functions. The challenge has been that staff outside R&D aren’t engaged with problem solving and innovation frequently enough to become adept at the methods or software. And they typically don’t have the time to work on these problems, which require close attention.

Innovation is not just an R&D issue. Innovation should be in everyone’s DNA in the enterprise. “What you do is simply create the knowledge base. You have the tools in place so that this [innovation] simply becomes the set of ethics, practices, and beliefs that are fundamental to as many people in the organization as possible, and they simply think and act that way,” suggests Bidwell.

The current generation of enterprise applications designed to enhance innovation through the support of structured problem solving is just beginning to capture the attention of business units outside R&D. (See Figure 7.) PwC believes these products are already being enhanced with thoughtful redesigns that bring most of their value to a broader range of enterprise problem solvers and idea generators in a more compelling, accessible interface.

Extending these methods and capabilities throughout the organization is imperative. Even after a brilliant idea is identified, it often faces many conceptual, engineering, market development, distribution, and customer acceptance challenges that demand creative problem solving. In short, the structured innovation approach can contribute beyond the discovery phase. Indeed, it is crucial that innovation also be applied to the incubation, acceleration, and scaling phases of new product development.

In other enterprise contexts, such as human capital management, thoughtful activities can be enhanced by the right software design and underlying technologies. As this happens, the highest performing, most innovative enterprises will be those that have brought their innovation and problem-solving worlds together as part of a full life-cycle, end-to-end, managed process.

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