March 18, 2011
by Vinod Baya
Several technologies help raise the innovation performance of enterprises.
Innovation remains a hit-or-miss proposition with more misses than hits at most companies. When innovation does occur, luck often deserves more credit than any systematic approach. There are, however, proven engineering and design principles and methods for attacking problems in need of innovative solutions. And there are software applications that treat innovation as another case of knowledge engineering, access, and distribution.
PwC views innovation as ideas turned into successful commercial products and services. As discussed in the article, “Can innovation be disciplined without killing it?,” on page 06, enterprises should treat innovation as an end-to-end process—what PwC calls the idea-to-cash process. Framed this way, a series of subprocesses move ideas through stage gates that filter and choose the best ideas; together they form the innovation life cycle. (See Figure 1.) Problem solving is core to moving the process forward at each of these stages, and emerging technologies are playing a role. The ideal innovation process is backed by an idea-to-cash infrastructure that includes people, processes, and software similar to other enterprise processes, such as enterprise resource planning (ERP), human resources (HR), or customer relationship management (CRM).
The first article in this issue of the Technology Forecast explains innovation as an end-to-end process and examines the opportunity and potential of this problem-solving approach. The article, “The strategic CIO’s new role in innovation,” on page 44 explains the CIO’s role as a business leader and as the IT leader. This article lays out the essential technologies that make it possible for the CIO to have an impact on the enterprise’s innovation capability. Technologies that support this end-to-end innovation process fall into two broad categories:
- Technologies supporting process—These solutions allow enterprises to treat innovation as a process and to integrate activities and flows. Two distinct classes of solutions make this possible:
- Idea management systems help manage the flow of ideas and their evolution, and optimize the idea-to-cash process.
- Product life-cycle management (PLM) and project or product portfolio management (PPM) systems, often used in the later stages of the innovation life cycle, help manage a portfolio of innovations and related product life cycles.
- Technologies supporting solution identification—These technologies support specific tasks and activities all along the end-to-end process. Many function- and industry-specific tools already are in use, such as design environments that include computer-aided design, computer-aided engineering, chip design, and others. However, the focus of this article is on industry- and function-agnostic tools. Solution identification tools help systematize the invention activity of the innovation process. These tools include a combination of structured problem-solving methodologies best represented by the TRIZ family of approaches and semantic search and knowledge management techniques that support problem solving.
These technologies, alongside an information sharing and collaboration platform, can power the end-to-end innovation life cycle. Figure 2 shows how these technologies map to the framework of structured problem solving that intuitive innovators do naturally.
The CIO should be the principal agent of technology enablement for the end-to-end innovation process, choosing and deploying appropriate technologies. Some useful technologies may already exist within the business units; these, too, should be brought into the strategic mix, regardless of ownership.
Being smart with ideas: Idea management systems
Idea management systems enable the organization to manage the discovery, incubation, acceleration, and scaling of ideas to create commercial value through the development of innovative products and processes. They provide a structured, disciplined approach to managing the innovation process and surfacing metrics to manage the flow and outcomes of the process.
The underlying approach for idea management is not an unfamiliar one. “Just as you track your leads in a sales system, we identified the idea as the starting point when directed work on a particular innovation project begins,” says Matthew Greeley, CEO of Brightidea, which develops and sells idea management software. Companies may engage in various activities such as brainstorming, market research, strategic analysis, competitive analysis, and others before an idea is generated or formalized; but for Greeley, the moment the idea first is recorded signals the start of the innovation process.
By digitizing the notion of an idea, the idea management system makes it possible to structure and manage what typically has been considered an ad hoc process. Idea management has been around for a long time in analog form: index cards, scratch pads, and whiteboards are widely used when generating ideas. Not unlike sales leads in the sales process, digitizing the notion of the idea enables decision making, forecasting, and the tracking and management of the idea through the innovation life cycle.
Idea management systems address many challenges in the innovation process. One is the need to filter what could easily become an overwhelming volume of ideas as open innovation approaches allow more and more employees, partners, and customers to participate in the idea generation process. With employees, partners, customers, and others who could potentially offer solutions and suggestions from around the world, most companies would have no way to cope with the sheer volume if idea assessment were entirely manual and flowed through a few people. Idea management systems provide the front end for harnessing and structuring this massive idea flow.
Key characteristics of idea management systems
The core characteristics of idea management systems offer support for capturing, filtering, and assessing ideas, as well as measuring the flow of ideas through the innovation cycle. They also support defining organizational roles related to innovation and managing workflow. Besides these features, the systems include certain capabilities that are imperative for innovation.
The CIO should be the principal agent of technology enablement for the end-to-end innovation process, choosing and deploying appropriate technologies.
Innovation is essentially a social process. Once suggested, an idea needs people to collaborate on it, and the idea needs to be evaluated, refined, iterated, combined with other ideas, and so on. These tasks make use of various criteria, such as potential value, synergies, market trends, match to expertise, and relationship to other ideas and existing efforts. There are usually several mechanisms for performing these tasks, and the mechanisms often include social networking aspects such as letting anyone comment and link to other ideas as well as having a formal evaluation group assigned (or several such groups, one per key approval criterion). Capabilities to help the vetting typically include voting, ranking, commenting, and flagging.
Although the idea management process is most easily conceived as moving ideas through a funnel that contains a set of filters, the process is not purely linear and these systems allow trial and error and iterations. Ideas can loop back to previous points in the funnel, as when they are merged with other ideas, or they can be held for future consideration. Figure 3 shows conceptually how such loopbacks happen at all stages of the life cycle, even as the focus moves from discovering to scaling.
Digitization of ideas does more than just manage the innovation process. Once recorded, ideas become a knowledge source for the enterprise, whether they are moved forward or canceled. They become information assets that can be reused, refined, or mined in future activities. This characteristic underscores the value of discipline and rigor in tagging ideas for future use. “We made a decision to be very rigorous in how we tagged and built our taxonomy for ideas that went in, so we actually can find things very easily by very specific topics,” says Jon Bidwell, chief innovation officer of Chubb.
The systems also should be capable of accepting information from and making information easily accessible to other systems. For example, a Brightidea customer exported data from an innovation campaign to a visualization tool to create a Flash presentation, allowing users to explore the information in a user-friendly manner. This was relatively easy because Brightidea’s product exposes data via a REST application programming interface (API). “That never would have happened if there was a 15-step process with three documents and four checkpoints to free up a data set,” Greeley says.
Creating an end-to-end innovation process flow depends on the ability to integrate the idea management system with other systems already used to manage products and their portfolios. For example, integration with PLM systems can feed findings from defect analysis and Lean-oriented product refinements into the assessment of related ideas, and can identify ideas for further exploration (a feedback loop that goes beyond the specific project). Or data from CRM systems could be analyzed against proposed ideas to see the overlap between customer pain points and proposed service innovations.
Use of idea management systems
Many organizations have started using idea management systems to structure and manage their innovation processes. The most visible use is in open innovation initiatives where enterprises such as General Electric Company, Cisco Systems, Proctor & Gamble, Dell, Starbucks, and others engage with their customers and the world at large to find ideas. Use of such systems is also on the rise within enterprises, including Chubb, InterContinental Hotels Group, Google, and PwC, for example.
Although rooted in the concept of ideas and their management, such tools enable a larger pool of people to be involved in the innovation process instead of limiting the activity to research and development (R&D) or product development teams. As a result, these systems allow collaboration among top management on strategies the team is developing, as well as collaboration by talent within and outside the enterprise on challenges and opportunities facing the enterprise.
Many emerging and established vendors provide solutions for idea management. Providers include Brightidea, CogniStreamer, ID8 Systems, Imaginatik, PhpOutsourcing Ideabox, and Spigit. SAP and Oracle offer solutions for idea management as part of their solution suites.
Some are offered as on-premises applications and others are offered on the software-as-a-service (SaaS) cloud-based model. CogniStreamer and Ideabox offer on-premises models. Brightidea and Imaginatik offer SaaS solutions. For a sampling of vendors that provide idea management solutions, see the sidebar on this page.
Future of idea management systems
At present, idea management systems focus on early stages of the innovation life cycle, in discovering and incubating ideas. These systems have the potential to evolve into full-blown ERP-like systems for the entire innovation process when they are integrated with other functional applications that span the acceleration and scaling phases of the innovation life cycle. The Brightidea product, for example, allows an organization to trace ideas from their origin through their evolution into proposals and funded projects. Brightidea provides the capability to manage proposals and projects, but the product also integrates with PLM or PPM systems. Imaginatik’s product allows integration with problem-solving and prototyping tools, while Spigit’s suite allows data integration with various enterprise systems.
The greatest impact idea management systems have had thus far is in reducing the friction in the generation and capture of ideas. As a result, most organizations that use them have a robust collection of ideas from which to further their innovation ambitions. Where many organizations need support is in the execution of these ideas to drive to cash or value. This is where the technologies for solution identification can make a substantial impact.
Accelerating and scaling with life-cycle and portfolio management tools
The use of idea management systems and solution identification systems is increasing, but many organizations already use PLM and PPM systems. These tools address the later stages—acceleration and scaling—of the idea-to-cash process. They shepherd the idea through the proposal, design, and manufacturing planning stages.
PLM describes a comprehensive framework of technology and services that permit companies, their partners, and customers to collaboratively conceptualize, design, build, and manage products throughout the product creation life cycle. While the innovation life cycle may focus on idea to cash, the PLM life cycle goes beyond cash to the product end of life. Early in the last decade, PLM became the primary means by which manufacturing companies achieve step-change improvements in product development processes. PLM products generally combine information from multiple systems—ranging from Word documents to computer-aided design (CAD) drawings—with role-based workflow management to streamline the flow of pertinent information to the various parties, and to ensure everyone is working from the most recent information.
Trends in global product development, the need for unified data management, and the necessity of rapid collaboration across the supply chain drive the adoption of PLM systems. The definition of PLM continues to expand to incorporate the entire new product development and launch (NPDL) process, and best-of-breed ERP and CAD-centric PLM vendors are competing for the new opportunities.
While PLM systems focus on a particular product, PPM systems look across the collection of product innovations and help companies focus resources on the products that will provide the highest value while managing the risk and uncertainty inherent in bringing new products to market. This is made possible through centralized product planning, cost estimation and forecasting, financial modeling, and creating information transparency throughout product life cycles.
A mix of traditional IT vendors and specialist firms provide PLM and PPM solutions. PLM and PPM systems are available from many established vendors, such as Dassault Systèmes, IBM, Oracle, PTC, SAP, and Siemens.
Executing ideas: Solution identification tools
Problem solving is a core activity along the entire innovation process, as Figure 1 illustrates. Problems are overcome by novel solutions, and any technology that expands support for solution identification will raise overall innovation performance. Solution identification tools take two forms. One is the theory and methods for systematic problem solving as a discipline. The other is the use of semantic knowledge management techniques to make the techniques and problem-solving capabilities accessible to all involved in the end-to-end innovation process.
Theory of Inventive Problem Solving
TRIZ is a mental discipline and method that supports systematic problem solving. Developed by Genrich Altshuller in Russia more than six decades ago, TRIZ is the best known inventive problem-solving approach. (It also is known as the Theory of Inventive Problem Solving [TIPS].) There are related methodologies and simplified versions of TRIZ.
These methodologies capture the principles behind known successful inventions. They are a result of detailed analysis and codification of millions of patents around the world and the knowledge related to them, which spans a large portion of known technical, engineering, and other disciplines.
In the days before software support, TRIZ users were trained to identify a general principle embedded in a specific design problem. The method then suggested a set of general approaches to the abstracted design problem that should be considered first as potential solutions. Thus in TRIZ, invention is using the general solution in a novel way, as it applies to the specific problem.
TRIZ solves problems by focusing on contradictions. In any system, a contradiction occurs if the increase in a useful function in one subsystem creates a harmful outcome in the same or another subsystem. For example, the need to increase strength contradicts the goal of reducing weight of the system. TRIZ works best when the problem can be phrased as a contradiction.
One classic TRIZ example involves contradiction in boat design: faster boats require narrower hulls, but more stable boats require broader hulls. In an interview with PwC, Peter Hanik, president of Pretium Innovation, describes how TRIZ principles anticipate the solution. In this case, the separation principle calls for separation followed by integration. Here’s what that means in practice: the narrow hull is produced at the subsystem level while the harmful side effect, compromised speed due to a broad beam, is counteracted at the system level. Integration means to establish a relationship between elements when the separation is performed. The result: a catamaran, which is a remarkably stable and very fast boat. (See Figure 4.) TRIZ results in a design that resolves the contradiction, making compromise unnecessary.
“Just as you track your leads in a sales system, we identified the idea as the starting point when directed work on a particular innovation project begins.”
—Matthew Greeley of Brightidea
Managing knowledge to support problem solving
The key to using TRIZ or related inventive problem-solving methods is recognizing patterns of similar contradictions and discovering solutions based on knowledge resident in patents or the experience of the enterprise. Modern software, particularly those that use semantic knowledge management, can considerably simplify this analysis and pattern recognition task, helping to abstract the problem with function modeling or root-cause analysis support. Such software also can simplify the pattern-recognition step through a keyword search augmented to reflect the cause-and-effect nature of solutions. It then finds specific instances of related problems and solutions from all industries and conceptual domains, positioning them for consideration by the problem solver.
As a result, the knowledge sources become a valuable innovation asset in their own right. By combining semantic knowledge with search, people can “find very quickly and precisely the concepts that they need to understand so they can make good decisions about how various potential options and ideas map to these different types of [business impact] metrics,” says James Todhunter, CTO of Invention Machine.
Building an enterprise innovation life-cycle platform typically will involve restructuring and managing information to support innovation. Building such a platform involves the introduction of knowledge databases with strong semantic analysis components tuned to digest and properly index documents most closely related to invention: patent repositories, lab manuals, research papers, Web sites, and so on. Tools that bring together these capabilities include Invention Machine’s Goldfire and software from Ideation International and IDEACore.
Goldfire’s Insight module supports research activities aimed at innovation. It uses semantic research technology to provide direct access to concepts as problems and solutions from inside and outside the company. The module creates a semantic knowledge base from all available knowledge, personal file systems, lab notes, Web sites, technical literature, and others. Insight captures an organization’s technical knowledge, past experience, and expertise, and makes it available to others in the organization when they need it. When it indexes the sources, Goldfire tries to understand the cause-and- effect relationships between the concepts. It can be accessed using a natural language interface. Users can find solutions to their problems from past patents and thousands of technical documents, identify relationships between concepts, and find precise answers to their innovation challenges.
Goldfire includes support for many innovation methods used across the innovation life cycle. Methods such as Value Engineering and TRIZ focus on problem definition and encourage creative thinking. Tools that perform root-cause analysis and device or process analysis aid in problem identification and resolution, while rich patent analytics help organizations see beyond current markets and technologies and identify solutions from other domains.
Some organizations develop their own solutions. IDEO, a global design firm that helps clients innovate and grow, has a knowledge capture and sharing system called IDEO Tech Box to store past problems and their solutions. Tech Box is a combination parts and materials library, database and Web site, and organizational memory. It allows IDEO to archive its experience gained from work in many industries and share it across its worldwide network. The Tech Box is a valuable resource that designers and engineers use to gain inspiration, break out of a holding pattern, or avoid reinventing the wheel.
When innovation is viewed as an end-to-end process that spans the life cycle from idea to cash, a range of emerging and established technologies play a role in raising the innovation potential of the enterprise. The technologies identified in this article do two things. They systematize and structure key activities all along the process. And they reduce friction and bottlenecks at key stages in the innovation life cycle.
Idea management systems simplify and streamline the process of surfacing, collecting, and reviewing large volumes of ideas. By digitizing the notion of ideas and creating transparency around the progress of any idea, these systems structure what has been an ad hoc process. In reducing the friction in the generation and capture of ideas, the bottleneck moves to how enterprises will execute on the ideas.
The execution is tied directly to the role of problem solving. Problem solving is core to how innovation happens and progresses. Inventive problem-solving methods such as TRIZ enable organizations to have a systematic approach to surfacing, defining, and solving problems.
Semantic knowledge management techniques make these methods accessible to many more people and tap into problem-solving knowledge in patents, within the enterprise, and in the broader technical and other communities. In addition to problem solving, execution also requires robust support during the accelerating and scaling stages of the innovation life cycle; here, the use of existing PLM or PPM products play a role.
Together these technologies provide some of the underpinnings for the technology infrastructure to support the end-to-end idea-to-cash process.