The ongoing development of innovative solutions is as essential to business success as is the generation of new blood cells to the functioning of the human body. Yet most businesses find innovation elusive. For every success, the company takes myriad false starts; digressions into unproductive areas; and steps toward developments that look promising but ultimately prove impractical because they're too costly, too late, or lack a real rationale for existence. Often these disappointments stem from the mistaken belief that innovation will flow freely if only it is made a core corporate value, there is a free flow of ideas, and employees are given time to pursue independent research. While such a business environment is helpful, free-form, winging-it innovation also leads to waste: spinning wheels, lost opportunities, and sometimes chaos.

Today, some businesses are turning to Integrated Enterprise Excellence (IEE), an enterprise system that provides structure for integrating innovation with analytics. It consolidates the Lean approach to waste reduction with the Six Sigma quality improvement methodology — and incorporates a pragmatic, no-gaming scorecard, which leads to the right activities and brings in the voice of the customer. IEE uses the familiar Six Sigma DMAIC — define, measure, analyze, improve, control — project execution road map not only at the project level, but at the enterprise level as well. (At the project level, the road map is referenced as P-DMAIC, while at the enterprise-process level, the road map is referenced as E-DMAIC.) The analyze phase of the enterprise-level DMAIC road map blends analytics with innovation as part of the corporate strategy-building process.

Where Lean Six Sigma Falls Short

When Lean meets Six Sigma, all projects begin with a problem statement, so the Lean Six Sigma framework is, de facto, a problem-solving system. Adding Lean expands traditional Six Sigma defect-reduction problem statements to include the reduction of waste in both time and resources. Yet the aim of typical Lean Six Sigma deployments is modest. A steering committee or some level of management selects projects with two objectives: to improve a process and/or to provide certification for an employee. When certification is the overriding goal, the company usually selects low-hanging fruit for the initial project, and that first project is often the last project the person completes. Either way, this system is a “push” approach to project creation; people hunt for projects because they need to get certified or because members of the Lean Six Sigma steering committee want to brag about how much money they saved the company. Such a system of project selection can produce initial successes, since the projects with the most potential benefit to the organization are obvious to everybody without enterprise analysis.

However, it has been my experience that as time goes by, companies using a push approach to choosing Lean Six Sigma projects find it increasingly difficult. Even for completed projects, financial benefits might be debatable; the project team might report $100 million in savings even if nobody can find that money. After some period of time, people have a hard time agreeing on which projects they should undertake. In addition, most Lean Six Sigma deployments do not look analytically at the organization as a whole during project selection. If a company selects projects without identifying the overall enterprise constraint, it can create counterproductive behaviors and the suboptimization of processes. In the end, the company as a whole might actually end up worse off as a result of a Lean Six Sigma project. This risk increases when the Lean Six Sigma deployment creates a functional entity to manage project selection and that entity remains separate from operational scorecards and from other business units.

In the IEE framework, in contrast, the organizational value chain is examined for improvement opportunities during the E-DMAIC analyze phase. This enterprise analysis utilizes Theory of Constraints, Lean, and Six Sigma tools to build targeted strategies for improving the business as a whole. These strategies then lead to the identification of improvement needs in value-chain performance metrics, so project creation is driven by a pull — rather than push — approach. The result can be either process improvement or R&D design projects that focus on developing innovative new solutions. Emphasis is given to creating financial benefits that will be felt by the entire company, not just at the individual sub-process level. In addition, the IEE project-selection process does not demand blind obedience to completion of a given number of projects in a set time period. Instead of prioritizing projects based on their presumed importance to one functional area, managers within an enterprise process management function analyze what can be done to make the enterprise stronger and more competitive as a whole.

When a company implements E-DMAIC, the enterprise process management function orchestrates the integration of existing enterprise processes with the new methodology, which can lead to an improved overall enterprise system that is more data-driven and sustainable. This can lead to significant reductions in waste and in firefighting activities. At the same time, activity checks and balances that ensure continuing improvements and timely project completions are part of the E-DMAIC control phase.

When DMAIC Goes Enterprisewide

Exhibit 1, on page 18, illustrates the nine-step E-DMAIC method for aligning projects with business needs. Notice that three of the nine steps involve the establishment of metrics. When creating metrics, balance is important. For example, you don't want to sacrifice quality to improve on-time delivery. At the same time, you don't want to force an unnatural balance throughout the organization like that suggested by the Balanced Scorecard, in which every organization is expected to give equal weight to the financial, customer, internal business process, and learning and growth perspectives.

The IEE approach tracks two types of high-level metrics as part of the company's value chain: 30,000-foot-level (operational) metrics and satellite-level (financial) metrics. An IEE company uses satellite-level metrics to track performance in areas such as financial revenue growth and profit margins. Once it has set performance targets for its satellite-level metrics, it builds strategies for achieving those goals. Then, from those strategies, it determines goals for its 30,000-foot-level metrics in an analytic/innovation assessment of the enterprise as a whole. The 30,000-foot-level metrics can include defective rates, on-time delivery, inventory, safety, product development time, and production lead time. Both types of metrics tie into a system for monitoring customer response; see Voice of the Customer on page 20.

The IEE approach to metric selection is important because achieving the right balance among metrics requires attention to the entire enterprise value chain. The outputs of a system are a function of the whole system, not just individual processes. System performance is a function of how well constraints — such as internal resources, external markets, or policies — are identified and managed. When we view our system as a whole, we realize that the output is a function of the weakest link. The weakest link of the system is the area that constrains output. If we do not exercise care in choosing metrics, we may focus performance improvement efforts on a subsystem that would not impact the overall system output even if it were substantially improved. Projects chosen for attention in a Lean Six Sigma setting must be those whose betterment would optimize the overall system.

Neither satellite-level nor 30,000-foot-level metrics should be bounded by calendar periods; instead, an IEE system determines whether a process's output, as measured by the appropriate metrics, is predictable. (See Common Cause: How Six Sigma Can Drive Better Management Reports in the May 2007 issue of BPM Magazine.) If the process is deemed to be predictable, the system can not only present how the process performed in the past, but also make a predictive statement about the future. This view of the company's functioning can change behavior from a focus on doing whatever it takes to meet the goals for the quarter (in the extreme, the Enron approach) to improving the system at a lower level so that the enterprise's overall output improves.