How to Link Strategies to Six Sigma Projects

In this article, we will focus on the important correlation between Six Sigma projects and senior management's goals and initiatives.

One of the most prevalent problems of many Six Sigma projects is the difference between the goals of the project and senior management's vision for the company, or its strategy. The creation of a Strategy Deployment Matrix helps to bridge the differences and develop a cohesive strategy for both the project and management of the company.

Strategy Deployment Matrix

In order to create a Strategy Deployment Matrix, a Six Sigma team must:

(a) Develop a list of all strategies of the company.

(b) Develop a list of all the metrics that the company uses to measure success. A metric can be something as simple as the number of customers, or as complicated as the level of quality that the marketplace ascribes to its products.

(c) Determine how strongly each strategy relates to each metric.

(d) Calculate the "weight" (or proportional strength) that each strategy relates to each metric.

We will use a few examples to illustrate exactly how a Strategy Deployment Matrix works.

Let's assume that a company lists three strategies:

  • Revenue Growth.
  • Keeping up with technology.
  • Good product features.

The company uses the following metrics to measure their company's performance:

  • The number of new products that were brought to the marketplace.
  • The amount of revenue from new products.
  • The rate of fast manufacturing.

Now that the strategies of the company are established and the metrics are defined, we will establish how they relate to each other. The company decides that the following Strategy-Metric combinations have a significant (or "high weight") correlation:

  • "Revenue Growth" (strategy) and "Revenue from new products" (metric).
  • "Keeping up with technology" (strategy) and "Fast manufacturing" (metric)

By comparison, for example, the strategy of "good product features" does not strongly match any of the existing metrics that the company uses. So the Strategy Deployment Matrix would assign that relationship a very low weight, or strength of correlation. The purpose of developing the matrix is to limit the list to only those strategies that senior management have identified that can be easily measured using metrics.

Using the examples above, this hypothetical company wishes to stress revenue growth by introducing new products on a regular basis, and they wish to keep abreast of the latest technology in order to manufacture products in a timely manner. This sentence would be the starting point for creating the company's mission statement, which is a brief statement that succinctly outlines the company's strategy and priorities.

The mission statement will help to alleviate the differences between the objectives of the Six Sigma project and senior management's goals and strategies.

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We will discuss analyzing data in a Six Sigma project in greater detail in later chapters. This analysis is the most important function of Black Belts who are working on a Six Sigma team. Throughout the project, the Black Belts of our hypothetical company will closely monitor data that shows how fast (or how slow) manufacturing has become in the company. They will also measure the revenue from new products. These two metrics will most certainly not be the only metrics measured throughout the project, but any deviation in these two specific metrics will be given much closer attention and such deviations will be brought to the attention of all stakeholders in the project, especially senior management.

Scope Creep

As we discussed in the previous chapter, the goal of many companies who wish to lead in the marketplace is to exceed their customers' expectations. Companies have limited resources and they usually have shareholders who they must answer to. As such, they must spend their resources wisely by limiting the scope of each Six Sigma project to only high priority initiatives as defined in the Strategy Deployment Matrix.

Scope creep is the term used to describe deviations from the original goals of a project. One of the principle reasons that most projects (both Six Sigma and non-Six Sigma) fail is due to scope creep. Each element of a project must be closely controlled. When costs and goals become uncontrolled, the project is doomed to failure.

Customer Demands and Budgets

We discussed how companies gather data from their customers and listen to their requests. The next logical step is to decide how a company is going to pay for such changes, or requests. The process begins with translating customers' language into employee language. If a customer says that they want a coffee maker to be "quieter," an engineer will take this word and translate it into words that an engineer needs to use in order to redesign the machine to meet the customers' needs. But, as we have discussed, resources are limited. How much does the company spend on making their machines quieter? How high of a priority is it? The Strategy Deployment Matrix helped the company identify their strategies and now it is time to assign a cost to each initiative.

A cost might not be discussed in terms of money. It might be regarded in terms of a trade-off. A quieter coffee machine might be able to be produced without spending more money, but the features of the machine might change. Will these changed features increase or decrease customer satisfaction? Only the customer can answer these questions. In a customer driven enterprise, the engineers do not make these decisions. If a feature is important to a customer, money must be spent to make the machine quieter rather than changing the machine's features.

Structured Decision Making

Not all decisions are easy. There are so many factors that go into the decision making process of how to, in this example, build a better coffee machine. The first step is to revisit the list of strategies, or goals, of the company. Through the use of surveys, focus groups, and other channels, the company will compile a list of concerns and questions that customers have about the product. Are there some structure or similarities to the concerns and questions? Do many of them have something in common? To make a structured decision about how to make their coffee machine quieter, the company must find out if there are similarities in their customers' concerns. It will give the company a clearer picture of what the customer wants.

But, in order to determine if a structure exists within customers' concerns, data must be analyzed. The best method to measure customers' concerns from an analytical perspective is to have the customers assign weight to each of their concerns. In customer surveys and interactions, companies should ask customers to rate the importance of features and other statistics using a scale (or weight) from 1 to 10. This gives numerical significance to their answers and gives the company an opportunity to measure satisfaction more conclusively.

Six Sigma projects rely on data to succeed in achieving their goals. If the data can come directly from the customer, the project will be in a better position to make significant and substantive changes which will make the company more successful and profitable.

Attributes of Good Metrics

Decisions by senior management or a company's board of directors must use objective data to accurately report on the needs of a company's customers. Not all data is objective and there are varying degrees of quality for each piece of data captured. The strength and effectiveness of a Six Sigma project will depend greatly on the quality of data that it has access to. We discuss the merits of a customer driven company and how companies must consistently allow their customers to set policy. Now, we will discuss the merits of data driven management.

Priorities are established by companies based on a wide variety of factors, and data enables management to quantify everyone's needs, including customers, shareholders, suppliers, employees, and managers.

In this article, we will take a closer look at metrics and learn the characteristics or attributes of good metrics. What should a company measure, and why?

Poorly chosen metrics can easily lead companies to institute the wrong behavior, to reward the wrong initiatives, and to become detached from their original goals. Metrics chosen for a Six Sigma project should have the following attributes:

  • All metrics should focus on the customer and measure the customer's experiences. Examples include the quality and dependability of a product or service, how long it takes to deliver a product, innovation, cost of producing the product, and, of course, customer satisfaction.
  • Metrics should be continually captured over as long a period of time as possible. A one-time snapshot of data is not as useful as analyzing trends over time.
  • Metrics should be clearly and fully reported, additional analysis should not be required to understand the exact meaning.
  • Metrics should be directly related to the company's goals and initiatives, especially the goals of the Six Sigma project. Superfluous metrics that do not report on adopted strategies should not be captured.
  • The metrics should be determined by representatives from various departments that will process the data: the data gatherers as well as the analysts and managers.

Measuring Performance

Now that we know what constitutes good data, we will look at how data is collected, measured, and analyzed in a Six Sigma project.

  • Phase 1. Performance Category. It's important to start by dividing metrics into specific categories. The categories reflect the mission of the company and allow for a more detailed analysis of performance. In a service oriented business, for example, categories might be reputation of service, timeliness of service, price of services, and so forth. Categories should be influenced most especially by the goals of the Six Sigma project. To determine the most effective categories, it is best to ask, "What are we trying to accomplish?"
  • Phase 2. Performance Goals. A target, or goal, should be established for each category developed in Phase 1. The target should contain specific actionable words. For example, if a category is timeliness of service, a performance goal for that category might be to answer all customers' phone calls within 5 seconds. The goals should be specific and clear. If the goals established in this phase are too complicated, overly simplified, or just unclear, it might be necessary to adjust performance categories in phase 1, rewrite goals, or both.
  • Phase 3. Performance Indicators. Each goal decided in phase 2 should have an indicator assigned to it, or several indicators. An indicator shows how progress is being measured. If a good indicator cannot be chosen, this might be a sign that the goal chosen is not as important as originally thought. The goals listed in Phase 1 are, and should be, under constant review during this process.
  • Phase 4. Data Elements. This is the phase when a company analyzes the actual data points, or elements. Data elements should be limited only to those data that can be directly influenced by the company. A project should not attempt to influence data elements that are beyond its control.
  • Phase 5. Parameters. Outside factors should be considered in this phase. As an example, if the economy is in a downturn and one of the goals of the project is to double revenue, this phase is where the company decides that this goal needs to be abandoned. Outside parameters serve to set the context for the goals and they describe the business environment in which the company exists at a given moment in time.
  • Phase 6. Means of Measurement. This is the phase where the company translates the data into action words. The analysts on the project will create a simple statement for each goal that answers the question, "How will this data be analyzed?"
  • Phase 7. Notional Metrics. This is the phase where you gain consensus from everyone on the project about what they want the data to demonstrate. It is the point where the team creates conceptual, broad metrics. From these broad metrics, you can continue to the final phase of creating specific metrics.
  • Phase 8. Specific Metrics. In this final phase, each data element is fully and clearly described and instructions for data collection are written. The team will also describe how each data element will affect the company's performance.

The Balanced Scorecard

Agreeing to commit to a Six Sigma project is a huge step for a company. The amount of time and resources that will be spent is enormous and it will change the company in sometimes irrevocable ways. Naturally, the leaders of the project want that change to be positive, but if the change is negative, it could mean disaster for the company's future. It's important for a company to set the right goals.

A balanced scorecard is used throughout the Six Sigma project to give the company a constant snapshot of the status of the project. More importantly, the scorecard ensures that the company's goals are derived from all interested parties, not just one. Customers are an important source for goals, but so are shareholders, employees, and suppliers. The goals must be balanced and the balanced scorecard will help in this important consideration.

Specifically, the balanced scorecard will show metrics from four major areas: customers, finances, internal processes, and company growth. An enormous amount of improvement in one of these areas often comes at the expense of another. Viewing a high-level view of all four areas at the same time helps an organization maintain balance in their progress.


On a balanced scorecard, limits will be displayed next to each metric reported. A limit shows the bottom and top level that is expected for each metric. If a reported metric falls outside of these limits, it alerts management that something is unusual. Anything unusual should be investigated immediately. Goals might need to be changed or the integrity of data collection might need to be investigated.

There are instances when a company will intervene and change direction in the middle of a project. In these instances, some metrics might be outside of the generally accepted limits and management may decide that no intervention is required.