Six Sigma and KPI’s: Return on Innovation Investment



course, most professionals are familiar with Return on Investment. Yet, another more insightful key performance indicator is your Return on Innovation Investment (ROII). Most companies and organizations invest a percentage each year into innovations. However, what is your return on these investments? In this article, we will analyze ROII, what it is, and why every Six Sigma professional should be using it.

What is Return on Innovation Investment?

 Return on Innovation Investment is a calculation that assesses how much revenue certain innovations make for an organization. On average, companies will invest 3.5% of their revenue into innovations each year. These categories include research and development, along with innovation activities. More specific industries, such as manufacturing and high-tech will invest greater percentages. Because organizations invest in these innovations, it’s important to measure how effective they are at generating revenue. That’s where ROII comes into play. This calculation provides insight into your innovation activities while comparing it with returns from other investments.

How to Calculate your ROII

 While there are multiple ways to calculate your ROII, the most effective way is in retrospect. First, you calculate the difference between your net profits from new products/services and their respective innovation costs. With this figure, you then divide by the respective innovation costs. You can calculate your ROII for future estimations. However, this requires more time and resources and may not be highly accurate.


While calculating your ROII is important, how often you do can be more so. Most organizations will calculate their ROII every quarter, at the end of an innovation project, or after a year. When and how often you make this calculation can greatly affect your rate of return. However, when you do calculate your ROII, you will have a percentage of your return. This directly correlates to how long it will take to regain. For example, an ROII of 25% each year will require four years to payback for your investment.


Another key factor in calculating an accurate ROII is where you source your data. It’s important to extract the correct data from the innovative investments you want to assess. Typically, you can use accounting and project data that team members will organize.

Why You Should Calculate your ROII

 While your organization may invest heavily into various departments, it’s important to understand your innovation investments first hand. First, innovations can either make or break efficiencies within your company. Because the Six Sigma philosophy focuses on improving efficiencies, you must calculate where these are being made. Likewise, your ROII is an ideal way to reflect on past projects and see where improvements can be made in the future. Although ROII can be used for future estimations, we do not advise this because of its high cost and inaccuracy. Furthermore, your return on innovation investment can help decide if your organization needs to devote more or less funding to it each year. If you see a negative trend for most innovations, you may not need as much funding as once predicted.

Making the Most of Quality Data


Plant-floor quality issues tend to focus on a company’s technical resources. When products fall out of spec, alarms sound and all hands are immediately on deck to fix things. Despite large technology investments to monitor and adjust production processes, manufacturers are still bedeviled by quality problems. The issue is not a lack of technology. It is a lack of quality intelligence.

When problems occur, manufacturers must obviously fix them. But the typical organization expends much more energy reacting to problems rather than preventing them. This is true despite our understanding that, “an ounce of prevention is worth a pound of cure.” We know that proactive measures can be immensely profitable, and yet our limited quality resources spend little time identifying strategic imperatives for avoiding problems. Instead, most of their time is spent responding to issues. Today’s quality professionals are too preoccupied with just fighting the fires that rage on shop floors.

Quality and the big picture

The most successful, forward-looking and competitive companies I work with focus on proactively preventing problems. How? By taking a holistic view of quality. They regularly step back to summarize and analyze large amounts of quality data. Stepping back gets them away from the fires, and out of the routine of fixing issues.

Imagine aggregating all of your quality data for the last month across all products and production lines. Doing so would allow you to see the nuanced quality differences between regions and plants. It would tell you where systemic issues need to be addressed and help prioritize improvement efforts. In other words, aggregating data allows you to see the big quality picture.

Today’s manufacturing plants make a dizzying variety of products. So you may be wondering how wholesale information can be extracted from vastly different parts, material types, and specification limits. To summarize information across different parts, data normalization can be used to allow fair comparisons even between disparate items. Today it is just a mathematical exercise; easy to perform with software, making data unification and summarization a reality.

Stop “storing and ignoring”

When critical features fall out-of-spec, alarms blare and support personnel descend on the shop floor and get the issues fixed. After completing their tasks, they quickly move on to the next daily priority or fire drill. In this case, at least the alarm data were used for solving the problem.

But what happens to data that triggers no alarms? What about data that meets specification limits? Most will say that if data is in-spec, then it is good enough. And that is the problem. When data is considered “good enough” it is just stored in a database, rarely to be seen again. The error here is assuming that since the data didn’t trigger an alarm, it contains no useful information. If data is not reviewed or analyzed, then expect to be blind to the information it contains. The truth is that value exists in any data you collect. Otherwise, it shouldn’t be collected.

When companies ignore in-spec data, they are throwing away enormously useful information. Many companies I have worked with have turned orphaned data into gold by extracting previously unknown information from it. It was unknown simply because they considered the data to be “good enough.” As a result, they were blind to the information the data contained. These experiences have me conclude that the greatest potential for modern quality improvement comes from aggregating and analyzing data that actually falls within specifications.

Seem odd? Not to me. Think of how frequently parts don’t meet specs. It’s rare. That means that very few data values are viewed for problem-solving purposes. And if those few data values receive the lion’s share of attention, what happens to the huge amount of data where no problems exist? They are stored and ignored.

And it’s getting worse. Because modern technologies support automated data collection, far more data is currently being gathered than in years past. This means that the amount of data being ignored is increasing. It’s staggering how much data is available and yet how little of it is ever viewed.

The reality is that companies rarely go back and look at data that is in spec. Yet, there is rich, valuable information hidden in those overlooked records. Imagine being an operations director who oversees 50 plants. If you could roll up all of your critical quality data across those locations, you would immediately have a holistic view of your manufacturing operations. You could identify which regions are the best performers. You could highlight the plants and production lines with the highest quality costs. You could pinpoint where defect levels could be reduced and which plants require attention to minimize the probability of recalls. And your company could become more competitive as a result.

Rather than simply reacting to quality problems, manufacturers need to direct their attention and time to proactively attacking quality. How? By regularly evaluating the massive amount of overlooked data that they already have.

Data aggregation through cloud technology

Traditional on-premises software solutions aren’t great for deploying across an enterprise. But cloud-based quality software platforms are. Since cloud-based solutions are securely hosted by vendors who monitor and maintain system infrastructure, the need for on-site IT support is minimized and capital costs are greatly reduced. The nature of cloud-based systems makes large-scale, multi-plant deployments fast, easy, and inexpensive, ensuring benefits are enjoyed sooner rather than later.

Plus, cloud-based systems connect manufacturing sites across the internet, support standardization, and store quality data from multiple plants in a centralized database. Because data is stored in one place, quality professionals, engineers, managers, and others can easily view the big picture of quality. A single data repository is ideal for supporting corporatewide quality strategies and initiatives.

Cloud-based quality systems should use simple web browsers, empowering quality professionals to break through geographical, cultural, and infrastructural barriers to connect facilities around the world—and provide data aggregation capabilities that can unlock critical information for driving quality improvements on a large scale.

The capability is here and the technology is inexpensive. So what keeps quality professionals from enjoying enterprisewide cost and defect reduction? It’s those fires you keep fighting every day. Don’t just snuff them out—prevent them in the first place and use the time savings to re-imagine how quality can transform your organization’s performance.

Six Sigma and KPI’s: Klout Score

Each day, new companies, organizations, and individuals join the online community of social media. Over the past decade, social media has completely revamped how we conduct business and gain traction. In the past, you would advertise on billboards and in magazines at high costs. Now, you can advertise your organization at nearly no cost and gain more interaction. However, just because you’re now on social media doesn’t mean you will thrive. Each organization is different and there are various ways you can alter your interaction with existing and potential customers. Yet, before you change up your online presence, you must see what traction you do receive. For this, we recommend calculating your personal Klout score.


What is a Klout score?


By definition, your Klout score is a measurement of your overall online influence ranging from zero to 100. First developed by a young start-up company, this underlining algorithm uses over 35 variables to measure your online presence. By simply downloading the application, you can connect your various social media accounts and it calculates their scores automatically. Currently, the application measures scores for Facebook, Twitter, and LinkedIn accounts only.


Your Klout score is a compilation of three separate scores. First, there is your True Reach. This score measures the size of your audience by assessing the number of followers, friends, and how often they interact with your account. Second, there is your Amplification Score. From 1 to 100, this score measures the likelihood that your messages and posts will generate interactions. Third, you have your Network Score. Likewise, this score also ranges from 1 to 100 and measures how influential the engaged audience is.


Klout score and Six Sigma


Of course, the goal is always to gain more followers, friends, likes, and retweets. However, there are smarter ways you can gain traction while maintaining efficiency. For Six Sigma professionals, Klout scores calculate exactly how much influence you have within your online market. One of the most appealing characteristics of the application is the automatic and continuous data collection. While other market share analysis requires a team of professionals, your Klout score calculates automatically. Typically, your score updates every month. However, depending on your needs, you can change this.


When calculating your Klout score, there are three important things to remember. First, the application uses a finite number of variables. While some organizations may have data for all of these, others will not. For the most accurate calculation, make sure your social media accounts provide the necessary data. Second, social media influence changes drastically, and often. Every day there is a new hot topic, popular idea, or inspirational post. Likewise, it can be difficult to monitor the ever-changing trends and remain relevant. To combat this, we recommend appointing a social media manager to your team who can provide accurate analysis in combination with your Klout score. Last, always compare your score to both competitors and customers. In general, a score above 60 represents a strong online presence and influence. However, since each industry is different, compare your score to others and see where you rank.

Life After Master Black Belt (MBB)

For many Six Sigma professionals, the ultimate goal is to become a Master Black Belt (MBB). This certification is the top-ranking Belt one can achieve while following the methodology. However, you do not simply become a MBB overnight. Most professionals spend years in a technical role before engaging in the appropriate training. Likewise, the correct MBB training and certification course require weeks of participation and experience. However, once you do become a Master Black Belt, you achieve a goal most others dream of. Yet, what is next for your professional career after achieving Master Black Belt? Here are a few things you can do with your newfound certification.

Working on Better Projects

As a Master Black Belt, you will oversee almost all projects. You will report directly to executive management and stakeholders, when necessary. However, your role as a MBB is directly dependent on the project at hand. Sometimes, such qualification is not needed. In this case, you will work as a lower Belt or assist others in project operations. Yet, in other more dynamic and complex projects, your skill set is in high demand. Because these projects can vary in their availability, your role as a MBB might fluctuate. Keep in mind, though, that your qualifications alone will put you above other Six Sigma professionals. This means leading higher profile projects, more often!

Providing MBB and Other Training

Another way Master Black Belts spend their time after certification is by offering training to others. Because of your high certification, you can offer training to all levels of Six Sigma professionals. Whether you chose to offer private training one-on-one or work for your organization as a trainer, the options are endless. Many professionals find this opportunity as a great way to gain greater leadership experience. Since Six Sigma focuses on improving processes and reducing variation, you will lead your peers towards greater efficiencies and smoother operations.

Perfect Your Skillset 

While not strictly limited to MBB’s, another option is to seek training for weaker skills. Do you want to improve your understanding of advanced SPC methods? Do you need to review non-parametric analysis? At this stage in your Six Sigma career, you have covered countless topics over hundreds of hours. Sometimes, information can get mixed up or misplaced. Take this opportunity to refine your skills that you might struggle with. Of course, it doesn’t hurt to review material you already perfect.

Become a Master Black Belt Consultant

Finally, many MBB’s who have outgrown their corporate molds become independent contractors, working for themselves. While your organization may not be able to offer you the next challenging project or role, you shouldn’t remain stationary. Become your own employer and offer your technical skills as a service to other organization. Many Belts wander down this route, even as early as Green Belt certification. However, with the level of training and experience you have, you will be a step above other Six Sigma contractors.

Call it What You Like, but Success is Spelled DMAIC

We are running a series of sorts on different companies that have implemented Six Sigma into their company culture, and in turn have achieved monumental success. Today we will talk about The Vanguard Group. They are an investment management company based out of Malvern, Pennsylvania, and they have over $4 trillion dollars in assets under their management.

We are talking about trillions of dollars, not millions or billions…so let’s see what they are doing!

First of all, when you log onto their website, they tell you their strategy. “Our Long Term Strategy? Put Clients First.” What the phrase lacks in sophistication, it more than makes up for in intent, and of course their ultimate success.

How Six Sigma is a Living, Breathing Way of Life at Vanguard

Vanguard has literally institutionalized Six Sigma into the entire Vanguard group organization. This was shared as a talk at the Vanguard Group WCBF 2nd Annual Conference Six Sigma for Financial Services in New York, back on May 11th 2006.

Now fast forward to present day and they have assets in the trillions, so obviously implementing Six Sigma to the entire organization has its benefits and rewards.

Vanguard’s Everyday Approach to Excellence

DMAIC, which stands for Define-Measure-Analyze-Improve-Control, is the template that Vanguard uses everyday. Let’s see how well you can spot each acronym in their company process for excellence.

The jargon is different but process is Six Sigma. They use a dashboard, which is created by the team for the team to clarify exactly how the individual performance impacts the team, the department and ultimately the entire company.

Voice of the Crew: Here the crew members are encouraged to suggest what can be done to improve performances among fellow staff; this also helps identify and track suggestions made to supervisors. Crew led forums are done on a weekly basis for constant improvements as well as to maintain recent changes.

Broken Windows: These are seen as opportunities to improve; these are also seen as having an obvious root cause followed by an obvious solution. These would be quick fixes with quick wins that would have an immediate impact on the client or department and would become part of the improved process. Since the crew is encouraged to be proactive, morale is usually increased after this process.

Crew Development: This is what Vanguard calls the growth of crew members to become effective leaders.

Back to Basics: This is Vanguard’s program that focuses on people management. This program entails one-on-ones, personal performance measures, training, rewards and recognitions.

For more information on our courses or services, please visit


For the past several years, new technology has been the focus of healthcare as an old industry looks for new ways to improve patient care and provide faster, more efficient services.

However, technology alone is not the answer. How that technology is applied can make the difference between a successful operation and one that struggles. To make the application of technology as efficient as possible, some in healthcare have turned to Six Sigma.

A case in point is Boston-based Shields Healthcare Group, which provides MRI, PET/CT and radiation oncology services at more than 30 hospitals in the New England area.

In a recent Health Information and Management Systems Society (HIMSS) conference in Orlando, Shields Chief Information Officer Chuck Spurr talked about how implementing Six Sigma proved to be a “change agent” for the company.

The Need For Process Improvement

Spurr spoke at a HIMSS conference forum called, “Driving Success With Collaboration and Six Sigma.” His talk focused on the idea that while new technology offers many improvements in healthcare, it also requires constant reevaluation of processes and a commitment to making them more efficient.

Shields turned to Six Sigma to accomplish that goal. The process improvement methodology provided Shields with the tools it needed to develop a system that gets various healthcare departments – each often working with their own software systems – to work together.

Six Sigma, started at Motorola in the 1980s, first focused primarily on manufacturing. But in the ensuing years, Six Sigma has been adopted by businesses across a wide variety of industries.

This has led to a growing number of people in business earning certification in Six Sigma and taking on a leadership role in improving a company’s operations.

Spurr himself is a Six Sigma Green Belt.

Key Elements of Six Sigma

In an interview conducted at the convention, Spurr talked about using Six Sigma for collaboration and the importance of communication overall.

“Six Sigma was our change agent,” Spurr said.

Communication is vital, he said, to ensure that software flows well across all systems within a company. A software product must be able to meet all the needs and answer all the questions of each different department, each of which may work with a system of their own.

Six Sigma has helped refine those processes, Spurr said, which can include issues such as cross-departmental communication and adding the right software “bolt on” to help individual systems work together.

He said Shield did not attempt to adopt every aspect of Six Sigma, but rather looked at areas that could immediately help the company’s performance.

Spurr said four key elements within Six Sigma proved vital. He said Six Sigma:

  • Tells you the direction a company is heading
  • Makes a company assess the current efficiency of its operation
  • Allows you to make quick changes
  • Allows you to develop methods for measuring success

“All wrapped around that is the data,” Spurr said. “You let the data drive you, which is a good thing when you are looking at a change agent.”

One of the keys for Shield was the Six Sigma methods of measuring success. As with other kinds of companies, all the data gathering and number-crunching changes nothing if there is no ability to measure the impact of changes.

“If the needle moves in the right direction, that’s awesome,” Spurr said. “If it doesn’t, that’s OK, too, because now you know what’s going on and you can react pretty quickly to it.”

Done in One: The Importance of First-call Resolution

For most contact centers, nearly one-third of inbound calls are repeat callers who weren’t satisfied the first time they called. More often than not, the antiquated switches that contact centers use don’t do a great job of reporting on the true first-call resolution (FCR) rate in a given center, so the problem may be even worse than it appears. Why is this?

Think of the iceberg analogy than Lean practitioners often use to explain cost of poor quality and the hidden costs that fall below the “water line.” What rises above that line is easy to quantify – it is the lowest-hanging fruit, so to speak, even though it is highest on the berg. Below the line, especially in contact centers, are problems like repeat callbacks, which is the opposite of FCR.

In pre-Six Sigma days, FCR at a call center was a blue-sky, nice-to-have metric, but nothing that managers held agents accountable for achieving. Instead, they opted for metrics focusing solely on time, like AHT (average handle time = talk time + post-call wrap up and any hold time during the call) or ASA (average speed of answer = how fast you pick up the phone).

What these metrics actually do is incite bad behavior. For example, an agent can keep both AHT and ASA low by just picking up a call and immediately hanging up on the customer, something many of us have experienced when we have phoned a call center. The agent AHT is an average of the daily AHT for a given time period, so naturally, if they hang up, they will have an AHT of a few seconds. Mix that into the normal AHT of an agent and, suddenly, their monthly stats look the lowest of any other agent.

See what I mean by inciting bad behavior? We like to call this “agent badness,” though personally, I think it is more of a sign that the agents are not getting adequate coaching (but that is for another article). AHT is influenced by multiple, equally likely root causes, so pinpointing improvements will only frustrate your Black Belts. I do not suggest contact center AHT projects for Green Belts ever, unless they are working on addressing a component of a larger Black Belt project.

By shifting your objective to improving FCR, however, you will have a much easier time proving and sustaining your results, namely reduced cost of goods sold and improved customer satisfaction ratings. A focus on FCR will also reduce customer churn and improve agent morale.

First, it helps to understand the inputs that affect FCR performance:

  1. Empowerment – Agents frequently don’t have the authority to resolve an issue, even when the solution is obvious. This results in call escalations to a higher tier, with increased hold time and abandonment. It also means the next callback will be an escalation call that ties up supervisor time.
  2. Coaching, not training – The agent may not have sufficient coaching time or ability to effectively deal with the customer call. Training has been proven to not move the needle at all whereas coaching is very successful at driving higher FCR rates.
  3. Information access – Agents need to find information more easily to provide answers or actions for customers. When the information is unavailable or difficult to access, sometimes agents will guess at answers or fail to provide them, both of which can lead to a callback.
  4. Back-end systems – These systems might not be up to the task. If the agent makes an address change, but it doesn’t propagate through the systems, then the customer will call back.
  5. Customer behavior – You need clues into customer perceptions and why the repeat calls are happening in the first place. This can help, for instance, when you discover customers are calling back trying to get a different result if their account is being suspended.

Improving FCR
Here’s how to get started with Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) project to improve FCR:

Step 1. Define: Conduct an information-seeking drill-down with subject matter experts (SMEs) who are proven resources in the center. This can help determine the objective and scope of your project. Those SMEs should also be a part of your project team.

Step 2. Measure: Track calls for a 30-day window in an Excel spreadsheet, if you do not have a more sophisticated system.

Step 3. Analyze: Flag repeat calls by analyzing agent logs and any interactive voice response (IVR) system data. (If you have an IVR or any other self-service tools, they should be included here). Identify whether an issue was resolved on the first call and, if not, the actual reasons for repeated calls. Look at all customer interface points because if the customer first contacted you via self-service systems, that counts as a call.

Step 4a. Improve: Make certain you provide a measurement system of record to measure FCR from the first day forward. You need useful information to conduct further root cause analyses and provide data for your control charts. What’s one ideal outcome? Could it be one where you continue to use the technology now in place, but make it work better for you? Or would it be better to leverage new technology?

Step 4b. Improve: Perform a measurement systems analysis (MSA) once that system is in place on IVR transactions and track where calls go once they are handled (defined as “the call is answered”). Look at calls and how the IVR is handling them. Many customers merely opt to zero out. That choice, however, isn’t giving you interpretable data. Callers choose to zero out for numerous reasons, including their desire to speak with a live agent.

One method of measurement can be a standard question that agents can ask the customer at the close of a call: “Is there anything else I can do?” or “Is this what you wanted?”

These questions allow a crude estimate of FCR. The best way to measure FCR as part of Improve is to add a question to your post-call survey (if you have one): “What your call successfully resolved the first time you called?”

If the answer is no, follow-up that question with a series of options, asking the caller why wasn’t it resolved during that first call: “a) Agent lacked authority; b) Agent lacked knowledge; c) etc.”

Step 5: Control – Build control charts around the “done in one” concept (a.k.a., FCR) and publish, like we do, to an intranet to which the agents have access. Make sure you multidimensionalize the intranet to allow agents to drill though center metrics to their individual agent FCR score.

You found the root cause now what do you do?

When an improvement team finds the root cause or causes of their process improvement problem they usually start to develop solutions using a Solution and Effect Diagram.[1] The Solution and Effect Diagram produces a number of potential useful solutions that the improvement team must sort through and prioritize to determine which are the most practical to implement and achieve the improvement goals set forth in the AIM statement. The prioritization process can be a confusing and time consuming process for an improvement team since they need to develop criteria to prioritize the solutions against, develop a rating scale, achieve consensus, and then do the prioritization.

To help simplify the prioritization process an improvement team can use a Solution Prioritization Tree. The Solution Prioritization Tree starts when the team has discovered the root cause or root causes of their process improvement problem and they have a number of potential solutions to evaluate as shown in Figure 1.

The Solution Prioritization Tree has a number of sections on its branches that the Improvement Team needs to fill-in to help in their analysis and prioritization of the potential solutions. The various sections of the Solution Prioritization Tree are a cluster of factors that helps the team to map the relationship between the problem, root causes and solutions. This process is useful since it helps the improvement team to:

  • ensure the solutions will bring about change that impacts the goals in the AIM statement positively
  • ensure the solution(s) selected address the significant main cause(s)
  • ensure that any solutions considered improve customer satisfaction with the process being improved
  • guide the team in determining the effectiveness and implementation of their solutions
  • help the team evaluate which solutions should be implemented

Constructing a Solution Prioritization Tree involves the following steps:

  1. Draw a Solution Prioritization Tree for each root cause found in the Cause and Effect diagram as shown in Figure 1.
  2. Label the front left box with the root cause name.
  3. List potential solutions developed on the Solution and Effect Diagram which address the root cause and place those in the boxes labeled Potential Solutions. Only three potential solutions are shown in Figure 1 but there may be many more.
    1. In the box labeled Improvement Steps detail the specifics that would be required to implement the potential solution attached to it.
    2. Develop a consistent set of Prioritization Criteria to rate each potential solution and its associated methods and tasks required to implement it. For this example we have used the following three criteria:
      1. Impact on the AIM Statement goals – will this particular solution contribute to achieving the goal(s) detailed in the AIM Statement
      2. Implementable – is the solution one that can be implemented easily and be cost effective.
      3. Improve Customer Satisfaction – improvements will increase customer satisfaction

Depending on the particular problem being solved other prioritization criteria may be more applicable and should be used. It is permissible to use more than three but too many criteria can make the prioritization process complicated and not user friendly.

  1. Rate each of the solutions on the three criteria that are chosen. Use the following rating scale for each of the prioritization criteria to see if improvement will be made in the process being improved:
Rating Scale Impact Implementable Customer Satisfaction
0 No Improvement Not Feasible No Improvement
1 Minor Improvement Some difficulty Minor


3 Major Improvement Somewhat easy Major Improvement
5 Significant Improvement Easy Significant Improvement


  1. Impact:

0 – no improvement will be achieved in the process

1 – minor improvement will be achieved in the process

3 – major improvement will be achieved in the process

5 – Significant improvement will be achieved in the process


  1. Implementable:

0 – not feasible to implement

1 – Implementable but with difficulty

3 – Somewhat easy to implement

5 – easy to implement

  1. Customer Satisfaction

0 – no improvement in customer satisfaction

1 – Minor improvement will be achieved in customer satisfaction

3 – Major improvement will be achieved in customer satisfaction

5 – Significant improvement will be achieved in customer satisfaction

  1. In column one the improvement team should decide the appropriate rating on this particular solution and how it will Impact the goals set forth in the AIM Statement. Each potential solution should make a contribution to achieving the desired future state of the process being improved. Usually, no one solution will achieve the total improvement but a few solutions when implemented in parallel will accomplish the desired change.
  2. In column two the improvement team should determine how Implementable the proposed solution will be. A solution that is implementable is one where the changes to the process can be accomplished quickly, with minimal costs, and will be accepted by those doing the work.
  3. In column three the improvement team needs to decide how Customer Satisfaction will improve with the proposed improvement to the process.
    1. In column four multiply the rating in column one, two, and three together to get a total score for each potential solution
    2. In column five the improvement team makes a Decision on whether or not to adopt the solution and implement it – (Yes/No).

To determine how many solutions to implement the improvement team needs to develop a project plan showing the sequencing of those potential solutions that scored high, resources required to implement them, timing, responsibilities, and targets to be achieved. This will give them an idea of how much they can take on to achieve the improvements desired.


Example: Approved Vacant Position Not Being Filled Quickly:

vacant position

Effective Use of Special Purpose KJ Language Processing

KJ Analysis is a method of developing insight into themes and relationships among issues. It helps drill from high-level issues at one level of context (usually abstract or vague) to a more detailed set of common, reusable statements. KJ is particularly useful in software because people have a tendency to state problems as abstract characteristics they do not like as opposed to making data-based statements about what they need. KJ is helpful in creating a flow-down of information leading to solid requirements at an appropriate level of context.

KJ can be used effectively in Six Sigma projects. And Six Sigma practitioners can benefit by a proper understanding of the approach.

Jiro Kawakita, whose Japanese initials “KJ” are the tag for the methodology he founded, deserves a great deal more visibility and credit for his insights and contribution to practical data-driven learning. As an anthropologist in the 1950s, he was confronted with lots of snippets of factual language data from his field research, and he had an “aha!” about using rules of abstraction to group the data and distill useful fundamental messages. His problem was not unlike today’s software developer’s in many areas of requirements development and problem formulation – where there is a sampling of data that touches on many important aspects of the story. Kawakita found a robust way to amplify the signal and reject a good amount of the noise in that data.

Contrasting KJ and Affinity Diagram

A number of web sites describe KJ as another name for an affinity diagram. This is an unfortunate generalization. Table 1 outlines some key distinctions between the two. Central is the fact that KJ focuses on facts, putting some rules around the traceability and clarity of every piece of language data introduced. This reduces variation in the meaning to be distilled – recognizing that no amount of language processing can overcome vague and ill-founded facts (garbage in/garbage out). Affinity diagrams, on the other hand, often encourage brainstorming, letting all ideas into the mix. Even before each tool kicks in, this difference in the incoming data is a major distinction.

Table 1: Contrasting KJ and Affinity Diagram
Affinity Diagram KJ Analysis
Preparation Little or none, spontaneous Care taken in constructing a “theme” question
Source Material Ideas, brainstorming Facts, data gathering
Grouping Quick, informal, logical grouping; often based on keywords; often no limit on group size – grouping is encouraged Pensive, in silence, based on “the story being told” in each note; typically three maximum per group – “lone wolves” are encouraged
Titling of Groups Quick, informal, “printer problems,” “poor communication” Disciplined, using rules of abstraction; complete sentences that answer the theme questions
Reflection/Post Processing Little or none, a stack of groups is often it Cause-and-effect dynamics, voting and conclusion statement powerfully capture insight

The nature of language processing driven by each tool is quite different as well. KJ carefully guides team thinking on what constitutes a language data group and limits the size of each group. The rationale for grouping is different in KJ – specifying abstraction as the guiding force. A KJ invites factual data like the black text at the bottom of the “ladder of abstraction” (Figure 1). Through grouping with other data that tells a related story, KJ labels move up in abstraction (as illustrated by the more general phrases in the red and blue moving up the ladder). This is a right-brain association activity. Affinity groupings often allow or encourage logical left-brain grouping.

Figure 1: The Ladder of Abstraction

Figure 1: The Ladder of Abstraction

Three Special Purpose KJs

One “hidden” power of KJ is its ability to adapt to special uses. Table 2 outlines three KJ types that have been most useful. The thing that creates a new KJ type is the “theme” statement – the question that is inviting all the data as factual answers. Small changes in the theme statement, even within one of these types, can make a big difference in the team experience building it, and in the outcome.

Table 2: Special Purpose KJs
KJ Type Theme Data Uses
or Problem-
What has been preventing us from…? Fact related to problems or obstacles (A major customer became confused with all the options and pulled out of the sales process.) Formulating a problem; focusing on where to do more detailed problem-solving work
of Image
What scenes and images describe…? Word pictures (Forgetting to record information in his log, a staffer then fills it in from memory.) Understanding an environment
Requirements What are the key requirements for…? Needs – Solution-free (Users define customer quality control procedures as required for their region.) Finding themes and underlying messages in a complex set of needs

Weakness or Problem-Formulation KJ – This KJ is probably the best place for a new facilitator or team to start. The theme takes on a weakness tone, looking for problems, obstacles, challenges, etc. The power in a weakness orientation is that it focuses a team on facts – and on the present and past. In contrast with the affinity diagram, this KJ does not seek ideas or brainstorming. That is an important point. It might seem more optimistic to say, “What can we do to improve X?” But that would seek ungrounded ideas. Turning the same situation around to a weakness view, it becomes, “What are our key problems with X?” That creates an entirely different set of responses. Sounds a bit pessimistic, but actually it is that way for a positive reason – to pull out the most pertinent, useful facts.

Figure 2: A Problem-Formulation KJ

Figure 2: A Problem-Formulation KJ

Context or Image KJ – A context KJ, also know as image KJ, seeks to document and distill powerful word pictures describing an environment. It is the KJ with the broadest reach. At first, many people have trouble distinguishing this from a problem-formulation KJ. A context KJ calls for all manner of images that describe “the way things are” in the environment of interest. Problems and weakness may show up as part of that picture – to the extent that they provide useful answers to the theme question. In addition, a context KJ may include images about future trends, and situations and dynamics that are neutral or positive. The problem-formulation KJ, with its focus on weakness, puts a narrower filter on the incoming data.

Requirements KJ – A requirements KJ calls for functionality in answer to a theme question such as, “What are the key requirements for…?” Many times the facts are in the form of a quote, representing a customer or “actor” describing what they need or would like to be able to do. “I can track and change my own orders online” or “For at least three years, we need to manage a mixture of the newest and some of the oldest technology” would be examples of basic fact statements at the base of a requirements KJ.

When to Do a KJ

To help decide whether to do language processing and, if so, whether to use affinity or KJ, consider these steps:

  1. Articulate the theme: the top-level question the team would like to use the data to answer.
  2. Develop the list of participants the team would like to see working on this.
  3. Gage the prospective value of the activity on these dimensions in the Language Data Processing Planner form below.
Language Data Processing Planner
Assign a prospective value for each activity, scoring anywhere between 1 and 5


Perspective 1 5 _________
The participants already have a common view of the data they would bring Participants have different data and different perspectives. There is value in their seeing the issue from one another’s perspective
Complexity 1 5 _________
The issues (regarding the theme) are not particularly complex. The hierarchy and/or relationships among the data are pretty constrained and easy to see already. The issue is complex. There are many ways the data could be distilled. It is not easy to see what the distilled answers would be.


5 _________
Most participants would not see this as an issue worth spending time on. Most participants see the value in better understanding this issue right away.
1 5 _________
We already have the data in a form that is communicable or reusable by others. The data regarding this issue is dispersed. It is hard to see the forest for the trees.

Interpreting the Planner Score:

Up to about 6 – Team KJ not worthwhile. Consider simple affinity or net-touch grouping by a smaller team, or no data processing if appropriate.
About 8 to 10 – Reconsider the theme and/or participant list.
About 12 and above – A KJ is probably worthwhile.

If a team decides to do a KJ, it should remember the data input fundamentals in the illustration below:

Figure 3: Data Input Fundamentals

Figure 3: Data Input Fundamentals

More on Language Processing

  • The Original KJ Method by Jiro Kawakita, Kawakita Research Institute, 1991.
  • The Language Processing Method by Shoji Shiba, et al, CQM, Boston, 1995.
  • Language in Thought and Action by S.I. and Alan R. Hayakawa, Harcourt Brace Jovanovich, fifth edition, 1990.
  • Customer Visits by Edward F. McQuarrie, Sage Press, second edition, 1995.

Scrubbing the Data – Part of the KJ discipline involves “scrubbing” the language on each of these incoming notes. Each note wants to be stated in “report language.” Also, the message in the note wants to be clear and unambiguous to any reader downstream – especially those who did not take part in the building of the KJ. Team members can help that process by putting each of their own notes to the test, rewording as necessary, before coming to a KJ meeting.

After KJ Is Done, Then What?

A good KJ session should yield several rewards. First, the team that created the KJ usually finds big gains in shared understanding about one another’s perspectives and facts. By working together to group, title and arrange their data, a team gets inside a common thought process about important meanings and dynamics.

For people who were not on the team, a KJ is a very efficient communication document. If the team had spent the same few hours in chairs around the meeting table with someone taking notes, it would be a longshot that many others would read and understand the notes. The KJ, on the other hand, is a 2-D pattern-oriented device that almost immediately conveys lots of information and related thought process to those who were not there. It is perfect for the “one-minute manager.”

Last but not least, over time a KJ can help the team that built it to remember and reflect back on their thinking. It can reboot the group mind months or even years later. KJs should be kept in an accessible place (and as online shareable versions) to get all possible benefits.


In their continuing search for a more efficient military, U.S. Army officials now annually honor those who have developed methods for saving money, improving operations and increasing combat readiness.

To do so, the Army has turned to Lean Six Sigma.

Since 2006, the Army has seen thousands within its ranks become Green Belts, Black Belts and Master Black Belts in Six Sigma. They have used Lean Six Sigma methodologies to save the Army more than $19 billion through eliminating operational inefficacy and improving services.

In May, Army officials held a ceremony in Washington, D.C., to honor 13 programs across 11 departments that ranked as the best Lean Six Sigma initiatives for 2016. In all, the projects saved millions of dollars and eliminated wasted time and effort by military personnel.

They’ve also made the Army stronger. Money saved from Lean Six Sigma programs can be “ploughed back into war readiness,” Karl Schneider, the senior career official performing duties of the undersecretary of the Army, said at the ceremony.

How The Army Uses Lean

The Army’s use of Lean Six Sigma methodologies began in 2006. The billions of dollars saved since that time have included cost savings in current programs, avoiding costs in future programs and generating revenue from reimbursable activities.

By 2010, the Secretary of Defense had made Lean Six Sigma a necessary step within the cost-benefit analysis of any new Army project. By 2011, the Army reported a 700-to-1 return on investment from the Lean program.

The Army continues to move toward its goal of making Lean Six Sigma a self-sustaining effort within the military branch’s numerous departments. The LSS Program Management Office helps facilitate the training needed to make Lean methodology a “routine way of doing business” across all Army departments.

The 2016 Award Winners

At the ceremony in May, held at the Pentagon, the 13 award-winning Lean programs came from a variety of departments. Three departments earned the Process Improvement Deployment Excellence Award:

  • The Office of the Assistant Secretary of the Army for Financial Management and Comptroller, for Lean projects that led to a total of $66.2 million in costs savings, cost avoidance and revenue generation.
  • The U.S. Army Medical Command for programs that led to better healthcare services for military personnel and cost savings of $5.7 million.
  • The 21st Theater Sustainment Command, U.S. Army Europe for programs that led to greater commander involvement and a cost savings of almost $3 million.

Benefits of Six Sigma Training

All of this means that opportunity is there for servicemembers who wish to earn Six Sigma certification. They not only can become involved with cutting-edge projects during their time in the service, but also attain skills that make them attractive job candidates after leaving the military.

While the roots of Six Sigma lie in industrial manufacturing, use of the methodology has become widespread across many different industries, as well as with nonprofits and government organizations.

Those with security clearance also can get the inside track on jobs with defense contractors, a growing industry that frequently utilizes Six Sigma.

As the Lean Six Sigma program shows, the Army values the benefits of those with training in Six Sigma. It not only creates savings for taxpayers, but provides solid employment opportunities for military personnel.