Process Improvement Leads to Satisfied Customers

Excellent performance is the result of an excellent process. Take a look at great sports teams. They are hailed for executing the basics at levels higher than the competition, and the best teams always seek ways to get better. They also have leaders who use process improvement to push the team to higher performance levels.
By By Paul Cardis, NRS Corp., and Dr. Jack ReVelle, ReVelle Solutions | November 30, 2006

Choosing Analysis Tools

Excellent performance is the result of an excellent process. Take a look at great sports teams. They are hailed for executing the basics at levels higher than the competition, and the best teams always seek ways to get better. They also have leaders who use process improvement to push the team to higher performance levels.

Companies have many programs to help improve processes. You have probably heard of some of them, including Total Quality Management, Kaizen (Continuous Improvement) and Six Sigma.

Within any company, there are multiple, related processes that must work together to achieve a desired outcome. By continually improving your processes, you are creating a powerful system for satisfying and delighting customers. When great processes are in place, they take home buyer satisfaction to new heights and more consistent levels.

Where Is Your Pain?

Every process improvement program must begin with the all-important question: where is your pain? You must begin with a general identification of what issues trouble your company and where. Of course, this is just a general description of what you hope to have process improvement efforts fix, but very important to establish a baseline that is the foundation for later decisions.

Process improvement teams will often revise their answer to this question once they collect more data and discover that, in fact, the pain resides in another part of the company.

Let's follow a client whom we'll call XYZ Builders to see how it handled a process improvement initiative. XYZ Builders lies in a major metropolitan market and came to us for help with its low scores for landscaping satisfaction. At first we thought the pain was landscaping delivery, but after we completed our root cause analysis, we realized it was something vastly different. Read on to learn more.

Decide What to Collect

The next step in getting to the source of pain is to begin measuring. It boils down to three key questions:

  • What you are going to measure?
  • How you are going to measure it?
  • What metrics are you going to use?

For the best process improvement you should measure errors and incidents using the following four metrics when possible:

  1. Frequency of incidents
  2. Trend of incidents (performance over time)
  3. Range of incidents (maximum and minimum range of errors)
  4. Rank order of identified issues
  • In the case of XYZ Builders, we examined the number of customers who had given the lowest score for landscaping; plotted trends over time; identified ranges of satisfaction or dissatisfaction per month; and ranked the landscaping comments provided by the buyers. This data was critical in making the root cause discovery. You should do the same with your customer data.

    Root Cause Analysis

    Collecting data is critical to this process, but it can yield more information than anticipated. How do you determine the source of the problem from all this information? The key to making the root cause discovery is to examine your data through analysis tools.

  • With XYZ Builders' data, we ran an analysis called regression. Regression is a statistical analysis procedure that takes all of your data and determines the importance of each against a single key variable. (See Choosing Analysis Tools, left, for more information)

    Armed with regression results, we discovered that the landscaping scores were related to sales scores and overall value. This result uncovered something very important: there was more to the story than just poor performance with our trade. We did further interviews with buyers and discovered that dissatisfied customers thought complete landscaping was included in the home price. The reality was that it wasn't, even though the builder was marketing and selling these homes as if the landscaping were included. In this case, we had a classic example of misleading expectations that had nothing to do with the performance of the trades contracted to do the work.

    Implement Change and Monitor Results

    Once you have a root cause or at least alleged root cause, you can set out to fix the problem. With misleading expectations during the sales and design process now clearly identified, our team helped the client clarify what landscaping should be included in the price. We also worked with the client's employees to properly communicate the offer and create a clear upgrade option for those who wanted to purchase the higher level of landscaping shown.

    Once the revised program was deployed, we monitored results to see if satisfaction levels increased — and they did.

    Learn Lessons, Adjust and Redeploy

    We initially thought the landscaping company wasn't doing its job and immediately came down on the trade. The reality of the situation was that it wasn't the trade's fault; the root cause was the builder.

    In many cases, we go down the road of improvement only to find out that we are not getting the results we expected. This is because we have not found the root cause, and we need to repeat the root cause analysis described above. By diligently monitoring and learning from data, you can adjust and redeploy your solution, getting the results you desire.

    Process improvement is critical and difficult, but with discipline and knowledge you can fix things we do every day that impede excellence. Moreover, builders interested in achieving high referrals and increased market share should be anxious to tap into these powerful tools. The best home building companies are already taking the leap into process improvement and yielding big rewards for their disciplined culture of excellence.

  • Author Information

    Paul Cardis is CEO of NRS Corp., a research and consulting firm specializing in customer satisfaction for the home building industry. He can be reached at


    Choosing Analysis Tools

    You can choose which variables you put in the regression equation, and it will tell you which ones have the most effect. We recommend using a consultant to run this type of analysis for your company. In lieu of using a statistician, you can use failure mode and effects analysis along with cause and effect analysis and scatter analysis (refer to "Quality Essentials" by Dr. Jack B. ReVelle) or a simple correlation function found in Microsoft Excel. Please note that correlations are not the same as regressions and often yield different results, so they must be used carefully in your improvement efforts. We prefer regression over correlation because regression does a better job accounting for misleading relationships in the data. Correlation is well known to be a weaker tool, but still effective if used properly.

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