Pdf on six sigma

May want to separate the needs based on the Kano Model categories p. Multivoting Highlights A quick technique for identifying priorities or at least narrowing down the options from a list of ideas To use multivoting… Prework: This method assumes you have an existing list of ideas or options.

Eliminate duplicates and combine related ideas before continuing. Number every idea or option being considered 2. Write each idea on a flip chart or whiteboard visible to all participants 3. Collect the slips and mark the votes on the flip chart or whiteboard. Review as needed. Always a good idea at the beginning of a process improvement project, even if you think your team members already have a lot of process knowledge. Most teams will want to do a SIPOC diagram at the beginning of their project to capture a high-level view of targeted operations helps communicate with sponsors and others.

Skim through to see if they could help your project. Very often there are discontinuities in the process during the hand-offs between functions. Effective at showing the many handoffs, transports, queues and rework loops in a process. The foundation for Lean improvement methods. Mandatory tool for all teams whose mission is to speed up the process and eliminate non-value-add cost. See also the complexity value stream map on p. Every project that involves process improvement should establish before and after levels of value-add and non-value-add cost.

You MUST walk the process and talk to the staff to find out what really goes on day to day. Only go to a level of detail that is helpful for the project. If boundaries are not spelled out, check with your sponsor s.

No one person will have all the process knowledge you need. Establish practices that make them living documents; refer to them in all team meetings, use in training and retraining; update with each process change, etc. Should show the role of feedback and information flow.

Useful early in a project to identify boundaries and scope. Not useful during improvement because of lack of detail. Low-level view: Depicts specific actions, workflow, rework loops, etc. Useful for a process of limited scope; too cumbersome when all you need is a view of the overall flow.

Select current as-is vs. Most projects should include a current map of the project. What would we do if we could start from scratch? Do a to-be chart as part of solution planning or when designing or redesigning a process.

That can help you focus on the gap between where you need to be and the current state. Clarify the purpose of observation. Identify observers. Prepare an observation form and train observers. Prepare staff in the workplace. Walk the process; carry out your observations plans. Have observers summarize lessons learned and present them to whole team.

Discuss the results. If, for example, observers are working in parallel at different points the process, make sure they all start and end their timing devices at the same time. But do them in any order that makes sense for your project. This should align with the scope of your project.

Too much detail will bog you down; too little will make the flowchart useless. To create a process map… 1. Review the process being studied and its boundaries as defined for your project.

Identify the type of chart you want to create. Have participants identify the steps in the process. Write each step on a self-stick note or card using the appropriate symbol see p. Only go in the reverse direction if a decision calls for repetition of a step. Does it match reality as you know it? Adjust as needed. When done, number the tasks sequentially through the most direct route, then number off-line tasks. Transfer completed map to paper or computer.

Would it be possible to do this other thing that would help me? Always do as much of the mapping where reality is. Videotape if possible. Transfer to computerized drawing only after the team agrees on a version. Parking Lot topics usually include 1 improvement ideas; 2 assumptions; 3 questions; 4 additional observations; and 5 out-of-scope issues and ideas. Take notes. Find or create a diagram of the workspace or obtain a hard copy of a form or worksheet if that is the target of improvement.

Work from an existing flowchart of the process steps or brainstorm a list of steps. Mark where the first step of the process happens, draw an arrow from there to where the second step happens, etc. Continue until you have mapped all process steps. Discuss the final diagram with an aim towards improving the workflow. So if you see a lot of crisscrossing lines, investigate ways to reduce handoffs and simplify the layout. The difference here is that you need to identify WHO does the work, not just what gets done.

Identify the different people or job functions involved in the process. List them down the left side or across the top of a flip chart or whiteboard. Brainstorm the steps in the process and write them on self-stick notes. Work through each step in order, placing the notes in the appropriate swim-lane.

Use the result to spark discussions on how to improve workflow. Try to combine or resequence work so one person can complete all their tasks at one time. Place those with less interaction in the lowest or right-most swim-lanes. Use dotted lines to reflect informal lines of communication those that occur outside the formal process if there is evidence that the informal link has an impact on the process.

Determine what individual product, service, or family you will map. Verify the Map Have non-team members who know the process review the flow and data. Check with suppliers and customers as well interface points. Make changes as needed then check the final results with people who work on the process. This will help the team to see everything going on in the process.

If you try to piece the VSM together step by step it will take longer and you will go too deep, too fast on specific steps. Flowchart and value stream symbols Value-add VA vs. See descriptions below. Add up the time spent in each category.

Use a Time Value Map p. Decide what to do next. Would your external or end customer complain? If you STOP doing it now, would your internal customers complain? If yes, then it is probably business non-value-add.

If you STOP doing it now would any customer internal or external know the difference? If not, the work is probably non-value- add. Be alert for quantized costs in your process and work to eliminate the sources. Determine process cycle time 2. Draw a timeline and divide into units equal to the total process time 4.

Place steps and delays along the timeline in the order in which they happen; use segments proportional to the times — VA steps go above the line — Non-value-add goes below the line think about using different colors for emphasis — The white space between boxes indicates queue or delay time 7. Draw in feedback loops and label yield percentages 8.

Follow instructions in the value-add analysis p. For each step in the process, collect data on how much time is spent on each type of work 3.

Visually display the results in a bar chart like that shown here 4. The goal is to level the times across steps so no step is longer or slower than any other step.

In the chart shown here, the total amount of time spent in all 10 steps is about minutes. If this company had 10 people working in the process, that equals about But the takt time is 55 minutes. As a rule of thumb, workloads at each step should equal about one takt. In this situation, they could reduce staff to 8 or 9 people so each employee has about 55 minutes worth of work.

Especially useful for any team dealing with a moderate to large customer base. Types and sources of customer data, p.

Use to prompt your own thinking before a VOC effort. Collecting VOC: Interviews, p. Recommended for any team that wants to develop a deep understanding of customer needs and how customers use the product or service Point-of-use observation, p. Use to gain greater insight or confirm interview results.

Focus groups, p. More efficient than doing separate interviews but still time intensive. Use as needed. Surveys, p. Best used to confirm or quantify theories developed after other customer contact. Also can be used to identify most important issues to research. Good for gathering quantitative information. Kano analysis, p. Developing critical-to-quality requirements, p. Since you will deal with customers face to face, you must leave a good impression. Be organized, be professional.

And make sure you follow up or customers will feel their time was wasted. If multiple people from different departments all contact customers separately, your customers may view you as incompetent.

Get help from experts, if available. Identify the output product or service being studied 2. Brainstorm to identify the customers of that output 3.

Develop profiles of the segments you will seek out for your projects Ex: high-volume vs. Midwest vs. Southeast customers 5. Include representatives from each segment in whatever customer contact you initiate interviews, surveys, focus groups, etc. Be clear about the purpose of the interviews. What role will the interviews play in the project? How will you use the information afterwards? Prepare a list of questions. Decide on interview method face-to-face, phone. Decide how many interviewers and interviewees will be present.

Do practice interviews internally to refine the script, questions and interview process. Contact customers and arrange interviews. Send out a confirmation letter or email stating the purpose of the interview and providing a list of general topics to be covered no need to share specific questions unless you think it will help customers prepare. Decide how you will collect data from the interviews. If you plan to record them audiotape, computer audio programs make sure you tell customers and get their permission to do so.

Conduct interviews. Transcribe notes and continue with data analysis. Be clear about the purpose of the observation. What role will the observation play in the project? Decide when and how you will observe customers in their workplace, in a retail situation, etc.

Develop and test an observation form for collecting the data you desire. See also customer interviews, p. Train observers to make sure everyone will follow the same procedures and leave a good impression with customers.

Conduct the observation. Continue with data analysis. Include follow-up contact with customers thank-you note, copies of observations, updates on changes made as a result of their contributions. If no one within your organization has experience with focus groups, consider hiring outside help. After the focus group, transcribe customer comments 6.

Develop survey objectives. Determine the required sample size see p. Write draft questions and determine measurement scales. Determine how to code surveys so data can remain anonymous if appropriate. Design the survey. Confirm that getting answers to the individual questions will meet your objectives adjust, if not. Conduct a pilot test. Finalize the survey. Send out survey mail, fax, email attachment to selected customers. Include a means for them to respond—SASE, return fax number, email reply.

Or post on your website and give participants instructions on how to access the survey. Compile and analyze the results. It is normally that way that feature is expected 3.

Based on customer responses, classify each need as a dissatisfier, satisfier, or delighter see definitions on next page 5.

If these needs are not fulfilled, the customer will be extremely dissatisfied. Satisfying basic requirements is the entry point for getting into a market. Satisfying performance requirements will allow you to remain in the market. Satisfying excitement requirements opens the opportunity to excel, to be World Class.

Identify relevant statements in transcripts of customer comments and copy them onto slips of paper or self-stick notes. Use Affinity diagrams p. Start with the themes or representative comments and probe for why the customer feels that way. Do follow-up with customers to clarify their statements.

Be as specific as possible when identifying the why. Conduct further customer contact as needed to establish quantifiable targets and tolerance specification limits associated with the need. Have you covered all key aspects of your product or service? Fill in gaps as needed. Use whenever you collect data. Review recommended for all teams since almost all data collection involves sampling. Recommended for all teams. Types of data 1. Continuous Any variable measured on a continuum or scale that can be infinitely divided.

Ex: Lead time, cost or price, duration of call, and any physical dimensions or characteristics height, weight, density, temperature 2. Discrete also called Attribute All types of data other than continuous. There is no intrinsic reason to arrange in any particular order or make a statement about any quantitative differences between them. Process measures One type of X variables in data. Measures quality, speed and cost performance at key points in the process. Some process measures will be subsets of output measures.

For example, time per step a process measure adds up to process lead time an output measure. Input measures The other type of X variables in data. Measures quality, speed and cost performance of information or items coming into the process. Usually, input measures will focus on effectiveness does the input meet the needs of the process? That increases the odds it will get done regularly and correctly.

Have collectors practice using the data collection form and applying operational definitions. Resolve any conflicts or differences in use. Collect VOC data see Chapter 4 to identify critical-to-quality requirements. List down the side of a matrix. Work through the matrix and discuss as a team what relationship a particular measure has to the corresponding requirement: strong, moderate, weak, or no relationship.

Review the final matrix. Develop plans for collecting data on the measures that are most strongly linked to the requirements. Stratification factors Highlights Purpose is to collect descriptive information that will help you identify important patterns in the data about root causes, patterns of use, etc.

The method described here uses a modified tree diagram shown above to provide more structure to the process. Identify an Output measure Y , and enter it in the center point of the tree diagram. List the key questions you have about that output.

Identify descriptive characteristics the stratification factors that define different subgroups of data you suspect may be relevant to your questions. Create specific measurements for each subgroup or stratification factor. Review each of the measurements include the Y measure and determine whether or not current data exists.

Discuss with the team whether or not current measurements will help to predict the output Y. If not, think of where to apply measurement systems so that they will help you to predict Y.

As a team, discuss the data you want to collect. Strive for a common understanding of the goal for collecting that data. Precisely describe the data collection procedure. When a customer gets in line?

When he or she steps up to a teller? Ex: If measuring the length of an item, how can you make sure that every data collector will put the ruler or caliper in the same position on the item? Specifically how are these forms or instruments to be used? In what units? Test the operational definition first with people involved in Step 2 above and then again with people not involved in the procedure, and compare results.

Does everyone from both groups get the same result when counting or measuring the same things? Refine the measurement description as needed until you get consistent results. Cautions on using existing data Using existing data lets you take advantage of archived data or current measures to learn about the output, process or input. Collecting new data means recording new observations it may involve looking at an existing metric but with new operational definitions.

Existing data is best used to establish historical patterns and to supplement new data. Select specific data and factors to be included 2. At each process step, the operator enters the appropriate data. The trade-off is faster data collection because you only have to sample vs.

No time element. Ex: Customers, complaints, items in warehouse Process — Sampling from a changing flow of items moving through the business. Has a time element.

In contrast, quality and business process improvement tends to focus more often on processes, where change is a constant. Process sampling techniques are also the foundation of process monitoring and control.

Sampling terms Sampling event — The act of extracting items from the population or process to measure. Subgroup — The number of consecutive units extracted for measurement in each sampling event.

Sampling Frequency — The number of times a day or week a sample is taken Ex: twice per day, once per week. Applies only to process sampling. Ex: collecting VOC data from people you know, or when you go for coffee. Use a random number table or random function in Excel or other software, or draw numbers from a hat that will tell you which items from the population to select.

The risk of bias comes when the selection of the sample matches a pattern in the process. To sample from a stable process… 1. Who will do it? Determine the minimum sample size see p. Making inferences about a population based on a sample of an unstable process is ill-advised.

Establish stability before making inferences. For additional details refer to Minitab Help. NOTE: Having uncalibrated measurement devices can affect all of these factors.

Calibration is not covered in this book since it varies considerably depending on the device. Be sure to follow established procedures to calibrate any devices used in data collection. Be sure to represent the entire range of process variation.

Good and Bad over the entire specification plus slightly out of spec on both the high and low sides. Select 2 or 3 operators to participate in the study. Identify 5 to 10 items to be measured. Have each operator measure each item 2 to 3 times in random sequence. Gather data and analyze. See pp. Watch for unplanned influences. This takes into account variability due to the gage, the operators, and the operator by part interaction. Part-to-Part: An estimate of the variation between the parts being measured.

Specifically, the calculation divides the standard deviation of the gage component by the total observed standard deviation then multiplies by This chart shows the variation in the measurements made by each operator on each part. Review control chart guidelines, pp. The control limits are determined by gage variance and these plots should show that gage variance is much smaller than variability within the parts. By Part chart The By Part graph shows the data for the parts for all operators plotted together.

It displays the raw data and highlights the average of those measurements. This chart shows the measurements taken by three different operators for each of 10 parts. Whether the difference is enough to be significant depends on the allowable amount of variation. In this example, each of three operators measured the same 10 parts.

The 10 data points for each operator are stacked. Whether that is significant will depend on the allowable level of variation. It is the best chart for exposing operator-and-part interaction meaning differences in how different people measure different parts.

This is not good and needs to be investigated. MSA: Evaluating bias Accuracy vs. If the answer is no, the measurement system is inaccurate.

Bias effects include: Operator bias — Different operators get detectable different averages for the same value. Instrument bias — Different instruments get detectably different averages for the same measurement on the same part. If instrument bias is suspected, set up a specific test where one operator uses multiple devices to measure the same parts under otherwise identical conditions.

Other forms of bias — Day-to-day environment , customer and supplier sites. Talk to data experts such as a Master Black Belt to determine how to detect these forms of bias and counteract or eliminate them. Testing overall measurement bias 1. Assemble a set of parts to be used for the test.

Calculate the difference between the measured values and the master value. Test the hypothesis see p. In the boxplot below; the confidence interval overlaps the H0 value, so we cannot reject the null hypothesis that the sample is the same as the master value. MSA: Evaluating stability If measurements do not change or drift over time, the instrument is considered to be stable. Measurement System stability can be tested by maintaining a control chart on the measurement system see charts below.

In concept, the measurement system should be able to divide the smaller of the tolerance or six standard deviations into at least five data categories. A good way to evaluate discrimination graphically is to study a range chart. Ex: Rating features as good or bad, rating wine bouquet, taste, and aftertaste; rating employee performance from 1 to 5; scoring gymnastics The Measurement System Analysis procedures described previously in this book are useful only for continuous data.

When there is no alter-native—when you cannot change an attribute metric to a continuous data type—a calculation called Kappa is used. All differences are treated the same. Select sample items for the study.

Have each rater evaluate the same unit at least twice. Calculate a Kappa for each rater by creating separate Kappa tables, one per rater. See instructions on next page.

Calculate a between-rater Kappa by creating a Kappa table from the first judgment of each rater. One rater with low repeatability skews the comparison with other raters. It means that these two raters grade the items differently too often. Calculate these values manually for any set of continuous data if not provided by software.

You will need these calculations for many types of statistical tools control charts, hypothesis tests, etc. You will rarely generate one by hand, but will see them often if you use statistical software programs. Essential for evaluating the normality; recommended for any set of continuous data. Statistical term conventions The field of statistics is typically divided into two areas of study: 1 Descriptive statistics represent a characteristic of a large group of observations a population or a sample representing a population.

Ex: Mean and standard deviation are descriptive statistics about a set of data 2 Inferential Statistics draw conclusions about a population based upon analysis of sample data.

A small set of numbers a sample is used to make inferences about a much larger set of numbers the population. However, a mean is required to calculate some of the statistical measures of variation. To determine the median, arrange the data in ascending or descending order. The median is the value at the center if there is an odd number of data points , or the average of the two middle values if there is an even number of data points. In that instance, the median would be far more representative of the data set as a whole.

Range Range is the difference between the largest and smallest values in a data set. Variance for a population uses a sigma as shown here. That means, for example, that the total variance for a process can be determined by adding together the variances for all the process steps.

Do not add together the standard deviations of each step. Although, applications of Six Sigma in sales and marketing are not common, it provides great potential for huge benefits Pestorius, Now companies are using Six Sigma to improve sales, marketing, and customer support. Pestorius noted that Six Sigma could improve sales and marketing processes.

Six Sigma helps marketing to attain a state of sustainable growth by positively influencing marketing's three process areas viz. Hence, to move up the competitive ladder, organizations need to deploy Six Sigma for enhancing sales and marketing performance. Such projects use standard Six Sigma DMAIC methodology define, measure, analyse, improve, and control methodology to identify the root causes of variation in the performance. For new products and processes, the DMADV methodology define, measure, analyse, design and verify applies.

Define: What is it that the sales department is seeking to improve? This stage defines the goals and customer requirements. Measure: How is the sales process measured? What is the current capability of the process? How is it performing in terms of variability? This stage measures the process to determine current performance. Analyse: What are the most important causes of sales related problems?

How to map the process, and prioritize for action? This stage analyzes and determines the root cause s of the variability. Improve: How do sales department remove the causes of problems i. How do they re- engineer the process and simplify? This stage improves the sales process by eliminating defects. Control: How can sales department maintain the improvements? What are various statistical process control tools to monitor performance? This stage controls future process performance.

This is expected to have great impact on customer satisfaction and loyalty by deployment through specific process improvement stages. It is mainly because not all market opportunities are worth an investment. The opportunities must be evaluated using a quantifiable approach and not one driven by guesses, agendas or intuition.

Define stage identifies the sales problem being addressed, the customers being affected, what they view as important, and what performance matrices will be used. Sales goal, scope, expected outcome, boundaries and project schedules are specified in define stage. Sales problems i. After the sales activities are identified, they are assigned to process improvement.

The define stage focuses on the defining the core business process influencing the customer i. Voice of the Customer VOC that have the highest priority for improvement. Without this information, few sales efforts can satisfy either the effectiveness or efficiency criteria that are so important in sales success.

Measure This stage measures the capability of the existing sales processes and focuses on the performance of the core business processes involved. The Measure stage determines what processes are potentially creating to the problem, develop a data gathering plan and system, collect data to determine the types of matrices and validate how the information data will be used to drive business decisions.

This stage identifies sales performance measures such as cost, efficiency, and service levels while focusing on problem areas. It also emphasises on defining value for the targeted markets identified in the define stage. Analyse The Analyse stage uses statistical tools and techniques to narrow the list of possible causal elements to those that contribute the most to the sales problem and find the root causes when and where problems occur.

Analyse stage requires the learning of new tools, matrices and their application in sales. Improve This stage consists of identifying and prioritizing improvement areas. The purpose of continuous improvement is to reduce the amount of common- cause variations in the sales processes.

Improve stage develops plans to change the sales process involved to eliminate or reduce the effect of the root causes of variations. It involves testing these plans, determine whether the solution is able to reduce variations, establish their efficacy, and then implement changes so that the overall sales performance can be improved. Statistical methods are used to validate the improvements.

After this testing, the improvement should be implemented throughout the process. Control In this last stage, focus is to eliminate the causes of problems and to maintain the continuity in sales process improvement. Control stage maintains changes made to the sales process and monitor process performance to determine whether it is in control. If the process is in control, the standards of cost, efficiency, and services are set to those of the improved process.

Hence, this stage identifies the controls that must be in place to sustain the benefit of the new process. Six Sigma Deployment: Enhancing Competitive Advantages While manufacturing costs have been squeezed effectively without compromising quality, sales and marketing operations have not seen comparable increases in efficiency as well as effectiveness.

Need an account? Click here to sign up. Download Free PDF. Pankaj M Madhani. Pankaj Madhani. A short summary of this paper. Download Download PDF. Translate PDF. A sigma quality level offers an indicator of how often defects are likely to occur, whereby higher sigma quality levels indicate a process that is less likely to create defects as the quality level also increases accordingly. Under the Six Sigma methodology, deficiencies are described in terms of 'defects' per million opportunities, with the score of Six-Sigma quality level equal to 3.

Here, an 'opportunity' is defined as any chance for non- conformance or not meeting the required specifications. Six Sigma is a disciplined, data-driven approach and methodology for eliminating defects in any process — from manufacturing to trading, and from product to service. It was originally developed at Motorola in the s for production processes characterized by high volume and the high degree of standardization with goal of eliminating waste by achieving near-perfect results.

In a current business environment characterised by changing buyer preferences, channel leverage, shorter product life cycles and increase financial pressure on sales growth, profits, and shareholder value, there is a lot of interest in deploying Six Sigma to sales and marketing to reduce the uncertainty inherent in it.

Six Sigma has been applied by various organizations in their sales and marketing processes with the ultimate goal of increasing customer satisfaction, sales revenue, market growth and profitability.

In this phase of Six Sigma, the focus was on cost reduction and economics and was termed as Generation II. Research has shown that most of the service processes are performing at less than 3. If the Sigma quality level is increased to 4. This clearly indicates a foldimprovement in process performance as the process yield will be increased to Process improvement methodologies such as Six Sigma deployment in services would bring significant financial returns to the organizations Antony, In manufacturing processes and services, usually there are very high correlations between the quality of process inputs and the outputs, thereby making operation easy, predictable, fact based and thus enabling smooth deployment of Six Sigma Figure 1.

Transactional processes that require high human input avoid control as process inputs and outputs are weakly correlated. As generations I and II projects have internal objectives of defect reduction and cost cutting, the transition from I to II is easy. However, generation III has external objectives of increasing effectiveness, enhancing value creation and boosting top-line revenue; hence its deployment is still evolving Figure 1.

Although, applications of Six Sigma in sales and marketing are not common, it provides great potential for huge benefits Pestorius, Now companies are using Six Sigma to improve sales, marketing, and customer support. Pestorius noted that Six Sigma could improve sales and marketing processes. Six Sigma helps marketing to attain a state of sustainable growth by positively influencing marketing's three process areas viz.

Hence, to move up the competitive ladder, organizations need to deploy Six Sigma for enhancing sales and marketing performance. Such projects use standard Six Sigma DMAIC methodology define, measure, analyse, improve, and control methodology to identify the root causes of variation in the performance.

For new products and processes, the DMADV methodology define, measure, analyse, design and verify applies. Define: What is it that the sales department is seeking to improve? This stage defines the goals and customer requirements. Measure: How is the sales process measured? What is the current capability of the process? How is it performing in terms of variability? This stage measures the process to determine current performance.

Analyse: What are the most important causes of sales related problems? How to map the process, and prioritize for action? This stage analyzes and determines the root cause s of the variability. Improve: How do sales department remove the causes of problems i. How do they re- engineer the process and simplify? This stage improves the sales process by eliminating defects.

Control: How can sales department maintain the improvements? What are various statistical process control tools to monitor performance? This stage controls future process performance. This is expected to have great impact on customer satisfaction and loyalty by deployment through specific process improvement stages. It is mainly because not all market opportunities are worth an investment. The opportunities must be evaluated using a quantifiable approach and not one driven by guesses, agendas or intuition.

Define stage identifies the sales problem being addressed, the customers being affected, what they view as important, and what performance matrices will be used.