Six Sigma Call Centers

Is Six Sigma The Ultimate Management Tool?

Today, Six Sigma covers a very wide range of industries such as healthcare, banking, manufacturing and construction, to name a few. The 2 methodologies adopted by Six Sigma take care of the existing process and the new processes that still need to be developed, through DMAIC and DMADV respectively. DMAIC and DMADV are acronyms for process improvement methodologies. The methodology is hailed as the finest quality management system or tool that the industry has ever seen.

What Makes Six Sigma The Finest Quality Tool Ever?

Six Sigma came to occupy center stage riding on its success of its founder and pioneer Motorola’s successful implementation. The comprehensive, structured approach of Six Sigma involves the entire organizational pyramid. The organization needs to dedicate 100% of its time to the usage of unique problem solving techniques, with no nonsense responsibilities.

The comprehensive approach involves top management with designated key roles responsible for identifying and reviewing projects. Middle implementation groups like the Champions and Master Black Belts dedicate their time to removing trans-jurisdictional bottlenecks and to problem solving. Trans-jurisdictional bottlenecks are potentially very serious and can possibly derail the implementation. Champions handle this very tactfully like seasoned warriors. Master Black Belts are extraordinarily talented in problem solving and in using sophisticated statistical tools.

Statistical tools are highly customized to the situation and are very versatile. These tools are used to question and measure the processes in any business environment with the goal to rationally analyze and design/correct them. If with Six Sigma, you can achieve 3.4 defects per million opportunities, save millions of dollars and satisfy customers in addition to making the company lean and mean and appealing to employees and owners alike, the methodology is indeed the ultimate management tool. But is it the ultimate quality management tool that can never fail? Or are there chinks in its implementation armor?

Failure of Six Sigma
Fortune magazine on January 22, 2001 writes about the satellite phone, Iridium, made by Motorola, the pioneer of Six Sigma. The phone was an utter flop as no one bought it. This means that Six Sigma only assures quality but not customer satisfaction. Customers only buy things they really want.

There are certain statistical snags that experts point at. They are critical of the universal standard rule that Six Sigma uses instead of going case-by-case on different tasks and not using more appropriate, common-sense based tools, such as decision, theory and cost- benefit analysis.

The statistical methodology: Some critics are skeptical that Six Sigma is a marketing ploy that helps make money for all those involved, especially the consultants. Since the methodology is taught and practiced in only one way and since there is an absence of standardization of both implementation and Six Sigma training, it lacks consistency. Still others are scathing in their criticism that those who claim huge successes were total failures in quality control before Six Sigma and that their focus on small areas brought huge returns.

Why Six Sigma Will work in Service Environments

Although Six Sigma has its roots in manufacturing, it works just
as effectively in service industries. It’s no secret that
service environments, such as financial organizations,
healthcare providers, retail companies, and hospitality
organizations have a harder time applying Six Sigma principles.
However, the core principles of Six Sigma allow it to
cost-effectively translate manufacturing-oriented Six Sigma
tools into the service delivery process.

Service organizations have different root causes of problems and
a unique set of processes and metrics. Thus, the tools and
methodology required to achieve the improvements of Six Sigma
are significantly different. While problems in the manufacturing
setting may lie within a process, the issue in a service
environment often is the process itself. Service industries are
full of waste–and ripe for the benefits of Six Sigma. It is
easy to apply relatively simple statistical and lean tools that
will reduce costs and achieve greater speed with less waste in
service processes. There are numerous case studies that
demonstrate how Six Sigma can be used in service organizations
just as effectively as in manufacturing-and with even faster
results.

In a service organization, the critical factors in quality and
efficiency are flow of information and interaction between
people, especially interactions with customers. Transforming the
process of these flows will yield quality results. At the heart
of every service business are the opinions, behaviors and
decisions made by people. Analyzing and modifying human
performance in service environments is as complex as any
manufacturing situation. Six Sigma achieves documented
bottom-line strategic business results by initiating an
organization-wide culture shift. Until a process focus-rather
than a task focus-is developed, the scope and endurance of
improvements will be limited. Analyzing and modifying human
performance in these environments is complex, but Six Sigma
provides the tools and methodology required to achieve
significant long-term improvements.

Service managers trained in Six Sigma become skilled at advanced
process analysis and problem solving techniques relevant to the
“real world” of service environments. They learn to identify and
eliminate poor decision-making processes, standardize practices,
reduce cycle times and manage the risk of the extensive changes
required for breakthrough process improvement in people-oriented
transactional processes. Successful Six Sigma services projects
will lead to improved customer satisfaction, increased profit
margins, reduced costs, and lower turnover. Six Sigma tools can
be used in many service environments, even service areas within
a non-service industry. Areas such as procurement, call centers,
surgical suites, government offices, R&D, and many more will all
receive benefits from implementing Six Sigma process improvement.

Six Sigma will help a service environment become a
customer-centered organization, gain control over process
complexity, and improve response time on signature services.
Peter Peterka is President of
Six Sigma us. For additional information on Six Sigma
Green Belt or other Six Sigma
Certification programs contact Peter Peterka.

Six Sigma Terminology

Affinity Diagram – A technique for organizing individual pieces of information into groups or broader categories.

ANOVA – Analysis of Variance – A statistical test for identifying significant differences between process or system treatments or conditions. It is done by comparing the variances around the means of the conditions being compared.

Attribute Data – Data which on one of a set of discrete values such as pass or fail, yes or no.

Average – Also called the mean, it is the arithmetic average of all of the sample values. It is calculated by adding all of the sample values together and dividing by the number of elements (n) in the sample.

Bar Chart – A graphical method which depicts how data fall into different categories.

Black Belt – An individual who receives approximately four weeks training in DMAIC, analytical problem solving, and change management methods. A Black Belt is a full time six sigma team leader solving problems under the direction of a Champion.

Breakthrough Improvement – A rate of improvement at or near 70% over baseline performance of the as-is process characteristic.

Capability - A comparison of the required operation width of a process or system to its actual performance width. Expressed as a percentage (yield), a defect rate (dpm, dpmo,), an index (Cp, Cpk, Pp, Ppk), or as a sigma score (Z).

Cause and Effect Diagram – Fishbone Diagram – A pictorial diagram in the shape of a fishbone showing all possible variables that could affect a given process output measure.

Central Tendency - A measure of the point about which a group of values is clustered; two measures of central tendency are the mean, and the median.

Champion -A Champion recognizes, defines, assigns and supports the successful completion of six sigma projects; they are accountable for the results of the project and the business roadmap to achieve six sigma within their span of control.

Characteristic – A process input or output which can be measured and monitored.

Common Causes of Variation – Those sources of variability in a process which are truly random, i.e., inherent in the process itself.

Complexity -The level of difficulty to build, solve or understand something based on the number of inputs, interactions and uncertainty involved.

Control Chart – The most powerful tool of statistical process control. It consists of a run chart, together with statistically determined upper and lower control limits and a centerline.

Control Limits – Upper and lower bounds in a control chart that are determined by the process itself. They can be used to detect special or common causes of variation. They are usually set at ±3 standard deviations from the central tendency.


Correlation Coefficient - A measure of the linear relationship between two variables.


Cost of Poor Quality (COPQ) – The costs associated with any activity that is not doing the right thing right the first time. It is the financial qualification any waste that is not integral to the product or service.

CP – A capability measure defined as the ratio of the specification width to short-term process performance width.

CPk. - An adjusted short-term capability index that reduces the capability score in proportion to the offset of the process center from the specification target.

Critical to Quality (CTQ) – Any characteristic that is critical to the perceived quality of the product, process or system. See Significant Y.

Critical X – An input to a process or system that exerts a significant influence on any one or all of the key outputs of a process.

Customer – Anyone who uses or consumes a product or service, whether internal or external to the providing organization or provider.


Cycle Time – The total amount of elapsed time expended from the time a task, product or service is started until it is completed.

Defect - An output of a process that does not meet a defined specification, requirement or desire such as time, length, color, finish, quantity, temperature etc.

Defective – A unit of product or service that contains at least one defect.

Deployment (Six Sigma) – The planning, launch, training and implementation management of a six sigma initiative within a company.

Design of Experiments (DOE) – Generally, it is the discipline of using an efficient, structured, and proven approach to interrogating a process or system for the purpose of maximizing the gain in process or system knowledge.


Design for Six Sigma (DFSS) – The use of six sigma thinking, tools and methods applied to the design of products and services to improve the initial release performance, ongoing reliability, and life-cycle cost.

DMAIC - The acronym for core phases of the six sigma methodology used to solve process and business problems through data and analytical methods. See define, measure, analyze, improve and control.

DPMO – Defects per million opportunities – The total number of defects observed divided by the total number of opportunities, expressed in parts per million. Sometimes called Defects per Million (DPM).

DPU – Defects per unit – The total number of defects detected in some number of units divided by the total number of those units.

Entitlement - The best demonstrated performance for an existing configuration of a process or system. It is an empirical demonstration of what level of improvement can potentially be reached.

Epsilon S – Greek symbol used to represent residual error.

Experimental Design – See Design of Experiments.

Failure Mode and Effects Analysis (FMEA) – A procedure used to identify, assess, and mitigate risks associated with potential product, system, or process failure modes.
Finance Representative – An individual who provides an independent evaluation of a six sigma project in terms of hard and/or soft savings. They are a project support resource to both Champions and Project Leaders.

Fishbone Diagram – See cause and effect diagram.
Flowchart - A graphic model of the flow of activities, material, and/or information that occurs during a process.
Gage R&R - Quantitative assessment of how much variation (repeatability and reproducibility) is in a measurement system compared to the total variation of the process or system.

Green Belt – An individual who receives approximately two weeks of training in DMAIC, analytical problem solving, and change management methods. A Green Belt is a part time six sigma position that applies six sigma to their local area, doing smaller-scoped projects and providing support to Black Belt projects.


Hidden Factory or Operation – Corrective and non-value-added work required to produce a unit of output that is generally not recognized as an unnecessary generator of waste in form of resources, materials and cost.

Histogram - A bar chart that depicts the frequencies (by the height of the plotted bars) of numerical or measurement categories.

Implementation Team – A cross-functional executive team representing various areas of the company . Its charter is to drive the implementation of six sigma by defining and documenting practices, methods and operating policies.

Input - A resource consumed, utilized, or added to a process or system. Synonymous with X, characteristic, and input variable.

Input-Process-Output (IPO) Diagram – A visual representation of a process or system where inputs are represented by input arrows to a box (representing the process or system) and outputs are shown using arrows emanating out of the box.

lshikawa Diagram – See cause and effect diagram and fishbone diagram.

Least Squares – A method of curve-fitting that defines the best fit as the one that minimizes the sum of the squared deviations of the data points from the fitted curve.

Long-term Variation – The observed variation of an input or output characteristic which has had the opportunity to experience the majority of the variation effects that influence it.

Lower Control Limit (LCL) -  for control charts: the limit above which the subgroup statistics must remain for the process to be in control. Typically, 3 standard deviations below the central tendency.


Lower Specification Limit (LSL) – The lowest value of a characteristic which is acceptable.


Master Black Belt – An individual who has received training beyond a Black Belt. The technical, go-to expert regarding technical and project issues in six sigma. Master Black Belts teach and mentor other six sigma Belts, their projects and support Champions.

Mean – See average.


Measurement – The act of obtaining knowledge about an event or characteristic through measured quantification or assignment to categories.


Measurement Accuracy – For a repeated measurement, it is a comparison of the average of the measurements compare to some known standard.

Measurement Precision – For a repeated measurement, it is the amount of variation that exists in the measured values.

Measurement Systems Analysis (MSA) – An assessment of the accuracy and precision of a method of obtaining measurements. See also Gage R&R.

Median – The middle value of a data set when the values are arranged in either ascending or descending order.


Metric – A  measure that is considered to be a key indicator of performance. It should be linked to goals or objectives and carefully monitored.

Natural Tolerances of a Process – See Control Limits.

Nominal Group Technique – A structured method that a team can use to generate and rank a list of ideas or items.


Non-Value Added (NVA) – Any activity performed in producing a product or delivering a service that does not add value, where value is defined as changing the form, fit or function of the product or service and is something for which the customer is willing to pay.

Normal Distribution – The distribution characterized by the smooth, bell- shaped curve. Synonymous with Gaussian Distribution.


Objective Statement – A succinct statement of the goals, timing and expectations of a six sigma improvement project.

Opportunities – The number of characteristics, parameters or features of a product or service that can be classified as acceptable or unacceptable.

Out of Control – A process is said to be out of control if it exhibits variations larger than its control limits or shows a pattern of variation.

Output – A resource or item or characteristic that is the product of a process or system. See also Y, CTQ.


Pareto Chart – A bar chart for attribute (or categorical) data categories are presented in descending order of frequency.


Pareto Principle – The general principle originally proposed by Vilfredo Pareto (1848-1923) that the majority of influence on an outcome is exerted by a minority of input factors.

Poka-Yoke - A translation of a Japanese term meaning to mistake-proof.

Probability – The likelihood of an event or circumstance occurring.

Problem Statement – A succinct statement of a business situation which is used to bound and describe the problem the six sigma project is attempting to solve.


Process - A set of activities and material and/or information flow which transforms a set of inputs into outputs for the purpose of producing a product, providing a service or performing a task.


Process Characterization – The act of thoroughly understanding a process, including the specific relationship(s) between its outputs and the inputs, and its performance and capability.


Process Certification – Establishing documented evidence that a process will consistently produce required outcome or meet required specifications.

Process Flow Diagram – See flowchart.

Process Member – A individual who performs activities within a process to deliver a process output, a product or a service to a customer.

Process Owner – Process Owners have responsibility for process performance and resources. They provide support, resources and functional expertise to six sigma projects. They are accountable for implementing developed six sigma solutions into their process.

Quality Function Deployment (QFD) – A systematic process used to integrate customer requirements into every aspect of the design and delivery of products and services.


Range - A measure of the variability in a data set. It is the difference between the largest and smallest values in a data set.


Regression Analysis - A statistical technique for determining the mathematical relation between a measured quantity and the variables it depends on. Includes Simple and Multiple Linear Regression.

Repeatability (of a Measurement) – The extent to which repeated measurements of a particular object with a particular instrument produce the same value. See also Gage R&R.


Reproducibility (of a Measurement) – The extent to which repeated measurements of a particular object with a particular individual produce the same value. See also Gage R&R.

Rework - Activity required to correct defects produced by a process.

Risk Priority Number (RPN) – In Failure Mode Effects Analysis — the aggregate score of a failure mode including its severity, frequency of occurrence, and ability to be detected.

Rolled Throughput Yield (RTY) – The probability of a unit going through all process steps or system characteristics with zero defects.

 
R.U.M.B.A. - An acronym used to describe a method to determine the validity of customer requirements. It stands for Reasonable, Understandable, Measurable, Believable, and Achievable.

Run Chart – A basic graphical tool that charts a characteristic’s performance over time.
Scatter Plot – A chart in which one variable is plotted against another to determine the relationship, if any, between the two.

Screening Experiment - A type of experiment to identify the subset of significant factors from among a large group of potential factors.


Short Term Variation – The amount of variation observed in a characteristic which has not had the opportunity to experience all the sources of variation from the inputs acting on it.

Sigma Score (Z) – A commonly used measure of process capability that represents the number of short-term standard deviations between the center of a process and the closest specification limit. Sometimes referred to as sigma level, or simply Sigma.

Significant Y – An output of a process that exerts a significant influence on the success of the process or the customer.

Six Sigma Leader – An individual that leads the implementation of Six Sigma, coordinating all of the necessary activities, assures optimal results are obtained and keeps everyone informed of progress made.

Six Sigma Project - A well defined effort that states a business problem in quantifiable terms and with known improvement expectations.

Six Sigma (System) – A proven set of analytical tools, project management techniques, reporting methods and management techniques combined to form a powerful problem solving and business improvement methodology.

Special Cause Variation – Those non-random causes of variation that can be detected by the use of control charts and good process documentation.

Specification Limits – The bounds of acceptable performance for a characteristic.


Stability (of a Process) – A process is said to be stable if it shows no recognizable pattern of change and no special causes of variation are present.


Standard Deviation – One of the most common measures of variability in a data set or in a population. It is the square root of the variance.


Statistical Problem – A problem that is addressed with facts and data analysis methods.

Statistical Process Control (SPC) – The use of basic graphical and statistical methods for measuring, analyzing, and controlling the variation of a process for the purpose of continuously improving the process. A process is said to be in a state of statistical control when it exhibits only random variation.

Statistical Solution – A data driven solution with known confidence/risk levels,  as opposed to a qualitative, “I think” solution.

Supplier – An individual or entity responsible for providing an input to a process in the form of resources or information.

Trend - A gradual, systematic change over time or some other variable.

TSSW – Thinking the six sigma way – A mental model for improvement which perceives outcomes through a cause and effect relationship combined with six sigma concepts to solve everyday and business problems.

Two-Level Design – An experiment where all factors are set at one of two levels, denoted as low and high (-1 and + 1).


Upper Control Limit (UCL) for Control Charts – The upper limit below which a process statistic must remain to be in control. Typically this value is 3 standard deviations above the central tendency.


Upper Specification Limit (USL) – The highest value of a characteristic which is acceptable.


Variability – A generic term that refers to the property of a characteristic, process or system to take on different values when it is repeated.


Variables – Quantities which are subject to change or variability.


Variable Data – Data which is continuous, which can be meaningfully subdivided, i.e. can have decimal subdivisions.

Variance – A specifically defined mathematical measure of variability in a data set or population. It is the square of the standard deviation.

Variation – See variability.

VOB – Voice of the business – Represents the needs of the business and the key stakeholders of the business. It is usually items such as profitability, revenue, growth, market share, etc.

VOC – Voice of the customer – Represents the expressed and non-expressed needs, wants and desires of the recipient of a process output, a product or a service. Its is usually expressed as specifications, requirements or expectations.

VOP – Voice of the process – Represents the performance and capability of a process to achieve both business and customer needs. It is usually expressed in some form of an efficiency and/or effectiveness metric.

Waste – Waste represents material, effort and time that does not add value in the eyes of key stakeholders (Customers, Employees, Investors).

X – An input characteristic to a process or system. In six sigma it is usually used in the expression of Y=f(X), where the output (Y) is a function of the inputs (X).

Y – An output characteristic of a process. In six sigma it is usually used in the expression of Y=f(X), where the output (Y) is a function of the inputs (X).


Yellow Belt - An individual who receives approximately one week of training in problem solving and process optimization methods. Yellow Belts participate in Process Management activates, participate on Green and Black Belt projects and apply concepts to their work area and their job.

Z Score – See Sigma Score.

Can Six Sigma Help Improve Clinical Results?

It is not that Six Sigma cannot improve clinical results; it is just that Six Sigma in the healthcare sector is a relatively new phenomenon and as such, not much has been written or documented on the subject.

Additionally, since healthcare centers normally avoid sharing their internal processes, it becomes quite difficult for outsiders to assess exactly how well Six Sigma is faring in the healthcare sector. However, since almost all the information that is available in public domain is positive, it can be said with certainty that it does help in improving clinical results.

For better understanding, let us discuss some of the ongoing healthcare projects involving Six Sigma.

Project For Reducing Chemotherapy Medication Errors

This Six Sigma project is currently underway at a prominent healthcare center in New Jersey. The main objectives of the project include reduction of errors in chemotherapy administration, improvement in documentation, reduction of waste, improvement in patient satisfaction and improvement in the turnover of patients receiving chemotherapy treatment.

The project is currently 6 Sigma DMAIC process (Define, Measure, Analyze, Improve, Control). The project may still be far from completion, but positive results have already started to pour in, evident from the improvements made in patient satisfaction and patient turnover.

Progress on the error reduction front is relatively slow, but the healthcare professionals involved are optimistic about the developments and are quite certain to achieve significant results in a month or two.

Project For Reducing Bloodstream Infections (Bsis)

This 6 Sigma project is almost in its final stages and the positive results achieved so far, vouch for the applicability and effectiveness of 6 Sigma in the healthcare sector. The main objective of this project was to make improvements in the existing healthcare delivery systems so as to meet the prescribed BSIs standards.

The project was executed with the support of the healthcare staff, responsible for developing many innovative solutions such as the “Infection Containment Kit”, development of standard operating procedures, and creation of control charts for improved infection monitoring. These solutions were quite useful because they enabled the healthcare center to achieve the desired results such as significant reductions in BSIs, increase in ICU capacity, and savings of over $400,000 per year.

All these benefits prove the point that Six Sigma is quite effective when it comes to making process improvements in the healthcare sector.

Six Sigma in the healthcare center may still be in its infancy, but considering the positive results that are being reported by healthcare centers and the optimism displayed by healthcare professionals, it can be said that in the years to come, 6 Sigma will no longer be in the trial mode and will instead become a necessity in the healthcare industry.

That is good news for all the stakeholders, especially patients’ for whom even a small clinical error can have fatal consequences.

Six Sigma Makes Its Way to the Contact Center

Contact centers have benefited so much by implementing Six Sigma that now it is impossible for them even to think that they can manage their operations without it even for a single day.

Why Six Sigma Is Better Than Other Quality Initiatives

Six Sigma may have been originally devised as a quality improvement tool for use in the manufacturing sector, but that has not stopped it from making its way to the services industry such as contact centers. It is different because it makes use of foolproof statistical tools and techniques that help in making the most accurate assessments, predictions and calculations, necessary for making effective and long-lasting quality improvements.

Six Sigma has stood the test of time when others have failed because it was quick to embrace emerging technologies, something that helped quite a bit in designing and developing newer and more effective quality improvement tools and techniques.

How Is Six Sigma Helping Contact Centers?

Most contact centers act as a vital link between a company and its customers. As such, it becomes quite important to provide high-quality services that will motivate customers to remain loyal to the company. By implementing this process, contact centers have been able to achieve this objective quite easily, which in turn has proved beneficial for both the company and the customers.

It has also helped to improve the efficiency of agents by reducing their workload and by providing improved work conditions to them.

How Is Six Sigma Helping Contact Centers To Expand Their Operations?

Contact centers that have implemented this process have saved millions of dollars over the years, which are now being used for expansion through the establishment of newer contact centers. Getting work for newly established contact centers is not a problem because every satisfied client automatically recommends the name of the contact center to other potential clients, bringing in more business for the contact center.

Handling the increased workload is also not a problem because 6 Sigma helps in streamlining operations so as to achieve optimum efficiency. Thus, we see that it actually creates a highly profitable business cycle that can be used by any contact center to expand its operations.

The Future Of Six Sigma In Contact Centers

Six Sigma is probably the only quality improvement initiative that has survived the test of time. We can say with quite a lot of conviction that it will continue to be used by contact centers as long as some other more effective quality improvement technique is not developed.

It’s effectiveness can be verified by the fact that companies that had implemented it ten to fifteen years back are still using it in spite of the huge changes in technology. After considering all these factors, it becomes much easier to predict the positive future of Six Sigma in contact centers.

Cutting-Edge Methods Help Target Call Center Waste

Ancillary call center processes have been perfect opportunities to implement Lean Six Sigma. However, some additional effort is needed on the main process of the call center – the call handling process.

With some software systems it is possible to bring about Lean culture and the elimination of waste.

Waste in Call Center Scenario

The agents in call centers will have to be considered as the processes, as they are ones who deal with customer calls. There will typically be a few types of calls received at the call center, but they may be responded to differently each time, as the person on the other end may react differently.

If an agent handles 50 calls a day, they may be responding in 50 different ways. Some help can be taken from (CRM) customer relationship management software to reduce the number of variations. To reduce these variations, a standard process is required. The agent should follow this process closely and management should make an effort to monitor the calls and the agents.

Wastes in call center includes wait times, unnecessary steps and so on. These wastes need to be addressed with due care. Improvements can bring about high levels of customer satisfaction, which is very relevant and important for successful call resolution.

Standardization of Processes

The most important need for call center operations is the standardization of the call handling process, which in itself is very difficult.

Though every customer reacts differently, there are places in the entire conversation where a standardized system can be more effective. For example, take the activation of a cell phone. The initial steps to be undertaken will be the same for all customers, so this process can be automated.

By playing a pre-recorded file on the steps involved, the variation in handling by the agents is eliminated.

Optimize Processes and Eliminate Waste

A standardized process may not be an optimized one. There may be certain activities which may be wastes. In this scenario, management can apply Kaizen or continuous improvement to eliminate waste.

-Wait times in the calls are major sources of waste. In the time when there is silence in a call, resources are tied up in the process but there is no output.

-Sometimes there are certain steps in a call that become necessary, such as asking questions for verification purposes. However, there are some questions which may not serve any purpose, yet data is being collected.

Eliminating such steps can be useful in eliminating waste.

-By mistake proofing, waste can be eliminated. If there are disclosures required by law, they can be pre-recorded and put in at such a stage that they are not left out of the process.

-By monitoring calls of different agents, agents who have higher error levels can be targeted for improvement training.

This would help in improving the productivity of the agents and eliminating waste due to errors and rework, as well customer dissatisfaction.

These steps can prove to be helpful in elimination of waste in the call center and bring about higher customer satisfaction level with the services provided. Additionally, it would mean happier employees and management.

What do you think average pay should be for my Six Sigma experience, qualifications and location?

I am 23 years old and work for a Fortune 50 company in the Midwest as a business development analyst. I have a Bachelor of Science degree in Economics with a minor in mathematical statistics. I have worked for my company for almost a year and they have sent me to two Six Sigma training courses; a week long course to get my Green Belt and a much more intensive and industry recognized Black Belt. I have since been on numerous products yielding +$2 mil results and led to my Certified Black Belt award.

I work on financial reporting, business development (presentations, system administrator work, business solutions for call centers and pharmacies, and creation of knowledge management content), work with individual teams to increase their cost efficiencies, and work on a large dynamic team.

Prior to graduation and my current job, I worked for five years as a pharmacy technician, mastering all three in-house training certification levels.

What do you think a competitive pay would be for my area and with my qualifications! I know it is tough in this economy to get a good barometer of the pay. Thanks!!