Six Sigma in the Contact Center

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Six Sigma in the Contact Center

• Northwest Call Center Professionals
• Help Desk Northwest
• May 17, 2006
• Mike Stone

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Agenda

• Introduction to Six Sigma
• Full Life-Cycle Case Study

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Introduction

• Six Sigma was invented by Motorola, Inc. in 1986
  as a metric for measuring defects and improving
  quality. Since then, it has evolved to a robust
  business improvement methodology that focuses an
  organization on customer requirements, process
  alignment, analytical rigor and timely execution.

http//www.motorola.com/content/0,,3074-5804,00.ht
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Six Sigma, the GE Way

• Six Sigma - A vision of quality which equates
  with only 3.4 defects per million opportunities
  for each product or service transaction. Strives
  for perfection.
• DFSS (Design for Six Sigma) is a systematic
  methodology utilizing tools, training and
  measurements to enable us to design products and
  processes that meet customer expectations and can
  be produced at Six Sigma quality levels. (DMADV
  - Define, Measure, Analyze, Design, Verify)
• DMAIC (Define, Measure, Analyze, Improve and
  Control) is a process for continued improvement.
  It is systematic, scientific and fact based. This
  closed-loop process eliminates unproductive
  steps, often focuses on new measurements, and
  applies technology for improvement.

Source http//www.ge.com/sixsigma/glossary.html
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Other Quality Systems

• Total Quality Management (TQM)
• Toyota Production System (TPS)
• Kaizen
• Lean
• Theory of Constraints
• Agile
• PDCA Plan, Do, Check, Act
• Good Manufacturing Process Pharma
• ISO 9000

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Key Concepts

• A process is all the activities involved in
  producing a product or service for a customer.
  It is cross-functional in nature
• Quality is defined by customer requirements for
  the chosen process
• Defects are defined and counted
• Inconsistencies in the process, known as
  variation, are studied
• Causes of variation are identified and addressed

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Key Terminology
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Key Terminology
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DMAIC
Define
Measure
Improve
Analyze
Control
Team Chartering Customer Focus Process Mapping
Measurement Variation Data Collection
Data Analysis Process Analysis and Focus Root
Cause Analysis Quantify Opportunity
Generate Solutions Select Solutions Implementation
Planning
Monitor the Process Documentation Institutionalize
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Case Study
IT services business Customer service call center
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Project Selection

• Business strategy
• How important is customer satisfaction?
• How important is it to attract new customers?
• Competitive position
• How do we compare to our competitors?
• Benchmarking
• Best projects
• Issue is well-defined with supporting data
• Scope is well-defined
• Objectives are stated in business terms and are
  measurable

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Project Selection

• Customer satisfaction
• Average
• Lower than best-in-class in industry
• Positive correlation with account growth
• Customer satisfaction and new accounts are
  statistically related to one another
• Business judgment
• No correlation with customer service spending
• Per call costs were not higher at strong
  competitors
• Goals Reduce support costs while improving new
  account growth

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Define

• Team Chartering
• Goal statement "Increase the call center's
  industry-measured customer satisfaction rating
  from its current-level (90th percentile 75
  percent) to the target level (90th percentile
  85 percent) by end of the fourth-quarter without
  increasing support costs.
• Milestones, tasks, responsibilities, schedule and
  communication plan.

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Define

• Customer Focus
• SIPOC diagram identify customers (stakeholders)
• Customers
• Staff
• Business
• Voice of the Customer interviews
• "What influences your level of satisfaction with
  our services?"
• Summarize customer requirements
• Identify measures for each requirement
• Next slide

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Define
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Define

• Process mapping
• Helpful during the Measure phase, as the project
  team considers how and where to gather data that
  will shed light on the root cause of the issues
  most pertinent to the project's goals.

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Measure

• Define measures and how the data will be gathered
• Example
• Customer Satisfaction
• By industry standard monthly survey
• The project will require additional, more
  frequent, case-by-case customer-satisfaction
  data. A measurement system that tracks with the
  industry survey will be devised and validated.

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Measure

• Define performance standards
• Example
• Customer Satisfaction
• Current Baseline
• 90th Percentile / 70-80 Satisfied
• Performance Target
• 90th Percentile / 85 Satisfied

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Measure

• Identify segmentation factors for data collection
  plan
• Focus data collection effort
• Use cause-and-effect tools
• How is Y naturally segmented?
• Call center, product type?
• What factors may be driving the Ys?
• Take a guess at what your important Xs might be
• Call type, customer type?

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Measure

• Assess measurement system
• Accuracy
• Does the measure agree with the truth?
• Repeatability
• Does the system always produce the same value?
• Reproducibility
• Will different people get the same results?
• Stability
• Is the system accurate over time?

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Measure

• Collect the data
• Automated
• Manual
• New metrics may be needed
• Display the data
• Look for clues into causes of variation
• Simple charts and graphs

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Analyze

• Measure process capability
• Compare current performance to standards
• Refine improvement goals
• Adjust goals if data shows departure from
  expectations
• Segment data
• Slice and dice data to look for patterns to find
  causes of variation

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Analyze

• Identify possible Xs
• Likely suspect causes of variation
• Identify and verify the critical Xs
• Narrow down to most important causes of variation
• Why do Problems and Changes cost more than other
  call types?
• Why are calls processed on Mondays and Fridays
  more expensive?
• Why do transfer rates differ by call type?
  (higher on Problems and Changes, lower on others)
• Why are wait times higher on Mondays and Fridays
  and on Week 13 of each quarter?

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Analyze

• Refine the benefit forecast
• Update the forecast of how much improvement can
  be expected
• Found that key support cost drivers (the delays
  and interruptions during call-servicing) were the
  same as those known to drive down customer
  satisfaction so a win-win seemed to be
  possible.

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Improve

• Identify Solution Alternatives

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Improve

• Verify the Relationships Between Xs and Ys
• Solution Selection Matrix
• Solution Alternatives
• Customer Requirements (CTQs)
• Regression Analysis
• Determine the strength of each solution against
  the CTQs

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Improve

• Select and Tune the Solution
• Details of the plan for the Monday staffing pilot
  program
• Xs to adjust Staffing level (add five for pilot,
  full increment to wait for evidence plan works)
• Ys to measure for impact and unintended side
  effects
• Wait time, v/s ratio, customer satisfaction,
  transfers, callbacks, service time.
• Compare "new staff" versus "old staff"
  (hypothesis test).
• Measure monthly to observe learning curve effect,
  if any

(continued on next page)
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Improve

• Details of the plan for the Monday staffing pilot
  program
• Measurement system issues Revise existing
  sampling plan and data collection process to
  distinguish new staff from old staff.
• Because the current customer satisfaction
  sampling gives only 1 data point per month (not
  enough to see a change), arrange a special sample
  five per day for the first 60 days of the pilot
  (80 percent from existing staff, 20 percent from
  new staff).
• People and logistics issues Communicate what is
  happening and why. Emphasize evaluation is not of
  individuals, only overall impact.

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Improve

• Implement Solution
• Pilot, if possible
• Collect data during pilot
• Xs and Ys
• Watch for unintended impacts
• Report out and obtain approval for full
  implementation

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Control

• Develop Control Plan
• Management control dashboards Ys
• Operational control indicators Xs
• Determine Improved Process Capability
• Business Growth
• Customer Satisfaction
• Support Cost per Call
• Days to Close
• Wait Time
• Transfers
• Service Time

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Control

• Implement Process Control
• Ongoing data collection and presentation
• Close Project
• Roll out process changes
• Training
• Transition control to management
• Validate results
• Refinements
• Project post mortem

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Tools
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Tools

• ANOVAANalysis Of VAriance (ANOVA), a
  calculation procedure to allocate the amount of
  variation in a process and determine if it is
  significant or is caused by random noise.

• Cause and Effect DiagramA cause and effect
  diagram is a visual tool used to logically
  organize possible causes for a specific problem
  or effect by graphically displaying them in
  increasing detail. It helps to identify root
  causes and ensures common understanding of the
  causes. It is also called an Ishikawa diagram.

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Tools

• Control ChartA graphical tool for monitoring
  changes that occur within a process, by
  distinguishing variation that is inherent in the
  process (common cause) from variation that yield
  a change to the process (special cause).

• Kano AnalysisKano analysis is a quality
  measurement tool used to prioritize customer
  requirements based on their impact to customer
  satisfaction.

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Tools

• ParetoThe Pareto principle states that 80 of
  the impact of the problem will show up in 20 of
  the causes. A bar chart that displays by
  frequency, in descending order, the most
  important defects.

• Run ChartA performance measure of a process
  over a specified period of time used to identify
  trends or patterns.

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Tools

• X-Bar and R ChartsThis set of two charts is the
  most commonly used statistical process control
  procedure. Used to monitor process behavior and
  outcome overtime.

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Resources

• http//www.isixsigma.com/
• http//www.sixsigmainstitute.com/
• http//www.motorola.com/motorolauniversity
• http//www.ge.com/sixsigma/
• The Six Sigma Way How GE, Motorola, and Other
  Top Companies are Honing Their Performance by
  Peter S. Pande, Robert P. Neuman, Roland R.
  Cavanagh
• Fourth Generation Management by Brian L. Joiner
• Leading Six Sigma by Ronald D. Snee and Roger W.
  Hoerl
• The Pocket Idiots Guide to Six Sigma by Marsha
  Shapiro and Anthony Weeks

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Six Sigma in the Contact Center

• Mike Stone
• Mobile [phone]
• mgstone2020_at_yahoo.com