Six Sigma how to apply it to a risk management environment · 2011-03-29 · Six Sigma –how to...
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Ian Searle – Vice President Risk Management: Emerging Markets Region Six Sigma – how to apply it to a risk management environment 22nd March 2011 V1.6
Transcript of Six Sigma how to apply it to a risk management environment · 2011-03-29 · Six Sigma –how to...
Ian Searle – Vice President Risk Management: Emerging Markets Region
Six Sigma – how to apply it to a risk
management environment22nd March 2011
V1.6
IRM Forum 2011
Session Summary (in no particular order)
Cutting through the theory
and jargon
Some Six Sigma basics
Applying the principles and a
few takeaways
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Session Objective
This is an educational session with simple objectives:
To share knowledge
To demystify the subject
To put the subject into a risk management context
And some assumptions…..
the audience members are Six Sigma novices
Speaker is the most informed person!
Six Sigma in sixty minutes is a challenge
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Agenda
Deutsche Post DHL
Summary
Six Sigma in Deutsche Post
Six Sigma History
Six Sigma Principles
Some Practical Examples
The Good Stuff
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Agenda
Deutsche Post DHL
Summary
Six Sigma in Deutsche Post
Six Sigma History
Six Sigma Principles
Some Practical Examples
The Good Stuff
IRM Forum 2011
Deutsche Post DHL
German post office/ “logistics”
DHL
Exel/ Tibbet and Britten/ Danzas/ NFC
500,000 staff
€50 billion revenue
252 countries
Risk management team of 215 in 6 regions
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DP DHL and Six Sigma
The business uses a hybrid of Six Sigma – dubbed “First
Choice”
This has been running for 5 years across the entire company
Some legacy businesses have operated it for 10+ years
All senior staff have IKOs set around First Choice
Involvement is strong “brownie point” winner
Strong training programme
Much internal and external promotion
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Agenda
Deutsche Post DHL
Summary
Six Sigma in Deutsche Post
Six Sigma History
Six Sigma Principles
Some Practical Examples
The Good Stuff
IRM Forum 2011
History of Six Sigma
Motorola developed the Six Sigma methodology in the mid-
1980’s
Motorola saved $17 Billion from 1986 to 2004, reflecting
hundreds of individual successes in all Motorola business
areas including:
Sales and Marketing
Product design
Manufacturing
Customer service
Transactional processes
Supply chain management
Statistical term dates back to the 1800’s (Carl Frederick Gauss)
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Development of Six Sigma
“Minimal error rate” became a critical byword as manufacturing
automation developed
Six Sigma became a management tool – some describe it as the
“most popular management tool in history”
Mass production companies embraced the concept
(automotive/ engineering)
Mass transactional companies began to take an interest
(financial lines)
Six Sigma has became an industry in it own right – Google it!
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Converts to Six Sigma
Air Canada
Amazon.com
AXA
Bank of America
Bechtel Corporation
Boeing
Caterpillar Inc.
CIGNA
Cummins Inc.
Deere & Company
Dell
DHL
DuPont
Raytheon
Samsung Group
Siemens AG
SKF
Vodafone
United States Military Forces
Ford Motor Company
HSBC Group
LG Group
Littlewoods Shop Direct Group
Lockheed Martin
Merrill Lynch
Network Rail
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Six Sigma – Nirvana or Nonsense?
“Dilbert and his pointy haired boss tackled two topics that are near and dear to
my heart: Six Sigma and innovation. In one fell swoop, he reduced both topics
to buzz words and hype.”
WARNING:
“You must learn to love statistics & quantitative analysis!”
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Agenda
Deutsche Post DHL
Summary
Six Sigma in Deutsche Post
Six Sigma History
Six Sigma Principles
Some Practical Examples
The Good Stuff
IRM Forum 2011 2009 11 11Contract Risk Pricing Toolkit 14
The textbook quotes: 6
A statistical measure of variation
Full Six Sigma equals 99.9997% accuracy
A methodology for improving key processes
A “tool box” of quality and management
tools for problem resolution
A business philosophy focusing on
continuous improvement
An organized process for structured analysis
of data
What is Six Sigma?
IRM Forum 2011
The Ian Searle Precis
Small things keep going wrong
The events are too small to matter – irritation factor
only
The cost of each event is just too small
More important things to do than fix them
“If only we had the time”
No one really knows the root cause
Where do you start?
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When to Use Six Sigma
Unknown causes/situations
Problems are commonplace and not well defined
When “broad brush” approach is inappropriate
When other problem solving methods fail
In a complex situation with many variables
Volume transactions/ processes
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Why Use Six Sigma?
Intense competitive pressures – especially from
rapid globalization.
Greater consumer demand for high quality products
and services, little tolerance for failures of any type.
Top management (and stockholder) recognition of
the high costs of poor quality.
The availability and accessibility of large databases
and the increasing ability to explore, understand,
and use the data.
Proven methodology to solve problems
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The Process: Overview
Scope the problem; break it down into component
parts
Don’t jump straight to a “logical conclusion”
Check that the importance of the problem/ project is
evident or can be readily demonstrated.
Check the project is viable and do-able in a short
time (90 days maximum).
Check that the output of the project can be readily
quantified.
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The Methodology: Overview
A core concept that drives the process
Provides a logical sequence for applying existing
problem solving tools and concepts
Various quality/management tools applied at each
step
Project sponsor review recommended at conclusion
of each step before moving to next step
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The Essentials for an Initiative
A baseline
A business case
A charter
“Voice of the Customer”
Data!
Root cause analysis
Solution
Pilot
Rollout
Project closure
Continuous review
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The Participants
Executive Leader/ Sponsor
Champion
Workshop Leader (Black belt)
Initiative team
Change Agent
Scribe
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Six Sigma Belts
3 levels (or Belts)
Based on level of competence in understanding and applying
related tools
Green belt - basic analytical tools; works on less complex projects
Black belt - emphasis on application and analysis; works projects
with help from Green belts
Master Black belt - understands application and statistical theory
behind application; trains other belts; leads project reviews
Actual definition and competencies for each belt can vary by
organization and training institutions
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The Processes – For Acronym Lovers Everywhere!
The Core Concepts 1:
D.M.A.I.C, (Define, Measure, Analyze, Improve, Control)
Define Define the project goals and customer (internal and external) deliverables
Measure Measure the process to determine current performance
Analyse Analyse and determine the root cause(s) of the defects
Improve Improve the process by eliminating defects
Control Control future process performance
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The Processes
The Core Concepts 2:
D,M,A,D,V (Define, Measure, Analyse, Design, Verify)
Define Define the project goals and customer (internal and external) deliverables
Measure Measure and determine customer needs and specifications
Analyse Analyse the process options to meet the customer needs
Design Design (detailed) the process to meet the customer needs
Verify Verify the design performance and ability to meet customer needs
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When to Use DMADV over DMAIC
When To Use DMADV:
The DMADV methodology, instead of the DMAIC methodology,
should be used when:
A product or process is not in existence at your company and one needs to be
developed
The existing product or process exists and has been optimized (using either
DMAIC or not) and still doesn't meet the level of customer specification or six
sigma level
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Agenda
Deutsche Post DHL
Summary
Six Sigma in Deutsche Post
Six Sigma History
Six Sigma Principles
Some Practical Examples
The Good Stuff
IRM Forum 2011
Six Sigma Step-by-Step DMAIC Process
Copyright 2003 Northrop Grumman Space and Mission Systems Corp. All Rights Reserved. 27
Develop Charter and
Business Case
Map Existing Process
Collect Voice of the Customer
Specify CTQs / Requirements
Measure CTQs / Requirements
Determine Process Stability
Determine Process Capability
Calculate Baseline Sigma
Refine Problem Statement
Identify Root Causes
Quantify Root Causes
Verify Root Causes
Institutionalize Improvement
Control Deployment
Quantify Financial Results
Present Final Project Results
and Lessons Learned
Close Project
Select Solution (Including
Trade Studies,
Cost/Benefit Analysis)
Design Solution
Pilot Solution
Implement Solution
Define
Measure
Analyze
Improve
Control
DMAIC = Define, Measure, Analyze, Improve and Control
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Seven Tools of Quality
Commonly used tools in just about every DMAIC Six Sigma project to help
understand an existing process and drive most effective improvements.
Fishbone diagram (finding the all the root causes)
Check sheet (collecting data)
Flowchart (Process Map-what is really happening)
Control chart (determining the initial and final state of process)
Histogram (determining the data distribution)
Pareto chart (finding the vital few)
Scatter diagram (for correlation/regression)
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Some Common Six Sigma Acronyms and Buzz Words!
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20 KEYS
SWIMLANE
TIMWOOD
POKA YOKE
8D
KAIZENKANBANS
ERROR
PROOFING
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Before We Leave the Theory…….
Ensure the “before” and “after” positions are tracked
Document the whole process - workbooks
When applied correctly, DMAIC will produce consistently better
results than most other methods
Adoption requires a cultural change in order gain best results
Top Management must be patient - there is no quick fix
Six Sigma is about getting the right answer, not just any answer
DMAIC is not for every project
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Agenda
Deutsche Post DHL
Summary
Six Sigma in Deutsche Post
Six Sigma History
Six Sigma Principles
Some Practical Examples
The Good Stuff
IRM Forum 2011
Six Sigma in DPDHL – “First Choice”
Driven by the Board
Huge investment – time and money
Embedded in managers’ IKOs
Major component of Group Strategy
Introduced for benefit of customers
Heavily sold to customers
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Six Sigma “Lite”
In DPDHL much of the concentration is around a slimmed-down version of Six
Sigma dubbed “Lean”
Lean Methodology: Reducing waste, anything that has no added value in the
eyes of the customer
Six Sigma Methodology: Reducing variation, defects and mistakes
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The Essentials for an Initiative – DPDHL Approach
A baseline – the problem or issue
A business case – the need to commit resources to fixing the issue
A charter – finely-tuned/ few words/ precise
“Voice of the Customer” – business partner inputs/ joint collaboration
Data! – all sources/ often “in the head”
Root cause analysis – measure problem and deep-dive
Solution – most efficient solution – not necessarily cheapest or
quickest
Pilot – where appropriate, then revisit and challenge
Rollout – post-pilot full launch
Project closure – advertising/ marketing/ brownie points
Continuous review – keep charters open indefinitely
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Agenda
Deutsche Post DHL
Summary
Six Sigma in Deutsche Post
Six Sigma History
Six Sigma Principles
Some Practical Examples
The Good Stuff
IRM Forum 2011
UK FRAUDULENT MOTOR CLAIMS
Case Study
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Crash for Cash – the Wake-up Call
The Early Alert
Insurer called the UK team to give early notice of some trends their Claims
team had been monitoring
Indications were DPDHL vehicles were being targeted by fraudsters as part of a
wider Crash for Cash scam
A meeting was requested to agree a joint response to the problem
A baseline was borne….
Lean requires the problem to be broken into
many small parts and each analysed separately
Lean also often makes each part a separate and
new initiative so complex issues can become
several initiatives
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Establishing a Charter - DEFINE
The issue was discussed with affected business partners
They were invited to participate in an initiative
Facts and opinions were gathered to ensure a single issue became the sole
focus
A First Choice Champion was allocated and a team assembled
The team:
Determined the business case based on likely results
Produced a one-line charter
Parked items that could detract from the focal initiative
External help sought to determine a stocktake around available data
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The team is Engaged - MEASURE
Process
6,000 claims analysed by forensic lawyers and uploaded to a fraud
database (linked to IFB)
Around half contained insufficient information to identify fraud (for later
review)
Only 300 cases contained enough meaningful data to facilitate deep dive
analysis – some lessons to be learned here on
poor quality of data captured
lost opportunity
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Stocktake Results - ANALYSE
Findings:
234 cases were worthy of a deep dive fraud analysis
This analysis showed 40 claims were almost certainly fraudulent –
others lacked sufficient defence material
22 “hard cases” identified for immediate claim shutdown
Value of the 22 cases nearly €1m
External inputs:
The insurance industry believes 10% of all claims are fraudulent – €1m
accounts for around 5% of DHL UK third party insurance costs so yet
more potential
£44 of every personal lines insurance premiums is spent on funding
fraudulent claims
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Follow-up - IMPROVE
Next steps (1)
Support insurer and the IFB who are driving anti-fraud measures.
Support insurer in repudiating claims – feed them meaningful data at the
point a claim received
Brief drivers to avoid getting into “slam-ons”
Brief and motivate drivers to assist in spotting potential fraudulent
claims when/ after an accident happens
Ask intuitive questions at data capture point (accident site is best point!)
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Follow-up 2 – IMPROVE AND LOOP-BACK
Next steps (2)
Encourage drivers to revisit past accidents to fill data gaps on the 200+
“parked” claims
Monitor repudiated claims and provide business partner with updates
Consider risk management initiatives to support defence of fraudulent claims,
eg “camera in the cab”
Roll out review, analysis and follow-up to other UK and Ireland business
partners
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Final Phase - CONTROL
DPDHL sponsored a formal framework for tackling the problem:
Post Accident
Monitoring incoming new accident reports
Monitoring new claims
Working with insurer on new escalated claims – eg litigated cases; faster evidence gathering
Pre Accident
DHL Risk funded the relevant UK businesses to take proactive measures .
Cameras in the cab.
Poster Campaign
Vehicle stickers
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Continuous Improvement
Raised awareness of potential fraud – fraud indicators
Cameras in Cabs – The Spin offs:
Changed driver behaviour.
Defense against non fraud claims.
Driver Control
Workforce positive feedback
Unions accepted and backed concept
Driver safety
Safe driver awards
Protected drivers in dispute cases
DMAIC output rolled out to other areas of the business.
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Other Initiatives
BMW packaging – damage claims
New contract data gathering – cross service
line collaboration
Contract simplification
Legal expenses costs – cross-service line
collaboration
Paperless claims processes
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Agenda
Deutsche Post DHL
Summary
Six Sigma in Deutsche Post
Six Sigma History
Six Sigma Principles
Some Practical Examples
The Good Stuff
IRM Forum 2011
Conclusion
A gauge of quality and efficiency, Six Sigma is also a measure of
excellence.
Embarking on a Six Sigma program means delivering top-quality service
and products while virtually eliminating all internal inefficiencies (Dedhia,
2005).
A true Six Sigma organization produces not only excellent product but
also maintains highly efficient production and administrative systems that
work effectively with the company's other service processes (Lucas, 2002).
The primary factor in the successful implementation of a six sigma project
is to have the necessary resources, the support and leadership of top
management.
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BACK-UP
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Everything is a Process
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Process Examples:
Building a product, e.g. a phone,
modem, base station, etc.
Developing software
Preparing financial statements
Preparing a sales presentation
Hiring personnel
Getting ready for work
Inputs
Processes must be measured to
establish a baseline (current condition)
against which future improvement can
be quantified
Process measurements may be either
direct or indirect:
•Cycle time in a product development
process (too long)
•A quality characteristic that falls
outside the specs (defect)
•A process characteristic that is
important for the product/service
•Retention rate (measuring employee/
customer satisfaction)
Process Outputs
IRM Forum 2011Copyright 2003 Northrop Grumman Space and Mission Systems Corp. All Rights Reserved. 51
Six Sigma Training – a Sample
Excerpts from standard Green Belt Six Sigma training:
Business Case development
Voice of the Customer (Critical to Quality items)
Basic Statistics and Sampling
Data distributions
Representative samples
Patterns in Data – Variation
Special vs common causes
Stratification of data
Run charts, control charts
Organizing Causes
Hypothesis Testing / Regression Analysis
