1 © 1995-2006 the paul selden companies, inc. sales process engineering a systematic approach to...

© 1995-2006

The Paul Selden Companies, Inc.1

Sales ProcessEngineering

A Systematic Approach to Improving Sales, Marketing &

Customer Service

© 1995-2006


Introduction & WelcomeIntroduce Yourself Name

Company’s Products and Sales Channels (OK to brag here)

Personal Background in engineering, ISO, TQM, SPC, etc. related to topic today

Instructor’s Background

© 1995-2006


About Paul Selden Business Experience: Founded Performance Management,

1978; board member, 3 related companies Six Sigma / DOE related experience: GE,

AlliedSignal/Honeywell, others Project Track Record: $100+ M sales Education & Cert.: Instructional Design, Large Scale Systems

Implementation, Behavioral Psychology, Certified Quality Engineer, Certified Performance Technologist

Author: Sales Process Engineering Researcher: 500+ tested sales & marketing factors on file Email: [email protected] Voice: 269-343-3700 x101

© 1995-2006


Definition What is “Sales Process Engineering”?

© 1995-2006


Sales Process Engineering: Definition The systematic application of scientific and

mathematical principles to better serve the practical goals of a particular sales process.

Who is a sales process engineer? A very smart and energetic sales person A manager who is also a builder and leader An internal or external consultant

© 1995-2006


New vs. Old View

Old View: Too focused on discrete, one-time transaction New View: Must include repeat sales and entire process, not

just “closing the deal” Old View: Engineering only works in manufacturing and product

development New View: Systematic approach works in most any field, such

as information flow, biology, sales, marketing, customer service

Old View

© 1995-2006


Engineering Gurus Agree On One Key Point

15%85%

More than 80% of problems in a process are dueto the systems, usually in management’s control.

IndividualSystem

If you fix the system, a lot of what you thinkare “people problems” are reduced, as well.

Sales Process Engineering focuses on structure first.

© 1995-2006


Workshop GoalsMAIN GOALS Learn a systematic approach to improving

sales, marketing, and customer service Learn tools Apply ideas to your own business Stimulate the imagination!

* Throughout, we speak of “sales” as outputs of a system or systems, not as a single “department.” Our focus will be on sales, marketing, and customer service systems.

© 1995-2006


Agenda Bienvenidos and Introductions The “DMAIC” Method of Improvement Define: Process Mapping The Big Picture Measure: Using “SPC” With Sales Data Analyze: Simulating the Steps and Using Cause-

Effect Logic to Find Greatest Constraint Improve: Brainstorming & Testing Improvements Control: Holding the Gains Summary and Adiós

© 1995-2006


Other Expectations? Ask As Other Issues Arise During Workshop We’ll Try to Cover With Only Two Days, We May Need to Put

Some on a “Parking Lot”

© 1995-2006


Agenda Bienvenidos and Introductions The “DMAIC” Method of Improvement

© 1995-2006


The Steps of “DMAIC”

Made popular under the name “Six Sigma” Useful general method for process

improvement We will use the DMAIC sequence to show

when to apply tools of Sales Process Engineering (other steps are also possible)

Define Measure Analyze Improve Control

© 1995-2006


DMAIC and Our Agenda


StatisticalProcessControl Statistical

ProcessControl

ProcessMaps

Simulation

Theory ofConstraints

Cause-EffectDiagrams

BehavioralPsychology

Flowcharting

Brainstorming

Design ofExperiments

© 1995-2006


Discussion

© 1995-2006


Agenda Bienvenidos and Introductions The “DMAIC” Method of Improvement Define: Process Mapping The Big Picture

© 1995-2006





ProcessControl

ProcessMaps

Simulation




Flowcharting

Brainstorming


© 1995-2006


Dr. Deming’s Map – Business As A System

Materials&

Equipment:Suppliers

A

B

C

D

Receive&

TestMaterials

Produce,Assemble& Inspect Distribute

Consumers

Tests of Processes, Machines,Methods, Costs

ConsumerResearch

Design andRedesign

- Source: WE Deming, 1982

© 1995-2006


Process Models: Ballistic System

Input Output

Process

No adjustment per feedback

Supplier Customer

Note: Six Sigma calls this the “SIPOC” model

© 1995-2006


Process Models: Guided System

Input Output

ProcessingSystem

(Adapted from Brethower)

Can correct output

© 1995-2006


Process ModelsAdaptive System

Input Output

ProcessingSystem

Customer:Receiving System

(Adapted from Brethower)

Output

Can correct output and adjust goal per shifts in customer needs

© 1995-2006


Business to Business Sales Acquisition Process

Leads

ContactAnalyzeNeeds

PresentDevelopProposal

CloseEnterOrder

Service

Follow-up

© 1995-2006


Repeat Business Process

ClientNeeds

AnalysisAdvise Agree

EnterOrder

Service

Invoice

Repeat Business ModelGoal: Profitable Ongoing & Increasing Sales

© 1995-2006


Sales Management Process

Attract,Select

MakeOffer,Hire

Train &Equip

SetGoals

Coach Evaluate Reward

Promote

LetGo

Retire

© 1995-2006


Customer’s B to B Buying Process

DetectMkt

Needs

ContactPotentialSuppliers

RevealNeeds/Wants

GenerateRFPs

CompareProps/

Sign Deal

Use &Maintain

Item

© 1995-2006


Checklist: Is Your Process Well Managed? Accountable process owner Well defined process boundaries Clear internal communication and responsibilities Documented procedures & training requirements Measurement & feedback close to activities

performed Customer-related measurements and targets set Known standards Know how well they perform against standards Know how to change/improve when needed

From Harrington

© 1995-2006


Tool:Flowcharting

SurveyLead

Qualified?

Passto Rep

Yes

No Pass toReferral

Plan

Portionof Telemarketing

LeadScreeningProcess

© 1995-2006


Flowcharting Flowchart: picture of steps in a process Variation: Functional flow chart (shows ownership of

steps) Common symbols: diamond (decisions) and

rectangles (procedures); many others Define boundaries of process under study Assemble true experts in flow to diagram Each process block should have definite input from

previous operation Each block should deliver output to next step or

operation downstream

© 1995-2006


Checkpoint

© 1995-2006


Activity - Mapping Your Sales Process Small groups - by company or in pairs

(consultants split up) Break your own process into 5 to 7 sequential

blocks representing MAIN sub-processes Details not important now, just big picture Draw decision diamonds between sub-

process blocks even if not sure what to put into decision diamonds for now

© 1995-2006


Mapping Your Sales Process

© 1995-2006


Discussion

© 1995-2006


Agenda Buenos Dias and Introductions The “DMAIC” Method of Improvement Define: Process Mapping The Big Picture Measure: Using “SPC” With Sales Data

© 1995-2006





ProcessControl

ProcessMaps

Simulation




Flowcharting

Brainstorming


© 1995-2006


Visualize Output Of Selling System As a Stream Over Time

Time

OurMeasure

(e.g.,Sales)

© 1995-2006


The Eternal Decision-Making Dilemma

Quarter

Revenue

Stay The Course or Take Extreme Measures?

© 1995-2006


The Quote Closing Experiment

© 1995-2006


Closing ScorecardQuarterQuarter

RepRep

TotalTotal

1 2 3 4

AverageAverage

TotalTotal

© 1995-2006


Examining the RecordAs a real life manager, which reps would you:

… send on the annual President’s Club trip?

… encourage to try harder?

… pat on the back for improving the most?

… fire? Is there a better way to make decisions than

this?

© 1995-2006


Scorecard Revisited

© 1995-2006


Need To “Filter Out” False vs. Real Alarms

False Alarm #1

Reacting to a normal outcome as if it were unusual

False Alarm #2

Failing to act on a genuinely unusual outcome

© 1995-2006


Source of the Filter: Natural Process Behavior

Time

OurMeasure

(e.g.,Sales)

Concept:Use “Like” Subgroups as Filter to

Detect “Different” Subgroups

© 1995-2006


Alarm Zones Set Empirical Triggers on Financial Data

Time

Upper Alarm Zone

Lower Alarm Zone

OperatingMargin

© 1995-2006


Four Cautions for Setting Up Basic Filter

1. Subgroup data “rationally” - like with like

2. Never dump all the data together and use “standard deviation” for the filter

3. Standardize measurement gathering procedure; stick to it

4. Follow the rules for selecting and interpreting charts

© 1995-2006


Calculating & Applying the FilterSee Worksheet

“It Is More Important to

Take the Right Action

Than to Find the Right Number”-- Don Wheeler

© 1995-2006


Plotting the Performance

5 10 15 20

10

5

15

20

RevenueRevenue

SequenceSequence

© 1995-2006


Testing For SignalsSee Handout

© 1995-2006


When Process is “In Statistical Control”Only random causes are presentVariation occurs around a consistent meanBeing in statistical control is based on

observations and calculations

Upper Natural Process Limit (UNPL)

Lower Natural Process Limit (LNPL)

Average

Time

Revenue

Chart - With Operationally Determined Limits

© 1995-2006


Operational Definition of ChangeWhat is an “operational definition?”Specifying the operation by which

something is done or assessedAllows for repeatable decision-making and

action Typical Management Graph

Revenue

Time

© 1995-2006


Two Strongest Alarm SignalsDesirable When performance trips alarm on the “good” side, it is vital to

detect it so that the factors causing it can be replicated or enhanced more consistently.

Undesirable It is just as or more critical to detect alarms on the “bad” side, so

the factors causing it can be prevented from recurring.

Good

Bad

© 1995-2006


Operational Definition of “Predictable”

Quarter

UNPL

LNPL

ServiceLevel

© 1995-2006


Meeting Quotas -- Or Tossing Dice?

Upper Alarm Zone

Lower Alarm Zone

Time

Revenue

Goal

Zone of EmpiricallyPredicted

Result

An Objective Definition of Need to Change System

© 1995-2006


Uses Credit and Collections Forecasting Performance Appraisal System Improvement Monitoring Service Levels Inventory and Stocking Goal Setting Setting Baselines Before Conducting “DOE” Other?

© 1995-2006


Discussion

© 1995-2006


Agenda Bienvenidos and Introductions The “DMAIC” Method of Improvement Define: Process Mapping The Big Picture Measure: Using “SPC” With Sales Data Analyze: Simulating the Steps and Using

Cause-Effect Logic to Find Greatest Constraint

© 1995-2006





ProcessControl

ProcessMaps

Simulation




Flowcharting

Brainstorming


© 1995-2006


Process Engineers Identify Two Types of Problems Sporadic problems: feedback detects, then

troubleshooting, fixing, and preventing reduces chance of recurrence

Systemic: ordinary feedback loop not sufficient, must change very nature of system or inputs; careful diagnosis, careful remedy testing, and implementation needed

ChronicProblems

in allProcesses

Sporadic

© 1995-2006


Approaches to Analyzing Cause-Effect Previous Studies Cause – Effect Mapping Simulation

© 1995-2006


Causes of Low Sales

Talk to Wrong Prospects

Lack of Contacts

Not Enough Names

Not Getting RightDecision-Makers

Coffee Drinking

Staring Into Space

“Cheating on Time”

Turnover

Poor Presentation

Poor Pricing

Poor Proposal

Tracking Orders

Paperwork

Travel to Client

Sales

Entry Errors

Late Delivery

Claims

Tim

e/P

eop

le

© 1995-2006


Top Ten Sales Process Problems - Selden1. Failure of marketing to find and capitalize on

existing information

2. Insufficient qualification of leads prior to passing to sales

3. Blind use of field sales to perform all types of contact

4. Absence of presentation impact analysis

5. Non-uniform and incomplete customer needs analysis

© 1995-2006


Top Ten Sales Process Problems (cont’d)6. Pricing policies and systems for complex

items

7. Labor intensive quote and proposal generation

8. Lack of ability to understand and adjust close to true customer motivations

9. Order entry errors

10. Broken implicit and explicit service commitments

© 1995-2006


Cause and Effect Diagram

LowerSales

Example: Causes for Lower Than Desired Sales

BargainShoppersDon’t LikeOur Price

Used Merchandise

Competes

No UniqueSelling

Proposition

“Politics”Influence

Decisions ToPut on Shelves

CustomersHave

Many Choices Poor SupportFrom Own

Staff

CustomerBuying

Season Short

Not RequiredTo Buy

Our Brand

© 1995-2006


Cause & Effect Diagrams Diagram of relationship between outcome and

potential controlling factors (from Ishakawa) Layout resembles “fishbone,” “stream and river” or

“branch and limb” appearance Effect is main trunk, causes are branches, main

causes can be boxed at branch ends Ask “5 Why’s;” don’t stop until all final “root” causes

exhausted Effect, or symptom of problem, must be clearly stated

or group will be confused Does not demonstrate true responsibility between

one cause and others

© 1995-2006


Checkpoint

© 1995-2006


Activity - Surfacing Cause and Effect Examine your process maps. Circle a portion you are having trouble with. Draw a cause and effect diagram exploring

“reasons why”

© 1995-2006


Why Simulate?Find gaps in understandingLess expensive than trial and errorMistakes don’t hurt you as in real lifePinpoint place(s) to improve with greatest

paybackOther?

© 1995-2006


Activity: Sales Process Simulation

Unit Sales Total SalesQuantity Yield Cost Cost

Input Names 4000 0.25 -2 -$8,000Qty, Yields Contacts 1000 0.2 -10 -10,000Costs Presentations 200 0.4 -250 -50,000

Estimations 80 0.8 -300 -24,000Proposals 64 0.135 -400 -25,600Closes 8 1 -500 -4,000

-$121,600Value per close $100,000Sales 800,000

% COGS 70% -560,000Gross Margin 240,000

%G&A 15% -120,000Sales Cost 15% -121,600GSA -241,600

Operating Income -$1,600

Operating Margin 0%

© 1995-2006


Activity: Simulating The Sales Process Pretend you can definitely improve two things, + or – 10% Write them down (up to 10% each).

a.Change __________ to _________

b.Change __________ to _________ Let’s try them out! Note the results here:

a.______________________________

b.______________________________ Which seems to be most optimal combination of settings?

a.Set _____________ at ___________

b.Set _____________ at ___________ Are you positive these are the best?

Note: This simulation does not include variability as a factor.

© 1995-2006


The Penny Simulation How Variability Effects Output

© 1995-2006


Discussion

© 1995-2006


Lessons of a Wavy Pipeline

Bottlenecks Shift

SuboptimizationOccurs

Perspective isEssential

Here’sthe real

problem!

Here’sthe real

problem!

© 1995-2006


TOC’s Thinking ProcessCompany Is

Not Selling ToMaximum

Potential (UDE)

Company IsNot Selling To

Maximum Potential (UDE)

SomeHQ DirectionsAre Conflicting

(UDE)

SomeHQ DirectionsAre Conflicting

(UDE)

Some FactorsVital To

Increase SalesAre Unclear

Training ProgramIgnores

Certain ImportantSkills

Some CostlyOper’al Mistakes

Are Occurring(UDE)

Some CostlyOper’al Mistakes

Are Occurring(UDE)

Some Reps SellBelow Full

Market Potential Mgmt DeploysSome Ineffective

Tactics andStrategies

Some ClientsAre Less

Forgiving ThanOthers

© 1995-2006


Activity: Theory of Constraints Where are your biggest bottlenecks? Review your cause and effect diagram What factor within your control causes most of the

other factors to happen? Add to, or re-draw your diagrams, accordingly.

© 1995-2006


Discussion

© 1995-2006




Improve: Brainstorming & Testing Improvements

© 1995-2006





ProcessControl

ProcessMaps

Simulation




Flowcharting

Brainstorming


© 1995-2006


Once The Causes for the Problem Are Found… Time for solutions Brainstorming: Common method – easy but

not often done well! Many other “Idea Generation” systems

© 1995-2006


Brainstorming Brainstorming: voicing, listing ideas in group No criticism permitted; no censorship Unconventional, wacky, outrageous ideas

encouraged Expanding, combining, adding to ideas encouraged Capture many ideas in short time Warm up with neutral ideas and examples of

discouraging comments to avoid Explain issue involved clearly; use facilitator Analysis may be next, but is separate

© 1995-2006


Checkpoint

© 1995-2006


Activity: Brainstorming Solutions Look at your cause and effect diagrams Brainstorm solutions that may overcome

undesirable, negative causes

© 1995-2006


Discussion

© 1995-2006


Caution! Brainstorming and creativity are great when

generating ideas Finding whether the ideas work requires

testing

Aha!

IDEA

“I think”

Aha!

IDEA

“I think”

Look!

TESTING

“I can show”

Look!

TESTING

“I can show”

© 1995-2006


Test Methods Simple Methods Using Statistical Process Control Design of Experiments (DOE)

© 1995-2006


Simple Method For Testing: Pre-Post With Control Group

Sales

Time

Group

Test

Control

(adapted from Selden)

Pre Post

© 1995-2006


Simple Method For Testing: Multiple Baseline

Sales

Time

Group

A

B

C


Pre Post

© 1995-2006


Using SPC to Test for ChangeDid our solution really work?

Measure new “recipe”ChartCalculate control limitsUse 8 Rules to determine whether change “is

real” or “just noise”

Leads Appts Proposals Orders

© 1995-2006


Challenge: Find “Sweet Spot”

Find Optimal Combination

In Complex Mix of Policies and Tactics

PricePromotion

Placement

Product

© 1995-2006


DOE vs. Simple Methods To tell which factor in the “cluster” is the

“active ingredient,” or which combination of factors is best, more formal designed experiments are needed

Special training in “DOE” (Design of Experiments) required

Simple test methods can tell differences between one “cluster” of factors and another

We’ll learn those now

© 1995-2006


DOE Can Quickly Find Key Factors and Best Combinations

FrostingNo

Frosting

Cake

NoCake

No Sale! $

$ $$$$

© 1995-2006


What to Test: Guidelines1. Factors tested must be controllable

Try: media choice, tagline, commission plan, training, mailing list used, price location, size, frequency

Tougher: presentation “style,” greeter “enthusiasm” 2. Factors should be affordable

Use: factors already in budget More costly: building new warehouses, plants, or

computer systems as a “test”3. Factors should be easy to introduce quickly4. No impossible or dangerous combinations

“Impossible:” Text Color: Yellow + Ad Type: Radio Dangerous: ideas that could seriously alienate good

clients

© 1995-2006


Looking At Results: GuidelinesResults should be:1. Measurable with known accuracy. 2. Measurable with sufficient accuracy not to obscure

results.3. As directly related to end goal as possible.4. Set up to provide an index of variation within each

recipe.

Examples

Easier: Sales, Time, Cost Savings, Refunds, Warrantee Claims, Reservations, Attendance

Tougher: “Attitude,” “Willingness to Refer a Friend,” Focus Group Outcomes

© 1995-2006


Regions of Impact

Factor Level (e.g., Advertising Frequency)

Effect(e.g.,Sales)

Region of RelativelySmall

Change

Region ofGreatestImpact

Region of RelativelySmall Change

Implication: levels chosen forcontrast must be sufficiently

“Bold” (widely spaced) toenable detectable difference

© 1995-2006


Familiar Method For Testing: A/B or Split Test

Sales

Time

Method

A

B

Limitation:Only tests one cluster of factors vs. another cluster (A vs B). Can’t

distinguish what factors are

responsible for the success of each

cluster.

A = Current Price, Product, Placement, Promotion, etc.B = New Price, Product, Placement, Promotion, etc.

© 1995-2006


Beauty of Screening Designs

How many balanced groups of two can we create from one sample?

Envelope: White Envelope: Cream

Copy:Long

Copy:Short

ReturnAddress:

Use

ReturnAddress:

None

ReturnAddress:

Use

ReturnAddress:

None

ReturnAddress:

None

ReturnAddress:

Use

ReturnAddress:

None

ReturnAddress:

Use

© 1995-2006


Displayed Another Way

Copy

- -

Run

+ -

- +

+ +

1

2

3

4

EnvelopeReturn

Address

-

-

+

+

- -

+ -

- +

+ +

5

6

7

8

-

-

+

+

Since we need eight runs for three factors, why not “saturate” the design space further?

© 1995-2006


Secret of Multi-Factor Balanced Designs …Example: Seven Factor, Eight Run Two Level

Fractional Factorial (below)

(Assume Only Factors A and G “Work,” Contributing Additive Impacts To Results)

A B C D E F G Results-1 -1 -1 1 1 1 -1 -121 -1 -1 -1 -1 1 1 12-1 1 -1 -1 1 -1 1 81 1 -1 1 -1 -1 -1 -8-1 -1 1 1 -1 -1 1 81 -1 1 -1 1 -1 -1 -8-1 1 1 -1 -1 1 -1 -121 1 1 1 1 1 1 12

Sum of +'s 8 0 0 0 0 0 40 0.0 MeanSum of -'s -8 0 0 0 0 0 -40Sum 0 0 0 0 0 0 0Difference 16 0 0 0 0 0 80Effect 4 0 0 0 0 0 20

Run

1

2

3

4

56

7

8

Factor

12

12

-8

-8

8

© 1995-2006


… Allows Each Factor to Express Itself, Across the Others

The balanced nature of this class of designs allows active factors to show their impact across the other factors, when genuinely present. Each level is used an equal number of times.

A B C D E F G Results-1 -1 -1 1 1 1 -1 -121 -1 -1 -1 -1 1 1 12-1 1 -1 -1 1 -1 1 81 1 -1 1 -1 -1 -1 -8-1 -1 1 1 -1 -1 1 81 -1 1 -1 1 -1 -1 -8-1 1 1 -1 -1 1 -1 -121 1 1 1 1 1 1 12

Sum of +'s 8 0 0 0 0 0 40 0.0 MeanSum of -'s -8 0 0 0 0 0 -40Sum 0 0 0 0 0 0 0Difference 16 0 0 0 0 0 80Effect 4 0 0 0 0 0 20

Run

1

2

3

4

56

7

8

Factor

-12

-12

8

8

-8

Factor A’s “Effect” = (8/4 “plusses”) – (-8/4 “minuses”) = 2-(-2) = 4

© 1995-2006


Examples of Factors Companies Are Testing Today Business to Business Sales: Contact Rate,

Proposal Detail, Meeting Location, Demo Style Wholesale Net Margins: Telemarketing, Sales

Planning Time, Factory Tours, Warranties, Commissions, Promotional Pricing

Internet Sales: Banner Ads, Tagline, Product Price, Logo Size

Direct Mail: Coupon, First Class, Refund Offer, Use of Color, Post Script, Reply Interval

Print Advertising: Background, Credit Promotion, Paper Type, Celebrity Endorsement

© 1995-2006


DOE Checklist1. Define opportunity & measurable effects

2. Create (brainstorm) list of possible causes

3. Narrow list (see “What to Test” guidelines)

4. Decide on “experimental unit”

5. Design, conduct, learn from screening test

6. Design, carry out, learn from refining test

7. Confirm and optimize

8. Implement on wider scale (if successful)

9. Repeat 1-8- Adapted from Kraber, Whitcomb & Anderson; Montgomery; Wheeler

© 1995-2006


Easy Screening RecipeSeven Factor, Eight Run Two Level Fractional Factorial

Resolution III (Main Effects Confounded With Two-Factor Interactions, others)

For example: [A] = A + BD + CE + FG + BCG + BEF + CDF + DEG

[B] = B + AD + CF + EG + ACG + AEF + CDE + DFG

Std Order

Run Order Block A B C D E F G

1 1 1 -1 -1 -1 1 1 1 -12 4 1 1 -1 -1 -1 -1 1 13 5 1 -1 1 -1 -1 1 -1 14 7 1 1 1 -1 1 -1 -1 -15 3 1 -1 -1 1 1 -1 -1 16 2 1 1 -1 1 -1 1 -1 -17 6 1 -1 1 1 -1 -1 1 -18 8 1 1 1 1 1 1 1 1

© 1995-2006


Test and Pilot, Then Roll Out Test in controlled settings first

Try to get consistently good results Pilot with another small group

Work out the “bugs” Roll out one group at a time

Fine tune as needed for each group

© 1995-2006


Activity: Ideas to TestList three ideas you could test to see if they could improve your system.

1.

2.

3.

© 1995-2006


To Change Behavior, Change Training, Policies, Rewards, and Feedback Loops

Most agree that it is more difficult to try to directly control people’s behavior by force

Instead, principle is to control instructional and motivational factors – let the behavior follow

“Don’t control the people, control the system.”

© 1995-2006


Include Five Elements In Your Plan For Change People must be able to use new approach or

it will fail Planning: anticipate and prevent problems

early Awareness-Building: internal “PR” to reduce

resistance to change Documentation: to make clear how things

must be done and to aid memory Training: % trained x % skills needed = ROI Ongoing Coaching: to prevent natural decay

© 1995-2006


Implementation Sequence

Element

StagePre-

Launch

Planning/Design

Awareness-Building

Documentation

Training

OngoingSupport

LaunchPost-

Launch


© 1995-2006


Checklist for Holding the GainsLook at your flowcharts and ask yourself. . . Have I explained the benefits to my people and the

customers? Can I answer the honest questions my people may

ask? Does my customer experience the improvements? Have I set up a system to ensure prompting and

rewarding the desired behaviors?” Have I trained my people in the new methods? Have I adjusted the reporting and evaluation system

to track the new behaviors I expect? Am I training my people in continuous improvement?

© 1995-2006


Use Control Charts To Help Warn of Sliding Backwards

Income

0

Average Order Size

Time

100

64.60

44.01

85.19

© 1995-2006


Agenda Bienvenidos and Introductions The “DMAIC” Method of Improvement Define: Process Mapping The Big Picture Measure: Using “SPC” With Sales Data Analyze: Simulating the Steps and Using Cause-

Effect Logic to Find Greatest Constraint Improve: Brainstorming & Testing Improvements Control: Holding the Gains Summary and Adiós

© 1995-2006


Involve Everyone In DMAIC With “Kaizen”



ProcessControl

ProcessMaps

Simulation




Flowcharting

Brainstorming


© 1995-2006


Kaizen - Continuous Improvement Kaizen = Gradual, Never Ending Improvement Kaizen means setting and achieving standards that

are always increasing Improvement is gradual, not dramatic Results can be very impressive nevertheless An attitude - relentless, enthusiastic, not satisfied with

letting problems continue or the status quo Involves everyone from top to bottom All successful cultures do this informally, but very

popular in Japan as a system

© 1995-2006


Any of These Tools May Help! Drawing process maps Charting sales results using SPC Creating a simulation Drawing cause-effect diagrams Identifying largest constraint Brainstorming ideas for improvement Testing if ideas work, using SPC and DOE Adjusting the system of measurement, rewards,

training and coaching to hold the gains Having the mindset of continuous improvement!

© 1995-2006


References Statistical Process Control

Don Wheeler, Bill McNeese Theory of Constraints

Bill Dettmer, Eli Goldratt Design of Experiments

Mark Anderson, Pat Whitcomb, Doug Montgomery Theory of Inventive Problem Solving

Ellen Domb, Darrell Mann, Genrich Altschuler, Behavioral Psychology

Paul Selden

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