Adding Quantitative Measures to Qualitative

Decision Making

• © Honeywell International

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Presenters

• Mary Stubbs

- Sr Project Engineer Manager, PMP, MBB

- Honeywell, Tempe, AZ

• Ganna Keith

- Product Design Engineer

- Honeywell, Torrance, CA

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Why Team Decision Making?

© Paragon Books, 2012

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Team Behaviors

• High performing team

- http://www.youtube.com/watch?v=C2YZnTL596Q

• Dysfunctional team

- http://www.youtube.com/watch?v=9yFkMQO0eyM

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• Time bound

Quality Team Decision Making

• Documented

• Full team engagement

• Structured

• Diversity of opinion / all stakeholders

• Fact based

• Clear problem statement

• Strong Facilitation

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• Honor the team’s commitment

- Start on time, end on time

- Thank the team for their participation

- Don’t feel that you have to use all of the time allotted

Facilitating Team Decision Making

• Know when the team needs a break

• Give directions clearly and briefly

• Set the stage by providing context

- Objectives, prior decisions, in/out of scope

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Facilitating Team Decision Making

• Deal head on with bad behaviors and encourage participation

- “Thank you for your insight, Linda, let’s hear from the rest of the team.”

- “Remember the 3-knock rule – One conversation at a time.”

- “What do you think, Natalie?”

• Help the team to communicate through echoing

- I believe I heard “…”, is that correct?

• Ask questions instead of making statements

- I wonder if we need to consider…

- What did we do the last time that we faced a similar situation? How did that work out?

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Facilitating Team Decision Making

• Keep the team on track, but allow for team process

- If the team is doing fine it is best to be quiet

- Some storming is expected and productive

- Know when to step in and “parking lot” an issue if the team is going down a “rat hole”

• Stay neutral, let the team make the decision

• If possible, add an element of fun

• Add data to help remove emotion

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Key Elements of a Decision Matrix

• Clear problem statement

• Definition of options being considered

• Factors that make options more desirable

• Weights on Factors

• Unambiguous scoring criteria for each factor

• Calculated Decision based on scores and weights

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Problem Statement

• Clear and complete

• Team consensus

• Form of a question is helpful

• Revisit if questions arise during the process

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Options

• Short list (<10) of possible answers to the question being asked in the problem statement

• Options need to be clear and not overlap

• Only include viable options that do not violate constraints

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Factors

• Factors that make options more desirable

• Generally 5 – 10 options

• Not related to each other

- For example, don’t want 5 out of 10 to be related to cost

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Weights

• Recommend 3, 7, 10 scale

• Not everything can be a 10, need some at every level

• Need team agreement on definitions

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Scoring Criteria

• Unambiguous scoring criteria for each factor

- Critical to team agreement on scores

- Use of specific scoring criteria facilitates team consensus

1 1

3

5 5

7

10 10

1 1

3 3

5 5

7 7

10 10

1 1

3 3

5 5

7 7

10 10

1

3

5

7

10

Scoring Criteria for

Neighborhood

High crime-rate area, no amenities

Above average crime rates, few

Average crime rates, some amenities

Below average crime rates, amenities

Very low crime rate, many amenities

Scoring Criteria for

Monthly Rent

>$2000

$1600-$2000

$1200-1600

$800-1200

<$800

Scoring Criteria for

Parking

Street parking only.

--

Complex has an open parking lot for

--

Personal parking space or garage.

Scoring Criteria for

Laundry

No on-site laundry available.

--

Shared laundry facility in the complex.

--

Washer and dryer in the unit.

Scoring Criteria for

# of Bedrooms

No Bedrooms. Studio apartment.

--

1 Bedroom.

--

2+ Bedrooms.

Average commute :30 mins or less

Scoring Criteria for

Space/Sq. Feet

<500 sq. feet.

500 - 600 sq. feet.

600 - 800 sq. feet.

800 - 1000 sq. feet.

>1000 sq. feet.

Scoring Criteria for

Distance to Work

Average commute: >60mins

--

Average commute: between 30 and

--

3

7

10

Generic Scoring Criteria

Scoring Criteria

Below Average

Good

Exceptional

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Scores

• Don’t average scores across the team

- Need to discuss enough to understand alternate viewpoints and share information across the team

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Calculated Decision

• Calculated Decision based on scores and weights

• Sum of products

-Weighting x Score

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Goldilocks and Her Team Choose Porridge

Temperature 10 3 3 10

Lumpiness 10 10 3 7

Whole grains 7 3 7 3

Viscosity 7 7 3 10

23 16 30

Which bowl of porridge should we eat?

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Decision Making

FactorsWeighting

Weighted Decision:

Options Baby Bear

Scores

200 130

Papa Bear Mama Bear

RAW SCORE:

3 3

7 7

10 10

3 3

7 7

10 10

no whole grains

mix of whole grains and processed grains

100% whole grains

Scoring Criteria -

Viscosity

very thim, like milk

very thick, almost solid

neither thin nor thick

Scoring Criteria -

Lumpiness

many large lumps

a few small lumps

no lumps

Scoring Criteria -

Whole Grains

Scoring Criteria -

Temperature150 <= temp <= 180

temp < 150 degrees

temp > 180 degrees

3

7

10

Moderate Importance

High Importance

Critical

Weighing Criteria

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Wrap Up

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Thank You!

www.honeywell.com

© Honeywell International