Group & Organizational Learning

Overview

• Groups learn to work together• What is it that groups learn?

– Communication• Team specific vocabulary• How to communicate overall

– Shared mental models• About the task• About the team

– Momentary attributes of teammates (e.g., overload)– Stable attributes of teammates (e.g., knowledge,

skills, abilities, values, attitudes, personality)• About the environment

Learning Curves

• Groups & organizations groups get better at production, the more production they do, with most benefit early on• Developing routines & standard operating procedures to

increase efficiency• E.g. Regular meeting times

• Learning task-specific knowledge and skills • E.g., Familiarity effects

• Learning team specific knowledge, attitudes & skills• E.g., Learning teammate’s strengths & weaknesses

• Learning general teamwork knowledge, attitudes & skills• E.g., How to run a meeting, delegation, planning, info-

sharing

Learning occurs with production:Empirical learning curves

• Reduction in labor hours as cumulative output doubles– Large variability in improvement– Median is 20% decrease with doubling of production

• Increase in quality as cumulative output doubles

Learning curve: Unit cost of production declines with increased

production, but at a declining rate

Efficiency or Effectiveness=Constant x Cumulative Production-b

Typically ~20% decrease in cost as cumulative

production doubles (with substantial variation)

Learning Curve: Formula

Learning curves happen at multiple levels

• Organization/Firm• Factory/Location• Shift within a plant• Work group• Individual worker

Surgeons Performing Heart Bypass Surgery

• Cardiac surgeons with privileges at multiple hospitals

• What is the impact of more experience?– Overall?– Within a hospital– Between hospital

• All coronary artery bypass surgeries, PA, 1994

Average Probability of Mortality After Surgery 1.770%

Impact of 1 SD increase in total surgeries -0.015%

Impact of 1 SD increase in same hospital surgeries -0.018%

Impact of 1 SD increase in different hospital surgeries -0.001%

Huckman, R., Pisano, G., Research, D. o., & School, H. B. (2006). The Firm Specificity of Individual Performance: Evidence from Cardiac Surgery. Management Science, 52(4), 473.

Predicting efficiency of an operation from experience of hospital, team & docs

• Tested in context of total joint replacement surgery groups (hip & elbow)

• The more each individual in the team has performed the surgery, a team have performed the surgery together & the more they do this in a hospital that does lots of surgeries, the more quickly the operation goes

Reagans, R., Argote, L., & Brooks, D. (2005). Individual experience and experience working together: Predicting learning rates from knowing who knows what and knowing how to work together. Management Science, 51(6), 869-881.

Joint Replacement Surgery(Reagans, Argote, Brooks, 2005)

• Controls are sensibleOperations take longer with older males, hip (vs. elbow) replacement, tumors, complications

• Experience improves speed of surgery

• Organizational: 100 transplants 18% reduction in time to complete (~34 minutes)

• Team: 10 transplants together 5% reduction (~ 10 min)

• Individual: Experience increases time for 1st five transplants and then decreases time

Familiarity in Software Development

Baseline Model + Familiarity Vars + Interaction Vars ColVariable Coefficient P-Value Coefficient P-Value Coefficient P-Value VIF

Software Size -0.044 0.003 -0.057 <0.001 -0.051 0.008 2.119Complexity -0.043 <0.001 -0.046 <0.001 -0.066 <0.001 1.348Team Size -0.171 0.005 -0.157 0.008 -0.282 <0.001 1.714Geographic Dispersion (0,1) -0.383 0.018 -0.344 0.029 -0.422 0.013 1.228Repairs (0,1) -0.322 0.001 -0.348 <0.001 -0.364 <0.001 1.038New Development MR (0,1) -0.489 <0.001 -0.375 0.001 -0.303 0.009 1.532MR Start Date (yrs from 1st MR) -0.074 0.184 -0.182 0.001 -0.167 0.003 1.125Priority (1=lowest; 4=highest) 0.073 0.340 0.095 0.201 0.126 0.086 1.461Development Evenness 2.000 <0.001 1.731 <0.001 1.594 <0.001 1.243Task Familiarity (Deltas) 0.163 <0.001 0.364 <0.001 3.351Team Familiarity (MRs) 0.082 <0.001 0.182 <0.001 3.582Team Fam x Task Fam -0.069 <0.001 3.802Task Fam x Software Size 0.004 0.744 2.004Task Fam x Complexity -0.047 <0.001 3.259Team Fam x Team Size 0.106 0.002 2.101Team Fam x Geogr Dispersion 0.104 0.012 1.503

N 1,110 1,110 1,110Adjusted R2 0.151 0.197 0.225R2 0.158 0.205 0.236Change in R2 0.158 0.047 0.031F test for change in R2 23.01 32.256 8.797p-value of F test <0.001 <0.001 <0.001Condition Index (collinearity) 19.773 19.964 20.610

• Task familiarity = mean # software changes team members participated in past• Team familiarity = mean # of software changes pairs jointly participated in• DV = Time to make a change (reversed: high = good)

When does familiarity help most?

Interaction Plot Task Familiarity x Number of Modules

-2.70

-2.60

-2.50

-2.40

-2.30

-2.20

-2.10

-2.00

-1.90

-1.80

-1.70

0.01 0.87 1.73 2.60 3.46

Task Familiarity

Per

form

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= -

LN

MR

Dev

Tim

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Low Number of Modules

High Number of Modules

Interaction Plot Team Familiarity x Geographic Dispersion

-3.30

-3.10

-2.90

-2.70

-2.50

-2.30

-2.10

-1.90

0.01 0.87 1.73 2.60 3.46

Team Familiarity

Per

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= -

LN

MR

Dev

Tim

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Co-Located

Distributed

Interaction Plot Team Familiarity x Team Size

-3.30

-3.10

-2.90

-2.70

-2.50

-2.30

-2.10

-1.90

0.01 0.87 1.73 2.60 3.46

Team Familiarity

Per

form

ance

= -

LN

MR

Dev

Tim

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Low Team Size

High Team Size

• When communication is more difficult

More team members Geographically distributed teams

When task is smaller (surprise)

What are the factors responsible for team & organizational learning

Factors that change with experience & can plausibly cause improvements in efficiency or effectiveness of production

– Individual learning, especially tacit knowledge– Development of routines & their refinement– Automation & refinement of equipment

Speed for new minimally invasive cardiac surgery

Pisano, G. P., Bohmer, R. M., & Edmondson, A. C. (2001). Organizational differences in rates of learning: Evidence from the adoption of minimally invasive cardiac surgery. Management Science, 47(6), 752-768.

Time to complete surgery by hospital experience

• Overall learning at hospital level (5% improvement with doubling of # of operations)

• Large differences in rate of learning btw hospitals(M goes from 500 minutes to 132, while average is fm 290 minutes to 210))

Why did hospital M learn faster than a typical team?

Hospital M learned faster than average• Team hand-picked for training by adopting surgeon

based on prior experience working together

• Adopting surgeon met with all other surgeons in cardiac unit. Perfusionist met with operating room nurse & anesthesiologist to discuss procedure. Surgeon has weekly discussions with cardiologists.

• Initial team performed first 15 operations before any rotation. New team members had to observe 4 & be mentored on 2 before joining.

• Adopting surgeon encouraged team coordination (e.g., feedback)

Hospital R learned slower than average• Initial team based on who was available

• No attempt to introduce procedure to other clinical groups or meeting to discuss cases ahead of time.

• Only 3 of 4 in first operation had training. Turnover in next 6 cases.

• Little teamwork. "We don't have any real teams here. It's just who gets assigned on any given day” “The nurses are interchangeable. We know our ‘little jog’ and don’t really know what the other people are doing.

Pre

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What is it that groups learn from working together?

• Lessons from the Ginnett paper on leadership in flight crews:

– Explicit expectations about procedures & rationale– Explicit division of labor/hierarchy – Demonstrating personal attributes– Demonstrating positive attributes trust – Development of personal social relationships– Transactive memory: Knowledge of what each crew

member is good at

Team vs. Individual Level Training• Groups trained to assemble a

radio– Subjects trained individually– Or in a group training

• Tested in group setting• Group trained together did

better than those trained individual

Liang, D., Moreland, R., & Argote, L. (1995). Group versus individual training and group performance: The mediating role of transactive memory. Personality and Social Psychology Bulletin, 21, 384-393.

Argote & Moreland: Subsequent research

• Motivation isn’t the cause• People trained individually & then given a group

building exercise were no better than people trained alone

• Learning to work in teams-in-general isn’t the cause• People trained in one group and then moved to

another were no better than people trained alone

Moreland, R. L., Argote, L., & Krishnan, R. (2002). Training people to work in groups. Theory and research on small groups, 37-60.

Transactive Memory

• Individual expertise is limited• Learning who knows what in an organization is

generally useful– Basis of division of expertise & task assignment, for

coordination– Provides access to resources external to oneself

Learn Who Knows WhatLiang, Argote, Moreland

• Only strong effect comes from individuals training & performing with their initial group• Transactive memory may

be one cause• Groups trained together

know each others strength & weakness & allows them to assign tasks accurately

• This accuracy predicted performance

• Mediation analysis suggests that knowing who knows what accounts for effects of group training

Grouptraining Errors

Assign tasksappropriately

Groupidentity

-4.28

1.66 -2.82

1.30

-5.61

Summary: What teams learn as they work together• Group-specific knowledge

– Task– People– Environment

• General teamwork– Ways to organize– Planning– Appropriate amount of communication– Team-appropriate attitudes

• Learning at both the individual and group levels– Transactive memory: e.g., Individual manager learns that person A is good

with complex problems but, doesn’t finish projects on deadline– Group learning:

• E.g., Routines such as aviation checklists– Technology: e.g., Group decides to physically organize so people who

coordinate most are close by

Familiarity is not always positive

• Groups can also stagnate: E.g., productivity of a research group peaks after 3-5 years of being together

• Katz (1982) – Performance (rated by managers) of 50 R&D teams– Tenure = average time people worked in group.

Communication as a mediator?

• Communication is correlated with tenure– Communication is

associated with project performance

– Less internal & external communication at beginning & end of group