the transfer of serious games to business research an example of knowledge transfer between...

The transfer of serious games to business researchAn example of knowledge transfer between management theory, a serious game, and practice

1st GaLA Alignment School, 20-24th June, Edinburgh, UK

Christian Schneider, ETH Zürich, [email protected]

The transfer between theory, SG, and practice

Tuesday 21 June 2011 2

?

Practice

SGTheory

The aim of the analysis is to do better than that…


Introduction to the logistics game

Theoretical background

Results

Conclusions and practical implications

Content


Basic facts about the logistics game

Given Between 11 and 16 players 3 instructors Approx. 2 hours A box full of raw material

Goal Produce the right amount of goods in the right quality at the right

time at minimal costs*.

* costs are determined by costs for personnel, stock, late deliveries and bad quality


Impressions from playing the logistics game

Rework

Shipping WP3

WP1

WP2

WP4

Stock

Sales

CustomerQC

DirectInternal TransportExternal Transport


Playing the game

Round 1 Round 2 Round 3 Round 4Start Stop

measuring performance




taking measures

taking measures

taking measures




Results


Content


Theoretical background (1/2)

The sand cone model by Ferdows and de Meyer defines a chronological order in which different manufacturing capabilities should be tackled in order to achieve lasting improvements in manufacturing.

Question: Can this model be verified in the logistics game?


Theoretical background (2/2)

Instead of specifying the exact parameters of the learning curve, Adler and Clark model how learning effects emerge by differentiating between first- and second-order learning.

Production activity

First-order learning

Second-order

learning

Productivity improvement

cumulative unit number

dire

ct la

bor

hour

s pe

r un

it

Question: Does this model help explain the outcome of the logistic games?




Results


Content


Results: quality performance and costs

Question: Does a sound performance in quality imply that the financial result is good as well?

0%

1%

2%

3%

4%

5%

6%

7%

1 10 100 1000

Sh

are

of

ba

d p

art

s,

Ro

un

d 4

Costs per good part, Round 4

0%

2%

4%

6%

8%

10%

12%

14%

1 10 100 1000

Sh

are

of

ba

d p

art

s,

Ro

un

d 3


0%

5%

10%

15%

20%

25%

30%

35%

1 10 100 1000 10000

Sh

are

of

ba

d p

art

s,

Ro

un

d 2


0%

20%

40%

60%

80%

100%

120%

1 10 100 1000 10000 100000

Shar

e of

bad

par

ts, R

ou

nd

1


0%

1%

2%

3%

4%

5%

6%

7%

1 10 100 1000

Sh

are

of

ba

d p

art

s,

Ro

un

d 4


0%

2%

4%

6%

8%

10%

12%

14%

1 10 100 1000

Sh

are

of

ba

d p

art

s,

Ro

un

d 3


0%

5%

10%

15%

20%

25%

30%

35%

1 10 100 1000 10000

Sh

are

of

ba

d p

art

s,

Ro

un

d 2


0%

20%

40%

60%

80%

100%

120%

1 10 100 1000 10000 100000

Shar

e of

bad

par

ts, R

ou

nd

1


0%

1%

2%

3%

4%

5%

6%

7%

1 10 100 1000

Sh

are

of

ba

d p

art

s,

Ro

un

d 4


0%

2%

4%

6%

8%

10%

12%

14%

1 10 100 1000

Sh

are

of

ba

d p

art

s,

Ro

un

d 3


0%

5%

10%

15%

20%

25%

30%

35%

1 10 100 1000 10000

Sh

are

of

ba

d p

art

s,

Ro

un

d 2


0%

20%

40%

60%

80%

100%

120%

1 10 100 1000 10000 100000

Shar

e of

bad

par

ts, R

ou

nd

1


0%

1%

2%

3%

4%

5%

6%

7%

1 10 100 1000

Sh

are

of

ba

d p

art

s,

Ro

un

d 4


0%

2%

4%

6%

8%

10%

12%

14%

1 10 100 1000

Sh

are

of

ba

d p

art

s,

Ro

un

d 3


0%

5%

10%

15%

20%

25%

30%

35%

1 10 100 1000 10000

Sh

are

of

ba

d p

art

s,

Ro

un

d 2


0%

20%

40%

60%

80%

100%

120%

1 10 100 1000 10000 100000

Shar

e of

bad

par

ts, R

ou

nd

1


Sh

are

of

ba

d p

art

s

Costs per good part

Round 1 Round 2 Round 3 Round 4

r = 0.28 r = 0.32 r = 0.17 r = 0.06

Finding: While costs correlate with quality in the first two rounds, this correlation weakens in round three and disappears in round four.


Results: quality performance and costs

Question: Do groups that have good quality performance in the beginning outperform other groups in round four?

0%

20%

40%

60%

80%

100%

120%

0 50 100 150 200S

hare

of b

ad p

arts

, Rou

nd 1


0%

20%

40%

60%

80%

100%

120%

0 50 100 150 200 250 300 350

Sha

re o

f bad

par

ts, R

ound

1


r = 0.24 r = -0.03

Finding: Good quality performance in the beginning has no correlation with the financial result in the last round.


Results: quality performance and measures

Round 1 Round 2 Round 3 Round 4Start Stop



taking measures

evaluate deltabest performers

worst performers



Question: Do the measures taken by the best performers differ from the measures taken by the worst performers?

Layout Lot size Training Removal int. transp.

Q-Training0

2

4

6

8

10

12

14

Best performers

Worst performers# ti

me

s ch

ose

n

Performance change between round 1 and 2 in number of bad parts:

Finding: The measures taken by the two groups are practically the same.



Question: Does the measure “quality training” improve quality more than other measures?

Finding: Groups choosing “quality training” as a measure improve quality less than the total average.


Round 1 Round 2 Delta Average number of bad parts

With Q-Training 10.86 3.57 7.29 Total 11.69 3.21 8.48

Average costs per good part

With Q-Training 4874.00 256.71 4617.29 Total 2443.22 109.31 2333.91

Results: quality performance & learning

Production activity

First-order learning: based on repetition and

learning-by-doing

Second-order learning: based on managerial or

engineering actions purposely improving the

manufacturing capabilities


Players‘ progress in

producing the part in the

right quality.

Measures aimed at

improving the production

capabilities.




Results


Content


Conclusions

Costs only correlate with quality performance in the first two rounds. Good quality performance in the beginning does not assure a superior

financial result in the end. Measures taken between round one and two have no influence on

quality. Quality training does not improve quality more than other measures.

The sand cone model can be confirmed inasmuch as quality improves early on.

The learning process helps to explain why quality performance improves independently of measures taken.


Practical implications

In manufacturing, improving quality helps to bring down costs early on.

Improving quality is not necessarily a matter of managerial or engineering actions, some aspects might improve simply as a function of the cumulated units produced.


What have we seen?


?

Practice

SGTheory

Production activity

First-order learning

Second-order

learning


Rework

Shipping WP3

WP1

WP2

WP4

Stock

Sales

CustomerQC

DirectInternal TransportExternal Transport

THANK YOU!


BACKUP



Layo

ut / T

rain

ing

Layo

ut / R

emov

al in

t. tra

nsp.

Layo

ut / L

ot si

ze

Lot s

ize / T

rain

ing

Lot s

ize / Q

-Tra

inin

g

Train

ing

/ Tra

inin

g

Train

ing

/ Q-T

rain

ing

0

2

4

6

8

10

12

# ti

me

s ch

ose

n


Results: quality performance & learning

Plateuing in round three and four Improvements of costs base on more sources of learning than

improvements in quality.


1 2 3 40

500

1000

1500

2000

2500

3000

0

2

4

6

8

10

12

14

Costs

Quality

Round

Co

sts

# Q

ab

s

Data sources

Played for the last 16 years Results of 81 games Played with students (70%) and practitioners (30%)


the transfer of serious games to business research an example of knowledge transfer between...

Documents

good quality performance

sound performance

right quality

logistics gamegivenbetween

chronological order

clark model

model help

good partround