responsible corporate problem solving - a siemens case study | ieee international technology...

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Responsible Corporate Problem Solving -

a Siemens Case Study with TechnoWeb 2.0IEEE The Hague - June 2013

Isaac Newton Acquah

2www.freshtracks.co.uk

3

In the beginning…. there was TechnoWeb

4commons.wikimedia.org

5

What is an Urgent Request?

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What is the problem?

7http://www.wordle.net/create

Locations on TechnoWeb Today

8http://www.wordle.net/create

Positions on TechnoWeb Today

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"Isolated knowledge islands"

Organizational and hierarchical

Business process- and project specificinformation

Local, time,cultural and language

Barriers exist in large organizations

TechnoWeb breaks down those barriers

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Barriers exist in large organizations

TechnoWeb breaks down those barriers

"Isolated knowledge islands"

Organizational and hierarchical

Business process- and project specificinformation

Local, time,cultural and language

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What is the problem?

12 commons.wikimedia.org

Everybody gets the Urgent Requests

13

Imagine…

14www.missoulakiwanis.com 

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Semantic Solution

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Urgent Request tagging

17commons.wikimedia.org

Targeted Messaging

17

18

What about outliers?

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Precision Recall

TechnoWeb Business slider

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2013Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

2010 2011 2012

Simulation Broadcasting Target Messaging

Research Timeline

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Findings: Ratio of answered Urgent Requests

Fourth Quarter 2010

First Quarter 2011

Second Quarter 2011

Third Quarter 2011

Fourth Quarter 2011

First Quarter 2012

Second Quarter 2012

Third Quarter 2012

Fourth Quarter 2012

Broadcast Targeted Messaging

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%92% 93%

96%92% 91%

87%

93% 92%87%

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10/2010

11/2010

12/2010

01/2011

02/2011

03/2011

04/2011

05/2011

06/2011

07/2011

08/2011

09/2011

10/2011

11/2011

12/2011

01/2012

02/2012

03/2012

04/2012

05/2012

06/2012

07/2012

08/2012

09/2012

10/2012

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

0

5,000

10,000

15,000

20,000

25,000

30,000

7,911

10,485

15,823 18,166

22,38824,501

Broadcast

Target Messaging

Community Size

Num

ber o

f Urg

ent R

eque

st N

otific

ation

s

Findings: Notifications sent out

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€ 1 000 € 10 000 € 50 000 € 250 0000.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

30.90

15.30

7.40

4.50

26.40

8.80

4.102.90

Simulation of the Semantic Target Messaging Algorithm (n=138)

Real Life Performance of the Semantic Target Messaging Algorithm (m=477)

Spam

Red

uctio

n Fa

ctor

Findings: Spam Reduction

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€ 1 000 € 10 000 € 50 000 € 250 000 € 1 000 0000.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

2.71

1.71

1.18 1.18

0.58

4.05

2.04

1.09 1.080.90

Simulation of the Semantic Target Messaging Algorithm (n=138)

Real Life Performance of the Semantic Target Messaging Algorithm (m=477)

Real Life Performance of the Old Broadcasting Mechanism (n=138)

Conv

ersio

n Ra

te (p

er th

ousa

nd)

Findings: Conversion Rate

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Saved emails from the new system in a 1 year, 4 months period…

8 235 786(October 2011 and January 2013)

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EmployeesSaved Costs

http://wallboom.com/smiley-faces-on-twitter.html

Positive side effects

27

Thomas Mayerdorfer

Clemens Wiener

Dr. Michael Heiss

Isaac Newton Acquah

Meet the team

Dr. ManfredLangen

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Work Experience

About me: Isaac Newton Acquah III

acquah@mercurypuzzle.com

at.isaacnewtonacquah.linkedin.com

twitter.com/isaacnewtonIIIGet in touch

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