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February 2015
From the Knowledge
Sharing towards the
Digital
Transformation
Louis-Pierre Guillaume
Knowledge Management Officer
Knowledge Management &
Communities
Usage of the Social Collaboration Platform
2© 2015 Schneider Electric
Knowledge Management & Communities
“Benchmarks and experience show that Communities are the foundation of
virtually every mature KM Program”
© 2015 Schneider Electric 3
Knowledge
ExplicitTacit
Human interaction
Lower Higher
Facilitated
sharing/transfer
between units
Reference documentation, internal encyclopedia
E-learning, search, troubleshooting tool, intranet portal …
Experience
Ex: After action reviews
Sharing practices
Ex: Communities@work
Build-upon spirit
Ex : Mentoring programs
Major Peer Reviews
Self-service
Lessons learned
Communities
Transfer of
practices
APQC – The new edge of knowledge management - 2011
A Community@Work is
A group of people who share
Common objectives written in a charter
© 2015 Schneider Electric 4
Collaborative working environment animated by the leader
Common strategic vision provided by the sponsor
5
4518
273
224
654
660
991
614
1260
223
354
402> 100 members
10 -100 members
< 10 members
104
773
2400
173
2760 18
0
435
869
643
140 Communities@work
25,000+ members in 100+ countries
170+ community leaders
Communities voted actives by their members in 2013
Communities voted actives by their members in 2014
Spice
Example of usage by communities
6© 2015 Schneider Electric
Poll to drive adoption
Mutual help
News of the week
Call for webinars
Show me the Value
7© 2015 Schneider Electric
Value of the communities
How do we measure it?
© 2015 Schneider Electric 8
ROE* instead of ROI
2. Engagement /satisfaction
• Community NPS**
• Voice of the members – Active
community
1. Adoption and participation
• Platform measurements (Spice)
• Number of attendees at eventsNPS**: net promoter score
ROE*: return on engagement
3. Efficiency
• Success stories with benefits
• The value realized
© 2015 Schneider Electric 9
Profile of the voters
94% of the voters are members of up to 3 communities
73% of the respondents voted for one 1 community
Active Community 2014 – Voice of the Members
Overall satisfaction
Net Activity Score 61
56 in 2013
Overall results
24,100 community members
assessed worldwide
5100 voters
126 communities short-listed
33 communities awarded “Active
Community 2014”
Participation & outcome
20 in 2013
60 in 2013
15000 in 2013
Question: I consider that my community is ACTIVE, because it provides
tangible VALUE to me, my business or my clients.
Do big communities have less chance of winning? Why not use Spice data?
© 2015 Schneider Electric
10
Active Community Assessment – How Robust?
Profile of the winners
•Providing a list of members gives a much greater
chance of winning (3 times more) than using the
community followers in the social media platform
•Winning in 2013 gives a much greater chance of
winning in 2014 (3 times more)
•A community whose Leader or Sponsor voted has a
greater chance of winning (3 times more)
•An R&D community has a greater chance of winning (3
times more)
13 0 < members < 50
9 50 <m<100
6 100 <m< 200
4 200 <m< 500
0 500 <m< 1000
1 1000 <m< 4100
Criteria to win
•Net Activity Score (NAS) > 60
•Participation > 30
Do big communities have less chance of winning? Why not use Spice data?
© 2015 Schneider Electric 11
Active Community Assessment – How Robust?
PCA: Principal Component Analysis
The shorter the arrow, the lower the influenceCommunity size or Social
network activity does not
matter
Member’s opinion
matters
Leaders’ Age
Impact of Distance between members or Community leader profile?
© 2015 Schneider Electric 12
Analytics of the Communities
NO IMPACT of distance nor profile on community
Social Network activity or Net Activity Score
Hierarchical distance
Physical distance
Good news: The activity of the Communities@Work
is decoupled from the distance.
They are transversal to and independent of the
organization (country, hierarchy).
Verbatim of C@W Sponsors in 2014
13© 2015 Schneider Electric
Employee Net Promoter Score (ENPS)
Are community members more promoters than Schneider-Electric employees?
© 2015 Schneider Electric 14
The active
community
members are
clearly
more promoter &
more engaged
than SE
population
One Voice result (wave 1 2014)
+11
Question : How likely is it that you would recommend Schneider Electric to one
of your friends as a good place to work?
Within margin of error at 95% confidence
Key Success Factors
15© 2015 Schneider Electric
Key Success Factors
● ExCom Sponsorship HR & IT =>
legitimacy
● Company Program => visibility
● Framework Communities@Work =>
deployment model
● Social collaboration platform =>
augmented interactions
● Business value => rationale to
dedicate time
© 2014 Schneider 16
Q&A
© 2015 Schneider Electric 17
louis-pierre.guillaume@schneider-electric.com
@lpguillaume

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From the knowledge sharing towards the digital transformation - Enterprise 2.0 Paris

  • 1. February 2015 From the Knowledge Sharing towards the Digital Transformation Louis-Pierre Guillaume Knowledge Management Officer
  • 2. Knowledge Management & Communities Usage of the Social Collaboration Platform 2© 2015 Schneider Electric
  • 3. Knowledge Management & Communities “Benchmarks and experience show that Communities are the foundation of virtually every mature KM Program” © 2015 Schneider Electric 3 Knowledge ExplicitTacit Human interaction Lower Higher Facilitated sharing/transfer between units Reference documentation, internal encyclopedia E-learning, search, troubleshooting tool, intranet portal … Experience Ex: After action reviews Sharing practices Ex: Communities@work Build-upon spirit Ex : Mentoring programs Major Peer Reviews Self-service Lessons learned Communities Transfer of practices APQC – The new edge of knowledge management - 2011
  • 4. A Community@Work is A group of people who share Common objectives written in a charter © 2015 Schneider Electric 4 Collaborative working environment animated by the leader Common strategic vision provided by the sponsor
  • 5. 5 4518 273 224 654 660 991 614 1260 223 354 402> 100 members 10 -100 members < 10 members 104 773 2400 173 2760 18 0 435 869 643 140 Communities@work 25,000+ members in 100+ countries 170+ community leaders Communities voted actives by their members in 2013 Communities voted actives by their members in 2014
  • 6. Spice Example of usage by communities 6© 2015 Schneider Electric Poll to drive adoption Mutual help News of the week Call for webinars
  • 7. Show me the Value 7© 2015 Schneider Electric
  • 8. Value of the communities How do we measure it? © 2015 Schneider Electric 8 ROE* instead of ROI 2. Engagement /satisfaction • Community NPS** • Voice of the members – Active community 1. Adoption and participation • Platform measurements (Spice) • Number of attendees at eventsNPS**: net promoter score ROE*: return on engagement 3. Efficiency • Success stories with benefits • The value realized
  • 9. © 2015 Schneider Electric 9 Profile of the voters 94% of the voters are members of up to 3 communities 73% of the respondents voted for one 1 community Active Community 2014 – Voice of the Members Overall satisfaction Net Activity Score 61 56 in 2013 Overall results 24,100 community members assessed worldwide 5100 voters 126 communities short-listed 33 communities awarded “Active Community 2014” Participation & outcome 20 in 2013 60 in 2013 15000 in 2013 Question: I consider that my community is ACTIVE, because it provides tangible VALUE to me, my business or my clients.
  • 10. Do big communities have less chance of winning? Why not use Spice data? © 2015 Schneider Electric 10 Active Community Assessment – How Robust? Profile of the winners •Providing a list of members gives a much greater chance of winning (3 times more) than using the community followers in the social media platform •Winning in 2013 gives a much greater chance of winning in 2014 (3 times more) •A community whose Leader or Sponsor voted has a greater chance of winning (3 times more) •An R&D community has a greater chance of winning (3 times more) 13 0 < members < 50 9 50 <m<100 6 100 <m< 200 4 200 <m< 500 0 500 <m< 1000 1 1000 <m< 4100 Criteria to win •Net Activity Score (NAS) > 60 •Participation > 30
  • 11. Do big communities have less chance of winning? Why not use Spice data? © 2015 Schneider Electric 11 Active Community Assessment – How Robust? PCA: Principal Component Analysis The shorter the arrow, the lower the influenceCommunity size or Social network activity does not matter Member’s opinion matters
  • 12. Leaders’ Age Impact of Distance between members or Community leader profile? © 2015 Schneider Electric 12 Analytics of the Communities NO IMPACT of distance nor profile on community Social Network activity or Net Activity Score Hierarchical distance Physical distance Good news: The activity of the Communities@Work is decoupled from the distance. They are transversal to and independent of the organization (country, hierarchy).
  • 13. Verbatim of C@W Sponsors in 2014 13© 2015 Schneider Electric
  • 14. Employee Net Promoter Score (ENPS) Are community members more promoters than Schneider-Electric employees? © 2015 Schneider Electric 14 The active community members are clearly more promoter & more engaged than SE population One Voice result (wave 1 2014) +11 Question : How likely is it that you would recommend Schneider Electric to one of your friends as a good place to work? Within margin of error at 95% confidence
  • 15. Key Success Factors 15© 2015 Schneider Electric
  • 16. Key Success Factors ● ExCom Sponsorship HR & IT => legitimacy ● Company Program => visibility ● Framework Communities@Work => deployment model ● Social collaboration platform => augmented interactions ● Business value => rationale to dedicate time © 2014 Schneider 16
  • 17. Q&A © 2015 Schneider Electric 17 louis-pierre.guillaume@schneider-electric.com @lpguillaume

Notes de l'éditeur

  1. Most KM approaches fall into the one or more of the four categories Tacit knowledge: in your head Explicit knowledge: in a document, video, database Self service: technology-focus: Spice, search, Quickr Lessons learned applied to processes and projects Communities: Communities of practices / Communities of Experts Transfer of Knowledge: identifying and transferring successful demonstrated practices and knowledge : Interaction person to person, most of the added value of the transfer is not written . A senior worket showing his know how on soldering to a new comer, contextuel comment of a Peer during a Peer Review, mentoring and coaching Two perspectives & levels of approaches Above the flow of work: core capabilities; IT, change management, communities, … In the flow of work: approach that fits the flow of knowledge in employees’ everyday work, delivering more value and less disturbing for people.
  2. It’s simple. A Community@Work is: a group of people who share activities on a professional topic. The members also share: Common objectives written in a charter. Members learn from each other by sharing experiences and best practices They share a collaborative working environment animated by the leader so that members can develop both personally and professionally They share a common strategic vision provided by the sponsor so that the community is aligned with the ambition of the company. So, communities are not SPICE subjects, Quickr sites, blogs or wikis, it's MORE than just a tool.
  3. Active community Label: 20 winners in 2013 33 winners in 2014
  4. Mutual help: Subro in Saudi-Arabia get help from the project managers community and the purchaser community to prepare a proposal to a bid.
  5. Net Activity Score: weighted agreement (1.0xStrongly agree + 0.5xAgree - 0.5xDisagree - 1.0xStrongly disagree) Advantage: integrates all opinions, similar to Net Promoter Score Net Activity Index = 100 if all the answers are "I strongly agree“ Net Activity Index = -100 if all the answers are "I strongly disagree" Net Activity Index = 0 if neutral
  6. The scatterplot seems to show that there are small and big communities The profile of the 33 winners show some trends.
  7. Principal Component Analysis (PCA) An Excel spreadsheet with 126 rows (126 communities analyzed) and 7 columns (the variables) LEFT GRAPH: “Membership” (size of the community) on the Y axis and “Spice average activity per follower” on the Z axis are orthogonal to the other 5 variables. Thus they are not correlated The variables whose arrows are close and close to the circle are strongly correlated (e.g. “Winner of the Active Community Label (ACL) in 2013” and “Participation rate in the 2014 vote”) The X axis looks like the axis of engagement RIGHT GRAPH: The 2014 ACL winners (green cluster) are on the right side of the axis of engagement. The center of gravity of both clusters are on the same level vs the Y axis (“Membership”) and the Z axis (“Spice average activity per follower” ). So no influence from these two.
  8. Physical distance The physical distance between two people is the distance that separates the centre of the cities in which they are located. The distance is the flying distance on the earth. The city information comes from the profile of the person in the directory IDS. If the city is not specified, then the centre of the country is used. A community is composed of n members. A member of a community has a physical distance with each of the other members of the community. A couple is two members of a community, so each couple has a physical distance. There are C=n*(n-1)/2 couples of members. The physical distance distribution is the percentage of members in a community that are at a given flying distance from other members of a community. A graph shows this distribution. Hierarchical distance The hierarchical distance between two people is the number of connection in the hierarchy that separate them. For example, in the Schneider executive Committee, the distance between Jean-Pascal Tricoire and Herve Coureil is 1, whereas the distance between Herve Coureil and Olivier Blum is 2 (Herve <–> Jean-Pascal, Jean-Pascal <-> Olivier) A community is composed of n members. A member of a community has a hierarchical distance with each of the other members of the community. A couple is two members of a community, so each couple has a hierarchical distance. There are C=n*(n-1)/2 couples of members. The hierarchical distance distribution is the percentage of members in a community that are at a given hierarchical distance from other members of a community. A graph shows this distribution.
  9. Employee Engagement Index, Inclusion, Development, Vision, Action Plan Awareness: above average (+4 to 7 percentage points) Collaboration, Empowerment, Worklife Balance: same Nothing below the average Inclusion % of employees who feel their opinion is taken into account Development % of employees who perceive that they have enough support for their development Vision % of employees who say they have a clear vision of the link between what is expected from them and the company’s strategy Collaboration % of employees who feel that collaboration is going well between teams and entities Empowerment % of employees who feel that their manager give them enough feedback to improve their performance
  10. Engaged Individuals: Cross-Entity Mobility