CISummit 2013: Luke Matthews, The Leading Edge of ONA; eData; Reorgs; Networks Outside the Organization

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The Leading Edge of ONA; eData; Reorgs; Networks Outside the Organization

Luke J Matthews, PhD

© 2013 Activate Networks 2Connected Insight Summit 2013: www.connectedinsightsummit.com

Reorg Case Study

• Company: A major telecommunication company

• Reorg type: Recent acquisition and re-structure

• Issue: Post- change, HR could not assess if the change initiative was successful

• Goal: To use Organizational Network Analysis (ONA) – through survey and email data – to discover what factors drove collaboration, specifically to confirm if the old structure, the legacy group, continued to drive how employees connected


Location?

Rank?

Sub-function?

Role?

Legacy group?

Question: What is driving collaboration post-change?


Method:Email Data Analysis

Timeframe: 15 weeks Criteria: From, To, Date, Time

Response Connection

Volume Connection

From To Date [email protected]

[email protected] 12:30:00 3/31/2012

[email protected] [email protected] 12:31:00 3/31/2012

[email protected]

[email protected] 12:35:00 3/31/2012

[email protected]

[email protected] 12:37:00 3/31/2012

[email protected]

[email protected] 13:15:00 3/31/2012

[email protected]

[email protected] 13:43:00 3/31/2012

[email protected]

[email protected] 14:01:00 3/31/2012

[email protected]

[email protected] 14:26:00 3/31/2012

[email protected]

[email protected] 15:02:00 3/31/2012

[email protected]

[email protected] 15:36:00 3/31/2012



5 6 7 8 9 10 11 12 13 14 150.84

0.86

0.88

0.90

0.92

0.94

0.96

0.98

Email Volume

Correlation to Prior Network

Weeks



An Email Network

• Ties are inferred from email log data

• Nodes are colored by physical location

Matthews et al. 2013 PLOSONE



7

ANI has found that 60-80% of email-inferred network ties are within the same network community.

We can then use network regression techniques to find which org structure features best predict individuals being in different network communities.

Network Community: A community is a group of nodes (individuals) within a network. Individuals within communities are more connected to each other than anyone else.


Location?

Rank?

Sub-function?

Role?

Legacy group?

Question: What is driving collaboration post-change?


Location 2.1 | 1.94

Rank 0.88 | 0.98

Sub-functions 10.1 | 4.89

Role 2.5 | 2.12

Legacy group 1.9 | 1.66

Results: Function, not legacy group.

Effect on being in different network communities Survey | Email


Implications:ONA through all stages of the Reorg

Pre-Change• Collect data on

the existing network structure and collaboration ties to allow for more informed decisions prior to initiating change

During• Monitor how the

change is impacting the network structure and identify which areas need additional targeting

Post-Change• Quantify if and

how initial goals were met

• Understand how the network functions to allow for more informed human capital planning


Situation Overview

The Role of Network Analysis

Situation Overview

A consulting company has teams of personnel on each account. Their clients provide an “impact” score of how much the consulting positively affected their business. ANI undertook a project to assess the key team characteristics that contributed to higher client impact scores.

The objectives of the ONA were to identify: • Identify network and personal characteristics of team members that accounted for high client impact scores.•Provide actionable recommendations on how to better construct consulting teams to maximize client impact.


Social Network Analysis Approach

•A comprehensive social network map was built by analyzing the email records of all employees.

•The only information used from email data were the sender, receiver, and date-time stamp.

•Survey instruments were used to assess personal strengths of each employees


Findings and Recommendations

Key Findings Recommendations

Teams with a strong information broker in the email network experienced greater client impact.

• Plan teams to include an individual with a short social distance to other employees in the company’s communications network

• Client impact should improve by 4% if a team’s most connected individual is just 1 step closer on average to the overall network.

Teams with a high managerial personal characteristics individual experienced greater client impact.

• Teams should include an individual with a high score for managerial type strengths.

• Client impact should improve by 3% if the team’s highest managerial score is raised by 1 standard deviation (0.15 strength points).

Teams can benefit from new members.

• Include at least one member on a team who has not worked previously with the other team members.

• Including a novel individuals on multi-individual teams should improve client impact by 3.5% compared to constructing teams from individuals who have all worked together previously.


Team Network

Nodes indicate project teams

Teams linked by lines if they share some of the same people on a team

Line thickness reflects the number of individuals shared by the teams

Node size reflects the number of people

Node color reflects client impact (red = higher, blue = lower)


Network Brokers Enhance Team Success

Network brokers improve a team’s Client Impact Scores• Teams with an individual who was more central in the

email social network had higher client impact. If a team’s most connected individual is just 1 step closer on average to the overall network then their client impact score averaged a 4% increase as compared to other teams.

Recommendation• Highly central individuals can bring in needed skills and

information from outside the team. Assigning a highly central individual can increase team client impact.


Personal Characteristics Analysis

Having one individual with managerial strengths improved client impact.• Teams with an individual who was 1 standard deviation

above the average (0.15 points) in managerial strength had an average 3% greater client impact.

Recommendation• Include on all teams a person who is finds fulfillment in

setting attainable goals and dividing labor to meet them. This can enhance the performance of other team members to result in greater client impact.


Team Construction Over Time

Having new team members improved client impact• We used information from team co-membership in 2010 to

predict the client impact of teams in 2011. Having at least one individual on a team who had not worked with his/her teammates in 2010 improved client impact by 3.5% compared to teams where all the individuals had worked together in 2010.

Recommendation• Continue to reassign at least a few people to project teams

each year to ensure that some new blood is added as multi-year projects progress.


RecommendationsR

EC

OM

MEN

DATIO

NS

These analytics can be optimized for different purposes and interactive views, for example:

• Managers may want feedback on the best additional team members to select given a present set of team members and a desired team size.

• Employees may want to know with whom they should try to network in the near future.

Benefits of Brokers

• Include on teams at least one individual with high brokering potential who can connect the team to the rest of the network.

• Teams benefit if at least one individual has a core strength area in management.

• Do not leave teams with the exact same set of individuals from one year to the next. Add new faces.

Incorporate New Personnel

Leverage Managerial Individuals

Technology

CISummit 2013: Luke Matthews, The Leading Edge of ONA; eData; Reorgs; Networks Outside the Organization