Solving People Management Puzzles Using Social Network Analysis

Call centers depend on their employees teamwork to be successful. It should consider taking advantage of the advances in Social Network analysis to gain actionable insights on team dynamics .

May I suggest that call center managers use social network analysis tools and technics to generate insights that help to increase team work and overall morale.

Here I ishare how actionable insights using social network analysis can be used in the call center environment. We start with a sample Social Graph as shown below:

Some Famous Examples

Social graphs provide a visual map of the relationships among teams. Here are showcase examples where social graphs were used to :

1. Identify criminal masterminds (Enron Case)
2. Reveal the identity of key influencers (Sawmill-Pajek)
3. Identify the bonds that keep a community intact (Zachary Karate Club)

Identify criminal masterminds (Enron Case)

The backstory on the Enron case was that the FBI investigated it for price fixing of the energy prices. They needed to identify the ring leaders. They used email trails to identify the ‘direct reports’. The bosses were those at the top that got a lot of emails, but almost never replied to them.

Reveal the identity of key influencers (Sawmill-Pajek)

This sawmill had multi racial workers. The key staff was Juan who can be seen in the middle node (light blue). He was the conduit/bridge for information from the bosses to filter through to the rest of the spanish speaking workers.

For a new policy to gain acceptance, the bosses wisely enlisted HM Juan to their effort and messaging.

Identify the bonds that keep a community intact (Zachary Karate Club)

The famous Karate club clearly showed that the group was in danger of splitting into two separate groups. The interactions showed close knit ties centered around Node 1 and Node 34. The group eventually did split along those lines.

Farmout Call Center Experience

Then I will go on to present the actual social graph of our call center and share some of the actionable insights we gained from this and how each of the participants might use it in their own centers:

1. Using email logs to confirm the formal reporting hierarchies
2. Using Lunch Date data to uncover rifts in the teams
3. Using Lunch Date data to identify key influencers, information brokers
4. Using Lunch Dates data to identify critical intervention points to stop spread of disease outbreaks.
5. Using Chat interactions data to identify potential leaders and in-house experts

Using email logs to confirm the formal reporting hierarchies

Using Lunch Date data to uncover rifts in the teams

Using Chat interactions data to identify potential leaders and in-house expert.

Community detection enabled, nodes with the same color belongs to same team. The network charts were generated using Gephi 0.91. Newer technics would use NEO4J instead.