Talk given during the "Management and Social Networks" conference in Geneva (2012). Towards a "theory of meeting", with a focus on meeting systems, efficiency, affiliation network, information propagation.

1. Yves Caseau – Management and Social Networks – February, 2012 1/12
Efficiency of Meetings as a CommunicationEfficiency of Meetings as a Communication
Channel: A Social Network AnalysisChannel: A Social Network Analysis
MSN 2012, Geneva
February 16th
, 2012
Yves Caseau – Bouygues Telecom
National Academy of Technologies of France

2. Yves Caseau – Management and Social Networks – February, 2012 2/12
MotivationsMotivations
 Affiliation Networks
 Social Network for which links are N-to-M versus 1-to-1,
either represented as an hyper-graph or a bipartite (two-
mode) graph
 CMS (Corporate Meeting System)
 « System » of scheduled meetings in a company
 A favorite topic of interest for management consultants
 TDC example: the strength of short daily meetings
 Meetings make a key communication channel in large
enterprises, because of the amount of time that is spent
 Describing Affiliation Networks
 Diameter (set of persons met in a month)
 Degree (number of meetings that one attends in a month)
 Cluster Rate: transitivity ratio (keeping within small groups)
 A number of tools/metrics are available:
[LMD08] M. Latapy, C. Magnien and N. Del Vecchio, “
Basic Notions for the Analysis of Large Two-mode Networks
”, Social Networks, Vol. 30, n° 1, Jan 2008. Di
(informationnel)
Dr (Diam.
Réunionnel)

3. Yves Caseau – Management and Social Networks – February, 2012 3/12
Coverage SimulationCoverage Simulation
 Communication needs may be
represented with a social network
 Valued with contact frequencies
 Typical size: 200 to 2000 nodes
 Typical structure (degree, cluster, …)
 « Coverage » means to build an affiliation networks which covers contact
requirements, either through directs edges or through short paths
 This is consistent with the way actual meetings are designed (need to capture
regular interactions of a set of people on a given topic)
 Random TVSN generation (time-valued social networks)
 Various cluster rate (from random graph to heavy clusters)
 Various degree distribution (from regular to power laws)
 Various contact frequency distribution (regular to exponential)
 Coverage heuristic: greedy algorithm that produces a set of
hyper-edges which contains the most significant edges from
the input TSVN
Carol
Lucy
1h / week
1h / week
1h / w
1h /
week
2h /
month
2h / m
1h / m
1h / m
2h /w
1h / m
1h / month
1h / 2 days
1h / 2d
1h / 2 days
1h / 2d
1h / w
Peter
Mary
Luke
Jane
Bob

4. Yves Caseau – Management and Social Networks – February, 2012 4/12
Metrics : Input (Structure) – Output (Performance)Metrics : Input (Structure) – Output (Performance)
Communication requirements
 Captured by TVSN
 Degree of TSVN → Di
 Contact Frequency Distribution
CMS structure
• Average size (A)
• Number of meetings (M)
• Average Frequencies (Fm)
Four metrics for communication performance:
• Latency is the speed of information propagation.
It is measured though the average distance
between two nodes
• Throughput is the ability from the meeting
system to transport information. It is measured
as the sum of the products (duration x
frequency) for all meetings.
• Feedback is defined as the ability to check
appropriation/understanding when some
information is transmitted.
• Loss is the opposite to the capacity to transport
information without change. The simplest
measure is the average path length.
N:
Number
of
people
A
R : number of
meetings/person
T = 100
(100h of meetings/committee per month)
F: frequency of each meeting
1/100
3/100
3/100
3/100
M : number of
meetings
Modulo a few constraints (« simple laws »)
 Fm * R = T
 M * Fm = N / A * T
Consequently, two trade-offs must be found:
 For each person, between few frequent
meetings and many infrequent meetings
 Generally, few large meetings or many small
meetings.
Topic of study
One of many dimensions !
Notourtopichere

5. Yves Caseau – Management and Social Networks – February, 2012 5/12
Results (meeting size)Results (meeting size)
The larger the meeting attendance, the better the latency
 At the expense of throughput (and feedback)
 Improvement of loss, larger meeting diameter

6. Yves Caseau – Management and Social Networks – February, 2012 6/12
Results (meeting frequency)Results (meeting frequency)
Frequent meetings provide latency improvement
 The loss in Dm is more than compensated by the improvement with the individual
meeting latency
 No degradation of bandwidth (small improvement)
 Small degradation of loss

7. Yves Caseau – Management and Social Networks – February, 2012 7/12
Latency: influence of meeting size / distributionsLatency: influence of meeting size / distributions
 Latency decreases with meeting sizes, as well as path length, but so
does « feedback ».
Special
case
More
efficient
(known
result )
Other form
of « power
law »

8. Yves Caseau – Management and Social Networks – February, 2012 8/12
Latency: influence of meetings’ frequenciesLatency: influence of meetings’ frequencies
 Frequent meetings produce better latency, better throughput at the
expense of longer paths.

9. Yves Caseau – Management and Social Networks – February, 2012 9/12
« Small World » Structures : Hybrid Networks« Small World » Structures : Hybrid Networks
High
Frequency
Meetings
 Hybridization (mixing meetings obtained with different control parameters)
produces « small world structures » in the sense of Duncan Watts
 “… networks which displayed the high local clustering of disconnected caves but
were connected such that any node could be reached from any other in an average
of a few steps”.
 Hybrid Affiliation Networks increases communication performance
(both latency and throughput)

10. Yves Caseau – Management and Social Networks – February, 2012 10/12
Approximate Formula for LatencyApproximate Formula for Latency
D = [log(Di) / log(Dr)] * R
 Actually an exact formula for simple cases
 Following table example : standard deviation less than 10%,
average is close to 100% (of actual value)
0
20
40
60
80
100
120
140
160
180
200
0 100 200 300 400 500
DR
ratio
D*10

11. Yves Caseau – Management and Social Networks – February, 2012 11/12
Optimizing the use of communication channelsOptimizing the use of communication channels
 Application of BPEM (Business Process Enterprise Model) to study the
impact of communication channels on performance
 Four categories of communication channels
 “Communication Channel Model”
 Characteristics
 Policies Communication
Channel
Model
BPEM
Results
(value)
Learning
(optimization)
Activities to be
assigned to resources
Channel
PoliciesCommunication flow
units to be scheduled
Scheduler
Receivers
Organization
Rules/ Culture
Information
Flows
Meetings
Face-to-Face
Electronic – Synchronous
Electronic – Asynchronous
• Randomization
(Monte-Carlo)
• Evolutionary
algorithms (learning):
local opt, genetic
algorithm
Channel Performance Characteristics:
Throughput, Latency, Loss, Scheduling constraints
Cf.
Previous
Formula 

12. Yves Caseau – Management and Social Networks – February, 2012 12/12
ConclusionsConclusions
 Analysis of Affiliation Networks which represent « corporate
meeting systems » is relevant to characterize and optimize
information flows
 i.e., although communication is but one of meetings’ goals, and
structural efficiency only one dimension of communication efficiency,
this is a critical dimension for large companies.
 Computer simulation confirms lessons from experience:
 Frequent meetings (hence less numerous) should be favored
 There should be a mix of small attendance meetings with larger ones
 More generally, communication flows optimization is a key
component of organization and management theory for
21st century enterprises
 Characterization of communication channels
 Understanding information flows that are generated through
business processes
 Towards a « theory of meetings »:
structure, semantics and dynamics
Yves CASEAU