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Yves Caseau – Management and Social Networks – February, 2012 1/12
Efficiency of Meetings as a Communication Efficiency of Meetings as a Communication Channel: A Social Network AnalysisChannel: A Social Network Analysis
MSN 2012, GenevaFebruary 16th, 2012
Yves Caseau – Bouygues TelecomNational Academy of Technologies of France
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)
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
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 ofmeetings/person
T = 100 (100h of meetings/committee per month)
F: frequency of each meeting
1/100
3/1003/100
3/100
M : number ofmeetings
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 studyOne of many dimensions !
Not
our
top
ic h
ere
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
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
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 »
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.
Yves Caseau – Management and Social Networks – February, 2012 9/12
« Small World » Structures : Hybrid Networks« Small World » Structures : Hybrid Networks
HighFrequencyMeetings
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)
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)
020406080
100
120140160180200
0 100 200 300 400 500
DR
ratio
D*10
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
ChannelModel
BPEMResults(value)
Learning(optimization)
Activities to be assigned to resources
Channel PoliciesCommunication flow
units to be scheduled
Scheduler
Receivers
Organization
Rules/ Culture
InformationFlows
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. PreviousFormula
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