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

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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)

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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

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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

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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

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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

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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 »

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Latency: influence of meetings’ frequenciesLatency: influence of meetings’ frequencies

Frequent meetings produce better latency, better throughput at the expense of longer paths.

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« 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)

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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

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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

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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