Management socialnetworksfeb2012


Published on

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.

Published in: Science
  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide
  • Les réseaux d'affiliation sont une forme de réseaux sociaux qui m'intéresse particulièrement puisqu'elle décrit la structure du « système réunion » d'une entreprise. Il se trouve qu'il existe également de nombreuses études sur ces réseaux (taux de clusterisation, degrés, etc.), dont celles, célèbres, sur les films et sur les conseils d'administration. Le point le plus important est qu'on retrouve les deux caractéristiques fondamentales : power law et fort taux de cluster (le terme français est « clique », qui désigne un sous-groupe fortement connecté).
  • A simple measure is the average speech time each attendee may expect in a meeting, that is the sum of (duration x frequency x inverse of number of attendees).
    Lorsqu’on s’intéresse au cheminement de l’information au travers d’une série de réunions, on peut distinguer deux cas :
    Le cas d’une information compacte, qui se propage « comme un signal ».
    Elle est facile à comprendre, il suffit d’avoir été présent à la réunion pour « être au courant ».
    La métrique associée est précisément la latence.
    Le cas d’une information complexe, difficile à comprendre, et qui nécessite un échange (avec reformulation).
    Dans ce cas, on comprend facilement qu’un trop grand nombre de participants nuit à la qualité de l’échange.
    Pour ce type de transmission d’information, ce qui nous intéresse est la capacité de la réunion à héberger des conversations, c’est-à-dire des échanges dans les deux sens
  • Characteristics: latency, throughput (one to M), sync/async of both ends, fidelity loss
  • Management socialnetworksfeb2012

    1. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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