E-Commerce Model and Models of Agility
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1 PHASE SPACE SHIFTS IN COMMAND STRUCTURES IN NETWORKED SYSTEMS Professor Neville A. Stanton Dr Guy Walker Linda J. Sorensen University of Southampton Human Factors Integration Defence Technology Centre
2 Overview ELICIT paradigm Modelling in C2 NATO SAS-050 Phase Space Cube From Approach Space to Phase Space From Typology to Taxonomy Multi-National Experiment Conclusions
3 Components of ELICIT interface Websites Who What Where When Inbox My Factoids
4 Architecture Websites Who What Where When Factoid Inbox Factoids provided at outset of trial, then on two further occasions. My Factoids
5 Architecture Websites Who What Where When Factoid Inbox Add My Factoids
6 Architecture Websites Post Who What Where When Factoid Inbox Post Add My Factoids
7 Architecture Websites Post Who What Where When Factoid Add Inbox Post My Factoids Add (Copy)
8 Architecture Websites Post Who What Where When Factoid Add Inbox Post My Factoids Add (Copy) Share
9 Sharing Who Where What When
10 Sharing Only have access to respective who/what/where/when websites Who Where What When
11 Have access to all who/what/where/when websites
12 Sharing
13 Sharing
14 Modelling command structures Chain Y Circle All-connected Wheel
15 NATO SAS-050 Phase Space cube OFT3 Edge Classic C2 NATO Approach Space
16 Octant Archetypes NATO Approach Space Who Where What When
17 Approach Space to XXXX Match the position of a network structure in the Approach Space with the corresponding task type or problem in the Problem Space. This will increase understanding of agility and focus for NEC organisation. Complex Problems NEC Problem Space? Approach Space? C2 Complicated Problems
18 Distribution of Information: 1 Broad dissemination = more dense. Tight control = less dense Tight Control DISTRIBUTION OF INFORMATION Broad Dissemination Distributed PATTERNS OF INTERACTION Patterns of Interaction: Hierarchical interaction = bigger diameter. Distributed interaction = smaller diameter Hierarchical Unitary ALLOCATION OF DECISION RIGHTS Centrality: Unitary decision rights = a few highly central agents. Peer-to-Peer Peer-to-peer decision rights = greater number of central agents.
19 Measures of Agility Challenge: Lack of appropriate Agility metrics to describe the changing shape of the organisational structure. We proposed 2 metrics to analyse Agility: 1) Volume 2) Deviation
20 Volume The larger the volume the greater the space covered by a given network structure The hypothesis is therefore that the volume delineates agility in that the greater volume covered the greater flexibility of the network (AoDR Max - AoDR Min) x (PoI Max - PoI Min) x (DoI Max DoI Min) Where AoDR is 'Allocation of Decision Rights', PoI is 'Patterns of Interaction' and DoI is 'Distribution of Information'. The point is to subtract the minimum and maximum values for each of the dimensions (to give length, width and height) and then multiply the resulting numbers together (to give the volume of the cube).
21 In-house Baseline Study Background This study compares two network structures; traditional C2 and Edge (peer-to-peer). Sample of 34 postgraduate students; 17 in C2 and Edge Aim To populate the NATO Approach space with empirical data to represent the movement of the networks over time. Explore which theory of SA; Shared SA or Distributed SA which provide the most insight into the actual functioning of the networks in terms of Situation Awareness. Development of the Log Analyzer Data analysed using the Log Analyzer Developed the Log Analyzer with the DoD software provider to allow sharing behaviour to be analysed at specific time intervals Development allows us to extract the data needed to calculate SNA metrics which in turn allows us to place the network structures in the NATO cube. The time interval also shows a measure of agility in the networks behaviour across task involvement Analysis EAST; ELICIT measures such as situation awareness, time to complete, correct identify and sharing behaviours; NATO Approach Space coordinate calculation and representation. Most of the analysis is complete; remaining analysis to focus on Distributed Situation Awareness.
22 Meta-analysis Meta-analysis of international ELICIT baseline data conducted. Data acquired through the ELICIT user community Meta-data sample contains 16 data sets: 8 C2 and 8 Edge. Inclusion of Naval Postgraduate School, United States 5 countries of origin: Portugal, Singapore, Canada, United States (West Point Military Academy and Boston University, Naval Postgraduate School) and the United Kingdom (Cranfield Defence Academy UK and Southampton University).
23 Performance of the networks
24 Sharing, posting and pulling
25 Allocation of Decision Rights
26 Patterns of Interaction
27 Distribution of Information
28 Analysis of Agility The data from the In-house Baseline ELICIT Study and Meta-analysis date was further analysed in terms of the agility metrics identified: Calculation of Volume for the movement of an N s sample data within the NATO Approach Space Volume compared across N s for C2 and Edge conditions.
29 Portugal Volume = Volume =
30 Singapore Volume = Volume =
31 United Kingdom Volume = Volume = 7.96
32 United Kingdom Volume = Volume =
33 Canada Volume = Volume =
34 United States Volume = Volume =
35 United States Volume = Volume =
36 United States Volume = Volume =
37 Volume by type
38 Volume by organisation
39 Summary Table Volume N Network structure AoDR PoI DoI Volume Portugal C Portugal Edge Singapore C Singapore Edge Cranfield C Cranfield Edge Southampton C Southampton Edge Canada C Canada Edge US West Point C US West Point Edge US Boston Uni C US Boston Uni Edge US NPS C US NPS Edge
40 Octant Archetypes NATO Approach Space Who Where What When
41
42 Meta-data overview
43 All information exchange types
44
45 Conclusions The data to fall into just one of the octants (the star octant). Two types of organisations (C2 and Edge) drift toward the same point in the NATO phase space. The phase space distinguishes between different organizational structures. A problem with the entire ELICIT paradigm is raised. What structures might have emerged in the Edge condition if there was an evolving task with no fixed endstate, a task which required teams to continually adapt and evolve with their environment?
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