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Laying the foundations A paper for ISMOR 20. 26 th August 2003 Glenn Richards. Contents. 1 Introduction 2 Battlefield Infrastructure Studies 3 Method 4 Data 5 Conclusions 6 Questions. Introduction. Section 1. Introduction. What is Battlefield Infrastructure (BfI)?

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laying the foundations a paper for ismor 20

Laying the foundations A paper for ISMOR 20

26th August 2003

Glenn Richards

contents
Contents

1 Introduction

2 Battlefield Infrastructure Studies

3 Method

4 Data

5 Conclusions

6 Questions

introduction

Introduction

Section 1

introduction1
Introduction
  • What is Battlefield Infrastructure (BfI)?
    • fuel, water, power and accommodation
  • Little previous study in the UK
    • availability of data has been the key
  • This presentation will
    • examine the studies
    • discuss relative merits of 2 OR methods and
    • discuss data requirements, types, problems etc
bfi overarching study 1
BfI Overarching Study 1
  • Aim
    • understand the provision of BfI
    • identify potential choke points in the systems
    • examine possible technologies to improve BfI
    • find possible links between the components of BfI
    • prioritise and focus future research
bfi overarching study 2
BfI Overarching Study 2
  • Soft analysis - problem elicitation
  • Method
    • literature search
    • capture of current concepts of operation
    • obtain baseline data
    • interviews with stakeholders
    • study day
    • identification of possible areas suitable for technology research
    • analysis of findings
      • hard issues
      • soft issues
bfi overarching study 3
BfI Overarching Study 3
  • Results
    • baseline statement of capability to support a deployed op force
    • interactions between the four components of BFI
    • directions for future research and analysis identified
      • e.g. use of pipelines for water and fuel distribution
  • Most importantly...
    • recommend more studies where required!
follow on studies
Follow on studies
  • Following the scoping study, requests for three follow-on studies:
    • Deployed Fuel Handling Equipment Support Studies
    • Deployed Water Handling Equipment Support Studies
    • UK Forces Deployed Operations Electric Power
method

Method

Section 3

general method
General method
  • Quantitative studies of BfI are ORBAT driven
    • based on the amount of men and equipment deployed to an operation
  • Use agreed scenarios for modeling
  • For water and fuel studies
    • existent doctrine used (eg 25 litres/man/day)
    • solutions based on achievement of policy norms
  • Different from a large amount of military OR
top down vs bottom up
‘Top-down’ vs. ‘Bottom-up’
  • Two approaches to solving military OR problems
  • What’s the difference?
    • ‘bottom-up’, from performance to capability
      • many studies - Engr to Arty
    • ‘top-down’, from ORBAT to required quantities
      • DFHE
  • Bottom-up establishes need, top-down accepts it
bottom up studies
‘Bottom-up’ studies
  • In a particular scenario or vignette
    • define/postulate a number of tasks that have to be achieved in a certain time
    • use the time in which a single equipment could conduct defined tasks
    • aggregate up to derive number of equipments required for whole scenario
  • Or
    • using equipment with defined performance
    • assess the capability of forces of different composition in combat simulation
    • quantities from performance
advantages of bottom up approach
Advantages of ‘Bottom-up’ approach
  • Applicable for many types of study from Arty to Engr eqpt
  • Gets buy in from immediate stakeholders
    • i.e. those at MJPs
  • Can be good to examine particular scenario reqts, as examining each one by a MJP
  • Customers used to approach capabilities
  • Easy to examine different equipment
  • Better feeling for scenario chronology
disadvantages of bottom up approach
Disadvantages of ‘Bottom-up’ approach
  • Often based on limited ops within a campaign
  • Problems capturing data: initial task list, task time etc
  • Data often superseded with arrival of new stakeholders
  • Problems amalgamating reqts from different vignettes especially for vehicles that perform more than one function
  • Results require interpretation to
    • relate them to the entire campaign
    • allow for military structural issues
  • Large amount of preparation for MJPs
  • Specialised military knowledge requirement
top down example dfhe rds
‘Top-down’ example: DFHE RDS
  • Obtain agreed ORBATS
  • Obtain agreed policy norms
    • fuel quantities, storage reqts, nodes, etc
  • Give battlefield locations, nodes
  • Using policy norms work out what’s stored where, moved where, support modules reqts, etc
  • Simple sums
    • Capability reqts
  • Info on current & future kit
    • Equipment reqts
typical supply network
Typical supply network

7 days

RSG

FSG

SPOD

Divisional Rear Boundary

BSA

Move 2 FCUs a day

MRA

14 FCUs

Cdo LoC

top down
‘Top-down’

Policy + doctrine

advantages of top down approach
Advantages of ‘Top-down’ approach
  • Simple, quicker
    • normally can be done by adding and dividing
  • May require less military input
    • good if military scarce
  • Avoid the problems of aggregation to campaign level
  • Can be used to examine:
    • achievement of policy norms (eg water supply)
    • equipment needed to meet accepted requirement (eg power supply)
  • Less hassle from changing stakeholders
    • guaranteed audit trail policy + agreed ORBATs
disadvantages of top down approach
Disadvantages of ‘Top-down’ approach
  • Works best with agreed policy & doctrine
    • useful as a ‘what if’ vis a vis strawman policy
  • ORBATs
    • always disagreements
  • Rigidly adheres to policy statements
  • Can become independent of physical data within scenario
  • Not applicable to everything: bridges etc
  • Need to physically get policy docs
  • Simple
    • NOT HEADLINE MAKING OR!
slide21

Data

Section 5

definition of data
Definition of Data
  • “Factual information, especially information organised for analysis or used to reason or make decisions. ”
  • In terms of OR studies what exactly constitutes data?
    • is anything that is input into a study considered to be data?
    • something that has been measured is data,
    • but what about estimates or mil judgement?
    • are the hard-wired assumptions imbedded in a model data?
  • Definition of data can be a complicated issue
    • means different things to different people (programmer, analyst, customer, military stakeholder etc)
  • In this paper all inputs into an OR study
why are data important
Why are data important?
  • Data is … Data are
    • after much debate data are plural!
  • OR used to inform decisions e.g. procurement etc. Why?
    • to apply scientific rigour and method to them
  • OR can be ignored unless it gains the ‘buy in’ of stakeholders
    •  input data also subject to the same rigour of scrutiny?
  • GARBAGE IN = GARBAGE OUT
  • Quality of data not always appreciated
    • often delivery of results takes priority over input data
types of data
Types of data
  • Several classifications of data can be proposed, eg
    • high /low level (e.g Govt BoI vs mobility of a land platform
      • low level feed into high?
    • hard/soft, objective/subjective etc
  • However, in practice distinctions fuzzy
  • Soft data
    • schemes of manoeuvre, future doctrine, threat data etc
  • Hard data
    • platform data, policy statements, ORBATs etc
problems with data collection
Problems with data collection
  • Time
    • hard to get, large amounts
    • up to 75% of study spent collecting data
  • Why hard?
    • often unvalidated/anecdotal
    • knowledge is power
    • data management not sexy subject
      • often subject to ‘fads’
      • expensive and time consuming, leading to poorly maintained sources or gaps
    • data just not known
    • imbedded within models: self perpetuating
    • data from previous studies are often used at the customer’s request
    • rotation of military staff
problems with multiple data sources
Problems with multiple data sources
  • First glance multiple sources better than none
  • Closer inspection problems become apparent
    • different data sources give different values
    • design v use
    • performance on a range v performance in the field v performance in a model
    • current v future
    • centralised v distributed
    • historical v predicted
    • objective v subjective
  • Each source of data may be the ‘correct’ one
    • arbiter: the customer and stakeholder community
methods used for obtaining data
Methods used for obtaining data
  • Despite problems all is not lost
  • Methods for obtaining data
    • communication
      • undoubtedly the best
    • use of military personnel
    • involve the customer at an early stage
    • use of existing data
    • industry and other technical experts
    • historical data
    • strawman data
    • sensitivity analysis
data conclusions
Data Conclusions
  • Data vital for any study
    • the quality of data and stakeholder buy in important
  • Where data not available strawman and sensitivity useful
  • Time should be spent ensuring data fit for purpose
  • If time spent collecting data reduced
    • more time for analysis
    • more cost efficient studies
  • More effort required managing data
  • More knowledge sharing and communication are required!
conclusions

Conclusions

Section 6

conclusions1
Conclusions
  • Top down and bottom up approaches both have advantages and disadvantages
    • horses for courses
  • Data are important
    • many problems
      • but that’s why they pay us to do it
    • many solutions
      • some outlined in paper
      • I’d like to know yours
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