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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


1 Introduction

2 Battlefield Infrastructure Studies

3 Method

4 Data

5 Conclusions

6 Questions



Section 1


  • 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



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




Divisional Rear Boundary


Move 2 FCUs a day


14 FCUs

Cdo LoC

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



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?


  • 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!



Section 6


  • 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