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Laying the foundations
A paper for ISMOR 20
26th August 2003
Glenn Richards
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Contents
1 Introduction
2 Battlefield Infrastructure Studies
3 Method
4 Data
5 Conclusions
6 Questions
Section 1
Introduction
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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
Section 2
Battlefield Infrastructure
Studies
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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
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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
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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!
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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
Method
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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
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‘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
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‘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
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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
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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
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‘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
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Typical supply network
RSG
7 days
FSG
SPOD
BSA
Move 2 FCUs a day
14 FCUs
Cdo
LoC
MRA
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‘Top-down’
Policy +
doctrine
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
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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!
Section 5
Data
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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
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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
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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
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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
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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
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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
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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
Conclusions
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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
Questions