Community OR Organisers: Martha Vahl, Eliseo Vilalta-Perdomo and Alejandro Ochoa-Arias ...

105 Pages·2010·0.91 MB·English

Community OR

Organisers: Martha Vahl, Eliseo Vilalta-Perdomo and Alejandro Ochoa-Arias

Martha Vahl Eliseo Vilalta-Perdomo

8/9/2010 : 09:30 : Room Windsor 0.03 Code:COR1
Modelling Dynamic Preferences of Disruptive Agents to Assess Risks of Violence
Outbreaks
Sumitra Sribhashyam*, Gilberto Montibeller** *The London School of Economics and Political
Science,, **LSE
Modelling threats caused by disruptive agents has been a booming area of interest, emphasised since
the 9/11 terrorist strikes and especially in the field of insurances. Several modelling approaches have
been attempted, including Monte Carlo simulations. Arguably, these methods may help in assessing
natural disasters, but they may not be as accurate to model threats caused by agents within a system.
Agents are subject to change their behaviour based on the system in which they evolve, and hence,
observed past behaviour may prove to be an irrelevant factor in determining their future one. The
proposed research aims to develop a framework for determining dynamic preferences over time of
disruptive agents, which may help anticipate a motivation to cause social unrest and help understand
how this impacts agents’ choice of a harmful action. The focus will be on modelling preferences
changes induced by changes in beliefs, objectives or desired outcomes caused by various exogenous
factors. The integration of multi-criteria decision analysis and system dynamics is investigated in order
to achieve the aims. We propose to model the preference ordering of the disruptive agents based on
their objectives to identify the most probable disruptive actions that such agents may perpetrate. To
model exogenous changes, which may have an impact on the agents’ preferences, we propose using a
system dynamics model. Combining the two approaches would inform how the agents may re-prioritise
their objectives in response to changes in their environment.

8/9/2010 : 10:00 : Room Windsor 0.03 Code:COR2
Evaluating Entrepreneurship Models from a Community Development Viewpoint: A
case study from central Mexico
Eliseo Vilalta-Perdomo*, Cynthia Montaudón-Tomas** *Tecnológico de Monterrey,
Guadalajara, **Tecnológico de Monterrey, Irapuato
Entrepreneurship is considered a dynamo for economic development. Certainly it has arise also the
belief that it might be useful to foster social development in deprived communities. This assumption is
challenged through a research done in central Mexico. Nine different entrepreneurship models are
recognized. Entrepreneurship programs from two different rural communities in the state of
Guanajuato are analyzed also from a community viewpoint. Among the findings of this project,
probably the most promising is to recognize that individual economic development and community
social development are not as linked as we suspected initially. They seem to be subjects from different
domains. A proposal to increase the life quality for future generations on rural communities is
presented. It is centered on creating and maintaining self-organized web-based networks.

8/9/2010 : 11:00 : Room Windsor 0.03 Code:COR3
Influence of heterogeneous groups on solving problems: the need of diverse
perspectives and heuristics
Ricardo Barros, Luis Pinzón Universidad de los Andes, Bogotá, Colombia
Group composition has been considered as an important factor in solving difficult problems.
Differences among members such as socio-demographic variables, abilities, ways of representing
situations and problems - perspectives, use of algorithms to generate solutions - heuristics, are
examples of approaches to understand diversity. In these approaches, some studies have shown that
homogeneity in groups is required to generate cohesion, deep discussions, and agreements. Others
studies have presented the need of heterogeneity in groups to generate better performance. In this
paper, primary school students participated in an experiment of solving mathematical problems.
Students were organized in groups having into account diversity in perspectives and heuristics to
analyze the influence of this kind of diversity on performance in comparison to homogeneous groups.
Implications of group composition on effectiveness in community group projects are explored.

8/9/2010 : 11:30 : Room Windsor 0.03 Code:COR4
Knowledgeland and the knowledgegap
Chris Sigaloff vice chair of Knowledgeland, a think tank in the Netherlands
Knowledgeland and the knowledgegap Sparking social innovations to improve society is an arduous
task. Knowledgeland, an independent think tank in the Netherlands, has ten years of experience in
setting up projects that create social innovation in the field of education, government, creative
industry, heritage and social media. These innovations are not realized by introducing a new law,
regulation or a comprehensive report - although these might help- but we tend to empower the
community's agents and stimulate innovation from bottom up. This calls for better cooperation
between multiple objectives, innovative power of professionals and a culture stimulating innovation
from the inside. However, we are confronted with a research and knowledge gap in how to actually
create a sustainable impact. Recipes or theories of innovation have little value for our daily practice.
This uncovers the paradox that knowledge about innovation is not knowledge for creating innovation
in real life. Established theory is in any case not supportive for achieving improvements and often
creates too many negative side effects. At this conference we would like to investigate, with the help of
the audience, if Community Operational Research can provide us with research principles that support
our ambition in making Dutch society smarter. Not only by setting up projects to stimulate social
innovation but also by building up a body of knowledge and research for innovation. Presenter: Chris
Sigaloff, vice chair of Knowledgeland, an independent think tank in the Netherlands geared towards
strengthening the knowledge economy.
9/9/2010 : 09:30 : Room Windsor 0.03 Code:COR5
Challenging Inequality? Vertical Interventions to Horizontal Problems? A study of a
Healthy Living Centre within Lincolnshire Probation
Jennifer Jackson, Rebecca Herron Community Operational Research Unit, University of Lincoln
Health inequalities are not a ‘new’ issue, rather successive governments and policies have sought to
understand and redress the structural and lifestyle causes of health outcomes. Health inequalities
nevertheless remain a ‘wicked’ problem with ill-defined areas of resolution. One governmental solution
has been the setting up of Healthy Living Centres amongst vulnerable groups who access health
services least, the most unique being a Healthy Living Centre set up within Lincolnshire Probation in
2003. As this paper explores the Community Operational Research Unit (CORU) was given a unique
opportunity to examine from 2003-8 the issues that this Healthy Living Centre (HLC) represents through
a sustained engaged research project. In particular to examine the impact and dynamics of state
intervention and public programmes for specific community groups and how organisational objectives
for ‘improvement’ vie with ‘community’ engagement and individual belief systems and actions. That
moreover engaging and evaluating ‘messy’ interventions and hard to reach groups is in itself a ‘messy’
process. This paper explores the nature of community OR practice in unravelling the multiple levels that
impact on interventions and how it seeks to help policy makers and practitioners with their ‘wicked’
problems and potential solutions of how to act.

9/9/2010 : 10:00 : Room Windsor 0.03 Code:COR6
Evaluating the impact of a Wellness Recovery Action Plan training for members of the
East Midlands Black Minority Ethnic community as a social intervention.
Martha Vahl
A training to deal with mental health issues using a self help WRAP method is deemed particularly
suitable for members of the BME community. Some of their problems are that they are either
overrepresented in some mental health services or fail to access them at all. The NHS commissioner of
the project expected WRAP to support the BME communities to engage and that the training would
become widely available throughout the East Midlands (Leicestershire, Nottinghamshire and
Lincolnshire). The impact evaluation aims to identify how successful the training has been. It is
intended to help participants to develop models for dealing with their community or mental health
issues. During the training changes in these models is expected, e.g resulting in participants being able
to act together inside their WRAP groups and to transfer the use of their models to the communities of
which they are part. A training is usually evaluated as a technical intervention, e.g. a self assessment
measurement of changes on certain variables (confidence, hope, skills, etc.) before and after a training.
The WRAP training is being evaluated as a social intervention. Both the method of evaluation and the
results are presented.

9/9/2010 : 10:30 : Room Windsor 0.03 Code:COR8
Working to develop an integrated programme of work operating as an OR analyst to a
local voluntary sector
Andrew Dobson Self-employed analyst
The speaker will describe his efforts over the last year to develop an integrated programme of work
operating as a pro-bono OR analyst and consultant to a local voluntary sector in south London. This
has involved working to develop productive working relationships with several different targeted local
voluntary organisations all involved with social care in different ways (eg contracted provider,
‘infrastructure’ group, social enterprise). The organisations were chosen with the aim of producing
work that could fit together into a coherent whole that might be more than the sum of its parts,
drawing on past experiences of developing work as an OR analyst with central government. The
speaker will reflect on the different degrees of progress made, on the nature of the work done, and
make some conclusions so far about the challenges of achieving the overall objective.

9/9/2010 : 11:30 : Room Windsor 0.03 Code:COR7
Community OR Tutorial Technical and Social Interventions
Martha Vahl, Gerard De Zeeuw St Lucas School of Architecture Brussels
This tutorial will explore the difference and use of the two concepts, e.g. technical and social
interventions. The aim is to identify the potential for research into Community Operational Research
(community operations and research CO+R). Technical interventions are based on knowledge
acquired through observations, e.g. training of skills to be used irrespective of the particular context of
the participant. Social interventions are based on knowledge acquired via a combination of
observations and preferences (objectives). The acquisition involves the design of a collective or
community with a proper form of coordination. Technical interventions examples are the main stay
of Operational Research, The models involved take the preferences or objectives of the commissioner
as given. These models are difficult to apply as preferences in Community Operational Research are
individually defined and vary over time. In the tutorial we discuss and compare a number of
approaches, such as Mode 2 knowledge production, action research, problem structuring methods,
SSM and others. We identify what type of research is needed to develop OR in dealing with
communities and what form these may take. We discuss a number of results of this type of research.

9/9/2010 : 12:30 : Room Windsor 0.03 Code:COR9
Why communities must be able to fail in order to survive
Jan Gerrit Schuurman, Rebecca Herron University of Lincoln
While it is possible to fail, without making any mistakes, mistakes indicate that failure is likely. We
discuss three interrelated problems. (1) Can it be known to a community that it is failing? (2) Can it be
known by its members that the community makes mistakes? (3) Can it be known what is the correct
thing to do by that community. We will argue that the positive answers follow from (1) the property of
being a community member, (2) the minimal interaction within any mereological sum of community
members, in order to be recognised as merelogical member of the same community and (3) sensing
properties of the community that matter for the continuation and well being of the community as an
entity with an ongoing history. A community property can be expressed in terms of a statistic, such as
the death rate due to infection. The cholera outbreak in 1854 in SOHO exemplifies that a community
that can fail, is a community that can recognise mistakes and correct its actions. The story points at
classes of actions on the part of any body trying to improve the living conditions of a particular
community. We maintain that the success of John Snow (who identified the sources of the cholera) was
complemented by the competence of the community to sense the worsening life conditions of the
community. The people had to sense failure, unaware of making mistakes. By correcting their water
storage, maintenance and retrieval habits, they were avoiding catastrophic failure.
Criminal Justice

Organisers: Ian Williamson and Brian Burton

Ian Williamson Brian Burton

7/9/2010 : 11:30 : Room Arts S21 Code:CJ8
The New Justice Framework: Trying to squash a complex system into a simple model
Janos Suto Ministry of Justice
The criminal justice system is a complicated system which presents a challenge to the modeller: Make
your model too complicated and it will be incomprehensible and unusable; but make it too simple and
it is of little use. Here I describe the process we went through when developing the New Justice
Framework – an ambitious model of the whole criminal justice system from crime to punishment.

7/9/2010 : 12:00 : Room Arts S21 Code:CJ5
A waterfall for the Crown Court
Brian Burton Office for Criminal Justice Reform
Waterfall models have their origin in manufacturing and IT development where the design process is
split into a sequence of stages. One only proceeds from one stage to the next when the first has been
completed. In a previous project to improve operational efficiency in the magistrates’ court we adapted
the Waterfall concept to the sequence of stages through which a defendant’s case may pass, from the
point of arrest to trial. Using centrally stored data, a local criminal justice board would be able to view
the distribution of alternative case disposals among defendants and the associated costs, including the
costs of unnecessarily repeating work. Here, I present a similar Waterfall for the Crown Court. I shall
review the new data now available for Crown Court cases and the formulation of costs for each
possible disposal. New features include total costs for defendants receiving different disposals, an
identification of avoidable hearing costs and a comparison of the costs of current processes with those
of more efficient, ‘ideal’ scenarios. The Crown Court Waterfall will be used to diagnose areas of
inefficiency both locally and nationally and to assess the potential impact of cost savings initiatives.

7/9/2010 : 13:30 : Room Arts S21 Code:CJ2
Improving Policing Processes through Participative Intervention
Ian Newsome Head of Profession, Corporate Review
There is a growing interest in improving the efficiency and effectiveness of policing processes through
the application of a variety of OR approaches. With the heightened pressure on public service budgets
there is an increasing interest in tackling cross-organisational processes, where significant untapped
improvement resides and to engage staff in identifying and realising the benefits. This presentation will
compare several practical participative approaches to process improvement that have been applied
within the policing environment and consider the outcomes they achieved along with their relative
strengths and weaknesses.
7/9/2010 : 14:00 : Room Arts S21 Code:CJ1
Patrolling games on graphs
Alexander Morton London School of Economics
A key operational problem for those charged with the security of vulnerable facilities (such as airports
or art galleries) is the scheduling and deployment of patrols. Motivated by the problem of optimizing
randomized, and thus unpredictable, patrols, we present a class of patrolling games on graphs. The
facility can be thought of as a graph Q of interconnected nodes (e.g. rooms, terminals) and the
Attacker can choose to attack any node of Q within a given time T. He requires m consecutive periods
there, uninterrupted by the Patroller, to commit his nefarious act (and win). The Patroller can follow
any path on the graph. Thus the patrolling game is a win-lose game, where the Value is the probability
that the Patroller successfully intercepts an attack, given best play on both sides. We determine
analytically either the Value of the game, or bounds on the Value, for various classes of graphs, and
discuss how our analysis could guide decisions when the Attacker can observe Patroller behaviour.

9/9/2010 : 09:30 : Room Arts S21 Code:CJ7
Six Sigma and Lean: bandwagon or benefit?
Ian Seath Improvement Skills Consulting Ltd.
In these challenging financial times public sector organisations are under increasing pressure to achieve
REAL efficiency savings. Gone are the days of “smoke and mirrors” and annual 2% savings targets.
Criminal Justice Sector organisations such as the Police and Probation were early adopters of process
improvement techniques and the requirement to carry out Best Value Reviews has reinforced the
importance of “process” in effective service delivery. However, many approaches to process
improvement got stuck at the implementation stage: it’s easy to re-design a process, but not so easy to
implement that re-design and ensure it is adopted and sustained. Six Sigma and Lean (or Systems
Thinking as some refer to it) are two of the more current process improvement approaches being
adopted. This presentation will explain the differences between the two approaches and describe how
they can complement each other (so-called Lean-Six Sigma). It will describe the potential benefits to
be achieved and some success factors to be considered in order to avoid the bandwagon effect of
adopting the “latest whizzo management tool”. The presentation will be illustrated with examples of
Six Sigma and Lean applied in the Criminal Justice Sector.

9/9/2010 : 10:30 : Room Arts S21 Code:CJ3
Modelling criminal careers: can we predict the future cost associated with an
individual's reoffending behaviour?
Paul Radford Ministry of Justice
A criminal career relates to the sequence of offences committed over time by an offender. Those
offenders who frequently cycle through the Criminal Justice System place demands on limited offender
management resources. The National Offender Management Service is tasked with reducing the
burden on these resources by commissioning and providing correctional services and interventions that
are designed to protect the public and reduce re-offending. It is not possible to provide these services
and interventions to all offenders, and therefore those offenders who are most likely to incur a
significant cost to the Ministry of Justice, and Society, should be prioritised. One of the ways this is
currently done is by assessing an offender’s likelihood of reoffending within two years, based on their
offending history and characteristics. This talk will describe how offending history and offender
characteristics have been used to predict the impact of an offenders total offending over a longer
period of time. Data from the Police National Computer has been used to calculate the cost to the MoJ
of an individual’s offending behaviour over a five year period, and ordinal logistic regression techniques
were then used to compute the probability of an offender falling into a defined cost band. The results
of this work, and limitations of the approach will be discussed and the audience will be invited to share
ideas of how Operational Research techniques could be applied to the subject of Criminal Careers.

9/9/2010 : 11:30 : Room Arts S21 Code:CJ6
Developing a quantitative measure for offending and re-offending harm
Ian Vincent Home Office
Traditional proven offending and re-offending measures are based on counts of convictions and/or
cautions. Relying on these measures to inform policy or measure performance, would imply that we
believe that each conviction for shoplifting is as important as a conviction for murder. The quest for
robust and compelling evidence leads us to consider alternative approaches, the extent to which they
capture harm and where the results differ. This paper presents a Home Office project to develop an
alternative measure; the reasons for basing this measure on average sentence length, the advantages
to working across departmental boundaries, the technical challenges and how the key assumptions are
impacting on the usability of the new measure.

9/9/2010 : 12:00 : Room Arts S21 Code:CJ9
An application of tabu search optimization techniques to the problem of Police staff
rostering.
Oliver Edleston, Lisa Bartlett Loughborough University
Within Leicestershire there is a strong interest in professionalization of the Police force whilst also
taking into account potential restrictions due to planned budget reductions. Front-line staffing has
been identified as a key area with potential for improvement through the consideration of staff
distribution and shift structure employed. A tabu search optimization approach is presented that has
been created in order to provide solution to this problem. The use of diversification and intensification
techniques are considered and applied to improve solution quality provided by the search. The base
search is shown to yield higher quality solutions than a similarly applied steepest descent algorithm,
with further improvement given through the search enhancements used.

9/9/2010 : 12:30 : Room Arts S21 Code:CJ4
A process-based cost-benefit analysis for digitising police suspect interviews
Ian Seath Improvement Skills Consulting Ltd.
The technology to move to digital recording of audio and video interviews is now available in the
marketplace and the question being asked is whether its implementation can deliver improvements in
efficiency, effectiveness and cycle-time. In this case study, we answer that question. The presentation
will be based on a piece of work looking at the cost-benefit of moving from tape-based Police
interviewing processes to digital processing. This involved some process analysis, activity cost and also
showed up some interesting "non-Lean" waste as well as proving the benefit of going digital.
Data Mining & Forecasting

Organisers: David Martens and Kostas Nikolopoulos

David Martens Kostas Nikolopoulos

7/9/2010 : 11:30 : Room Windsor 0.04 Code:DAM1
Forecasting the Effectiveness of Policy Implementation Strategies through Structured
Analogies
*Nicolas Savio, **Konstantinos Nikolopoulos Manchester Business School, University of Wales,
Bangor
Policy implementation strategies (PIS) are schemes originating at a governmental level intended to help
attain some over-arching policy objective (social, economic or environmental). Determining the nature
and characteristics that a PIS will take is an important decision making process for any government as
there will undoubtedly be limited funds for such a purpose. It is argued that an ex-ante¬ prediction of
the effectiveness of a new PIS can serve as a much needed decision support tool and should be an
integral part of any cost-benefit analysis. This research proposes and evaluates the use of Structured
Analogies in the hands of policy experts for producing such forecasts.

7/9/2010 : 12:00 : Room Windsor 0.04 Code:DAM2
A Forecasting Support System for Intermittent Demand
Fotios Petropoulos, Vassilios Assimakopoulos National Technical University of Athens, Greece
Intermittent demand patterns are characterized by infrequent demand arrivals coupled with variable
demand sizes, when demand occurs. Such patterns prevail in many industrial applications, rendering
the need of a specialized Forecasting Support System (FSS) requisite. Intermittent Demand Forecasting
System (IDFS) incorporates established forecasting techniques used widely in intermittent demand
patterns, offering an efficient expert forecasting engine based on competitions among implemented
techniques. The system allows statistical forecasts derived from implemented techniques to be
combined with judgments made by the user. These judgments can be the choice of the appropriate
methods’ parameters or methods combined as well as the adjustments made upon the statistical
forecasts based on user’s knowledge (soft data) and expertise. Numerical and graphical interpretations
of statistical and forecasting analysis with appropriate accuracy metrics grant the effectiveness of the
forecasting procedure provided by the IDFS. Finally, IDFS supplies detailed reporting information on all
aspects of the analysis and forecasting while also showing information about the accuracy of different
extrapolation techniques.
7/9/2010 : 13:30 : Room Windsor 0.04 Code:DAM3
Forecasting the success of a new eco-friendly Policy
Akrivi Litsa, Vassilios Assimakopoulos Forecasting @ Strategy Unit, National Technical University
of Athens
Governments often use budget so as to provide incentives for citizens to adopt new policies, especially
when these are promoting eco-friendly technologies e.g. to subsidise the price of a hybrid-car. The
public money spent on each policy, is considered to be value-for–money only if many citizens do adopt
the proposed policy. This is also known as the 'cost-effectiveness' or the 'economic success' of a new
policy. The latter should not be confused with the 'economic impact' of the new policy, as this is
usually referred to the respective macro/micro socio-economic impact. This study reports on a
experiment with semi-experts using Structured Analogies (SA) forecasting the success of a new policy
promoting replacing old household air conditioners with energy saving units under a new environment
and technology initiative implemented by a European government. The findings shows evidence that
Structured Analogies (SA) is a useful forecasting tool for policy making, however all methods predicted
results that were considerably off the mark, indicating the difficulty of the forecasting task under
examination.

7/9/2010 : 14:00 : Room Windsor 0.04 Code:DAM4
Support forecasting by quantifying non-expert judgment through text mining on
financial news
Mike Nikitas, Vassilios Assimakopoulos National Technical University of Athens
Forecasting financial products like stocks, bonds, funds, indices etc, heavily relies on inside information,
expert opinions, statistical analysis and of course, media content. Published news is most important in
terms of coverage. The greatest percentage of people buying and selling financial products, driving
high volumes on markets, do not have access to inside information or experts and do not have the
skills to analyze statistics. They rely on financial news from various sources, newspapers, television,
radio and the internet. The sentiment received from the understanding of the media content reflects
their judgment for financial decisions. Through the current research effort, we identified correlations
between financial news sentiment and financial decisions. In order to achieve this, at first, we present
a methodology and the respective software to distinguish how bad or how good is a published text for
a company, for an industry or for a whole market. Using neural networks, and our captured news data,
we trained our software to be able to identify goodness and badness of news. For the same period of
time, we have captured the values of non commodity financial products. By quantifying how good or
how bad are the published news and by comparing them with real financial values we identified
correlations that are very useful for short term decisions. As a result of our research work, the identified
correlations are utilized to model non-expert judgment, and able to produce a tangible factor to
support statistical methods for short term forecasting on specific financial decisions.

7/9/2010 : 14:30 : Room Windsor 0.04 Code:DAM5
Regression Rule Extraction from Neural Networks for Software Effort Prediction
Karel Dejaeger, Wouter Verbeke, David Martens, Bart Baesens Katholieke Universiteit
Leuven
In the field of software effort prediction, the effort needed to develop a new project is estimated based
on historical data from previous projects. In the past, various algorithmic approaches to this problem
have been researched. More recently, the applicability of machine learning techniques like CART and
neural networks has been investigated. Neural networks are a tool often selected for software effort
prediction as they have the capability to approximate any continuous function with arbitrary accuracy.
A major drawback of neural networks is the complex mapping between inputs and output which is not
easily understood by a user. A method to mitigate this potential problem is the application of a rule
extraction technique that derives a set of comprehensible IF-THEN rules from a trained neural network.
We describe such a rule extraction algorithm and compare the applicability this technique to other
machine learning techniques like linear regression and CART. It is found that the most accurate results
are obtained by CART, though the large number of rules limits comprehensibility. Considering
comprehensible models only, the concise set of extracted rules outperform the pruned CART rule set,
making neural network rule extraction a more suitable technique for software effort prediction.

7/9/2010 : 15:30 : Room Windsor 0.04 Code:DAM6
Data mining with swarm intelligence
David Martens*, Bart Baesens*, Tom Fawcett** *K.U.Leuven, **Stanford University
Swarm intelligence is a relatively new subfield of artificial intelligence which studies the emergent
collective intelligence of groups of simple agents. It is based on the social behavior that can be
observed in nature, such as ant colonies, flocks of birds, fish schools and bee hives, where a number of
individuals with limited capabilities are able to come to intelligent solutions for complex problems. In
recent decades the Swarm Intelligence paradigm has received widespread attention in research, mainly
as Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). These are also the most
popular swarm intelligence metaheuristics for data mining. Both classification and clustering have been
addressed with these metaheuristics. In this presentation, we will discuss how such paradigms can be
used for data mining by explaining the main workings, providing a literature overview and addressing
some open issues.

7/9/2010 : 16:00 : Room Windsor 0.04 Code:DAM7
Comparing Classification Techniques to Forecast Customer Churn in the
Telecommunication Sector
Wouter Verbeke*, Karel Dejaeger**, Bart Baesens** *Department of Decision Sciences and
Information Management, Faculty of Business and Economy, Katholieke Universiteit Leuven,
**Department of Decision Sciences and Information Management, Katholieke Universiteit Leuven,
Naamsestraat 69, B-3000 Leuven, Belgium
Customer churn prediction models indicate the customers with a high propensity to attrite, and
therefore allow to improve the efficiency of customer retention campaigns. A myriad of data mining
techniques has been tested to predict customer churn, but the literature reports contradictory results.
This study presents the results of an extensive benchmarking experiment, including various state-of-
the-art classification algorithms which are applied on eleven real-life churn prediction data sets from
wireless telecom operators around the world. The appropriate test statistics and performance measures
are used to rigorously test the impact of three different factors on the performance of a churn
prediction model, i.e. input selection, oversampling, and classification technique. It is found that input
selection is crucial to achieve good predictive power, and that a limited number of attributes suffices to
predict customer churn with high accuracy. Oversampling on the other hand does not improve the
results significantly. Furthermore, a large group of classifiers is found to yield comparable performance,
including a number of techniques that induce comprehensible models, such as logistic regression and
Bayesian Networks.