STRUCTURED MARKET ANALYSIS AND STRATEGIC CHOICE
(Meizi Chen, LSE, MSc Operational Research and Analytics)
The LSE’s management science masters programme (now Operational Research and Analytics) has sourced anything up to 100 projects in one year with organisations ranging from global giants to relatively tiny but dynamic start-ups.
Inevitably, the majority have focused on one application area and often on one skill set. However, the LSE has a strong tradition of research and teaching methodologies to support strategic planning and decision-making in situations where a multidisciplinary approach is needed. It also tries to equip masters students with the ‘soft skills’ needed to champion their specialisms within an organisation, perhaps operating as internal consultant and having to build ‘intelligent customer’ capacity and awareness of what could be achieved.
That was very much the case for Meizi’s project, undertaken for a client new to the LSE’s programme, IMI Precision Engineering. The client was looking for support in identifying areas within its sales and marketing operations where better data analytics and structured decision-making could help shape strategy choice and subsequent focus. Pilots would then hopefully generate valuable results but also demonstrate the benefits to a wide range of internal stakeholders, with potential future roll-out of the best ideas.
This was ‘real-life management consultancy’. The details of this project are confidential but Meizi worked across teams to explore ways to approach forthcoming decisions and build the necessary data sets and ran a structured multi-criteria decision analysis (MCDA) trial.
The LSE’s project supervisor, David Collier, said ‘Meizi was chosen for this project because of her broad knowledge of suitable methods and her Distinction from Penn State in Supply Chain and Information Systems, but also because of her personality and adaptability. It is hard to come in cold to an unfamiliar organisation in a new country and convince potentially sceptical engineers but somehow Meizi managed it.’
Meizi agreed with that assessment of the challenge but recognised the opportunity. She said ‘the three-month consulting project was a highlight from my time at LSE. It was a valuable experience applying sound academic theory and offered, most importantly, a real in-depth task to immerse myself in. It was a great opportunity for me to improve my technical, communication, and analytical skills, but also gave me the confidence to start my career after graduation’.
Francesca Dematteis for IMI Precision Engineering said ‘I enjoyed the experience of mentoring Meizi. We were really pleased with her and with our first experience of a summer masters project. Exploring possibilities inevitably means a few false starts but we learned a lot from the process and it really did inform the choices we subsequently made’.
Meizi is now back home in China with an important role in a fast-growing education business but she still keeps in touch with the friends she made through the project.
DISCRETE STATE MODEL FOR BANKNOTE LIFE
(Emily Loizidou, University of Southampton, MSc Operational Research and Finance)
The aim of Emily’s project was to model the process of banknotes deteriorating through different fitness states. The quality of circulating banknotes is an important consideration for central banks and variations in performance can have significant implications on the management of the cash cycle.
De La Rue is the largest commercial producer of security documents working with governments, central banks and commercial organisations in more than 140 countries. The company provides central banks with the tools, including the software DLR AnalyticsTM, they need to make data-based decisions.
Modelling the demand for new banknotes is a challenge faced by all central banks. The requirements for new banknotes vary between denominations and are influenced by circulation volume forecasts, seasonal patterns, policy changes and the banknotes performance in circulation. There is limited research in modelling banknote deterioration, and very few central banks have the capability to monitor the quality of individual banknotes using serial numbers as they move through their life in the cash cycle. The implication of having heavily worn banknotes in circulation can be severe.
Central banks set fitness standards that they consider acceptable to maintain a certain quality of banknotes in circulation. When banknotes are returned from circulation to be examined or sorted, they will either pass or fail according to these criteria. Small changes to the standards can have large implications on the number of banknotes assessed as no longer suitable for circulation and ultimately destroyed. It is therefore important to be able to model how banknotes wear over time, both to support more accurate banknote demand forecasting and provide the ability to fine tune banknote fitness standards whilst understanding the direct impact on destruction volumes.
A discrete state model was used to represent the transitions between different fitness levels for banknotes. There are two main categories for banknote fitness: (1) fit and (2) not fit. Each category can be subdivided into additional levels. All banknotes will begin their life in the first state and move to other states according to their deterioration path. A semi-Markov model was used to replicate the different progressions of banknotes through the discrete states. Varying different parameters allows the model to be applied to different cash cycles which can have distinct characteristics. It can forecast the number of banknotes in each of the fitness states and allows an assessment of the overall quality of banknotes in circulation at a given time. The ability to vary parameters will allow “what if analyses” to be completed.
Dr Simon K Jones, Forecast Manager at De La Rue, stated that ‘it is essential that the quality of banknotes in circulation is monitored closely by central banks. A large volume of worn or damaged banknotes can make security features difficult to use and potentially counterfeit rates may increase. De La Rue equip Central Banks with traditional forecasting methods in their cash cycle software DLR AnalyticsTM. There is an opportunity to enhance these traditional methodologies to incorporate the quality of banknotes. This advanced mathematical approach enables the fitness of banknotes to be predicted and can provide an insight into the impact of “what if scenarios” such as considering adjusting inspection frequencies or modifying fitness standards. Extensions to the DLR Analytics application are underway and the inclusion of this model is on the roadmap.’
EACH YEAR STUDENTS on MSc programmes in analytical subjects at several UK universities spend their last few months undertaking a project, often for an organisation. These projects can make a significant impact. This issue features reports of projects recently carried out at two of our universities: London School of Economics and Southampton. If you are interested in availing yourself of such an opportunity, please contact the Operational Research Society at [email protected]