Customer Stories

The Lancaster Centre for Forecasting (LCF) works in partnership with leading organisations across a variety of sectors including retailing, manufacturing, services and the public sector. We provide expert knowledge to improve companies’ forecasting methods and processes, and provide insights on supply chain, customer behaviour and marketing activities. “Customer Stories” presents challenges faced by organisations we have worked with, how we tackled them and what were the achieved improvements. Projects can be set up as a Masters student project or Consulting project. For further references please contact us.

Industry sectors covered

Banking & Insurance Sector Pharmaceutical & Chemical Sector
Energy Sector Public Service & Health Sector
ICT and Technology Sector Retailing Sector
Manufacturing Sector  

Banking and Insurance Sector

In this highly competitive service-oriented industry, customer churn and cross selling are some of the key questions for managers. Data mining techniques allow businesses to detect relevant factors that drive customer behaviour and cross selling. Typically those organisations also have large call centres where time series methods or multivariate regression models can be used to estimate demand, enabling better planning of resources.

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Energy Sector

Energy consumption has multiple seasonal components and exogenous indicators such as temperature, wind direction - but also bank holidays and special days. Neural networks and advanced exponential smoothing models are able to provide accurate forecasts for such problems.

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ICT and Technology Sector

Fastpaced technology development cycles challenge the industry. Since infrastructure is expensive, being able to forecast the adoption of new technologies/services allows businesses to invest the right amount into infrastructure and innovation to fulfil the expected demand. Relevant forecasting techniques include, for example, diffusion or choice models.

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Manufacturing Sector

Manufacturing organisations have to deal with demand volatility. The increased volatility, often associated with the bullwhip effect can cause substantial costs in terms of inventory and bound capital, but also reduced service levels. Accurate forecasting is crucial to mitigate this uncertainty. Other challenges include predicting and managing customer complaints, for example in terms of adequate staffing levels. Another challenge for manufacturers is forecasting the demand for spare parts. The diversity of forecasting challenges in this sector requires a wide range of forecasting methods and tools that will lead to desirable improvements.

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Pharmacutical and Chemical Sector

The complex production pipeline requires businesses to forecast long-term demand in advance to optimise stock levels and investment. Change-detection can lead to significant cost savings identifying changes in buying behaviour, as well as the impact of marketing activities. Models include traditional forecasting models such as exponential smoothing or ARIMA but also statistical modelling to detect changes in sales behaviour.

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Public Health and Service Sector

Running hospitals and medical practices involves high costs and resource allocation is important, requiring accurate forecasts. The Centre has also worked on providing insights on the salary drift of medical personnel. These are often highly political decisions and require scenario based models. Other public sector areas involve traffic forecasting.

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Retailing

This sector typically deals with high volatility in demand due to events such as promotions or weather. Another challenge is to deal with the high numbers of items that need to be forecasted. Typical instruments involve automatic statistical forecasting, promotional modelling and hierarchical forecasting. Moreover, data mining techniques enable businesses to study buyer behaviour to improve shelving and promotional timing.

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