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|Forecast Solutions Planning: Testimonials and Case Studies|
Testimonials and case studies
Training for the operations team at Aspall cider
Aspall wanted a one day introductory course on demand planning and stock policy for people across a wide mix of disciplines in the operations team:
"I thought the training workshop gave everyone a good insight into demand planning, different methods and factors to consider, whilst considering stock cover. Very beneficial,particularly as we roll out ERP and MRP in the months to come"
Damian Mills, Head of Operations, Aspall Cyder Limited
On-site workshop for Nobia
Nobia is the leading European kitchen group with many famous brands including Magnet, Hygena, Gower and Poggenpohl. In-depth training for the demand planning team was provided:
David Bruce, Demand Planning Specialist, Nobia
Forecasting in Excel at Denhay Farms
Denhay Farms supplies premium bacon and cheese products to major grocery multiples. Forecast Solutions provided general forecasting training, then helped Denhay develop a forecasting process in Excel. Weekly forecasting was needed and it was necessary to deal with the volatility shown in weekly seasonal indices. A method was needed to take account of promotions in the sales history and to build future promotions into the forecast. The outcome was a simple but effective sales forecasting system.
"The new system is going really well. Our MD is really pleased with it and it really was worth doing, so thank you so much. In terms of the seasonality and putting the promotions in, it works perfectly. Many thanks again for your help with this, it really has revolutionised our forecasting system!"
Ellen Streatfeild, Denhay Farms Ltd
Ellen Streatfeild, Denhay Farms Ltd
Causal Analysis including Price Sensitivity at Calor Gas
Forecast Solutions has carried out a number of causal analyses for this leading supplier of LPG fuel. Statistical analysis was carried out in order to investigate the effect on sales of weather variations and a number of economic indices. In another project the effect of price changes on a number of customer service factors was examined. Linear and non-linear regression analysis was used, with the use of time lag effects where appropriate. The results were implemented as a forecasting model in Excel.
"As well as being very skilful in analysing a wide range of data Doug responded brilliantly to our requests regarding presentation of results and the functioning of the Excel system ... we are delighted with the results."
Mark Roberts, Calor Gas Ltd
Demand Planning Training for Lucite International
Lucite International is a major manufacturer of polymers and resins. Their supply chain manager attended the Forecast Solutions two day demand planning and sales forecasting workshop.
"Many thanks for the advice and suggestions … and many thanks for last week's workshop - it was exactly what I was hoping it would be. I'd like forecasting to be something that we pursue as a priority, so I may well be back in touch for your help"
Mark Devenport, Supply Chain Manager, Lucite International UK Ltd
Sales Forecasting and Stock Allocation at News International
Forecast Solutions was asked to carry out an end to end review of forecasting and stock allocation methods for News International's UK newspaper titles. This involved time series forecasting of daily sales of newspapers and daily stock allocation to retailers using SAP APO. After the review a number of improvements were immediately implemented and others put on extended test.
"... very happy with the work .... would use your services again"
Nigel Lomas, News International Supply Chain Director
Tool and equipment hire - Construction industry
This major player in tool and equipment hire experiences major shifts in business related to the fortunes of the construction industry. Forecast Solutions carried out causal modelling to create forecasting models for output in each main sector of the construction industry. Further analysis was then conducted in order to quantify the relationship of company sales to construction output and to economic indices. The results of both the industry modelling and company specific modelling were implemented in a forecasting system in Excel.
Forecast Accuracy Analysis - FMCG distribution
A forecasting database was constructed from historical demand and forecast data for this distributor of FMCG products. Forecasting simulations were carried out so that a detailed comparison could be made for statistical time series forecasting versus current methods. The analysis identified the forecasting models that were most effective and helped define the improved sales forecasting methods, procedures and forecasting software that would be needed in the future.
Weather Sensitivity Analysis - Horticultural products
Historical weather data was sourced and analysed in order to investigate the effect of weather variation on product group sales at this manufacturer of horticultural products. Regression analysis was carried out using population weighted data on temperature, sunshine hours and rainfall in order to create weather sensitivity models. The relationships found were then built into the forecasting process such that the sales history was adjusted for weather effects before being submitted to the time series forecasting system.
Effect of Sales Calling Activity - Health Care
Internal and industry sales data was used together with information on GP sales call activity to carry out a causal analysis for this major health care company. As well as average sales calling frequency, the analysis examined the effect of gaps in calling of various durations and the effect of group meetings and roadshows. Important pointers were obtained to help with sales resource planning and the focussing of sales calling activities.
Sales Forecasting Process Improvement - Beverages
This FMCG manufacturer started from the position where each sales person created a SKU x customer forecast and these were aggregated across the business to form the overall SKU forecast. Analysis suggested that greater use could be made of statistical forecasting methods, so in a first phase of improvement a statistical forecast was introduced, for review and modification by each sales person. Forecast accuracy showed a significant improvement. In a second phase an additional process was introduced involving a top-down forecast at total SKU level and a reconciliation meeting. Major improvements in forecast accuracy were achieved.