Critically Evaluate the Practical Use of Forecasting in Organisation
Forecasting forms an integral process within an organisation where data from several sources are processed and integrated to manipulate projections for different departments. Finance develops a long term forecast to evaluate the investment needs and capital; Marketing develops a mid-term forecast projecting sales; Operations produces a forecast to make decisions on short term scheduling, inventory management and long term capacity planning and Human Resources uses the forecast to evaluate personnel needs. Though each department could use a different forecasting model depending on the time horizon and demand behaviours, they are mostly interlinked and work hand in hand with the supply chain management system. This essay critically evaluates different forecasting methods and practices within Cancer Research UK, a charity dedicated to beating cancer through research.
Selection of the models within an organisation depends primarily on the nature of the parameter that needs to be forecasted – the precision and reliability, planning horizon, time and budget constraints and the availability of historical data. Financial, Marketing and Operational Forecasts tend to follow a quantitative model within the charity since most of the information is available within the business systems like historical sponsorship return or the number of supporters signing up for a fundraising event. Time-Series model can be implemented where data patterns from the recent past are likely to continue into the future with minimal anomaly. For instance, if there is no significant change in the number of fundraising events from the past two years, a similar stable pattern of sponsorship return can be expected to continue for the forthcoming year. Marketing and short-term operational forecasts could be based on cause-and-effect model, where there is likely to be a driver of activity that determines the outcome. For instance, the number of incoming calls received is the effect of the number of
Selection of the models within an organisation depends primarily on the nature of the parameter that needs to be forecasted – the precision and reliability, planning horizon, time and budget constraints and the availability of historical data. Financial, Marketing and Operational Forecasts tend to follow a quantitative model within the charity since most of the information is available within the business systems like historical sponsorship return or the number of supporters signing up for a fundraising event. Time-Series model can be implemented where data patterns from the recent past are likely to continue into the future with minimal anomaly. For instance, if there is no significant change in the number of fundraising events from the past two years, a similar stable pattern of sponsorship return can be expected to continue for the forthcoming year. Marketing and short-term operational forecasts could be based on cause-and-effect model, where there is likely to be a driver of activity that determines the outcome. For instance, the number of incoming calls received is the effect of the number of