getting to grips with forecasting

02-08-2013

By Manj Kalar, Technical Manager – Central Government and Financial Management

To manage the significant decrease in public sector finances over the last few years organisations have focused on cuts to back office functions to protect the front line. However as financial pressures continue, new and more innovative solutions are going to be required to avoid cuts to front line services.

To understand how to balance ever decreasing budgets, a good assessment is required of future income and the demand for the services. This is where forecasting will help.

All across the public sector there has been relentless focus on reducing costs to manage the supply side – i.e. the organisation’s ability to provide the level of public service required. However with warnings of the effect of further cuts impacting on an organisation’s ability to continue to provide the current level of public service, those charged with leadership need to forecast not only on the supply side, but the likely demand for the services.

Managing demand is unfamiliar territory to many, and this change in perspective goes to the heart of the relationship of the state with the individual – from automatically providing public service to the individual at the point of need, to assessing what services can be provided – and infers inherent uncertainty.

The difficulty finance professionals have is precisely the inherent uncertainty in forecasts where they strive for accuracy. Done well (by choosing the correct forecasting method for the specific situation) risks can be managed.

Any forecast inevitably contains a degree of uncertainty – because it is a plan for the future and certain assumptions are made – so it is important to quantify and understand how much uncertainty there is within a forecast.

The Department for Work and Pensions were recognised at CIPFA’s Annual Conference for using the ‘Monte Carlo’ method. This method goes beyond standard forecasting by taking a range of possible values, instead of a single guess, to create a more realistic picture of what might happen in the future. The key feature of a Monte Carlo simulation is that it can tell you – based on how you create the ranges of estimates – how likely the resulting outcomes are.

This is only one of many approaches to forecasting. So how do we know which method is right?

Professor Malcolm Prowle (of Business Performance at Nottingham Business School) and former CIPFA president Roger Latham are writing, with the support of CIPFA’s in-house expertise, A guide to forecasting methods in public services.

The guide, on sale this autumn, will provide an overview of the theory and framework of forecasting, and of the different types of qualitative and quantitative techniques. The publication examines the actual and possible uses of each technique in the public sector, and considers their pros, cons and suitability.

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