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Strategic CFO guide to service sector forecasting

11th Sep 2019
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Forecasting in the services industry is part art, part science, part discipline. Unlike companies that derive their revenues from products alone, service sector businesses cannot limit future projections to existing market share, inventory management and general consumption levels.

Instead, service sector businesses are caught in the ebb and flow of a glut of variables meaning that forecasting in this space relies on a canny combination of maths, intuition and experience. It presents a range of challenges when predicting demand levels that simply can’t be met by stockpiling ‘services’ to meet the needs of busier periods.

It’s a fine line for CFOs to walk. You want to set a realistic view of where the business might be, but you also need to set aspirations - and expectations - for your teams to hit and be guided by.

Then there’s the question of ‘regular irregular’ work such as foreseeable but infrequent events that can create surges in demand. Take the example of the air conditioning/heating sector, which sees an influx in requests in the Autumn as customers fire up their heating for the winter. Our client, Adcock, sees a yearly spike in demand as soon as the temperature drops – forecasting not only needs to anticipate the increased demand for stock but also the engineers required to carry out the installations and repairs.  

While sector experience and knowledge does play a part, we see several strategic tactics that forward thinking CFOs in the services sector should have to hand to help with forecasting:

Probabilistic forecasting

Probabilistic forecasting assumes there isn’t a single future, rather multiple different futures – making it a useful tool for the services industry where the numerous variables at play can create a range of different outcomes.

The magic of probabilistic forecasting is that it doesn’t assume a fixed outcome with data equally distributed around the mean. Using this more dynamic model, CFOs can list probabilities for all future demand, with the output accounting for both lead time and demand forecast probabilities.  

This can make a big impact. Take what happens within the engineering sector, with businesses like our client Alimak Hek. For them having complete visibility of stock levels for spare parts to repair breakages quickly is key to their business model. It can be the difference between buying in the correct quantity based on the desired service level and the probability of future demand, versus (to coin a well-trodden Brexit phrase) ‘stockpiling’ for safety measures – incurring expensive storage and maintenance costs.

Forecasting deferred income

Deferred income is another important aspect of the service sector and it can be a challenge to forecast. The difficulty arises as cash received for an item in advance is not recognised until the goods or services have been sent or provided to the purchaser. Until that point, the cash received will be recorded as a liability on the balance sheet, which can make it tricky for denoting anticipated cashflow.

This might mean a maintenance contract whereby a customer pays an annual contract which the provider may only be able to account for when calls are made i.e. buying a ‘pot’ of maintenance time and only being able to account for the hours as and when they are used. As above, historical data can be helpful as a guide for what might happen in the future – using point of sale tracking can give businesses an idea of when they might need staff and stock available for these flashpoints.

Forecasting for attrition

It can be an unenviable task, but an important role of forecasting is learning to anticipate customer drop-offs. In the service sector, it’s all about keeping in-house experts and engineers busy, which requires ensuring that companies have the right levels of capacity but being mindful of growth and shrinkage. Previous rates of client loss can, once again, be a good guide for the future, but this too can be refined. The rate of customer loss can, for example, be broken down into revenue brackets – so you might find you have an average attrition rate of 5% for the lowest revenue bracket, 3% for mid-range clients and 1% of your highest revenue customers. This can help to give you a good idea of revenue churn, which is a different, but equally important metric to customer drop-offs.

The human element

Of course, for all of the clever forecasting models you can create, human intuition and sectoral insight still play a huge part in putting together future budgets – especially in the absence of definitive evidence. This human element is important as it can allow CFOs to connect the dots in the absence of statistical proof but can be flawed if it means we favour an established narrative in the face of clashing evidence.

The truly strategic service sector CFO will balance this blend of intimate sector knowledge with forecasting models that offer a range of probabilities. It’s this blend of instinct and strategy that can turn finger in the air guesswork into valuable insights that can help you dictate the growth of your business.  

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