Having a reasonable view of what may happen in the short and medium-term, financial forecasts can help guide the business through seasonal ebbs and flow.
Financial forecasts are the best way to get an idea of the short term performance of your business. Coupled with your knowledge of your business, your industry, and what your pipeline is achieving, they can prove to be powerful tools for planning ahead.
It also forms the basis of budgets, sets the business on a sound trajectory, and sets the scene for what the majority see will be the future.
As financial forecasts are so important, you’d imagine a lot of work would go into making them as reliable and robust as practically possible. After all, getting forecasts wrong would be a disaster worth spending the money to avert.
So how do you create your monthly forecasts:
A manual approach (gut feel) using estimated of what work you will win in the coming months
Assessing the probability or likelihood of securing future sales is a sound approach and one used by 90% of businesses. It’s a time tested approach. Its flaw is that it relies on the judgement of what you believe may happen and will generally exclude a large number of softer factors that simply can’t fit into the brain all at once. Consider the impacts of:
- Your marketing campaigns
- competition’s pricing or marketing plans
- seasonal fluctuations
- Customers buying decisions
- interest rates
- suppliers costs
There are so many commercial tools on the market that assist with forecasting. The problem is the majority of them rely on data inputs which means you need to have the data available to feed into them.
They also run off a single linear forecasting model which is limited at best. There are a lot of different ways to forecast financials and the best ones tend to be non linear.
This is perhaps the worse form of forecasting ever. Setting a budget is a healthy thing to do. Using it for a forecast though is more like a wish list. Tell me you don’t fall into this category.
Use a predictive model
Now we are talking. If you are one of the handfuls of businesses using a predictive modelling approach to forecasting then congratulations, you are one step ahead of the pack.
Non-linear predictive models are dynamic mathematical tools that test predictions against reality overtime and then learn from their mistakes. This is AI in action, machine learning to be precise.
Consensus approach using multiple forecast techniques
You’re in the top 1% if you are using a consensus approach to forecasting. The Consensus approach takes the results of multiple predictive models and pits them against each other.
If one model predicts results that are wildly different from other models, then we can confidently discard that.
The consensus approach is like getting advice from 6 or 7 advisers. You ignore the wildly ambitious one and go with the flow.