Keeping you up to date with topical business news and views.
Keeping you up to date with topical business news and views.
Whether you are in start-up mode, or your business is more mature and in a rapid growth phase, planning and forecasting for uncertain and dynamic conditions can be challenging. Here we look at some tips and tools to help you prepare your financial forecast.
Uncertainty is a basic and persistent aspect of decision making, strategy and planning. It’s a reflection of trying to make decisions using imperfect information that is vague or open to interpretation. Some information may be missing, or there may be risks that you are aware of but haven’t assessed. For example, when you know that you have a share of the market, but you don’t know the total market size to work out your market share. However, you probably have an idea of where your business sits in the market, and so could estimate a range.
There may also be factors with the potential to affect your business, but you don’t know that they exist. Thirty years ago, we were just getting used to mobile phones to make calls; few imagined the potential for apps, the Cloud, social media. While you can’t plan for these, you can include a contingency buffer to cover unexpected costs.
Uncertainty around future events can be greater as we try to forecast for a longer period. A twelve month earnings forecast may be predicted relatively reliably. Pushing that time frame out to two, three, even five years, poses greater issues. We face complex and uncertain situations every day:
Yet future outcomes can be estimated, with probabilities and predictions, and that’s how we can handle them in forecasting.
TYPES OF UNCERTAINTY
When estimating future events, understanding the level of environmental uncertainty can help us, and this can be analysed in terms of Miliken’s State, Effect and Response.
State Uncertainty refers to when you are unable to determine what could happen as a result of the business environment. It’s an inability to forecast industry or market events. For example, if you’re running a business that sells large machinery which is usually financed by banks. You deal with State Uncertainty when you really can’t be sure what the interest rates offered by banks will be. Instead, you can usually work out the range of options (6%, 7%, 8% interest rates) or probabilities (40% chance of 6%) and model the impact that they would have on your business.
Effect Uncertainty refers to when you can’t figure out how outside environmental events might affect your business, either now or in the future. It stems from a lack of skills, knowledge and resources that could assist you to understand or influence market reactions. Say you think the interest rate will be 7%, but you are not sure whether that will prevent purchasers from buying your equipment. Again, you can estimate the impact on your business by modelling a range of sales.
Once you know what effects a change in state could have for your business, you can then plan a response. Response Uncertainty refers to your inability to be sure of how the market will react to the actions that you take. For instance, if you arrange fixed interest rate finance at 7% for your customers, you can’t be sure that they will want to take up that offer.
Businesses typically respond to uncertainty in one of four ways:
BUDGET AND FORECAST APPROACHES
Once you have considered the type of uncertainty that you are facing, think about how you can improve your forecasting process. Start by choosing an approach that matches your environment. Taking last year’s results or budget, plus a percentage increase, is commonly used because it’s easy. Yet this approach does not take account of changes in the operating environment that are likely to be present for a young or fast growing business.
You’ll achieve greater agility using zero based budgeting, recognising that your situation may be different this year. Or you could use rolling forecasting, a continuous look forward on an 18-24 month basis and typically updated every month or every quarter. You’re making decisions throughout the year, always looking ahead and able to make tweaks to your budget as the situation changes.
One danger when presenting numbers in budgets or forecasts is that a level of certainty or accuracy can be assumed.
Sales Forecast: $343,000 or $343,212
Think of the different impact of these sales numbers. Round thousands can imply a higher level of estimation. Also, what’s the perspective of the person presenting the budget. Are they so convinced (and convincing) that the budget is achievable, that you start to treat the numbers as certain?
Check the sensitivity of the forecast to changes and, as discussed earlier, where there is uncertainty provide a range of outcomes, based on probabilities. Consider preparing best, base and worst budgets:
Assume the failure of new strategies such as product launches, export strategies, and capital expenditure payback. Modelling the outcomes may result in creative insights and identify possible issues otherwise overlooked.
Think about sources of data for your assumptions. You’ll likely be talking to your colleagues to garner assistance for sales, costs and expense forecast assumptions. Consider talking to your bank about interest rate and exchange rate assumptions. Some banks also offer benchmarking services that are useful for assessing how your business is performing compared to the market, and whether your goals are realistic.
Check the Statistics NZ website for forecast information on population, tourism numbers, consents and electronic card transactions. There is also a new ‘Business Performance Benchmarker’ tool which provides statistics on market size and ratios (using data from IRD).
To sum up, when preparing budgets and forecasts where you are faced with a great deal of uncertainty, think about the type of uncertainty you’re facing, what elements you can control and do research or change your approach to reduce the level of uncertainty. Use appropriate methods such as zero base budgeting or rolling forecasts and use ranges, scenarios and sensitivity analysis on key variables.
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