John Stretch explains why proper forecasting could have saved Tongaat from the challenges it now faces.
“The pressures felt by the sugar industry in South Africa, the deteriorating situation in Zimbabwe and Mozambique, and the decline in developer confidence in KwaZulu-Natal are not entirely the fault of Tongaat’s management and the board, and are somewhat excusable. What is not excusable however, is … the unrealistically optimistic forecasts and prospects eagerly offered by the company to its various stakeholders,” said Tongaat whistleblower Dave Woollam in his account of the events leading up to Tongaat’s share price decline
Like Kodak, Tongaat didn’t (or refused to) see it coming. And when they finally did, they reacted too late. The full story behind Tongaat’s accounting choices is still emerging. But what has emerged has underscored the importance of forecasting.
Forecasting is Finance’s responsibility
Developing predictive models, forecasts and scenarios are one of the finance department’s most important activities. The CFO is the custodian of forecasts and is responsible for harnessing an organisation’s power of anticipation.
Data gathered throughout the business should be used to develop and communicate a most likely business scenario for the company over the next 18 months, and the degree of certainty that can be attached to this scenario, at least once a quarter.
Business forecasting is an acquired skill, but with practice, accountants can get better at producing useful forecasts and projections to support decisions, based on reasonable assumptions and specific conditions. Forecasting is a science and its accuracy improves as we develop a greater understanding of our companies and our industries, supported by experience, repeated analysis, learning, judgement, supporting data and good systems.
As forecasting expertise improves, actual events should begin to turn out closer to expectations and within a narrower range of variability.
Give me science, not art
Scientists today have excellent tracking systems in place, to monitor the flight paths of meteorite threats after one struck Mexico’s Yucatán Peninsula and wiped out the earth’s dinosaur population.
By forecasting the flight path, plans can be made for deflecting objects on collision courses with the earth. This is an example of how data can be collected, processed, analysed and used to build predictive models, and thus reduce risk.
Unpredictable and unknown risks in a business can be converted into uncertainty by collecting, analysing and interpreting large amounts of data. When the data is analysed to identify patterns and trends, uncertainty can be converted into known risk.
The CFO needs to ensure that the right technology and qualified people are in place. People who are able to see the big picture, analyse and interpret data, build predictive models, harness the power of information technology, and create detailed cost and revenue databases that unlock patterns and trends in business behaviour and build sophisticated and responsive forecasting models.
Known and unknowns
American politician Donald Rumsfeld was once asked whether the government of Iraq had weapons of mass destruction which it could supply to terrorist groups, to which he responded:
“These are known unknowns. That is to say, these are things that we know we don’t know. But there are also unknown unknowns. There are things we don’t know we don’t know.”
The “unknown unknowns” remind us that there are limits to our learning from observations and experience. There are gaps in human knowledge and the absence of evidence is not evidence of absence.
“Known knowns” are forecast numbers that can be predicted with relative accuracies, such as salaries and office costs.
“Known unknowns” are items we know about but outcomes are difficult to forecast, such as litigation or loss of a major customer.
The “unknown known” occurs when people refuse to acknowledge threats revealed in a forecast, which they subconsciously know to be true.
Sometimes the real forecast risk lies in denial of these “unknown knowns” ? the real truths that people cannot accept. Large, long-lived, and successful organisations are more likely to deny the dangers revealed by forecasting because years of success tend to entrench conventional wisdom.
Prior to the invention of the digital camera, and for some years thereafter, Kodak didn’t foresee the risks to their traditional business and eventually filed for bankruptcy in 2010. Is this what happened at Tongaat?
If risk isn’t understood or debated, and if data and analytics are not a key element in decision-making, organisations can fail. CFOs need to create a culture of healthy disagreement and fact-based analysis to identify negative trends and their implications.
Unchanged business models work until they are disrupted, sometimes with disastrous outcomes.
Intel founder Andy Grove who wrote the book ‘Only the paranoid survives’ said when competitive change occurs in an industry, a company must adapt to new ways, or decline and ultimately fail.
“Success breeds complacency. Complacency breeds failure. Only the paranoid survives.”
The case for rolling forecasts and scenarios
The finance function has a mission to improve the organisation’s ability to anticipate and forecast.
Many world-class companies view forecasting as a core, organisation-wide competence, but they clearly need a better planning mode than the annual budget.
The need for agility and quick response has motivated many organisations to convert from fixed annual budgets to dynamic rolling forecasts which are regular updates based on the best information currently available.
Companies now use rolling forecasts and relative, incremental targets, to measure performance and understand scenario planning.
Transforming a traditional finance function involved in recording transactions, fixed annual budgeting and tax returns, into a team that is part of running the business, is not a simple matter. It’s essential to recruit and develop the right high-calibre people.
But without these people and skills, like Tongaat, your business could remain in the dark and lack the insight to deal with the surprises that the future operating conditions may deliver.
