Instead of using historical sales data, CFOs making financial transformations are shifting to driver-based forecasting. In the Australian construction industry alone, market conditions have moved so quickly in the last 24 months, that history can no longer be trusted to tell the future.
In the Australian construction industry alone, market conditions have moved so quickly in the last 24 months, that history can no longer be trusted to tell the future.
Forecasting P+L and balance sheets based on actuals and historical data is proving less reliable. The historical data can’t capture the market dynamics like real-time data can and forecasts based on historical data don’t give good indicators for the decision-making processes. Driver-based forecasting models are going to replace the models based on historical trends for budgeting and forecasting. Anthony Coundouris, Head of Client Relations are Octane says:
“Historical data can’t be a good determinant for the forecasting because the pace of change from one increment to the next is so great, that by the time the data is recorded, the opportunity or the threat is gone. With driver-based forecasting, you can build, and export different forecasts based on what-if scenarios.”
Anthony says:
“There is a huge opportunity for these guys to pick up projects from failing construction companies. However, the question remains: which ones are good and which ones are duds?”
Driver-based forecasting uses the key levers or drivers in your business to help you evaluate the impact of internal or external changes. Let’s take an example of acquisitions of construction projects. The predictive models can break down costs for each job and determine the profitability to help you discern which projects to acquire.
Billables are another important driver. Billing data on market rates help you forecast your payables and receivables. Billing analytics can help establish efficient accounting that is free from duplicate invoices, disputes, and gaps in price margins. A very good example would be equipment costs. It doesn’t matter if you are buying or renting the equipment, the forecasts based on the traditional approach miss by as much as 40%. Leveraging forecasts from real-time data can easily mitigate such over or underestimation.
Amendra warns:
“Companies need to have the tools and data at their fingertips to allow themselves to be able to see the insights by performing what-if scenarios on drivers to optimise their cost base and their funding arrangements with their banks and financial institutions.”
The sources of data will be varied. Ranging from the financial data from the suppliers, contractors, and other participants in your network to the data that your ERP platform collects from the operations and forecasts inside your own organisation.
On top of that, non-financial data like weather patterns, market data that captures the shift in costs of materials, interest rates, inflation, labour force, and Government policy along with safety data, waste data, and workflow data that directly or indirectly contribute to the financial decisions and forecasting will increase the total volume of data that your organization needs to capture.
Some construction companies are still trying to rely on manual methods like spreadsheets. But Excel has limitations. First, it has a hard stop at a million records. We can’t expect Excel to deal with such varied sources of data in real-time with millions of records when it can’t even deal with the company’s own full history of actuals.
Secondly, it’s impossible to collaborate and maintain a single truth across the whole organisation using spreadsheets. Even if you try to maintain huge volumes of real-time data in Excel, it easily breaks when you try to link the logic.
Anthony says:
“CFOs tell the same story of how they came across the forecasts from inefficient spreadsheets that took too long to put together. They say if only they could have known about it 30 days ago, they could have taken evasive actions.”
So there has to be a way to unify data and maintain a single source of truth for analysis eliminating the need to pull it from the disconnected databases and spreadsheets. Such a platform will enable your company to absorb internal and external data increasing the speed of reporting while reducing errors and inefficiencies involved in the manual processes.
Anthony remains optimistic:
“We don’t want you to be afraid of the huge amount of data. Embrace all the data that comes from your internal departments and from external sources. But don’t be restricted by Excel because it simply lacks the agility and dexterity to crunch the big data that’s going to be in your hands soon. TM1 can bring millions and millions of records from your historical and real-time data sources like a snack in a matter of milliseconds.”
Accurate forecasts and reports from IBM TM1 Planning Analytics add agility, speed, and accuracy to thrive during and after disruptions in the industry. Forecasts based on real-time data can mitigate your risk by detecting triggers and optimizing the costs to improve your profitability while you develop your rate models and enter negotiations for competitive proposals.
Amendra concludes:
“In fact, most construction companies can achieve driver-based forecasting in eight weeks and for less than A$80,000. I’m surprised not more of them are shifting.”