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Construction firms typically operate with small margins and robust competition. Any improvement in operations, such as in project forecasting, could help firms to edge past other firms, yet many construction organisations are hampered by disconnected processes and tools that lead to forecasting problems.

With the advent of specialised software, forecasting has become an incredibly powerful tool, said Andrew Tucker, product manager at software firm Viewpoint.

Five elements are necessary for accurate project forecasting:

  1.      Setting up an accurate and trackable project budget
  2.      Managing subcontract/material commitments & buy-outs
  3.      Accurate collection of field labor and productivity data
  4.      Forecasting flexibility for various project types
  5.      Trend and variation reporting

Setting up an accurate and trackable project budget requires three core elements.

“Simply put, that is knowing where you started, knowing where you’re headed, and knowing exactly where you are now,” Tucker said.

Accuracy in each of those elements is crucial, he noted, as “accurate contract valuation and project performance measurement therefore come from putting accuracy into each of those three elements.”

Various metrics will benefit from a commitment to accuracy.

“It’s important at project level you lock in your original contract values, your original budget, margin, margin percentage, and your original schedule, and then everything else can be tracked from there,” Tucker said.

The budget must be broken down into easily forecastable cost centres, sometimes called phase codes. Putting thought and effort into those breakdowns allows for easier and more accurate measurement of project performance.

The level of granularity is important, Tucker noted, so that the data is detailed enough to provide clarity in tracking forecasts or budget. In addition, appropriate granularity makes some information much more clear.

“You don’t want to be mixing forecast gains and losses in a summarised cost center format,” Tucker said. “It might not highlight any opps that are there.”

The second step is managing subcontract/material commitments and buy-outs. These items represent commitments coming from purchase orders, subcontracts, and other things that require committing large amounts of money up front. Using commitments provides a ready window into forecasting.

“Early entry of commitments gives you that visibility into expected costs in your forecasting, rather than waiting for the actual costs to come in,” Tucker said.

In addition, forecasting on a commitment basis can be simpler, in that committed cost plus forecast cost to complete equals the forecast final cost.

In addition to forecasting on a commitment basis, it’s important to maintain a tight approvals process to ensure not only that you’re committing costs at the correct values within the allocated budget, but also that your cost is committed to the right forecasting cost centres.

Appropriate software can aid this process, maintaining a process that’s efficient and highly configurable.

“For example, small commitments might only need one approver, but a large commitment might need three or more approvers, with potentially sequential notification workflow between approvers, and even better if that can be automated,” Tucker noted.

The commitment process should also cover all types of committed costs so that there’s never a committed cost showing up that hasn’t been approved.

“Every type of committed cost, we’re talking about subcontract commitments, variation commitments, purchase order commitments, and even non-order related invoice commitments,” Tucker added.

Commitments also enable closer tracking over time, allowing you to see whether your committed cost has changed and, if it has, determine why that is the case.

Commitment management can benefit from automation in a number of ways, Tucker said.

“For example, as your commitments come in, your forecast cost to complete should automatically reduce to preserve your forecast final cost,” he noted.

Automation could also be used to add easily-missed details. The effect of variations on your cost, for instance, can be quickly calculated and added – a task made easier by the right software.

The third element of forecasting involves the accurate collection of field labour and productivity data. Naturally, accuracy is important, Tucker said, but equally important is the timeliness of the data collection and the speed at which you get the data back to the office.

Using the right tool in the field is is essential for this process.

“Ideally you have a tool that can accurately capture data and then quickly and seamlessly, even automatically, load this data back into your cost management software,” Tucker noted.

This data collection process directly supports accurate forecasting. Quicker, more accurate data collection (captured directly from the field) allows for faster and smarter decision making.

Civil projects exemplify the power of this approach.

“Quantity done is the key to measuring earned budget. Earned budget can then be compared to cost of work in progress to calculate productivity factors, which in turn can be used to calculate extrapolated forecast final costs,” Tucker said.

Forecasting flexibility, element number four, is necessary because of the number of different project types. Civil and commercial construction, for example, require different forecasting methods, but automation aids accuracy in both and enables the flexibility in choosing to forecast on a cost basis or commitment basis.

According to Tucker, certain cost centres should be forecast on a cost basis, and others on a commitment basis.

“For example, a subcontract cost center, it makes more sense to forecast on a commitment basis, and a labour cost centre or a preliminary cost centre, it makes more sense to forecast on a cost basis,” he noted.

In addition, though flexibility in forecasting is important, it is equally important to maintain some level of consistency in approach across the business. This allows for a holistic look at where your company stands and where it is headed at a given point.

Trend and variation reporting, element number five, offers a powerful tool for forecasting, but only if the data is accurate. Capturing data in consistent periods allows you to build up accurate trend data.

Reporting can be almost fully automated with strong business intelligence (BI) tools.

“On a monthly basis those BI reports can be generated automatically,” Tucker said. “They can be dynamic graphical representation of all your projects, without having to build them every month. They just automatically come from that core data capture.”

Examples of trend reporting include extrapolated forecast final costs, contingency squeeze and the forecast impact on margin, margin variance, and many more. In addition, forecasting accuracy can be checked, so as forecasts are replaced by actuals, you can start to note trends in the accuracy of forecasting.

 
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