Protect profit margin and reduce risk before bidding

An evolution in the entire risk process is yielding a profound benefit for contractors.

Traditionally, risk analysis was viewed as a reporting exercise, with exposure determined after an analysis was run and a report compiled.

By running a risk analysis using advanced tools, contractors can proactively determine if their bid will deliver a competitive advantage.

This is possible because of an ongoing evolution in the entire risk process, involving advanced tools that support the process and the contractor who’s actually doing the work.

Let’s dig into how we arrived at this point to illustrate how these changes impact the future of the risk process.

Traditional estimating/scheduling vs. Risk-adjusted forecasting

Cost and/or schedule forecasts rarely represent the most likely scenario; rather, they depict the best-case scenario.

That’s because inherently, they don’t take into account some of the bad things that may occur, whether it’s no quantity growth or less-than-optimum productivity rates, external impacts and so forth.

This all-too-common “single-lens view” of forecasting omits multiple scenarios and outcomes and needs to progress to what we call risk-adjusted forecasting. It’s moving the needle from saying, “The most optimistic scenario is X” to “Our most likely scenario is Y.” The difference between those two is really the contingency we should carry on the project.

Risk modelling 101

With risk, as with any system, there are inputs, there is an engine or analysis, and there are outputs.

That concept doesn’t differ from a contractor bid perspective. We still need to start with the underlying base model, which is our base cost and our underlying schedule, and strip out any contingency that may have been baked into the estimate.

That goes well beyond just removing the contingency line item. It’s also necessary to strip out any contingency embedded in individual cost accounts or cost elements themselves, because at the end of the day, this analysis will determine how much additional contingency is needed to add into that base.

This leads us to the two key ingredients in our risk model: uncertainty and discrete risk events.

Uncertainty represents, for example, the range of quantities, not considering bad things that potentially could happen (i.e., weather events or labour strikes). That all falls into the discrete risk bucket of ingredients.

Uncertainty is really more around the notion of, “Perhaps we’re not 100 per cent certain as to the quantities that we will be asked to deliver.”

Again, it’s very important to understand the two different types of variables that go into the risk model. The analysis part isn’t a sort of magic black box — it’s brute force mathematics that’s a repeated simulation of the execution of the project.

Advanced software can take into account all of those differing or potentially differing combinations of outcomes based on those risks and variables of uncertainty and quantity growth by running thousands of iterations to account for those different scenarios.

And then it comes back with a range of outcomes based on each of those iterations, which then leads us to outputs.

Risk reporting

There are two fundamental risk reports a contractor should absolutely use:

What is my exposure?

This represents the range of outcomes from all of those iterations in the simulation. What is my best-and worst-case scenario?

From a contractor bidding perspective, you don’t want to go in with the most aggressive best-case scenario, not hit it and lose money.

Conversely, the worst-case scenario is a sort of “black swan” scenario. Yes, you’re going to cover yourself by putting it at that price, but the chance of you winning the bid at a very pessimistic price is probably very low.

Use this report as a yard stick to measure where you should bid, or at what level of confidence you should bid.

Why so? 

This partner report is the why — why are my risk exposure and contingency what they are? Where are those risk events hitting me? On what areas of my project do I need to concentrate my mitigation efforts?

This tells you which risk events, quantity growths and so forth are most likely to hurt you, assuming you win the bid and get into execution.

Owner vs. Contractor view on risk

With owner organisations, the resulting risk analysis and outputs are largely used as a validation point at the pre-final investment decision.

This is where the organisation is seeking funding or there is a concept select phase where it’s trying to determine the most appropriate scenario to build the project.

Schedule risk is often more impactful than cost risk, largely because owners are looking at risk around things like first production — the turning point for revenue.

Leading drivers in this area for owners include:

  • High degree of parallel scope
  • Competing work with subcontractors (e.g., fabrication)
  • Limited definition and visibility into delivery timeframes for long lead procurements
  • Local content requirements

From a contractor’s perspective, they’re bidding on a specific project, and it’s more of an evaluation to determine the right competitive bid price that also minimises exposure of margin erosion.

Leading drivers include:

  • Design and quantity growth (each design iteration results in higher quantities)
  • Productivity degradation (will we be able to complete work at historical rates?)
  • Contract covered risks vs. uncovered risks

Base cost vs. Contingency margin

Bid breakdowns can be highly complicated and could have thousands of line items. Those bid packages can be categorised into three chunks: the base price, the contingency needed to add to that base to cover the unknown and risk, and the margin on top of that.

One of the most powerful benefits of conducting a risk analysis is the ability to generate a complete range of outcomes spanning best- and worst-case scenarios, rather than simply saying, “Hey, let’s throw 20 per cent on this project for contingency.”

How to build a risk model

There are two key ingredients in a risk analysis: uncertainties and risk events. Uncertainties traditionally have been modelled using distributions, which can be in the form of what we call three-point estimates, where we try to define a minimum or optimistic, and maximum or pessimistic, value.

While it’s mathematically sound, it’s actually quite difficult to extract those ranges from an engineer, foreman, superintendent and other discipline leads.

Wouldn’t it be better to go out and canvas the expert opinion of multiple contributors? For example, check directly with foremen, planners and design leads on the feasibility of a particular activity that the planner has put forward in the schedule.

Advanced risk analysis tools provide a scorecard interface that integrates those expert opinions into the model. This ability to minimise the exposure to the complexity of risk analysis, while still getting the benefit, represents a massive leap forward.

Let Artificial Intelligence guide you through the process

Construction and design experts are invaluable human assets with years of project knowledge. Unfortunately, that expertise has been hard to retain, with experts migrating between organisations or potentially retiring out of the industry.

This is changing with the advent of artificial intelligence (AI), which can capture and store that human expertise.

The computer can actually make informed suggestions and critiques using its vault of historical data (e.g., identifying new project risks based on risks from previous projects).

AI planning tools are also growing more proficient at not only validating plans already created by the human planner, but also making suggestions as to what activities, durations and even sequence of work should be used to develop a project plan.

Risk-adjusted forecasting reduces bid risk

The whole science of risk analysis is driving towards risk-adjusted forecasting — using AI to capture historical performance and lessons learned, accounting for expert human opinion and potential risks, and a new understanding of exposure that better protects profit margin. This all leads to a new level of bid risk reduction.

For more information about InEight’s planning, scheduling and risk solutions, visit InEight.com.

Dan Patterson is InEight chief design officer and Paul Self is InEight EVP project planning and scheduling.

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