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Using analytics to develop deeper insight into project performance

Most projects don’t start off bad. They begin with the best of intentions, but lack the nurturing, caring and planning necessary to be successful. There are also those projects that take a dark turn, but their trajectory provides a false sense of security to management.

Fig.1

They exhibit signs of being a best-in-class project—one that will become the cover page of the sales brochure. However, below the surface, there are signs and indications of the truth. A client starts to pay just a little bit slower. A key trade partner goes bankrupt. The supply chain sees a small interruption. Before long, the poster project quickly becomes the pariah.

 

 

Firms are spending a great deal of energy attempting to understand the short- and long-term ramifications of the post-pandemic world. Throughout the world, there are projects that were irreparably harmed due to stops and restarts, while others barely saw a hiccup of a delay.

For many projects, the work in progress (WIP) report may have seen little disruption, allowing leaders to take a deep sigh of relief. Is this a tad premature? Are some of these projects heading into the bad zone? In what seemed like an eternity ago, we had sports. Take a college football game pitting two rivals—the Southern Reptiles versus the Northern Polar Wolves—against each other. In this game, the Southern Reptiles are favored by two touchdowns, or 14 points.

Fig.2

Put another way, the Reptiles are “spotting” the Polar Wolves 14 at the start of the game or handicapping their odds. In the end, if the Reptiles win, which is expected, but fail to achieve a two-touchdown advantage, then fans and pollsters will see it as a failure. It’s an uncanny example of winning but failing at the same time.

Similarly, consider a contractor that has a project they bring in at 20% gross margin. On the surface, this sounds like a win. However, after you factor in that the project was estimated at 45% and the overhead of the firm is 21%, you realize that this project was an unmitigated disaster.

 

Now consider projects in the new environment. What if projects in this new post-COVID-19 world had similar handicapping practices to provide a different set of optics? Consider the list of projects in Figure 1.

Fig.3

Figure 1 illustrates the firm’s WIP for its complete portfolio. In addition to showing the variance from bid day, additional comparisons are shown pre-pandemic and the margin as of today.

The contract values are shown to help provide context on the margin contribution. From this perspective, the forecast for the firm looks relatively strong. It appears the team will win, but as we know from sports, this is also the reason we play the game.

One of the first areas that should be analyzed is the collection cycle. Figure 2 is an illustration of the same project list, but with a different characteristic—the handicapping factor.

 

For each project, the collection rate was show pre- and post-COVID-19. The resulting “Payment Risk Handicap” is shown on the far right side. The aim of this factor is to normalize the data in such a way provides an accurate comparison. For instance, the factors are shown in Figure 3.

It is important to note that all of these handicapping factors are deeply subjective. While there are most likely industry benchmarks, the idea is to use the internal firm comparatives.

For example, industry collections hover around 45 days for above average performance. That being said, the contractor in this example operates in multiple sectors, so it is important to provide a factor that can translate to all project types. 

Fig.4

In Figure 4, now look at Multifamily B. This project actually showed some modicum of margin enhancement (from 7.00% to 7.15%) but it is also showing a deterioration in collections.

 

On the surface, this one indication does not demonstrate potential failure, but is it a portent of things to come. In a similar fashion, the same process could be done for other aspects of the project.

Fig.5

For instance, the aim is to examine areas that might have been adversely affected by the pandemic or any other economic deviation. In Figure 4, the supply chain and the critical path are investigated.

Hospital B project shows the greatest impact related to material procurement. Interestingly, this project was performing at a margin of 11%, but it also shows the greatest potential risk through schedule overages. The handicapping factor was calculated based on the overage shown in Figure 5.

Similarly, a firm can measure the potential General Condition Burn Rate, which is another extension of the schedule impacts, as shown in Figure 6.

Once again, we see Multifamily B rear its ugly head. While it would be intuitive to assume that any projection or forecast would account for general condition overages, there are probably many instances where managers fail to correlate the critical path and monthly cost report effectively.

Fig.6

After additional factors for trade contractor performance and internal process compliance are also calculated, Figure 7 provides a summary of each handicapping factor, as well as a total.

It comes as no surprise that Multifamily B shows the greatest potential for becoming bad. So, was the intent to create a tool that serves as a self-fulfilling prophecy? The aim of any tool—whether it be a standard WIP report or a handicapped version—is to drive action.

Fig.7

With so many warning signs, senior management not only has the optics to defuse a potential disaster but also to implement steps to protect the firm, including the following:

  • Owner meetings—Discuss payment terms and examine customer liquidity.
  • Schedule—Develop alternate work schedules or alternate products that may be more readily available.
  • Subcontractor performance—Conduct a series of deep trade partner coordination meetings to discuss performance, risk mitigation, etc.

Harkening back to the football example, if the Southern Reptiles were down by two touchdowns at the end of the football game, there would be great disappointment from the fans, coaches and team. However, the scoreboard actively provides feedback throughout the game and team leaders use that data to develop course corrections.

If they are down by two touchdowns in the first quarter and they have zero yards of rushing, the coaches can then enact a mitigation plan. Leadership teams today cannot be lulled to sleep by a satisfactory scoreboard. Doing so will allow complacency to set in and the good projects to quickly become the bad ones.