The Construction Industry’s Dilemma: Managing Contract Risks
Brian Perlberg Esq. and Joshua Levy, Esq.
Posted: April 16, 2021 | Legal
Our industry has long grappled with the best way to manage risks in construction contracts and other project documents. This battle persists because these contracts and documents carry serious risks that can easily torpedo a company. In response to this dynamic, our industry has developed two approaches to managing this process: underinvestment and overinvestment. However, each approach is flawed. Below, we describe new approaches that of fer a better way.
Overinvestment: Large construction companies have invested substantial resources into using attorneys, risk management professionals, or even building out internal departments to understand risks in project documents. While this represents a robust approach, such functions can be a pinch point for information flow. (It is hard to communicate contract risks gleaned from subject matter experts at the organizations’ higher levels down to the project team who needs to manage those risks!) Such functional support also means investment in overhead — which only continues to grow as the business grows — and is not the best use of such resources. As our industry becomes more complex in nature, these subject matter experts should be dealing with more complex and strategic issues, and not bogged down by boilerplate contract terms.
Underinvestment: On the other hand, much of our industry cannot afford to make such a substantial investment to better understand contract risks. So these smaller to mid-sized companies use overburdened or underqualified personnel to help them understand their risks. These are the companies that are signing contracts every day where a single bad term could be crippling, yet they may not even appreciate that the term “underinvestment” exists.1
This overinvestment vs. underinvestment dynamic leaves our industry in an impossible situation. How does one manage risks given our market conditions? Construction margins are decreasing (so overhead is not ideal), yet projects are becoming more complex in nature (meaning risks are increasing).
Unfair Terms Lead to Big Problems for the Industry
On top of this dilemma, the culture of the construction industry is one of leverage to “shove terms down the other party’s throat.” Contractors are constantly left anxiety ridden as they decide whether to qualify bids at risk of losing the job. Subcontractors are in the same boat: fearful that raising redlines with a general contractor will cause the GC to use someone else. This culture of fear is not healthy. Industry studies estimate inefficient use of contract terms on a project can increase that project’s costs in the range of 3 to 20 percent.
However, this culture is in part perpetuated by a fundamental lack of understanding of contract terms by much of our industry. For example, every time a contractor accepts a bad term, an owner is then able to leverage this acceptance upon that contractor — or another contractor — when negotiating a subsequent deal. This dynamic creates a vicious cycle that is in part perpetuated by unsuspecting contractors accepting unfair terms. Even the over-investors that understand risks are being pressured to accept bad contract terms to stay competitive with their under-investor peers.
While industry coalitions such as ConsensusDocs have formed and created templates to normalize good contract terms, it is incumbent upon our construction community to level up and become more alert to sound contracting practices. When our industry experiences a critical mass consisting of fair contract templates (ConsensusDocs) and a better industry understanding of what is fair and considered a best practice, the industry will see real progress against the above-mentioned dilemma. An industry can exist where contracts become more balanced, risks better mitigated, and (perhaps) profits will rise. This will lead to a better, safer, more collaborative industry for all.
Technology is Ready to Provide a Solution
The good news is that technology now exists which can allow companies to choose an alternative to the impossible choice of having to overinvest versus underinvest in such risk reviews. Solutions are being developed to use artificial intelligence and machine learning to help our industry understand construction contracts and other project documents. Companies and people are able to pull the AI lever (which is much more cost effective than relying upon humans) to gain critical insights into their construction documents which have either previously gone unappreciated (until something bad happened), or only realized upon engagement of professionals.
Well, what is artificial intelligence? What is machine learning? AI is a broad concept relating to computers or machines performing tasks that simulate human behavior, such as reviewing documents. Machine learning is a subset of that, allowing that same computer or machine to automatically learn from its prior review of data without having to be expressly updated or programmed for each case. This is possible because AI systems are able to “learn” from humans how to identify and extract relevant items the way a lawyer, risk manager, or savvy executive would. This doesn’t obviate the need for a human to contextualize or analyze what the AI found. However, the time saved in looking for needles in haystacks proves its worth, similar to how a doctor may use an MRI to better understand what is going on with a patient.
This technology is now being used with contract and insurance policy reviews. AI technology using Natural Language Processing can be trained to identify and tag phrases in contracts and insurance policies (among other document types), directing the reviewer to the relevant provisions and language. These systems are a great way to conduct a “first pass” through a document for speed (such as when qualifying a bid proposal going in), as well as a final pass for accuracy (such as to confirm that nothing important was missed or changed before being executed). These systems can also be used to automate contract checklist reviews to ensure that company standards and policies are being adhered to more efficiently, and even to communicate such standards to project level personnel so that they can better administer their projects. Finally, these systems can also be used to identify historically what types of risks a company has taken on and how those risks correlate to the company’s results, creating invaluable data from which to manage. In other words, AI is an extremely powerful tool to extract big data to help inform future decision making.
Can Construction Finally Adopt Tech to Solve This Problem?
With all of the above in mind, the challenge is that the construction industry is way behind the curve when it comes to adopting and embracing technological advancement. Simply put, other major industries are earlier adopters of tech trends. However (while still glacial compared to the overall constellation of industries), the pace of adoption and acceptance is beginning to accelerate as the construction industry becomes better educated, millennials (and even more tech-savvy generations) are entering management/leadership functions, and more practical applications of tech are becoming obvious and apparent.
As tech adoption becomes more commonplace, it is easy to see why AI for contract reviews is a hot topic in the construction industry: big buildings are built upon mountains of paper. Yet the people managing the day-today are builders who want to build buildings, and have little to no appetite for a bunch of contract terms.
Think about the administrative burden on mid- to small sized construction companies who are bidding a lot of work and need to qualify proposals, or the twenty-something project manager for a large company: to manage a typical construction operation means that one must administrate through large, intricate contracts, subcontracts, scopes, and specifications. On top of that, these documents are almost always intertwined with accompanying insurance policies. That is a lot of fine print! And those fortunate souls who can make sense of this web of risk are usually only comprised of expensive lawyers and/or sophisticated insurance brokers/risk managers. Meaning that in the vast majority of our hugeindustry, core operators have to seek out others’ help to manage terms which govern the projects that must be built. As one can imagine, managing all of this paperwork in realtime is no easy feat, and having technology to assist in that is a big help.
Additionally, the power of AI can be used to efficiently conduct historical reviews of past contracts to tease out big themes and answer big questions such as: “Which issues are truly market terms? Do my peers really regularly accept a term someone is urging me to accept? Is there a correlation between bad terms and bad project outcomes?” Simply put, the use of AI by our industry will eventually lead to a better understanding of what is market now, but also provide a better understanding of how those risk profiles play out later in regard to project results and claims. Use of this type of technology therefore has the power to create transparency to a commonsense market approach to managing contractual risks.
Our industry must continue to evolve as new cost effective risk management tools come online. This is imperative, given the increased complexity of our projects against diminishing profit margins. The barrier to becoming better and more risk-proactive is lower than it has ever been … because of technology. The above-described use cases for AI is the most recent example; and if reasonably adopted, our industry can look to a better day where the industry takes a more balanced approach to contract terms.
About the Authors: Brian Perlberg Esq. CM-Lean is ConsensusDocs Executive Director & Senior Counsel. Mr. Perlman is a nationally recognized construction law attorney who is lead counsel for a unique, industry-wide coalition of leading construction associations producing best practice standard construction contracts.
Joshua Levy, Esq. is the cofounder and curator of Construction Industry, and co-founder and strategic advisor to the recently launched AI platform, Document Crunch. He founded this platform to scratch his own itch: to more efficiently review and advise on voluminous contracts in the construction industry. In addition, Josh currently leads the legal advisory team and commercial contracting function for a $1.5B operation throughout North and South America, which focuses on large-scale engineering/procurement/construction (EPC) renewable energy projects such as solar, wind, and battery storage facilities; and also other complex production facilities in sectors such as power, chemicals, paper and water. Josh also previously led the legal department of a regional business unit of one of the largest commercial general contractors in the United States. In these roles, Josh has negotiated and reviewed billions of dollars’ worth of construction contracts across numerous industries, including renewables, energy, hospitality, healthcare, aviation, higher education, industrial, and multi-family. Prior to going in-house, Josh served as a construction practitioner for two large law firms in Florida, representing developers and contractors. Josh graduated with honors from the University of Florida with a Bachelor of Science in Construction Management, and earned his Juris Doctorate from the University of Miami, graduating magna cum laude.
1R. Zaghloul and F. Hartman, Construction Contracts: The Cost of Mistrust, Int. J. Proj. Manage., 21 (6), 419-424 (2003); Construction Industry Institute Contracts Task Force, “Contract Risk Allocation and cost Effectiveness Publication 5-3 (1988); see also, Mohan Kumaraswamy, Constructing Relationally Integrated Teams, J. Constr. Eng. and Manage. (Oct. 2005); See also Equitable Risk Allocation, Research Summary 210-1, Construction Industry
Institute Research Team on Contracting to Appropriately Allocate Risk, 2006 commenting, “Inappropriate allocation of risk results in at least a 3% contingency or risk premium in bids. These increased costs can be saved by observing the principles of realistic risk allocation.”