Written By: Jim Plasynski, Chief Revenue Officer, KorTerra

I recently spoke at the Global Excavation Safety Conference on operationalizing risk scoring to reduce damages. Over the past few years, the damage prevention industry has faced new challenges driven by macro market changes that are increasing both the volume of work and the cost of labor and materials.

In November 2021, the bipartisan Infrastructure Investment and Jobs Act authorized a $1.1 trillion budget to advance and restore critical U.S. infrastructure over five years. That bill represented more than a $400 billion increase over any previous funding package. The funds target fiber buildout, roadway and bridge improvements, water and wastewater infrastructure, and more. The construction work attached to these projects is having a direct impact on the 811 system and damage prevention operations at every level. The 811 system was already stretched by pre-infrastructure-bill fiber buildouts, and the next wave of federally funded projects, likely hitting communities over the next three years, will add even more pressure.

Increased ticket volume isn't the only challenge. Labor shortages, supply chain constraints, higher fuel costs, and inflation have driven up operating costs across the damage prevention community. Regulators are also increasing scrutiny of asset owners and their ability to demonstrate compliance with legal obligations. With all of these pressures converging, damage prevention leaders are forced to evaluate whether their current processes can actually reduce damages in an environment where risk is growing from multiple directions.

How Has Technology Advanced Risk Scoring in Damage Prevention?

For the past three decades, technology adoption in damage prevention has accelerated alongside advances in mobile platforms. Many organizations have invested in ticket management systems that create efficiencies for field teams around the workflows attached to 811 tickets. In recent years, ticket management providers have begun applying machine learning and artificial intelligence to assess the risk profile of individual tickets, giving damage prevention teams data-driven insight into where damages are most likely to occur.

Why Aren't All 811 Tickets Equal in Damage Risk?

What determines the risk level of an 811 locate ticket? Not all tickets carry the same likelihood of a damage event. A residential landscaping ticket and a multi-mile fiber installation crossing dozens of underground facilities present fundamentally different risk profiles.

Established ticket management companies like KorTerra have been gathering ticket data across more than 1,100 customers and tens of millions of tickets per year for decades. That data has produced a detailed understanding of the variables that elevate risk on a given ticket: dig site size, facility overlap, excavator history, ticket type, geographic patterns, and more. These datasets are now being trained against machine learning models to provide organizations with risk scores on their tickets that reflect actual, evidence-based probability of damage.

How Are Risk Scoring Models Trained for Damage Prevention?

What data goes into a damage prevention risk scoring model? A combination of ticket data, GIS mapping data, and historical damage records are applied against a machine learning model to generate an effective risk score for each customer. Multiple model configurations are evaluated to ensure the best-performing model is selected for a specific customer's data, producing ticket risk scores that are both meaningful and actionable.

Why does risk scoring matter for damage prevention teams with limited staff? Most damage prevention teams don't have enough people to investigate every risky scenario. Risk scoring gives these teams an evidence-based way to identify the tickets where damage probability is highest, so they can focus their limited intervention resources on the work that matters most.

How Does KorTerra's Risk Scoring Find the Highest-Risk Tickets?

I've spoken with nearly a hundred companies on this subject, and the message I hear repeatedly is: "We're looking for the needles in the haystack, but we don't have enough resources to comb through the hay to find them." In a recent conversation, a top-tier energy provider shared that their staff only has the capacity to take action on the top 1% of their riskiest tickets.

That reality shapes how risk scoring models need to be built. They have to surface a manageable percentage of tickets, not flag half your volume and leave your team in the same position.

What results does KorTerra's risk scoring deliver? In our work with customers, KorTerra has consistently provided risk scoring models that identify 55% to 75% of damages within approximately 10% of the total ticket population. That means you can find anywhere from half to three-quarters of your damages in roughly one out of every ten tickets. That's an actionable distribution. Your damage prevention team can focus intervention efforts on the highest-risk tier, and if your energy is directed at the tickets most likely to produce damages, you will see reductions in total damage count, damage-per-ticket ratios, and year-over-year damage costs.

How Should Organizations Operationalize Risk Scoring in Their Damage Prevention Programs?

If your organization is considering implementing risk scoring, spend time before launch defining the actions your team will take when a high-risk ticket surfaces. The scoring model is only valuable if it triggers a specific intervention.

What should you require from a risk scoring provider? Make sure your provider delivers a score distribution where a small, workable percentage of tickets are flagged as high risk. If 30% to 40% of your tickets come back with elevated scores, you won't have the resources to act on them, and the scoring adds no value. You might as well flip a coin. Also require that the provider can tell you which attribute data is driving the elevated risk on each ticket. Without that transparency, your team can't determine what type of intervention is appropriate for the situation.

What interventions should damage prevention teams take on high-risk tickets? Define clear actions for different risk scenarios and communicate them to your teams, whether you work with internal locators or third-party contract locators. Examples include routing high-risk tickets to a senior locator, triggering an automatic audit review, or implementing a watchdog process that requires a second review before the ticket closes. The nature of the risk in each scenario should be communicated clearly so preventive measures match the actual conditions in the field.

Risk scoring is producing measurable results across the 811 system. By applying machine learning to ticket data, organizations can surface the tickets with the greatest damage potential and allocate their intervention resources accordingly. As risk scoring programs continue to mature, the impact on underground infrastructure protection and damage reduction will grow.

Reach out to our team at info@korterra.com to learn more about how risk scoring can work for your operation.

About KorTerra, Inc.

KorTerra is the leading provider of damage prevention software, protecting billions of dollars in underground infrastructure. For over 30 years, the leading stakeholders in gas distribution, pipeline operation, telecommunications, electric distribution, contract locating, and city, county, and state governments have trusted KorTerra as their damage prevention solution. KorTerra helps mitigate risk and ensure the safety of field personnel by providing secure software platforms for processing 811 locate tickets, tracking and reporting asset damages, meeting regulatory compliance, and more. Explore additional solutions at korterra.com and follow KorTerra on LinkedIn.

Media Contact:
Paige Nygaard – KorTerra, Inc.
952.368.1911
marketing@korterra.com