After more than 20 years in the insurance industry, working on three continents in various product lines and capacities, I have seen many changes occur alongside a notable constant: Insurance consumers want to pay less, and insurance company returns don’t satisfy shareholders.
Therein lies the rub. The conventional way to increase returns has been for insurers to increase premiums (based on what is presumed to be a fixed risk level), but that approach is contrary to the client’s desire. Yes, insurers also look to improve operational efficiency and claims handling, but those efforts are yielding diminishing returns.
Why not take a different tack and really focus our efforts on reducing the cost of risk? We’d then diminish the tension between insurers and their clients. Client premiums would drop, and insurers’ profitability would rise.
Like many, I believe that insurance is on the cusp of dramatic change. Insurers that thrive will put risk reduction at the forefront of their value proposition. That risk reduction will translate into lower premiums for diminished risk. Clients, and society at large, will be the ultimate winners.
The increasing availability and variety of data, more sophisticated tools to extract insights from that data and technology to cost-effectively support risk reduction will fuel this evolution. Insurers will need to rebalance their resource deployment away from the evaluation of risk for the purpose of assuming liability (underwriting) to the evaluation of risk for the purpose of reducing risk (risk consulting). Clients will come to expect insurers to provide advice on actions they can realistically employ AND the savings they will be guaranteed if they take those actions.
Whether change displaces current insurers or they evolve remains to be seen. Some insurance executives see a future of insurance that delivers a different value proposition to clients. We see a value proposition that primarily focuses on reducing the cost of risk. Insurers will increasingly supplement expertise with data, analysis and technology focused on reducing the cost of risk. They see a future where the industry unlocks the insights in insurers’ own data, integrates external sources as they become available and closes information gaps that exist. They see a future where clients are empowered with clear, objective risk measures that allow them to control their risk level … and their premiums.
In this future, insurers become tech companies where the insurance policy covers the limited remaining risks and in essence serves as a warranty of the risk services provided.
My discussions leave me optimistic that there are like-minded executives who see a different value proposition for insurers. But most I have spoken with draw the conclusion that neither their company nor any they know has the critical mass of support necessary to drive change.
To adapt and stay viable, insurance companies need to think about how evolutions in technology and data science can benefit clients and reshape business models. My goal is to encourage that debate.
I’ll be introducing a topic and perspective every other week that will focus generally on evolutions in the industry and the power of technology to transform the way risk is quantified, along with associated pitfalls. Each piece will conclude with a polling question and, depending on the volume of response, these results will be published.
Coming topics will include:
New Data and New Tools: When we think of data, most think of text and numbers that has been organized. By expanding our thinking, we can add satellite imagery, sensor-derived data, the Internet of Things (IoT), traffic cameras, customer service phone call recordings, pictures and many other potentially valuable sources. Imagine being able to analyze traffic light cameras to understand real-time risk at intersections. Imagine crowdsourcing the analysis of satellite and aircraft imagery to identify properties affected by natural disasters. Imagine being able to review a snapshot of a damaged automobile and adjust many claims without human intervention. Research, and in some case practical applications, exist in these and many other areas. We need to identify the information we need to know to understand risk and then either find the data that will help us or create our own. How do we ensure that the insurance industry is at the forefront of collecting, generating, integrating and analyzing all forms of data to drive deeper insights?
Data, Data Everywhere but Not a Drop for (Clients) to Drink: Every insurance company collects and generates a tremendous amount of data. Some of that data is structured; a much larger volume is memorialized in pdf files, pictures and customer service call recordings. While potentially useful for clients, the data is rarely made available at all and even more rarely in a format that provides insights. Insurers are investing in using that information to drive better claims outcomes, better risk segmentation and better internal processes. Clients expect to benefit from insurers’ resources but generally don’t get the insight they need to effect change. What would it mean if we insurers transformed our business model so that data-driven insights and risk mitigation strategies replace risk transfer as the core of value proposition?
Risk Mitigation Strategies and New Technologies: Imagine being able to identify the moment a risky behavior is occurring and having the ability to automatically intervene or alert the appropriate person. In some realms, that possibility already exists. Applications exist to alert drivers to their own risky behavior. Active technology exists to automatically apply the brakes to prevent collisions. Yet even where appropriate data exists, insurers are hesitant to make definitive recommendations based on specific technologies. Insurers are unique in that they price risk and ensure the realization of financial benefits from investments in risk reduction. Should we as an industry more actively become creators or advocates of risk technology? Can we have enough faith in our recommendations to integrate benefits immediately in prices? Does the traditional insurance policy become a form of warranty that our risk advisory services are effective?
Transparent Risk Indices: We are about to enter an information age where it is possible to quantify risk objectively in real-time. Creating risk indices, making them transparent and using them as the basis for establishing price would give clients confidence in the objectivity of the process and confidence that if they invest in changing those indices they will immediately get the benefit. The indices will also give non-insurance risk capital providers the opportunity to deploy capital against and trade risks that previously lacked the transparency. What can we learn from other financial services that have developed transparent risk indices that allowed capital to be deployed against those risks from a wider variety of sources?
Real growth — not incremental improvements to last year’s numbers, but big results coming from new opportunities you manage to seize and commercialize — is hard to come by.
There are so many distractions, so many rabbit holes you can fall into — the lure of a cool technology, a move by a competitor that appears to be smart, a high-pressure conversation with a board member, a convincing argument from a colleague on why an idea will or won’t work or a CFO waving a red flag.
There are also so many ways to convince yourself that the status quo, at least for now, is tolerable — the comfort of a good current quarter, the reassurance of lots of money being plowed into new technology, the establishment of an innovation team or being recognized with an industry award.
But somehow, things still don’t feel quite right. You wonder why, in spite of upbeat business reviews from trusted employees, the new product pilots aren’t quite panning out. Some new start-up (or two, or three or more) seems to be whipping up a storm in the market, and you feel left in the dust (or left to contemplate paying a hefty premium to buy what someone else managed to build right under your nose).
What to do?
The answers are astoundingly simple, so simple, in fact, that they elude the very smart, big-school-degree types running around corporate America today. These leaders are fully in control of their growth destinies, yet all too often are unable to deliver and either blame some externality or create a mirage that all is well.
Here’s the three-step formula to get real growth:
Define the customer problem you are solving. This is the first, almost painfully obvious step. Yet, consider how many people in big roles define their business’ marketplace value around internally generated definitions of value, claim to know customers’ needs but never talk to customers or allocate resources to deploy new technologies with no connection to how customers act or how they lead lives in which your business probably plays only a teeny, tiny role.
Let’s parse what this first step means.
Define: with absolute clarity, in a way that lets you understand the total scope of opportunity, not just what’s in front of your nose and linked to today’s P&L drivers.
The: one, with focus.
Customer: the people who take their wallets out of their pockets and give you their money – not the internal lobbyists.
Problem: a real pain point, not something that merely makes people feel good. People will prioritize getting rid of their pain as way more important than a gratuitous feel-good purchase.
You: the bigger you, the organization, mobilized around your singular focus.
Solve: dramatically better than anyone else, so you have a massive jump on others in the market who will chase after any good business opportunity to eat into or take over share.
Establish the fundamentals to cultivate growth.
Governance: If your plan is to create big sources of growth, the CEO has to own the goal, including implementation, and hold the rest of the C-suite accountable. If not, accept your destiny as an incremental player, at best.
Accountability: Big new sources of growth will come from separate accountability outside the established P&L structures. No fault to the P&L leaders; their work is important and drives the company today. But the goals, timeframes, talent and implementation path to run a scale business is based on predictability, control and risk reduction. Contrast these attributes with what’s needed to spawn a big, new business: experimentation, failure, ambiguity and risk-taking. The established P&L priorities will always overwhelm the nascent ideas trying to grow into big future profit producers.
Talent: The people who are absolutely brilliant at running the machine are unlikely to be the same folks who will create the next big thing, and vice versa. That’s not personal, it’s the reality that we are all really good at some things and mediocre at others and should just avoid yet others. Be truthful about that, both regarding yourself and when evaluating others.
Metrics: Find the metrics that connect customer needs and wants to the customer actions driving the P&L. It’s a cop-out to say this can’t be done, and it’s easy to fall back on familiar but irrelevant metrics. Focus on customer behavior measurements to drive decisions. High-level reporting of income statement and balance sheet line items are interesting, and certainly matter to your investors. But they will blind you to the below-the-surface measures that matter – the real drivers that are moving every day as your customers make decisions affecting your performance whether or not you acknowledge them. Operate your business at that level, and you will drive your destiny.
Process: Industrial-strength processes that enforce predictability, control and risk reduction will steamroll over anything that doesn’t look exactly like what came before. Remember the definition of insanity often attributed to Albert Einstein: “doing the same thing over and over again and expecting different results.”
Embrace and behave according to the mindset of a founder, or move on. In The Startup Playbook, author David Kidder cites the five qualities of the successful entrepreneur. These attributes apply equally well to leaders in any enterprise, not just what we have traditionally defined as start-ups.
Know thyself. Your team’s success will be a direct reflection of your self-awareness and deployment of your own gifts to whatever opportunity you go after.
Ruthlessly focus on your biggest ideas. Focus means laser-like drive against the beacon you see out in front of you that represents realization of your solution to the customer problem. But not to the exclusion of listening – being able to filter and apply that which is valid, without getting diluted by the well-meaning, but utterly useless opinions you will be offered. It’s a tightrope.
Build painkillers, not vitamins. Back to Point 1. Solve a real problem. Don’t create a nice-to-have.
Be 10x better. That’s Kidder’s estimate of how far ahead you have to be to outrun and outlast the inevitable competition.
Be a monopolist. At least in mindset, think gigantically. Think about how you can own the market, not just create something that will satisfy a near-term demand.
Creating big sources of growth with real results can be predictable. You just have to follow the formula.
Data-driven analysis is a critical decision-making tool for Construction Financial Managers and other industry leaders.
Decision-making is arguably the most important responsibility of company leadership.
Companies that make better decisions make fewer mistakes, and achieve a distinct competitive advantage in the marketplace.
The underlying purpose of benchmarking is to continually improve the quality of organizational decision-making.
As construction risk management consultants, we help contractors prevent accidents, mitigate claims, and reduce the total cost of risk through a continuous improvement process.
We believe companies must instill management accountability for continuous improvement by linking performance measurement to both prevention activities (leading indicators) and operational results (lagging indicators). As the adage goes:
“What gets measured is what gets done.”
In our consulting roles, we frequently help companies establish realistic performance measures by conducting various types of claim and loss analysis.
This type of data analysis is usually the starting point in a performance improvement process — and a common practice among insurance agencies, brokerages, carriers, and risk management consulting firms.
In addition, we are often asked to conduct a benchmarking analysis that compares one company's claim and loss data against peer companies or to the construction industry as a whole.
The term “benchmarking” refers to the comparison of a company's performance results against those of similar peer companies. Benchmarking evolved out of the quality improvement movement in the late 1980s and early 1990s.
Its initial intent was to identify leading companies regardless of industry sector, and apply their best practices to improve one's own company. Over time, benchmarking has become synonymous with process improvement.
The traditional view of benchmarking required two separate disciplines focused on performance improvement: measures and methods. Identifying and capturing performance indicators (the measures) is only the first step; developing and implementing performance improvement (the methods) is the second and most important step for the benchmarking process to be truly effective.
The Health Club Analogy
There is limited value in benchmarking without applying new methods to address continuous performance improvement. Performance improvement requires more than the measurement of performance indicators; it requires the implementation of changes in management disciplines to attain improved operational results.
Using only performance indicators without implementing new methods to improve operations is akin to joining a health club and expecting the benefits without actually using the equipment or committing to an exercise program.
Merely jumping on the scale and gauging your weight relative to others doesn't help you achieve your own weight loss goals anymore than comparing your pulse and respiration rate to others helps you attain your aerobic or cardiovascular fitness goals. What matters most is that a person embarking on a weight loss or fitness program stays committed to the process and monitors his or her own progress.
Similarly, we believe the ongoing monitoring of claim and loss data specific to an individual company is even more important than the initial measurement of insurance claim and loss data relative to other companies.
Baselining As Benchmarking
The term “baselining” refers to the internal benchmarking process that occurs when a company compares its performance against its own results year after year. Ongoing, internal monitoring allows a contractor to determine if the company's claim and loss trends are improving or deteriorating, and to make the critical performance improvement decisions necessary to facilitate a change in results.
Referring back to the health club analogy, baselining does not compare an individual's weight and aerobic fitness to that of the other health club members. Instead, individual fitness goals and measures are established, monitored, and tracked to verify continuous personal improvement.
Similarly, a construction company can develop a baseline analysis of its loss cost performance by reviewing loss and claim data for a minimum of 3-5 years. Company results are compared from year to year, and ideally are broken down by operating entity, division, project, manager, or even crew levels.
Exhibit 1 provides a sample of a baseline analysis that compares one company's relative claim and loss performance within all of its operating divisions.
This analysis reviews the historical loss cost data for the entire company and breaks it down into meaningful data relative to each operating division. The total workers' comp, Comprehensive General Liability, and auto liability incurred claim costs (sum of paid and reserves) for each company division over a five-year period were compared to the total man-hours for each division, producing a cost per man-hour figure.
The results illustrate dramatic differences in total claim costs per man-hour for each division. This baseline analysis was the first step in raising awareness of the predominant loss leaders within the company. This increased awareness led to a detailed analysis that established plans of action and realistic cost targets by company division for the upcoming year.
We acknowledge that there are numerous benefits to measuring the frequency, type, and cost of insurance claims compared to peer groups and/or the entire construction industry. Such analyses provide the ability to:
Identify leading types and sources of claims
Establish strategic objectives to prevent the occurrence of common industry claims
Create awareness among managers and employees about the costs of claims and the impact on profitability
Post positive results on company websites and for use in other marketing materials
The Bureau of Labor Statistics provides safety-related data so that companies can externally benchmark injury and illness data against specific industry groups. (Check out the Web Resources section at the end of this article for more information.)
In addition, Bureau of Labor Statistics data is used to calculate and compare OSHA Recordable Incident Rates and Lost Workday Incident Rates, both of which are common construction industry benchmarks. This data is useful when making high-level comparisons within construction industry segments relative to injury and illness rates.
We also use external benchmarking analyses to establish risk reduction, loss prevention, or cost containment goals. In “Risk Performance Metrics” by Calvin E. Beyer in the September/October 2007 issue of Building Profits, a sample benchmarking comparison shows a representative contractor's duration of lost workdays workers' comp cases in median number of days compared against the median duration for the industry. Results such as these can highlight the importance of an increased focus on injury management and return-to-work programs.
The benchmarking analysis in Exhibits 2A and 2B compares a contractor's workers' comp claim and loss performance to an established group of peer contractors in the same specialty trade. (These companies engaged in similar work, and performed in states with similar insurance laws and legal climates.)
The analysis was based on total incurred workers' comp costs and total number of workers' comp claims as compared to payroll for each entity. Overall, Company D had worse results than the other three companies.
This prompted an in-depth review of Company D's workers' comp losses by division and occupation. As shown in Exhibit 3, the company experienced significant claim frequency and severity issues within the first six months of employment.
These findings triggered the development and implementation of specific activities designed for Company D's new employees.
Below are some of the activities that were incorporated into the formal improvement plan:
new hire skills assessments
daily planning meetings
Other Sources Of Benchmarking Data
Professional associations and industry trade/peer groups also provide comparative data for benchmarking purposes.
The Construction Financial Management Association's Construction Industry Annual Financial Survey is an excellent source for understanding the key drivers of contractor profitability. We use the survey data to determine comparative profit margins for different types and classes of contractors when we calculate a revenue replacement analysis to show the additional sales volume needed to offset the cost of insurance claims. (This technique was highlighted in the “Risk Performance Metrics” article previously mentioned.)
Similarly, the Risk and Insurance Management Society (RIMS) conducts an annual benchmarking survey that reviews insurance rates, program coverages, and measures of total cost of risk.
An example of a peer group data source for benchmarking is the Construction Industry Institute (CII). The Construction Industry Institute is a voluntary “consortium of more than 100 leading owner, engineering-contractor, and supplier firms from both the public and private arenas” (www.construction-institute.org). It develops industry best practices and maintains a benchmarking and metrics database for its participating members.
Another peer group example involves members of captive insurance companies sharing and comparing claim and loss data for the group as a whole. There is a major advantage when a true peer group shares benchmarking data: Such data sharing often leads to peer pressure in the form of increased ownership and accountability for improvement by the companies shown to be the poorest performing members.
We continue to search for more new sources of industry best practices and comparator data. A possible emerging source for the construction industry is the National Business Group on Health. This organization has developed standardized metrics known as Employer Measures of Productivity, Absence and Quality™ (EMPAQ®).
EMPAQ® helps member companies gauge the effectiveness of their injury and absence management and return-to-work programs. The founder and principal of HDM Solutions, Maria Henderson, served as a project sponsor for EMPAQ® from 2003-2007, and co-presented with Calvin E. Beyer on “Return to Work as a Workforce Development Strategy” at CFMA's 2008 Annual Conference & Exhibition in Orlando, Florida.
Limitations Of External Benchmarking
We fear that the increasing popularity of external benchmarking analyses may indicate that it has become a “quick fix” solution or a management fad. When asked to conduct an external benchmarking analysis, we always ask the following questions:
What is your purpose in seeking these comparisons with other companies?
Who are you trying to convince and what are you trying to convince them to do?
What specific peer companies should be used for comparative purposes?
Are these companies (and their operations and exposures) truly similar enough for a fair comparison?
Beware Of Pitfalls
There are many hurdles to surmount in locating suitable companies for external benchmarking comparisons. Generally, when benchmarking comparisons can be made, more often than not the greatest value lies in the workers' comp line of insurance coverage.
Here are some key factors to consider when choosing contractors for external benchmarking comparisons:
Percent of self-performed work vs. subcontracted work
Payroll class codes and hazard groupings of selfperformed work
Differential geographic labor wage rates
Payroll rate variances between union and merit shop operations
Size of insurance deductibles
Claim reporting practices
For example, claim reporting practices must be similar in order to minimize distorting the frequency or average cost of a claim. If one or more comparison companies self-administers minor claims or does not report all claims to their carrier, using carrier loss reports for the comparison is an invalid method.
We also find that comparing the frequency of claims and total loss dollars divided by thousands or millions of dollars of payroll (exposure basis) is a helpful workers' comp benchmark between companies of similar operations in similar states.
Likewise, a suitable benchmark for auto liability performance compares the frequency of claims and total loss dollars per one hundred vehicles.
When benchmarking fleet-related claims, ensure that the number and size of fleet vehicles — as well as the type of driving (urban vs. rural) and the total number of miles driven annually — are similar among the contractors whose claims are being compared.
Benchmarking comparisons of Comprehensive General Liability insurance results are especially challenging due to delays in reporting third-party bodily injury and property damage claims, in addition to the expected long tail of loss development for these claims.
All of these factors are compounded by vastly different litigation trends and liability settlements in various states and regions of the country.
Common Limitations Of Data Sources
Whether or not you intend to develop a baseline of your company's claim data or to benchmark your company's performance against a peer company, there are several issues that must be successfully resolved regarding the data's quality and integrity.
Based on our experience, we classify the key challenges associated with exposure and claim/loss data into the categories shown in Exhibit 4: availability, accuracy, accessibility, standardization, reliability, comparability, and date-related problems.
Value Of Multiple Measures
Evaluating data from various sources and different angles is also valuable. Why? Because it's possible to gain a better understanding of the whole by dissecting the parts. This practice illustrates the principle of multiple measures.
This approach is substantiated by 2006 research, which concluded that the “simultaneous consideration” of frequency and severity provides a more comprehensive result than performing analysis based solely on one factor.1
This is similar to our approach when we conduct a “Claim to Exposure Analysis” and review historical frequency and severity vs. the relative bases of exposure for each line of casualty insurance coverage.
Returning to the health club analogy, when starting a formal exercise program, you often begin with such general baseline measurements as height and weight; this is usually followed by additional measurements, such as BMI, body fat content, and the girth of arms, legs, and chest (the baseline).
As we all know, weight alone is not always the best indicator of success in fitness efforts. In fact, since muscle weighs more than fat, an increase in total body weight may actually occur after beginning and maintaining a fitness program.
Although you might not experience a dramatic weight drop, you could see a reduction in waist size and BMI — positive changes that would not be evident unless multiple measures were being used and reviewed.
Benchmarking insurance claim and loss data performance is like comparing one person's height and weight against the ideal height and weight charts based on the entire population.
Wouldn't it be more effective to establish your baseline weight and other multiple measures initially so you can see the progress you are making?
This is similar to the baseline measurements that a company should take (as well as the multiple measures) that are necessary to meet your company's performance improvement goals for financial success, operational excellence, or risk reduction.
Cal Beyer collaborated with Greg Stefan in writing this article. Greg is Assistant Vice President, Construction Risk Control Solutions, at Arch Insurance Group. As a member of the Southeast Regional team in Atlanta, GA, Greg supports underwriting and claims in risk selection, claim mitigation, and risk improvement activities. He is also responsible for high-risk liability risk reduction initiatives including contractual risk transfer, construction defect prevention, and work zone liability management.
1 Baradan, Selim, and Usmen, Mumtaz A., “Comparative Injury and Fatality Risk Analysis of Building Trades,” Journal of Construction Engineering and Management, May 2006, pp. 533-539.