Maximizing Agency Potential 

By John W. DeWitt

Insurance carriers certainly feel the pressure on top-line growth in the current underwriting cycle – but more focused and effective agency management is a perennial challenge in any economy. Simply put, how do you more accurately evaluate, and then maximize production of, distribution channels – without incurring substantial additional costs?

“Traditional agency management approaches face limits as competition intensifies in a finite market,” notes Gary Ciardiello, a New York-based principal at Ernst & Young who leads the firm’s predictive modeling group in the Insurance and Actuarial Advisory Services Practice. “Innovative insurers increasingly are recognizing the need to augment production management with a data rich, metric based more analytical framework.”

To this end, Ciardiello and his colleague Benny Yuen, senior manager at Ernst & Young, have been working to develop analytics-driven processes that complement traditional agency management practices and improve the way carriers evaluate and improve agency performance. They describe this as a holistic approach to agency management – one that incorporates objective analytical tools in conjunction with more subjective approaches to maximize agency potential.

“Analytics do not replace what companies are already doing to manage their agencies,” Ciardiello explains. “But analytics can provide a more disciplined, and rigorous framework for understanding agencies’ performance and maximizing their potential for improvement.” The ultimate goal, Ciardiello and Yuen believe, is to create some set of standardized metric that calculates “agency potential.”

To illustrate the analytical approach and its value, consider the example of two independent agencies, in different geographies, that place personal auto insurance for the same insurer (see chart). Their current premium volume is the same – $250,000 – and their market potential is similar. A traditional evaluative measure, such as premium volume, would indicate that the two agencies in this comparative example have the same growth potential. But premium volume is a lagging indicator, whereas the Agency Potential Index that Ernst & Young has developed tells a much different forward-looking story. Agency B scores 22 points higher in the composite Agency Potential Index.

To generate this metric for Agency Potential, several indices, based on a 1 to 100 scale, have been developed and applied to each agency. The final composite score indicates each agency’s forward potential – providing empirical insight that can help the insurer allocate its marketing dollars more productively. (Note that this example uses simple averages. In practice, statistically derived weighting methodologies would be applied to each index to arrive at the overall score.) A comparison of individual indices explains some of the reasons why Agency B scores higher – because of factors such as better infrastructure, more competitive rates in its market, a stronger brand, and superior alignment with the insurer.

The Limits of Traditional Agency Management Approaches
Compare the analytical approach in the preceding example with traditional, tried-and-true approaches that carriers employ to manage their agencies. Insurance companies and their sales and marketing teams often focus on production metrics (such as premium volume), profitability metrics, compensation strategies, and agency plant strategies. Some also address back-office metrics – such as over order vendor reports, up-rating frequency, and target markets. In addition to tracking agencies’ written premiums, current production metrics can include new business counts, inforce counts, and retention ratios. More sophisticated approaches can encompass the number of quotes and conversion rates along with average premiums.

To influence these metrics – for instance, to increase the volume of quotes per agency – insurance companies rely upon traditional levers, such as changing commission structure, underwriting guidelines, or pricing, or investing in sales and marketing. However, while these approaches can be effective, “pushing any of these levers inevitably results in expense or profit implications,” Ciardiello notes.

Traditional agency management strategies also rely more on the intuition and anecdotes of the sales and marketing team, rather than empirical data. This subjective process depends heavily on knowledgeable individuals, can be difficult to replicate, and is inherently imprecise, potentially leading to overinvestment or unnecessary expense. In other words, traditional levers might improve the performance of some agencies, but not of others – and without more analytical insight, it’s hard to know why, or what else to do.

Developing Analytical Measures of Agency Potential
More accurately understanding the underlying potential of each agency helps explain why seemingly similar agencies perform differently – and indicates how carriers can maximize the performance of agencies with the greatest potential. “Potential can be defined by understanding and analyzing two sets of factors – internal and external,” Yuen explains. “Internal factors are those agency attributes that are in the control of the agency. External factors are those in the marketplace, outside the direct control of the agency.”

For instance, internal, agency-controlled factors to take into account might include the agency’s years of experience, credit, E&O limits, and size – its premium volume, number of employees, and CSR ratio. (The number of companies represented is also important when managing independent agencies.)

External factors to consider might include the competitiveness of the agency’s rates – measured by win rates and market perception – as well as market size and brand awareness. Insurance companies already pay attention to these factors, Ciardiello notes – but inconsistently and in isolation rather than as part of an analytical framework. Another important factor, less commonly evaluated, is how well the agency aligns with the carrier.

“These key external factors typically are being looked at on an ad-hoc basis – and typically on an inconsistent basis - maybe annually or quarterly – and are evaluated subjectively, from a sales or marketing perspective, rather than by actuaries or other analytical executives,” Ciardiello says. “There’s nothing wrong with this – but there is room for improvement by combining analysis with subjective evaluations.”

To analyze these various external considerations in a rigorous and holistic manner, Ciardiello and Yuen recommend that insurers develop a series of factor-specific indices that in turn will be integrated into a single composite metric of agency potential. While an exhaustive list of the factors can not be practically considered, companies would get a powerful start on building a robust analytical framework by calculating indices for rate competitiveness, market size, brand awareness, and agency alignment.

A useful and statistically meaningful Rate Competitive Index could include a quote/conversion analysis and win rate analysis, whereby geographical market baskets encompass targeted customers, inforce profiles, and census information. The other important component to integrate into a rate competitive index is market perception, which can be evaluated with reasonable objectivity via the utilization of mystery shoppers and surveys. These measures, when combined with analysis of marketing spend, can also be used to generate a Brand Recognition Index.

The Market Size Index would encompass commonly measured attributes such as the number of insureds per agency, the number of agencies per capita, and the number of competitors’ agencies per insured.

A measure less commonly used by most insurance companies is the Agency Alignment Index. It’s also a bit more challenging to quantify – but worth the effort, Yuen says, because of the often unrecognized role that alignment plays in constraining or maximizing the potential of an otherwise well-positioned agency.

“An agency can have certain sweet spots in its book of business, and those sweet spots may or may not align well with the insurance company’s sweet spots,” he explains. “If the agency writes a lot of 40- to 45-year-old single males, but the company is not strong in servicing that area, there is a misalignment between the agency and the company that hampers their ability to successfully write new business. The overall sales numbers wouldn’t give that particular insight.”

These indices, and any other agency metrics, should incorporate feedback loops – in other words, should be self-learning and continually refined through ongoing practice and experience. “You will have to adjust the dials on all these indices, take a holistic approach when reviewing them and balance them properly for individual organizations – and that balance can and often does change over time,” Ciardiello notes.

Integrating the Indices: The Agency Potential Index
Given that Ciardiello and Yuen propose a more holistic as well as analytical approach to agency management, the next step after developing a set of agency performance metrics is to integrate these metrics into a composite Agency Potential Index. Speaking more technically, companies would develop a predictive model utilizing a multivariate regression approach – in contrast to the traditional actuarial method of analyzing one variable at a time.

“If you don’t look at all underlying factors in the book, you can get a false read,” Ciardiello explains. “You have to factor in all these data points and indices together to see what the potential production would look like.”

The individual indices and other agency metrics that encompass internal and external factors would be combined to calculate the composite agency potential index. The weight for each factor would be determined by the most appropriate statistical method – for instance, logistic regression, relative scoring, or principal components analysis. The statistical method would depend on the specification of the index as well as on other considerations such as whether a factor is objective (e.g. number of insureds per agency) or more subjective (e.g. market perception). A subset of the company’s most successful agencies – say, the top 10% – would be used to benchmark the remaining agencies.

Each agency in the composite agency potential index then would be scored on a scale of 1 to 100. If calculated properly, each agency that scores, say, an 84 would have the same production potential – even if the factors generating that composite score are different.

Leveraging the Composite Agency Potential Index
Ciardiello and Yuen envision a number of beneficial applications for the composite agency potential index. Embedding the index into growth strategies could help an insurance company focus on its best opportunities for growth, documenting what works and what doesn’t while creating a consistent framework for ongoing distribution channel analysis. The index also could guide the development of agency action plans, influencing agency appointments and objectives.

Benchmarking is another potentially powerful application of the index, which would provide a means to normalize production information across agencies and then perform “apples to apples” comparisons. This approach could uncover highly useful insights that other approaches to agency management ignore, resulting in business plans that are more analytically driven and more precisely tailored to each agency.

“If you’re getting a lot of production out of an agency that doesn’t have a high score, maybe you’ve maxed out that agency’s potential,” Yuen explains. “In other cases, an agency might have a high score but really isn’t performing based on its potential, so there’s an opportunity that exists to further improve its performance.”

For more information, visit: www.ey.com/us/actuarial.

Leveraging Predictive Models to Maintain Profitability in a Soft Market
For more in depth analysis of this topic, view our web seminar! While predictive modeling applications have proven to be very effective in underwriting, customer management, marketing, and other areas, deployment of models should be aligned and reconciled with other business considerations and strategies. This session touches on the concept of decile management as it relates to the deployment of predictive models.

John W. DeWitt is a marketing consultant and business writer based in New Salem, Mass. He can be reached at john@jwdewitt.com or www.jwdewitt.com.