Academic journal article Defense Counsel Journal

Enough of Anecdotes: An Objective Way to Assess Defense Counsel Competency

Academic journal article Defense Counsel Journal

Enough of Anecdotes: An Objective Way to Assess Defense Counsel Competency

Article excerpt

IADC member Michael W. Brink is Liability Division Manager of the Interinsurance Exchange of the Automobile Club of Southern California and a member of the IADC Insurance Executives Committee.

IN RECENT years, much has been said and written about the relative value of legal services in the defensse of civil cases. Spiraling costs have spawned dramatic changes in the way insurers and corporations secure legal services. Use of staff counsel, case budgeting, bulk contracts, finite litigation plans and a variety of alternative billing arrangements are just some of the strategies that have been employed in an effort to gain control over what, at least in the 1980s, was a dizzying upwards spiral.

Much has also been said and written about what triggered this focus on the costs of legal services, the impact on the price of goods and services and the ultimate effect of all this on affordability and competitiveness. This is not a historical review of this phenomenon, interesting as that might be. Suffice it to say that there is sufficient blame to go around; further finger pointing is count6r productive.

There is also much to say about the various approaches being employed in an effort to improve not only the affordability but also the predictability of the costs of legal services. Some of these initiatives have been quite imaginative; they have brought about much needed dialogue and have provided perspectives on the way legal services are now being valued by insurers and other corporations.

But permeating the entire spectrum, one critical need continues to exist--finding a truly objective way to measure counsel performance, notwithstanding disparities in the complexity and financial exposure of particular cases.

COUNSEL SELECTION

In the past, counsel selection by insurance companies and corporations was based largely on referral, relationship, or cost alone. Almost all information was anecdotal. A lawyer or law firm would achieve a good result on a particular case and would be sent more business. Soon, a volume of work would develop, either from the same source or from other referrals. A reputation would develop, based on anecdotal information on a few cases. Perhaps the cases were typical, perhaps not. Claim or risk managers felt they knew the product of a given lawyer or law firm because of their involvement in the review of cases handled by that attorney or firm. But the greater the case volume, the less likely the product of any particular case is typical, especially in areas such as third-party property and casualty defense. Factoring in the cost of achieving the results in a set of diverse cases becomes extremely difficult, virtually worthless, when applied against such a subjective base.

There are familiar debates about the results achieved by one lawyer or law firm compared with those of another lawyer or firm; or about how the product of house counsel is just as good as that of rewined counsel, and at a lower cost; or about how the case results of one lawyer or law finn are better than those of another lawyer or law firm, and the fact that the former's hourly rates are lower. But then the usual questions a risk about the comparability of case mix among the firms being compared. Because of the variables, the debate is endless.

Endless evenings of these debates, entertaining as they may have been, motivated an attempt to find some genuinely objective measures of legal services as valued by insurers and corporate interests today.

HOW TO DO IT

It was necessary to gather data in a variety of areas involved in case handling that would provide objective measures of performance. Eighteen categories were identified. These are listed and explained on pages 100-102 of this article. The first 10 categories are further described some detail later and are depicted graphically, based on data accumulated in 1994. Categories 11 through 18 are self-explanatory, except Nos. …

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