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Assuming you know nothing: insight: the crucial art of validating the numbers you see and use can prevent poor decisions.

Managers are typically data junkies. Their motives are commendable: Having more data, they believe, better enables them to increase profitability and formulate appropriate business strategies.

But a single-minded focus on gathering new information can distract managers from a much-neglected issue: Checking the validity of the numbers they already see and rely on. This is crucial, because some of what we think we know is false or misleading, and leads to poor decisions. Here are some ways to avoid this pitfall.

Compare information gathered from different sources. One life insurer was confident that its investments were correctly valued, until the financial crisis prompted it to use and compare multiple pricing services. The insurer discovered that different pricing sources had widely divergent price estimates for many securities. In particular, complex securities rarely traded in this new environment, and the different pricing services used widely different methods to estimate their prices. So for these securities, what the insurer had thought were observed prices were in reality model-driven estimates of questionable accuracy.

Make sure that the numbers you see tell the whole story. At one major insurer, the tax department prided itself on saving the firm millions by carefully managing its exposure to theAltemative Minimum Tax. It estimated the firm's year-end underwriting profits by means of a twice-yearly survey of the firm's various profit centers, and used the results to order the investment department to alter its mix of taxable and tax-exempt securities, to minimize the firm's estimated tax obligations. Fortunately, the firm's investment chief, alarmed by the massive transactions that the tax department assured him were essential, engaged a team to explore the firm's tax strategy. It discovered that the tax department's calculations omitted the transaction costs incurred by the portfolio changes that they ordered. These costs can be considerable, since many tax-exempt securities are illiquid. As it turned out, the costs of tax-driven portfolio changes often exceeded the tax benefits these changes were intended to achieve.

Check whether outcomes agree with preliminary estimates. Decisions often need to be made before all relevant data is available, so plausible estimates or forecasts replace data that is missing. But once decisions are made, the accuracy of these estimates is seldom examined. Yet checking their accuracy can be highly informative. In the tax strategy example just described, the investment team serendipitously found an employee who had saved all of the profit forecasts produced in response to the tax department's expensive and time-consuming twice-yearly survey. A simple statistical analysis of historical forecasts and outcomes revealed a stunning fact: there was absolutely no relationship between forecast changes in profits and actual ones. A far better predictor of a year's underwriting profit was simply the prior year's profit. So the elaborate strategy to manage taxes turned out to have no validity whatsoever.

The implication: "It ain't what you don't know that hurts you. It's what you know for sure that just ain't so."

Audio:

Listen to an interview with William H. Panning at www.bestreview.com/ audio or scan this code with your smartphone.

Best's Review columnist William H. Panning is an independent consultant and former executive vice president at Willis Re Inc. He can be reached at bill@ williamhpanning.com.
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Title Annotation:Property/Casualty Loss/Risk Management
Author:Panning, William H.
Publication:Best's Review
Date:Jul 1, 2012
Words:532
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