FP&A Peril: Too Much Data, Too Little Judgment

Financial planning and analysis staff can’t begin to give CFOs what they want until they learn to apply more subjectivity in their analyses.
David McCannApril 23, 2012

Financial planning and analysis (FP&A) teams that want as much data at their fingertips as possible yet insist on using only “perfect” data in their analyses are unlikely to provide the kind of actionable insight many CFOs seek from those teams, a new report suggests.

The desired level of insight can come only from financial planners who incorporate more judgment into their analyses and fewer raw numbers, according to the CEB Financial Planning & Analysis Leadership Council, a new program of the Corporate Executive Board, or CEB. (To understand common FP&A challenges, the council performed qualitative analyses based on extensive interviews with 70 corporate FP&A heads as well as academics and consultants. It also did some quantitative, survey-based research.)

Poor financial analyses may stem in part from overly detailed analyses that consume too much time. “When you give people too much information, they actually underperform,” says CEB executive director Michael Griffin. “There is more and more data coming in. But that doesn’t make it any easier for FP&A teams to deliver actionable insight to their business partners.”

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On the other hand, other potential slip-ups occur when qualitative or external inputs are used when hard, internal data is unavailable or imperfect.

Such failures disappoint CFOs. To their credit, the leaders of FP&A teams willingly point the finger at themselves. Only 29% of those surveyed say they consistently deliver insights about the business. The rest say they sometimes or never do that.

The difference between those two groups lies mainly in the degree of willingness to use subjective judgment to illuminate or discount what the raw numbers seem to say. In a separate survey of 444 finance employees of all types, the CEB found that 37% were “informed skeptics,” who apply judgment to their analyses and are comfortable with dissent and listening to other viewpoints.

Those are the preferred type of staffers, flanked by two extremes: “unquestioning empiricists” (44% of respondents), who trust data over judgment and value consensus, and “visceral decision makers” (19%), who seldom trust analysis and make decisions unilaterally.

That “unquestioning empiricists” comprise the largest of the three groups is hardly surprising, Griffin says: “Finance folks are very comfortable with data, but less so with the application of judgment into the data.”

The “informed skeptics,” on the other hand, possess the relevant skills for decoding large amounts of data, managing ambiguity, and using judgment to influence their analyses, the CEB writes. “Unfortunately,” its report says, “there are a relatively small number of these analytic experts, constraining the scope and depth of analytic capabilities across finance. As such, FP&A teams’ greatest risk comes from too much data, not too little.”

The insight deficit not only limits finance’s influence on the business, it also has a measurable negative impact on financial performance. The FP&A teams under the 70 leaders surveyed in the latest research were divided into what the CEB assessed as analytically mature and low-performing ones, and the former enjoyed a 6% premium on total shareholder return.

With judgment playing such a critical role in analytics, the CEB defines what it sees as the five elements of judgment and in what ways they should be incorporated into FP&A:

Synthesizing diverse data. Integrate into the analysis both qualitative and quantitative data, as well as external viewpoints.

Inferring trends. Distinguish patterns that are relevant from those that are not; identify risks and opportunities based on data analysis.

Generating insight. Isolate actionable and noteworthy implications, and teach managers something new about their business.

Redirecting poor business assumptions. Surface key biases and assumptions that affect the results of data analysis; identify and size the impact of environmental factors that may not be reflected in the data.

Influencing business decisions. Deliver controversial messages comfortably and with authority; clarify decision trade-offs to internal customers.

The CEB identified three broad take-aways from its research. First, stop relying on boilerplate performance-review criteria that were created for finance generalists. Instead, tailor the FP&A competency model by clearly defining analytic skills and behaviors that are unique to that discipline and lead to insight generation.

Second, identify key decision points where FP&A can cut down on unnecessary, non-value-added work, and establish protocols for analysts to collaborate with business partners. Finally, don’t spend much time looking for the perfect data or analysis to answer business questions. Teach analysts to make smarter trade-offs between timeliness and accuracy by setting guidelines about what types of decisions or projects require perfection versus those that require only directional analysis.

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