Beyond the more recent fad of big data, managers have long been swayed by the idea that better data equals better decisions.
While there is certainly truth in this, how “good” that data is will always depend on the person using it to make the decision, and CEB research shows that line managers are often prone to misusing the data they are given.
It’s certainly encouraging that the lure of better data has led to more funding for financial planning and analysis (FP&A) teams – in 2013, it represented the fastest growing category of finance spend – but it also increases the risk that more money will be wasted in the pursuit of bad decisions. And the cost of misused financial analysis is significant: when it comes to major strategic decisions, it can cost companies up to 1% of revenue.
Heads of FP&A are aware of this problem but they tend to attribute the misuse of their analysis to the firm’s organizational culture, and so something outside of FP&A’s expertise and ability to change. But CEB research finds exactly the opposite. Contrary to popular belief, the single biggest cause of analytic misuse is the nature of the financial analysis itself, which is certainly something FP&A can work on.
How Companies Misuse Financial Analysis
The misuse of financial analysis falls into the following three types:
Decision makers don’t use financial analysis: Analysis that is not used is either brought in too late to make a difference or is not valued by decision makers. Frequently, these analytic projects are treated as a check in the box exercise or validation of a decision already made. Only 25% of FP&A executives say decision-makers consistently use analysis in the right way.
Decision makers misinterpret financial analysis: Almost half of decision makers lack the analytic judgment to fully understand the results of analysis. So, even though they might be willing they’re not always able.
Decision makers selectively use financial analysis: Many decision makers cherry-pick analysis to support a pre-ordained conclusion. They assume their idea is well founded and just need to find the data points to justify their decision.
Misuse of Financial Analysis Is Within FP&A’s Control
Despite what heads of FP&A may think, organizational characteristics — such as the type of decision being made, who has the rights to make a decision, people making opportunistic decisions, and the corporate integrity of those making the decisions — only make a negligible contribution to the misuse of financial analysis (see chart 1).
Chart 1: Biggest contributors to misuse of financial information in decision making Based on regression and relative-weight analysis; n=248 companies Source: CEB 2015 Financial Analysis Impact Assessment; CEB analysis
Problem-Focused Analysis Makes For Better Decisions
To help managers get the most from financial analysis, FP&A teams need to shift from an answer-focused approach to a problem-focused approach.
Most FP&A organizations concentrate too much on providing decision makers with the right answers and recommendations. But this only exacerbates the misuse of analysis as it obscures alternatives and financial tradeoffs implied by the recommendations.
The best analytic teams instead anticipate the types of analysis line managers will need for future decisions, edit and iterate the financial models they use before they plug numbers in, and question any conventional wisdom about the business on which the analysis relies. CEB’s research shows that this problem-focused approach is twice as effective as an answer-focused approach in encouraging decision makers to use financial analysis in the right way (see chart 2).
To provide problem-focused analysis, FP&A teams should focus on three principles:
- Anticipation: Anticipate decisions beyond the near term during analysis.
- Prototyping: Engage stakeholders through prototyped analytic models and identify hidden decision-maker beliefs.
- Disruption: Disrupt decision makers’ conventional thinking by challenging stakeholders on unforeseen tradeoffs and critical uncertainties.
Chart 2: Impact of financial analysis approaches on the quality of analysis Standardized beta coefficients based on regression analysis, dependent variable = quality of analysis* Source: CEB 2015 Financial Analysis Impact Assessment; CEB analysis
* – The quality of analysis is measured by a combination of timeliness, accuracy, comprehensiveness, actionability, and succinctness of the analysis, as rated by senior decision makers.
Strategic decisions: e.g., major acquisition, new market entry, capital allocation.
Tactical decisions: e.g., segment profitability, pricing, product improvements.
Short-term performance decisions: e.g., correcting short-term variances from budget.
Learn more about improving business decisions with financial analysis by listening to this webinar replay.