The #3 Concern of CFOs: Forecast Accuracy

Duke University and CFO Magazine recently asked 475 CFO’s in the United States to rank their top three internal and external concerns (see Global Business Outlook Survey website).

Here they are, along with the weighted ‘average importance’ score:

Top External Concerns    (Average Importance Score)
1. Consumer Demand    1.35
2. Credit markets/interest rates    0.88
3. Housing market fallout    0.69
4. Cost of fuel    0.66
5. Cost of non-fuel commodities    0.55
6. Upcoming change in U.S. Administration    0.48
7. Other    0.41
8. Financial regulation    0.30
9. Environmental regulation    0.14
10. Int’l political instability    0.11

Top Internal, Company-Specific Concerns   
1. Cost and availability of non-finance labor    1.35
2. Ability to forecast results    1.29
3. Cost of health care    1.20
4. Supply-chain risk    0.76
5. Other    0.42
6. Data security    0.39
7. Cost and availability of labor in accounting/finance    0.30
8. Auditing costs    0.12
(Source: CFO magazine, May 2008, p.23)

All of the external concerns were related to the weakened economy and political environment (in the U.S. and abroad).  The external concerns made their way to the internal concerns mostly around costs (of labor, health-care, auditing, etc.).  But the most interesting answer was the #3 overall concern (internal & external combined): “Ability to forecast results.”

Organizations have always had a concern with forecast accuracy, but it’s being felt more keenly now.

So how does Enterprise Performance Management help address forecast accuracy concerns?  Here are nine areas to look at:

1.    Have a formal forecast process in place – companies are trending towards rolling sales & expense forecasts;

2.    Use a multidimensional tool so that forecasts can roll up by geo, product, customer type, etc. as the business demands.  Multidimensional tools also let you add weighting, bias and probabilities;

3.    Improve the quality of the data – forecasts are based on prior period actuals, make sure the basis of your forecast is reliable;

4.    Measure and report forecast errors – expose the causes of the problem, and take action to fix them.  Use data mining tools to locate sources and trends of errors;

5.    Senior Management must make a commitment to improving forecast accuracy.  Their variable compensation should be tied to it.  A forecast accuracy scorecard can be used to track progress towards goals;

6.    Communicate the impact of poor forecast accuracy to everyone in the organization who has anything to do with forecasting, including the opportunities lost with mismanaged discretionary spending as well as the impact on stock price caused by a wide miss or revised earnings estimates to the market;

7.    Make assumptions follow the forecast.  In other-words, fully expose the assumptions that make up the forecast by quantifying the assumptions or, at a minimum, including narratives with each forecast – to the most granular level manageable (many forecasting tools now let you do cell-level annotation, for example);

8.    Look at new methodologies such as risk-weighting, predictive models and prediction markets;

9.    Continuously learn about best practices in forecasting – see the International Institute of Forecasters  for example.

Comments

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