I recently participated in a panel discussion about the rise in the use of rolling forecasts in corporate planning. I’m not surprised by this trend; I have encouraged it. Ever since the financial crisis started three years ago, I’ve been writing that companies should rethink how they plan and budget to respond to increasing business volatility. Rolling forecasts are useful because they continually extend the formal planning horizon out more than a year rather than having it stop abruptly at the end of a company’s fiscal year. They can be the right first step in improving the effectiveness of a company’s budgeting process, but ultimately I believe that organizations need to adopt a better approach to planning – what I refer to as integrated business planning. Moreover, companies that want to adopt a rolling forecast approach must first make important changes to their planning and budgeting processes to make them leaner, more focused and faster.
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It turns out that some consumer goods manufacturers and retailers are having a hard time finding space on container ships and even finding containers to ship in. This has driven up the cost of shipping these items and at times resulted in deliveries arriving too late for scheduled promotions or seasonal demand peaks. This, during a time of constrained consumer spending in North America and Europe and an extended period where the Baltic Dry Index (a measure of shipping rates for bulk commodities such as ore and grain) has been dropping at a record-breaking rapid clip. This sort of unexpected and counterintuitive event has been having a negative impact on the affected companies. Could they have anticipated this possibility? Should they have? I think the answer is: Yes.
Anyone who has had to regularly produce a written business forecast that goes out more than a couple of months understand all too well Yogi Berra’s famous observation: “It’s tough to make predictions, especially about the future.” Certainly the economic events of the past two years have regularly made forecasts obsolete in a very short period of time. Using the wisdom of crowds can help the accuracy of forecasts in some cases because the impacts of individual biases are largely cancelled out. But surveys of expected business trends turn out to be most accurate in stable business environments when simple extrapolation turns out to be the best forecasting tool. It’s less reliable at turning points because people tend to extrapolate from current conditions. Nonetheless, I think it’s always good to examine surveys of expected business conditions, if only because they accurately summarize current attitudes.