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Learn From ConAgra's Forecasting Debacle: Switch To Range Forecasting

July 09, 2014
ConAgra stock recently dropped 7.4% or about $1 Billion in market capitalization when it reduced its earnings forecast from $.60 to $.55/share. Had their previous forecast been a $.55-$.60/earnings per share range instead of a firm $.60/share, no one would have noticed. Learn from this. Switch from single-point to range forecasting now.

ConAgra’s CEO Gary Rodkin said the miss “was driven by two key factors; one, weaker than planned Consumer Foods volumes, and two, significantly lower profitability in our Private Brands operations.”

They had expected Consumer Foods sales of almost $1.9 billion (down 3% vs. prior year) but ended up with sales of $1.8 billion (down 7%).

Their forecast meant something totally different if:
  • $1.9 billion was the absolute maximum they could sell if everything went right,
  • $1.9 billion was the bare minimum they were going to sell even if everything went wrong,
  • $1.9 billion was the most likely forecast.

These might have translated to:
  • somewhere between $1.7 billion and $1.9 billion
  • somewhere between $1.9 billion and $2.1 billion
  • somewhere between $1.8 billion and $2.0 billion

The issue is not that people lie in their forecasts (though some do). It’s that different forecasts mean different things to different people and lead different people to expect different things.

Don’t believe precise forecasts. As Wharton Professor Leonard Lodish puts it, “It’s better to be vaguely right than precisely wrong.” So, push for a range and for an understanding of the scenarios that lead to the range.

Net, range forecasts with explanations give you more and better information than do single-point forecasts. Switch to range forecasts.

 

Tighten the Range

Once you’ve done that, work on ways to tighten the range.

Jeff Fotta is the president of Gryphon Networks, a company that makes sales intelligence and marketing compliance solutions for distributed workforces.  Their cloud-based technology collects and analyzes call data from any device to transform sales activity into actionable sales intelligence. It removes that subjective bias of sales rep CRM input, to produce more accurate sales forecasts and teach underperforming sales people best practices gleaned off of the top-performing ones. Sales Intelligence helps sales managers get clearer visibility as well in three ways... Read More at Forbes.com