How to Forecast When History is No Longer Relevant
By Janet Dorenkott, VP and Co-owner, Relational Solutions, Inc.
During the first day of IE Group’s Consumer Packaged Goods Forecasting and
Planning Summit last week, almost every speaker reiterated that historical
trends and year-over-year comparisons do not carry the same weight that they
have in the past. And although these metrics are still valuable for forecasting,
many other factors now need to be considered due to the rapidly changing
economy and buying behaviors of consumers.
One of the main thoughts behind this reconsideration of traditional methods
is that consumers are saving again and, thereby, taking money out of the
market. Pat Conroy of Deloitte Consulting estimated that if consumers save
just seven percent more than they have in the past – not an unlikely scenario,
according to his research – they will be removing $500 billion from the economy.
He also made an excellent point that, as consumer spending goes down, a greater
percentage of the money that they do have to spend may be allocated toward
services vs. products – his theory being that their expendable income will
go toward fixing products they already own to stretch their investments.
We also heard in the presentations that there is a new attitude – "Frugal
is cool." People are buying fewer luxury items. Even those consumers
who can afford them are leaning toward purchasing less conspicuous and more
"everyday" products. Another factor affecting purchasing is the
general fear in the market coming about due to the government’s explosive
spending, the housing crisis, the banking and auto crisis and more.
Tim Weidenhaft of General Mills echoed the sentiment that shifts in demand
patterns due to economics also makes purchase history less relevant. He pointed
out that this is causing higher demand volatility and a resurgence of coupon
A key sentiment in many presentations was that automating the integration
of POS scan and forecast data and integrating it with things like promotions,
shipments, forecasts and orders through applications like POSmart, is a critical
factor. Also, leveraging panel data, weather trend data, syndicated data
and even economic data that can be purchased through third party sources
are several more ways to improve forecasts.
Discussion Questions: Given the current trends in consumer spending (and
saving), what factors in addition to historical trends should be used to
help determine your forecasts? What other impacts from the economy should