Retailers apply sophisticated data intelligence to cut through the unpredictability of seasonal planning
Product orders for the July 4th holiday were planned months out. Now retailers can reap the fruits of their labor or start moving unsold patriotic gear, fireworks, patio sets and summer paraphernalia to the clearance area if they didn't get their seasonal forecast right.
Right forecasting has become critical at a time of high inventory costs and thin retail margins, which are challenged by consumer resistance to retail price hikes due to rising product costs that retailers have been passing on.
Retailers of all stripes are using optimization software and advanced statistical modeling to determine consumer demand for short-cycle seasons and events. While short-cycle planning is the norm in the apparel world, it is more of a challenge for grocery retailers who are used to fulfilling more predictable weekly Center Store replenishment levels.
The difference is the new green sweater coming onto the sales floor during the winter season with no sales history as opposed to the 14-ounce box of Cheerios with a long shelf life of sales history.
While seasonal merchandise is not grocery retailers' main business, the segment can be profitable if the right strategy is applied after weighing various scenarios that could impact demand.
Yet, there are unpredictable events that no technology or retailer can predict.
Months ago, when orders were placed for all the July 4th celebration merchandise, what retailer would have guessed the demise of Osama bin Laden would result in a surge of consumer patriotism this year with greater demand for patriotic merchandise?
This was a positive indicator revealed in the National Retail Federation's annual Independence Day survey, conducted by BIGresearch, along with consumers indicating greater participation in Independence
Day activities this year, including outdoor cookouts — good news for food retailers.
Weather indicators, always a factor in seasonal planning, appeared brighter for the July holiday weekend.
Berwyn, Pa.-based Planalytics, suppliers of weather data intelligence, forecasts favorable to more moderate weather conditions throughout the country compared to springtime floods and severe weather in the South earlier in the year. North America was trending pleasant in comparison to extremely warm conditions a year ago. Predicting seasonal demand is especially tricky when decisions have to be made months in advance to the run-up of the season.
Fourth-quarter 2011 orders were placed in January and retailers will soon be attending seasonal merchandising events in preparation for 2012.
Cheryl Gherlone, vice president of general merchandise, Efficient Collaborative Retail Marketing, Cleveland, will host a Fourth Quarter Planning meeting, Oct. 2-4, for retailers and suppliers across all channels who buy seasonal general merchandise for Halloween, Christmas and winter. The meeting, which has been held for the last four years, is expected to draw 50 or more retail companies. Among those signed up from the grocery channel are C&S Wholesale, H.E. Butt Grocery, Supervalu, Raley's, Reasor's Foods and Valu Merchandisers.
The high cost of importing seasonal goods, driven by fuel costs and product safety testing costs, is an issue, said Gherlone.
“As a buyer you don't want to buy too early nor do you want to wait too long. It's a roulette game with importing especially for commodity items,” she said.
The Import Price Index, which measures prices paid for goods sold into the United States, has advanced 12.5% over the past year. When fuel is excluded, the index rose 4.4%.
The rising cost of goods and just how much the consumer is willing to pay for imports is one in an ever-growing list of factors retailers juggle in seasonal planning. Gherlone said she wouldn't be surprised if buyers look to buy domestic goods over imports.
Prior to optimization software, which came into play about a decade ago, retailers relied solely on historical data and to some extent their gut feelings to forecast demand, said Marc Dietz, vice president marketing, DemandTec, a San Mateo, Calif., supplier of software and analytic forecast solutions.
While this may work on a week-to-week basis with the same merchandise, price points and predictability of general in-store activity, it is not effective outside the norm such as in predicting new promotions that never ran before that carry higher price points and new items in the mix.
“There are so many factors impacting demand all at once,” said Dietz. Consumer demand modeling gives retailers the ability to factor in variables — price, assortment, promotions, seasonality, competition — all impacting demand.
“Walking the tightrope of being overstocked and understocked has always been a challenge,” he said.
In a whitepaper — “Seasonality and Its Effect on Lifecycle Pricing” — Revionics, a price optimization service provider in Roseville, Calif., defines the seasonal variable as a “predictable cyclic or repetitious behavior in demand for products.”
“Seasonality is intrinsic customer demand independent from fluctuation demand due to casual activities like price or promotion,” explained Jeff Moore, who authored the whitepaper and is vice president of science and innovation for Revionics.
Good demand models project seasonal demand based on historical patterns, usually two years' worth of data, while adapting in-season to deviations from history.
Moore admitted that as good as the science gets it has limited capabilities when it comes to understanding behavior due to deviations like the effect of macroeconomic conditions on behavior. “We have limited capabilities to help with some of those things. There is still an art to it.”
In grocery, it is rare to see substantial increases in holiday-driven demand more than two weeks before the event, with the possible exception of decorative or novelty products tied to the event, the Revionics whitepaper noted.
Generally, grocery tends to exhibit less seasonal variation than other retail segments because demand for food and household goods is year-round. However, some product categories — beer, wine, baked goods and specialty items — naturally enjoy demand increases with their links to Christmas, Halloween, Thanksgiving, the Super Bowl and St. Patrick's Day.
Moore emphasizes the importance of weather in the seasonal equation. “That difference in weather year over year can impact the outcome of promotional events and influence demand.” Revionics incorporates analysis from Planalytics into its season modeling.
On a scale of 1 to 10 with 10 the highest score, Scott Bernhardt, Planalytics' chief operating officer, rates the importance of weather 7.5 on the scale. “There are more important things than the weather,” he said, even though he believes weather matters a lot. He rates competition 9.9 out of 10.
Bernhardt said he can't predict the weather or a major snowstorm two days before Christmas, but he can give an accurate outlook.
“In my business it's not weather but the ability to understand how weather affects people and reverse solve that problem going forward. If you look statistically at Christmas and what most likely the weather will be and how people are going to react, you'll get very close to what Christmas will be like in 2011. You report what is most likely to happen in that window of time and how likely people will react in that situation.”
The process is similar to the Carnac the Magnificent routine played by the late “Tonight Show” host Johnny Carson. Carnac provided the answer first followed by the question. In Bernhardt's case, the answer is the number of product units needed to meet demand followed by the weather forecast for a certain period of time.
The next stage of forecasting drills even deeper to behavioral segmentation based on purchase patterns. Shopper insights have become the secret ingredient especially for grocery retailers who realize in a world of competing formats they can no longer be all things to all people, said Dietz.
“The next level is to treat customers as segments and individuals as opposed to the aggregate average customer,” said Dietz. Retailers want shopper insights implemented at the point of decision and not hidden away unused in the database, he added.
More of this type of analysis is being done as a collaborative planning effort with suppliers and the dialogue is being changed from ‘bring me a plan to grow my category 1% to bring me a plan to grow the health-organic shopper segment in Northern California because I need to boost my share of the market there,” Dietz explained.
He advised retailers to watch out for social media, online shopping and, to some extent, automatic replenishment through online shopping at home as trends that could significantly shift demand in the future.