How to Increase Productivity of Promotional Forecasts

Promotional forecasting poses many challenges for both retailers and suppliers, but using retailer point-of-sale and inventory data to calculate missed opportunities can yield more accurate sales predictions.

With access to retailer sales data from past promotions, suppliers can use templates and proprietary algorithms from Retail Solutions Inc. to calculate the missed sales opportunities due to out-of-stocks for specific items on a store-by-store basis. By combining this information with a view of the retailer’s inventory levels while planning the next promotion, the trading partners can better work together to calculate an optimal order size for each store.

Retailers, juggling tens of thousands of SKUs and multiple promotions at any given time, might not always have the resources to accurately forecast sales of a single item on promotion. Suppliers, meanwhile, lack an accurate, store-level view of retailers’ sales from previous promotions.

Using retailer data facilitates constructive discussions between trading partners around promotional planning by putting both parties on the same page from the start. Suppliers who use RSi templates and algorithms also play a more active role in maximizing the ROI of their own promotional spending.

With RSi’s next-day delivery of store-level data, the numbers are timely and location-specific, an advantage over other data sources that might be aggregated for an entire banner and compiled less frequently. This allows for forecasting adjustments and fine-tuning that would not otherwise be possible.

Battling Out-of-Stocks

The challenges of forecasting are compounded by the inaccuracies that out-of-stocks add to forecasting efforts. Failing to factor in the negative impact that out-of-stock conditions have had on sales in previous promotions can lead to erroneous forecasts, which can perpetuate problems with product availability on the shelf.

Out-of-stocks are a pervasive challenge with multiple causes and myriad ramifications, but the problem can be especially acute during promotions.

A landmark 2002 study supported by the Grocery Manufacturers

Association and Food Marketing Institute concluded that the

worldwide out-of-stock level for fast-moving consumer goods

(FMCG) was about 8.3%, leading to a 4% reduction in sales.

Many of the causes of out-of-stocks may lie within the stores

themselves, such as poor shelf replenishment, but often faulty

forecasting is to blame. The study found that 47% of out-of-

stocks could be attributed to poor sales forecasts, resulting in

inadequate inventory.

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How to Increase Productivity of Promotional Forecasts

In addition to the lost sales opportunities, out-of-stocks have other significant impacts on both retailers and suppliers, according to a 2008 follow-up study supported by GMA, FMI and the National Association of Chain Drug Stores.

For retailers, out-of-stocks contribute to a decline in store loyalty and decreased customer satisfaction, plus increased operational costs incurred

when store personnel spend time searching for items in back rooms or conducting unplanned shelf stocking.

Of course, out-of-stocks can also misinform subsequent forecasts by leading to an inaccurate view of actual product demand, both for the promoted item and for any items that shoppers might have substituted for it. This distortion of actual demand can impact manufacturers’

production levels.

For manufacturers, out-of-stocks can also lead to trial of competitors’ brands and loss of brand loyalty and brand equity.

Of particular note is the negative impact that out-of-stocks have on promotional effectiveness. The 8.3% out-of-stock rate cited in the GMA report could be double during promotions, according to some reports.

For manufacturers, out-of-stocks can also lead to trial of competitors’ brands and loss of brand loyalty and brand equity.

BATTLING OUT-OF-STOCKS(continued)

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“They can leverage RSi’s proprietary algorithms to ask, ‘If we were in stock the whole time, what could we have sold through?’” explained Tom Gregorchik, sales engineer at RSi.

For example, if a store sold 100 units of an item during the previous promotion, but was out of stock for five days, the supplier can calculate a more accurate forecast for that specific store by using the RSi templates to estimate what sales would have been if the store had not been out of stock on those five days. Data is also available to understand past price points so when any new pricing strategies are introduced, they can understand what the anticipated demand is at a chain level all the way down to the store level.

When the supplier then meets with the retailer to discuss an upcoming promotion, or to examine a recently completed one, their discussion will be enhanced by this analysis of specific missed sales opportunities. The trading partners can together calculate how much product needs to be shipped to each store based on the retailer’s available inventory.

During RSi user groups, where the company’s customers share their best practices, suppliers often talk about how they leveraged RSi’s capabilities to create a better relationship with the retailer around promotional forecasting.

This methodology also places more responsibility for inventory levels in the hands of the supplier, whose promotional dollars are at risk when faulty forecasts lead to out-of-stocks and reduced product sales.

“Suppliers are paying for promotions, and not always getting the full benefit of the true demand at the store level,” Gregorchik said. “They are showcasing their products in the circular and having endcaps to stimulate demand, and many times the shelf is swept clean.”

In one example of promotional forecasting using RSi’s tools, a maker of personal care products was able to calculate sales lost due to out-of-stocks at the store level and worked with the retail partner to execute the forecast. They were then able to evaluate inventory levels at the stores and the retailers DC and plan their own internal shipment forecast accordingly. That led to a 20% lift in unit sales during the one-week promotion at one retail chain, compared with the previous five similar promotional periods.

“They can leverage RSi’s proprietary

algorithms to ask, ‘If we were in stock

the whole time, what could we have

sold through?’”

-Tom Gregorchik,sales engineer at RSi

Using RSi to Enhance the Discussion

Suppliers can use the RSi templates to see key data from previous promotions, including product volumes sold through by item and by store. Combined with a view of inventory levels, this allows suppliers to use RSi to calculate a range of values for the missed sales opportunity from out-of-stocks.

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In another example, an analysis of a supplier’s eight-week seasonal candy promotion in a drugstore chain showed that an increasingly large percentage of stores became out-of-stock as the holiday approached. In the last two days of the seasonal promotion — when sales should have been the heaviest — 27% of stores were out of stock on a promotional item Using RSi’s templates and proprietary algorthims to understand the true opportunity, the trading partners adjusted their forecast for a subsequent holiday and saw a sharp increase in sales of the promoted items.

The analysis should be focused on high-volume products to maximize the impact of the forecasting adjustment.

Suppliers need to collaborate closely with the retailer’s forecasting specialist to determine specific details, such the timing of the analysis or whether certain stores should be excluded.

A follow-up meeting should be held immediately after a promotion to plan the next one while memories are fresh and to capitalize on the availability of daily sales data.

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CONCLUSIONS DRAWN FROM THESE EXAMPLES:“They are putting

their products in the circular, and the products are

out of stock, or they are paying

for an endcap, and the shelf is

swept clean.”

-Tom Gregorchik,sales engineer at RSi

The RSi system also includes price elasticity models to allow for forecasts based on variations in the promotion. The suppliers can see two years of history to examine the relationship between price and demand.

Evaluating price elasticity can be especially valuable when stock is limited, so that a reasonable price point can be established to maximize sales without out-of-stocks.

Suppliers using RSi will generally have visibility into inventory both at the store and DC levels.

With a view of a retailer’s inventory, suppliers can see how many days’ worth of supply are already available. If the retailer was overstocked, it would indicate to the supplier that an order might not be forthcoming, and shipment levels can be adjusted accordingly.

The key ingredient in promotional forecasting using RSi templates and algorithms is the data itself — which is the retailer’s own POS and inventory data that is being shared with the supplier.

Traditionally suppliers have had to come up with their own data to forecast sales, which can often be at odds with the data that a retailer is using to make a forecast for the same promotion.

Because RSi uses the retailer’s own POS data to populate the templates, and the suppliers are simply running an analysis of the data, conversations

occur more readily about why the promotion might not have run well the last time, and what adjustments are needed.

“That first step has already been bridged — the retailer has confidence in the accuracy of the data,” said Gregorchik.

PRICING ADJUSTMENTS

DATA IS KEY

BATTLING OUT-OF-STOCKS(continued)

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Timely UpdatesThe timeliness of

the data is another

advantage RSi has over

syndicated providers,

since it provides next-

day POS data from the

retailer. That can be

especially helpful in new-

product forecasting.

Suppliers can see on a

daily basis if there are

certain stores or certain

regions where a new

product or product

variety is performing

better relative to other

stores or regions, for

example. They can also

adjust their production

levels to accommodate

higher-than-expected

demand.

“With new items, there’s

no history, so it is a little

bit more of an art than

a science,” Gregorchik

said. “But with RSi in the

picture, it becomes more

of a science.”

ConclusionUsing retailer POS and inventory data to forecast sales volumes for seasonal offerings and product promotions can help reduce out-of-stocks and drive increased revenue.

Suppliers who leverage the templates and proprietary algorithms offered by RSi can generate more accurate promotional forecasts. By using the retailers’ own sales and inventory data, suppliers also open the door to a more productive dialogue with the retailer by eliminating disputes over data.

RSi data is also store-specific and timely, allowing for fine-tuning of promotional forecasts that would otherwise not be possible. Suppliers who use RSi templates and algorithms assume more responsibility for forecasting, allowing them to maximize the ROI of their promotional spending.

To learn more about how to leverage RSi in promotional forecasting, visit www.retailsolutions.com.

RSi Forecasting | www.retailsolutions.com