All posts by Tara McAdams

You can mark this down. Retailers preserve margin with predictive demand analytics.

Content by Planalytics

As the global supply chain issues subside and retail buying departments revert to more normal purchasing practices, markdowns will reemerge as a profit-busting challenge to manage and mitigate.

For retailers, the misalignment of inventories with consumer demand often leads to lost sales due to out-of-stocks or higher markdowns when they have overestimated demand. Revenue, profit, and shopper experience all take a hit when an item is not available when a customer wants it. On the other hand, going heavy on inventory as a way to avoid lost sales comes with huge costs.

A survey conducted by Coresight Research and Celect estimated that non-grocery retailers in the U.S. absorb markdown costs of about $300 billion annually, or about 12% of overall sales.

Markdowns are a costly expense but also an area of opportunity for retailers. So how do retailers use analytics to proactively address markdowns and enhance profitability?

Using Predictive Demand Analytics to Optimize Inventories

The above mentioned research found that “misjudged inventory decisions—including overbuying, buying the wrong type of products and misallocating inventory—account for an estimated 53% of unplanned markdown costs for retailers”. Diving into root causes, the report identified that the largest factor leading to unplanned markdowns was “reduced demand due to external factors such as unseasonable weather, sudden changes in consumer behavior and competitors’ unplanned promotional activities”.

Traffic levels (store and online) and the sales of particular products in specific locations do vary significantly from day-to-day and week-to-week due to changes in the weather. In fact, no other external variable influences demand shifts as frequently, meaningfully, and directly as the weather.

Ignoring the influence of the weather can increase markdowns and negatively affect profitability. Planalytics’ experience working with retailers has shown that leveraging predictive weather-driven demand analytics, both ahead of the selling season and during the end of the season when markdowns come into play, can preserve margin in several ways.

Weather-driven demand metrics isolate and quantify – as a percentage or in units – the influence that the weather has on sales. These metrics can be calculated months ahead for planning and merchandise allocation purposes (e.g. -15% weather-driven demand for Sweaters in Boston in October compared to the prior year) and recalculated in-season to factor in forecasted weather conditions (e.g. +28% weather-driven demand for Barbeque Grills in the southeast this weekend).

3 Ways to Limit Markdowns with Weather-Driven Demand Metrics

Markdown optimization can be a big contributor to profit enhancement. Retailers can expect to improve their gross margins by anticipating demand better and ultimately reducing markdown costs. Here are three ways to apply the analytics and profit:

• Pre-season planning & allocation: When retailers plan the next season or year they must correct the weather bias embedded in past sales performance. This “deweatherization” process improves accuracy by accounting for when favorable weather conditions exaggerated sales or unfavorable conditions deflated sales. In situations where prior sales are inflated, the positive weather environment rarely materializes to the same degree again the next year. The result: retailers often end up with excess inventories that need to be marked down to clear stocks. So instead of unintentionally chasing weather-biased sales from the prior year, which are statistically unlikely to repeat, retailers can use weather-driven demand to improve plan accuracy and adjust inventories on a market-by-market basis. As a result, excess stocks are trimmed in markets that will not match strong comp sales levels, reducing eventual markdown costs. Moreover, retailers can increase inventory levels in markets that are likely to rebound strongly from weak, weather-dampened prior year sales. This results in fewer lost sales where consumer demand is elevated.

• In-season markdown decisions: The next opportunity to proactively manage markdowns presents itself in-season, after sales have peaked. By considering when, where, and how much the upcoming weather will impact consumer demand, a retailer can take advantage of favorable conditions to delay markdowns for a period of time or reduce the depth of markdowns (e.g. 30% off instead of 50% off). There is no reason to throw away margin if the weather will be boosting demand naturally. For example, a December or January snowstorm may produce strongly positive weather-driven demand projections for hats and gloves and snow blowers and more in affected markets. The retailer that adjusts the timing or degree of markdowns can capture more higher-margin sales on their snow categories while still drawing down inventories as the season winds down.

• Digital marketing to drive more full-priced sales: Targeting audiences that will be experiencing a positive weather backdrop increases message relevancy and conversions and is yet another way to leverage weather-driven demand metrics. Take a situation where a particular region has had soft sales, and stores are currently carrying excessive inventory that will eventually need to be marked down. If a favorable weather-driven demand environment is on the way, ramping up digital advertising in these markets would help drive sales that reduce stock levels at full price or before deeper markdowns become necessary. Businesses consistently capture larger than expected sales boosts when they coordinate marketing activities to capitalize on favorable, weather-assisted demand environments. More effective, targeted deployment of advertising spend is a proven way to increase sales overall, and in many cases, reduce the very inventories that could most use a helping hand before turning to the blunt and profit-eroding instrument of markdowns.

Retailers that use proven predictive demand analytics stand to reap a variety of financial benefits that come from aligning inventories with consumer purchasing trends. With visibility into how the key external factor of the weather will influence demand, retailers can smartly plan and manage inventories across stores and regions in a way that minimizes markdowns and preserves margin without sacrificing availability and sales. Learn more by visiting www.planalytics.com.

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Weather Permitting: How to Use Weather Data in Retail Forecasting

By Evan Gold, Planalytics

Retail is detail. And there is a lot of ‘detail’ for retailers to manage and factor into the business every day. When it comes to external variables, nothing is more consistently and directly impactful on demand than the weather.

This is because the weather influences consumer buying behavior everyday – and it never stops changing; no other external variable shifts demand trends as immediately, frequently, and meaningfully. Despite knowing all this, too many retailers ignore the impact of weather and this adds error to plans and demand forecasts.

How Weather Influences Retail Demand

In an NRF post, I shared five myths of the impact of weather on retail sales:

1. You can’t plan for the weather.

2. It all evens out in the end.

3. Consumers will shop during the holidays, regardless of the weather.

4. My products aren’t seasonal, so the weather doesn’t affect me.

5. I’m an online retailer — the weather doesn’t impact me.

Let’s face it: the influence of weather on your consumers’ behavior is complex and nuanced, and temperature or precipitation data is easily misinterpreted and misused. And even though meteorology has come a long way, weather is a notoriously fickle and uncontrollable factor, and no forecaster can reliably predict it beyond the next few weeks.

Because of this, it’s understandable that many retailers believe planning for weather’s impact on sales is an impossible endeavor. However, ignoring the effect of something with such a profound impact on consumers’ day-to-day lives can lead to severe miscalculations in everything from sales and inventory to markdowns and staffing levels.

Predictive demand analytics gives retailers the visibility they need to proactively adjust planning, allocation and replenishment decisions based on when, where, and how much changes in the weather will influence purchasing.

Using weather data for retail forecasting starts with measuring the impact of weather for specific items, time period, and locations. Once the relationships are defined, you can incorporate weather-driven demand analytics across various time horizons–past, present, and future–to align with key retail functions.

How to Use Weather Analytics in Retail Forecasting

The impact weather has on consumer demand will vary by product, time of year, and location. Aligning these impacts across key retail functions is best completed in a scalable and sustainable manner.

Through systemic integration, the quantifiable impact of weather can be applied to critical activities and processes in the merchandising life cycle as well as core business functions such as reporting and analysis. These include:

• Planning: Weather normalized demand planning to improve forecast accuracy across specific products

• Allocation: Increase sales and minimize markdowns by aligning store inventories ti weather-based shifts in sales

• Replenishment: Improve product availability by factoring in the weather’s impact on demand over the coming weeks

• Performance analysis: Weather-adjust sales provide a clear picture of true performance

• Marketing and advertising: Optimize spend, offers, and messaging with weather-driven demand based on expected weather

• Forecasting: Improve topline business forecasts and budgeting

What are the Benefits of Using Weather Analytics in Retail Forecasting?

By applying weather analytics across the business, retailers can add up to a 2% to total topline sales. Better availability leads to more sales and profit. Predictive weather analytics also help on the expense side of the ledger. Inventory costs, markdowns and shrink are three primary examples.

Improve retail forecast accuracy by up to 30% across specific product areas.

Increase sales by reducing out-of-stocks: Having product available when shoppers want it drives sales and customer satisfaction and loyalty. By optimizing inventory and decreasing lost sales due to stockouts, retailers can boost net Income by 2 to 6%.

Improve margins: By better aligning inventories with market-level demand, retailers can expect a 20 to 70 basis point profit lift through higher sales, lower inventory costs, and/or by optimizing the timing and depth of markdowns. Retailers selling fresh products can generate millions of dollars in cost savings annually by reducing perishable shrink by 10-35%.

• Optimize digital marketing: Retailers can improve conversions when they use weather analytics to make messages more relevant and make smarter decisions about where to allocate spend. Targeting favorable weather time periods and regions/markets enable companies to capture sales from receptive audiences and improve ROAS (return on advertising spend) and other key metrics.

When you model and subscribe to weather “signals” across products, categories, stores, and regions as part of your retail planning process, each unique signal delivers additional context and clarity into the effect of weather on your business.

Planalytics weather-driven demand analytics integrate with ToolsGroup retail planning solutions including demand forecasting, dynamic retail allocation, and replenishment software.

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Planalytics Planting Season Outlook for North American Agriculture and Global Market Update

Planalytics Planting Season Outlook for North American Agriculture comes at a critical time for global commodity traders, marketers and other agribusiness professionals. Dryness and drought across the central US continue, raising concerns about domestic Winter Wheat yield potential as the crop emerges from dormancy.

Join Planalytics AgriBusiness Insights team as we look at how weather is shaping up across North America heading into spring. Also participating at this critical juncture will be Sterling Smith, Director of Agricultural Research at Sompo International to provide color on global markets following Russia’s invasion of Ukraine.


Speakers will include: 

  • Sterling Smith, Director of Agricultural Research, AgriSompo North America
    A veteran of the industry, Sterling Smith is well known across North America and Europe and a regular contributor on Bloomberg, CNBC and Reuters. Prior to joining AgriSompo North America, Sterling’s career has taken stints at Bloomberg where he led the Agricultural product, Citi, as head of Agricultural Research, CHS and as an introducing broker for various firms at CBOT.
    .
  • Michael Greve, Director of Meteorology, Planalytics, Inc.

*There is no cost to attend, but registration is required (registration link below).

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ToolsGroup Partners with Planalytics to Bring Weather-Driven Analytics to Retail Planning

Retail planning customers can isolate, measure, and manage the influence on weather on their businesses

BOSTON, February 16, 2022: ToolsGroup, a global leader in supply chain planning and optimization software, has partnered with Planalytics to integrate their weather-driven demand (WDD) analytics with ToolsGroup’s retail planning solutions, enabling customers to isolate, measure, and manage the influence of weather on their businesses. This added insight ultimately results in increased forecast accuracy, more optimized inventory, and fewer lost sales as a result of sales-driven weather volatility.

ToolsGroup’s retail causal engine allows customers to take Planalytics’ WDD models and subscribe to weather impact analytics across products, categories, stores, and regions, with their metrics quantifying both historic and projected weather-based changes in demand. From merchandise class/sub-class/SKU-level to historical sales data, customers can capture the specific data points most important to their business.

Planalytics weather-driven demand analytics integrate with ToolsGroup retail planning solutions including demand forecasting, dynamic retail allocation, and replenishment software.

“We are thrilled to partner with ToolsGroup, enabling customers to proactively manage the impact of weather at scale,” said Frederic Fox, Planalytics Chief Executive Officer. “The seamless integration of predictive demand analytics into the industry leading retail planning solutions from ToolsGroup will help businesses quickly achieve meaningful benefits.”

“We’re excited to be able to offer customers weather-based demand insights from Planalytics,” said ToolsGroup Global Product Management Director Brett Bever. “Weather is constantly influencing consumer buying behavior, and is a crucial external variable to include in retail planning to boost top-line sales.”


About Planalytics
Planalytics, Inc. (www.planalytics.com) is a global leader in predictive demand analytics that enable companies to understand the customer context driving buying decisions and take action at scale. Planalytics provides product-specific, localized demand adjustments that isolate and quantify the consumer’s relationship with the weather. With visibility into weather-based demand volatility, retailers and other consumer businesses are able to enhance core processes including planning, allocation, replenishment, reporting, and digital marketing.

About ToolsGroup
ToolsGroup is how organizations improve product availability while right-sizing inventory, no matter how complex their supply chain is or how much demand changes. In a world that rarely follows the rules, our retail and supply chain planning suite optimizes and automates supply chains from production to purchase, enabling manufacturers, distributors and retailers to be ready for anything. That’s why global leaders like Absolut, BP and Harley-Davidson rely on us year after year. For more information, follow ToolsGroup on LinkedIn, Twitter, YouTube, or visit www.toolsgroup.com.

 

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Demand Planning Could Help Retailers Dig Out After Winter Storm Landon

By Kari Hamanaka

. . . “Usually storms like this, as impactful as they can be, typically the impacts are limited and minimal from a pure supply chainperspective,” said Evan Gold, executive vice president of global partnerships and alliances at Planalytics. “I think businesses do a good job getting out ahead of these events. I know it’s a big storm, but it’s winter. It’s the middle of winter right now. It’s a large storm. I think the bigger issue is more on the demand side and have those businesses made the adjustment for the pending demand swings that we’ve seen.”

Planalytics provides predictive demand analytics to help companies measure and understand the impact of weather on specific products.

Businesses, from logistics firms to retailers, typically have enough time ahead of major storms to plan store inventories or set out contingency plans, Gold pointed out. Retailers that know a storm is coming may ship out boots or thermals to stores in the affected part of the country ahead of the storm.

“The customer’s going to buy in advance of a storm when they can still go to a store. The same goes for a transportation company,” Gold said.

The storm this week is expected to bring heavy snow, sleet and freezing rain to various parts of the central United States and then move to the interior portion of the Northeast, according to an alert from the National Weather Service on Wednesday. The service’s warning for the storm, which was named Landon, spans from parts of New Mexico to Vermont with reports pegging some 90 million people in its path. . . .

. . . Ultimately, for the apparel industry, Planalytics’ Gold said storms such as the current one “tend to be a net negative,” pointing out clothing is a discretionary purchase.

Categories likely to see sales lifts this week include outerwear, hats and gloves and thermals, according to Gold. Any early spring merchandise rolled out onto sales floors may temporarily slow in parts of the country impacted by the storm.

“All of those spring categories or early spring categories, those are obviously the ones that you’re going to see the big hit on,” Gold said. “But, there’s still time. This is week one of the retail season. Typically, this is one of the slowest times.”

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NRF’s Latest Holiday Report Paints a Pretty Picture for Retail

By Glenn Taylor

. . . Now, the National Retail Federation’s unofficial results indicate that November-December sales grew 11.5 percent, outpacing initial estimates of 8.5 percent to 10.5 percent for a projected $843.4 billion to $859 billion haul, Katherine Cullen, NRF senior director of retail and consumer insights,said in Friday’s webinar hosted by predictive demand analytics platform Planalytics.

“This is historic, particularly when we consider the fact that last year we saw growth of about 8 percent for the holiday season,” she added. “As we look to the future, those comps may be hard to match, but definitely speak to where the consumer is and what we are expecting.”

NRF backed up the idea that November may have buoyed holiday sales overall, with 61 percent of consumers starting their shopping by early in the month, according to the trade group’s November Consumer Holiday Survey. Early November shoppers have been growing in number each of the past three years, totaling 59 percent in 2020 from 56 percent in 2019 and 55 percent the year prior.

NRF’s data suggests that fewer shoppers now wait until the last minute to buy their final round of gifts. Forty-two percent of shoppers said they bought their last gift at least one week before Christmas Day, more than the 40 percent who did last year. In 2017 and 2018, this number was as low as 34 percent, NRF said.

“One of the key reactions to the supply chain disruptions is that retailers really started communicating to consumers early about shopping for the holidays,” Cullen said. “They were encouraging consumers to start their shopping early, and to allow for the curve of demand to be flattened and also to allow for more time if new inventory was coming in. If there were delays or items were backordered, this could allow for more time for their items to get to shoppers.”

Beyond supply chain disruptions, Cullen indicated that earlier Thanksgiving and Black Friday promotions played a role in the November shopping push, as 49 percent of consumers took advantage of some form of head-start holiday sales before Thanksgiving.

However, it seems retailers maintained their promotional cadence throughout the season, as 56 percent of shoppers felt the early deals were the same as offers that came later on in the season, up from 53 percent in 2020 and up from 48 percent in 2019.

“That says to us that shoppers felt that they were finding good Thanksgiving-type deals early in the season, well before the Thanksgiving holiday,” Cullen said.

Nevertheless, 65 percent of shoppers said they would continue holiday shopping after Dec. 25, indicating that they still plan to pounce on holiday sales and promotions, and redeem gift cards they received during the season. . . .

. . .

Weather events can’t be ignored in 2022

Turning to 2022, retailers must better assess the impact that weather can have on their operations. Weather has a larger economic influence on the holiday season than any time during the year, Evan Gold, executive vice president, global partnerships and alliances at Planalytics, said during the webinar.

For example, disruptive weather like a blizzard would keep shoppers at home, while warmer, dry weather naturally encourages store traffic. While November averaged the coldest temperatures since 2019, it was also the driest with the least snowfall in four years, meaning shoppers had fewer obstacles to visiting stores, Gold said, adding that the reasonable weather likely drove a higher percentage of seasonal buys.

“The weather directly influences the items that consumers are putting into their shopping carts,” Gold said. “Both physically as well as virtually, consumer purchasing is directly correlated to the weather conditions when and where they’re doing their shopping. When consumers are shopping in cold weather, they’re more likely to put those seasonal items into their baskets as well as purchase hot foods and drinks as they shop. In warm weather locations, shoppers can increase purchasing of categories like electronics, home goods and outdoor categories.”

In total, Gold said there were 18 individual weather-related events that cost the U.S. over $1 billion each.

He cited numerous disruptive events in 2021 that drove or dampened demand for certain products, including the historic February freeze in Texas, the triple-digit Pacific Northwest heatwave in June, Hurricane Ida in August and September, the wildfires that ravaged the Western U.S. throughout the summer and early fall, as well as the deadly tornadoes that touched down in Kentucky and Illinois in December.

These events illustrate the volatility in today’s climate that retailers can’t afford to ignore, Gold noted.

“Volatility is the new normal, and if you’ve not quantified the impact of these events on your business, you’ve already built errors in the year 2022 forecasts,” Gold said. “The impact of the weather is known. Accounting for this impact as you build your 2022 plans will bring improvements to your demand forecast accuracy, would also drive financial gains and optimize your inventory levels.”

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