WARM WEATHER HELPS HOME DEPOT SALES RISE ALMOST 10% IN 4TH QUARTER, AS HOME PRICES INCREASE AND DEMAND FOR NEW HOME CONSTRUCTION STARTS 2016 WITH SLOW GROWTH

The Home Depot’s fourth-quarter sales included an 8.9% sales increase in US stores that have been open for at least one year. This is despite the challenges facing the rest of the retail industry. Sales were strong the entire quarter, but warm weather in December brought in a sales spike – Home Depot attributes $100 million in sales growth to the milder weather. High sales were seen for power washers and pressure-treated lumber by homeowners building decks.

Home prices also rose in December, showing the strongest gains since July 2014. The Home Price Index showed a rise of 5.2% in the 12 months ending in December, versus a 5.2% in November. The national median sale price for a home in December was $213,800, 8.2% from the previous year. There is a limited inventory of homes for sale, and demand for new homes is likely to drive more new construction and help keep a ceiling on the rising home prices, although January 2016 was a slow start for new home construction for the year.

Accelerated Analytics helps Home Depot vendors, such as WM Barr, Hillman Group, Alexandria Molding, and CPG Building Products to manage their sales and inventory data to drive results. Our vendors use our analytical measures, such as sell through, inventory shortages, out of stocks, weeks of supply and consumer purchasing trends, to take quick actions to ensure they are optimizing inventory and growing sales.

Source: Wall St. Journal

Calculating Sell-Thru

Sell through (or sell-thru) is a very useful metric for vendors to use in evaluating item performance, because it provides a composite measure of sales and inventory. But like many business measures, there is more than one method of calculating sell through.

The most common calculation is: Sell Thru % = Units Sold / (Units On-Hand + Units Sold). Sell thru is typically evaluated on a daily basis for fast moving products or weekly for slower moving or replenishment based products.  A higher value is better, indicating your sales velocity is good and your inventory is appropriately forecasted. If sell thru is low, this indicates either poor sales or too much inventory. In most cases, sell-thru for an item is compared in recent periods like current week and last week, as well as in aggregate across several months or even a year.

When evaluating sell-thru, it is also useful to group together products which have been selling for a similar period of time and/or which are sold into the similar store types. For example, comparing sell-thru for a product with 5 weeks of selling activity against a product with 20 weeks of selling activity most likely will not produce a useful comparison. In the same way, comparing sell-thru for a product in a group of stores in a highly affluent area is not likely to compare favorably to a group of stores with a low income level.

Most retail buyers have a set sell-thru percentage they use to judge vendors based on product category or department.  It is important for vendors to discuss the sell-thru expectations with the buyer in order to align with those objectives.

For reference, we've compiled sell-thru percentage data that you can use as a benchmark. The complete infographic includes the sell-thru percentage for eight retail categories each at 8, 13, 26 and 52 weeks. To download the complete infographic, simply complete the form below and we will e-mail you the link to download it.

FOSSIL GROUP EXECUTIVE MOVES TO VERA BRADLEY, INC., AS CMO

Vera Bradley, Inc., has hired Theresa Palermo from Fossil to be its new Chief Marketing Officer. Ms. Palermo will start at Vera Bradley on June 22.

"Theresa comes to Vera Bradley with an accomplished retail marketing background," said Vera Bradley CEO Robert Wallstrom. "She has a terrific blend of creative and analytical skills and a solid track record of building brands, engaging consumers, and driving sales through designing and executing comprehensive marketing programs. Marketing is a key focus for Vera Bradley as we work to create excitement around our brand and introduce consumers to our myriad of new products. We are anxious for Theresa to get started." 

As CMO, Palermo will be responsible for marketing strategies and initiatives that build brand awareness and revenue growth across all of Vera Bradley’s product channels.

Palermo was VP, Global Marketing and PR for Fossil Group. Prior to Fossil, she held key marketing roles with Collective Brands, The Timberland Company and the J.Jill Group.

Vera Bradley, Inc. designs women’s handbags and accessories, luggage and travel items, eyewear, stationery, gifts and baby products.

Both Fossil Group and Vera Bradley, Inc. are customers of Accelerated Analytics, using their POS and Inventory analytics and reporting tools to manage stock levels, store performance, sell thru and sales activity.

Source: Retailing Today 

Calculating Sell-Thru

Sell through (or sell-thru) is a very useful metric for vendors to use in evaluating item performance, because it provides a composite measure of sales and inventory. But like many business measures, there is more than one method of calculating sell through.

The most common calculation is: Sell Thru % = Units Sold / (Units On-Hand + Units Sold). Sell thru is typically evaluated on a daily basis for fast moving products or weekly for slower moving or replenishment based products.  A higher value is better, indicating your sales velocity is good and your inventory is appropriately forecasted. If sell thru is low, this indicates either poor sales or too much inventory. In most cases, sell-thru for an item is compared in recent periods like current week and last week, as well as in aggregate across several months or even a year.

When evaluating sell-thru, it is also useful to group together products which have been selling for a similar period of time and/or which are sold into the similar store types. For example, comparing sell-thru for a product with 5 weeks of selling activity against a product with 20 weeks of selling activity most likely will not produce a useful comparison. In the same way, comparing sell-thru for a product in a group of stores in a highly affluent area is not likely to compare favorably to a group of stores with a low income level.

Most retail buyers have a set sell-thru percentage they use to judge vendors based on product category or department.  It is important for vendors to discuss the sell-thru expectations with the buyer in order to align with those objectives.

For reference, we've compiled sell-thru percentage data that you can use as a benchmark. The complete infographic includes the sell-thru percentage for eight retail categories each at 8, 13, 26 and 52 weeks. To download the complete infographic, simply complete the form below and we will e-mail you the link to download it.

Using Sell-Thru for decision making

Sell-Thru is a key performance indicator for vendors and retailers alike.  Sell-Thru allows one to understand the velocity with which inventory is being consumed as it relates to sales.  Because sell-thru is a leading indicator, it is also very useful for predictive analysis.

When calculating sell-thru, careful consideration should be given to how the formula is constructed.  As with any business metric, there is more than one possible answer, but only one is correct in terms of meeting the business user's needs.

So ask yourself: what is the difference between calculating sell-thru using all available weeks of sales and inventory data as opposed to using the most recent 4 weeks of data?  Both methods are valid, although they may produce very different results.  The first method will tend to flatten out fluctuations due to promotions.  This is useful if the item is on replenishment and operates within established min/max guidelines.  The second method of calculating sell-thru, using the most recent 4 weeks of data, tends to provide a rolling snapshot of performance.  This is very useful if an item is  highly promoted and one wants to understand the impact of lift within a given promotional window.

Both methods are correct, but one will be more useful than the other to business decision makers at your organization.  Here are three best practices to make sure your team arrives at the most useful method:
1)  Have simple design sessions with business users to write out on a whiteboard all calculations.
2)  Discuss if the calculation supports the intended business decision.
3)  Adjust the formula accordingly.
4)  Identify low, middle, and upper performance conditions for each metric so exception dashboards can be created.
5)  Document your work in a place all team members can access so there is no confusion on how the calculation is performed, or how the performance conditions are aligned.