TAKEAWAYS FROM ACCELERATED ANALYTICS’ GS1 CONNECT 2016 SESSION: ‘The Importance and Value of Data Sharing – Using Point-of-Sale Data to Deliver Outstanding Customer Experiences’

I had the opportunity to lead this session last week and came back with some takeaways that I wanted to share, as I feel they are reflective of the state of retail today and how retailers and vendors are using point-of-sale data to manage their business in this time of OMNI-channel, customer-experience driven retail.

Customers want a single-vision of brands and be able to have a consistent, complete and winning experience every time they shop, in whatever channel they shop in. To ensure products are available when and where the customer shops, retailers need real-time inventory visibility, a seamless order management system and the ability to deliver. Retailers and brands realize they need to work together to have both a single view of the customer and a single view of their data in order to be successful.

Some interesting, yet not surprising, statistics were gathered from the retailers and vendors represented in the room. When asked about managing their POS data week to week, 66% were using POS data that was not provided via an EDI 852 file, eliminating their ability to automate the collection and processing of the data electronically, and instead having to work with multiple sources and formats of data. This process of data management and then trying to create usable reports to have meaningful partnership conversations between retailer and vendor is extremely time consuming: 83% of the retailers in the room spend 11-50+ hours per week managing and processing their POS data. More staggering was 95% of the vendors in the session were spending 11-50+ hours per week: 30% spending 11-20 hours, 40% spending 25-50 hours and 25% over 50 hours per week!

The good news is over half of the attendees in the room felt they are getting better at managing and using POS data each week, but 30% still admit to ‘Barely Using’ their POS data. Recognizing that heavy resources are needed to use POS data, especially on the vendor side, is making vendors ask, “Do we build an in-house solution to manage this, or outsource it?” CLICK HERE for an infographic detailing the pros and cons of each, and the differences in resource and financial investment.

Based on the time and effort being made by most of those represented, it is clear that POS data sharing is important for effective collaboration between retailers and vendors to “get it right for the customer”. POS data can be used to not just track units sold overall, but can give product/store level details on out-of-stocks, weeks of supply, sell thru %, average sales, geographic trends, inventory investment and lost sales opportunities. CLICK HERE for our industry sell thru % guidelines infographic.

We need to do everything we can to exceed our customers’ expectations and deliver an outstanding experience for them when they come across our brand. Sharing POS data and then using it to partner together to analyze it will help shape the customers’ experiences and give us inventory visibility and fulfillment across channels to meet customer expectations.

Want to learn more? Contact Jennifer@AcceleratedAnalytics.com to start a conversation. CLICK HERE to download whitepapers on analyzing POS data like a pro.

- Jennifer Freyer, Director of Sales and Marketing, Accelerated Analytics

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.