As technology upgrades, so too will the back office for c-store operators. With automation and artificial intelligence (AI) as tools to drive efficiency and a plethora of data becoming available, it’s important to note where retailers should be focusing and what’s ahead for the back office. CStore Decisions reached out to Perry Kramer, managing partner for Retail Consulting Partners, for his take on back-office trends.
{CStore Decisions (CSD)} What technologies are allowing for the biggest efficiencies in the back office today?
{Perry Kramer (PK)} Changes in inventory management related to ordering, allocating, receiving and out-of-stocks are having a big impact on retailers’ ability to keep the shelves full and improve their inventory turns. The ability to get data to central systems in real time or near real time for store and distribution centers and then consume that data in back-office systems to generate and communicate orders to suppliers has had significant impacts on those that can execute it well. However, the learning curve can also be dangerous, resulting in overstocks of slow sellers and out-of-stocks of fast sellers if the product life cycle is not managed from end to end, including space planning on the store selling floor. …
{CSD} Are there any challenges retailers should be aware of as they upgrade their back-office tech? {PK} It is more important than ever to focus on data accuracy and integrity. These are going to be critical to any use of AI tools in the future for inventory analysis and supply chain analysis. As they upgrade their systems, they must focus on building an organization that has a chief data steward that drives integrity of data, the elimination of duplicated data, and ensures accuracy and integrity of data shared with third parties — including suppliers and marketing partners.
{CSD} What key performance indicators (KPIs) should retailers monitor in the back office but often overlook?
{PK} A critical KPI often overlooked is the slow seller or no seller report. Too often c-stores look at inventory turn as an average, which allows problem items to fall through the cracks. The slow seller and no seller report can identify a few critical things: 1.) Items that are just not selling that could be stuck in a stock room and not on the selling floor. 2.) Items just occupying selling space that needs to be converted to profitable space by marking the items down and admitting to a bad buy. 3.)Normally fast-selling items that are entirely out of stock. Focusing on the top items on this report can have a big impact.
{CSD} What back-office trends are you seeing coming down the pipeline for c-store retailers?
{PK} … C-stores are getting much better at leveraging consumer loyalty data. They are driving this through debit cards, rewards at the pumps, food rewards and traditional loyalty cards. The integrity and accuracy of this data is critical to the use of modern tools for consumer segmentation and marketing programs. There will be significant efficiencies in the use of the marketing data in the next few years as the use of AI and analytics moves from “diagnostic” (How did this happen?) to “predictive” and then “prescriptive” analysis … (What will happen?) followed by (How it will happen?).
The other noteworthy change coming down the road is Sunrise 2027, the use of QR codes (2D barcodes). For retailers to take advantage of the additional data contained in these barcodes, significant changes will need to be made in the inventory transactional and point-of-sale scanning and data capture technology. There are significant long-term opportunities in this area, but the systemic changes to take advantage of them is also significant in effort and cost.
{CSD} If a chain could only invest in one area of the back office this year, what should it be?
{PK} It is a combination of improving the accuracy and timing of inventory-related transactions throughout the entire procure-to-pay process. This will involve improving visibility into “clean and accurate” inventory data that can be leveraged for improved ordering, allocation and replenishment. In the c-store space, this is running neck and neck with consumer data for where the biggest AI-driven efficiencies will be seen in the next five years.
