Virtually all retailers are looking to trim expenses while increasing traffic and conversions, and their eyes often fall on the same area for cost-cutting: labor. When my retail customers ask me how to reduce labor costs, my answer is always the same: “Don’t cut staff. Find ways to increase productivity and revenue with the people you have.” This approach is simple with the help of an advanced analytics solution, such as prescriptive analytics. Prescriptive analytics is a software solution that leverages AI and machine learning to analyze data and determine:

  • What is happening
  • Why it happened
  • How much it costs not to act
  • What to do to optimize the outcome
  • Who should solve it

With prescriptive analytics, the relevant personnel are directed how to make high-impact improvements in the form of simple action steps — many requiring few to no labor resources. Here are some easy ways prescriptive analytics can help increase revenue and productivity, with minimal burden on labor:

Conduct peer-peer cross-training

Every retailer wants to increase sales, and the register presents an ideal opportunity. Store associates can influence customers to make impulse buys via upselling or cross-selling. To optimize results, some amount of sales training may be required. Training is typically a huge investment for retailers, but there’s another, less expensive way to upskill that prescriptive analytics can help identify.

One of my customers leveraged a prescriptive analytics solution to identify revenue opportunities. The solution quickly noticed that many cashiers had a high level of single-item transactions. This indicated the associates could be upselling and cross-selling their customers to expand their baskets. To increase basket size, the prescriptive analytics solution automatically directed the retailer’s store managers to adjust employee schedules to pair the associates with lower numbers, with those who had a higher average basket size. This peer-peer training quickly resulted in a significant sales lift for the retailer — and no expensive training or additional hiring was required.

Optimize scheduling based on traffic

Scheduling is an inexact science for retailers. Too many associates will result in excessive downtime, but too few will negatively impact the customer experience. The number of variables at play make staffing levels difficult to predict, which is why many managers may end up guessing. Retailers who optimize their staffing can see huge cost savings.

Prescriptive analytics can add much more precision to the scheduling process. It can analyze data from demand patterns, foot traffic, sales trajectories, and more, to determine the best number of associates to schedule at a given time. Some solutions can also determine when additional labor resources should be drawn from other departments, and alert front-end managers to take action. The goal is to align the system of planning (i.e. projected staffing needs) with the system of reality (i.e. actual staffing needs today/tomorrow) while having the flexibility to adjust it as close to demand sensing as possible. Prescriptive analytics can accomplish all of the above.

Optimize placement of complementary items

Most retailers are very familiar with the concept of complementary items, or two or more items that are frequently purchased together. These combinations may be intuitive (e.g. shampoo and conditioner), unexpected but justifiable (e.g. diapers and alcohol) or less obvious (e.g. dining-room chairs and premium kitchen pans — more people around the dinner table calls for better-quality cookware!). Retailers with visibility to these complementary items can maximize store sales without asking anything extra of their associates.

Prescriptive analytics can provide that visibility. The right “pattern” (an algorithm that looks for specific things in data) can analyze millions of historical transactions, identifying specific combinations of items frequently found in customers’ baskets. It can then automatically send out a prescriptive action to merchants, directing them to pair these complementary items. The result is not only an increased occurrence of impulse buys (read: more revenue) but also a better shopper experience from customers having an easier time finding items they unknowingly want.

When the time comes to address labor costs, layoffs should be a last resort. Investing in the right technology, like prescriptive analytics, can help offset expenses by identifying simple, high-ROI opportunities to increase revenue; and by extension, profits, margins, and productivity.