Strategic Data Analytics to Help Reduce Shrinkage

Data analytics can help retailers, restaurants, and manufacturers reduce shrinkage by enabling loss prevention professionals to use early warning indicators to stop problems in their tracks, according to a report by PricewaterhouseCoopers. However, companies typically have different early warning indicators, and they’re often difficult to identify because the data is not usually in one place, an article in CSO magazine notes.

According to the article, once companies gather and analyze their data, they are able to get ahead of problems, address them early, and save money in the process. Organizations typically measure shrinkage costs later in the cycle (with signals such as inventory levels, shoplifting rates, accidents, etc.), and by the time they have the information they need to react, it’s too late and the damage is already done.

However, there are other metrics that companies can use as early warning signals, according to CSO.

Inventory integrity can serve as a powerful metric to help companies glean better insights into the business. For instance, although the total volume of inventory may still be in line with expectations, if the individual SKUs don’t match up to what’s in the system, that’s an indicator of a potential problem, CSO notes.

“I might have run something up incorrectly, or entered something incorrectly,” says Bill Titus, managing director of PwC’s loss prevention strategy and analytics. “That’s an indicator of how efficiently a store is being operated.”

Other early indicators could include: management positions that haven’t been filled, employee turnover, price change volumes, and cash variances.

For example, if data analysis shows a store performance suffers after a store management position has been vacant for 90 days, a company can take steps to ensure the job is filled before the 90-day mark, according to CSO.

“At 60 days, I can have someone pick up the phone and talk to human resources about filling the position,” Titus notes in the CSO article. “Rather than five or six months down the line having to send someone in because you have a huge amount of turnover, customer satisfaction is down, and so on.”

Not only does reacting earlier cut a company’s losses, it also enables them to reduce the number of employees needed to manage that loss because it can use more “appropriate, strategic, and cost-effective interventions.”

PwC offers the example of a major US retailer that reduced its shrinkage costs from nearly $1 billion to $250 million by enhancing its data-driven loss prevention program.

The key data for this analysis comes from such areas as: point of sale, finance, human resources, store operations, and supply chain departments. Additionally, organizations can add external data sources, like crime rates, financial and economic indicators, and industry benchmarks, to enrich the data and gain valuable insights according to CSO.

“It is hard to pull this data together,” Titus says. “It lives in 10 different places in the company, some isn’t accurate, some lives in spreadsheets.”

“This is incremental,” Titus says. “You need to develop a strategy to help you move along this path.”