Report: Strategic Data Analytics Can Reduce Shrinkage

Loss prevention pros use early warning indicators to stop problems before they start

coupons
Credit: Chris Potter

Strategic data analytics can reduce shrinkage for retailers, restaurants and manufacturing companies by helping loss prevention pros use early warning indicators to stop problems before they start.

According to a new report by PricewaterhouseCoopers, these early warning indicators can be different for each company, and difficult to identity and use because few companies have all the data in one place.

But once the data is gathered and analyzed, companies can get out in front of problems and address them early, at lower cost, or with higher effectiveness.

For example, in one case, PricewaterhouseCoopers found a high a degree of correlation between the volume of coupons processed and increased shrink, said Bill Titus, managing director of PwC’s loss prevention strategy and analytics.

It turned out that the same mechanisms that lead to a dramatic increase in coupon redemption also led to more shrinkage.

Specifically, they're both caused by deteriorating risk controls.

Traditionally, he said, companies measure risk later on in the cycle, using indicators such as inventory levels, shoplifting rates, and accidents.

But there are other metrics that companies could be using as well, that could serve as early warning signs.

Take, for example, inventory integrity. The total volume of inventory may still be in line with what's expected, but if the individual SKUs don't match up to what's in the system, that's a sign that something is going wrong.

"I might have run something up incorrectly, or entered something incorrectly," he said. "That's an indicator of how efficiently a store is being operated."

Other early indicators could be unfilled management positions, associate turnover, price change volumes, and cash variances.

Say, for example, a company learns that things usually start deteriorating after a store management position has remained unfilled for 90 days.

"At sixty days, I can have someone pick up the phone and talk to human resources about filling the position," Titus said. "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."

Reacting earlier doesn't just reduce losses, he said, but also reduces the resources required to manage that loss because a company can use more appropriate, strategic, and cost-effective interventions.

The data required to do this comes from point of sale, finance, human resources, store operation, and supply chain departments.

"It is hard to pull this data together," Titus admitted. "It lives in ten different places in the company, some isn't accurate, some lives in spreadsheets."

In addition, external sources of data can be added as well, including crime rates, financial and economic indicators, and industry benchmarks.

But a company doesn't have to do everything at once, said Titus.

"This is incremental," he said. "You need to develop a strategy to help you move along this path."

According to the PricewaterhouseCoopers report, one large US retailers was able to reduce shrink from closed to $1 billion to $250 million through a revamped, data-driven loss prevention program.

"We can help a client understand where you are on the maturity model," he said. "And if you want to go here, this is what it will cost you, and this is the benefit you will get from it."

This story, "Report: Strategic Data Analytics Can Reduce Shrinkage" was originally published by CSO.

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