How To Prevent Loss In Retail?
The retail industry finds itself tackling an unprecedented crisis. Retailers are scrambling to stay relevant by any means necessary- cutting costs, conserving cash and retaining what is left of the customer base. The Global retail loss linked to inventory failures from crime or waste, cost traders approximately $104.5 Billion (about 1.34% of sales), last year alone. This has been mainly attributed to retailers laying off loss prevention staff and store personnel, reduction in technological investments, and increase in theft by people who have succumbed to the growing economic pressure.
In this article, we review the sources of retail loss and how analytical techniques can help in loss prevention, cost effectively.
Loss prevention programs:
Retailers can use a combination of LP programs to fight retail loss. The implementation of such a program is designed on three objective.
Deter: as the name suggests, the goal is to prevent loss in the first place. Methods like screening candidates, training them on LP programs, installing alarms, signs and CCTV are commonly employed.
Detect: the objective here is to identify the loss immediately and take steps to rectify it. CCTV cameras and data mining play a huge role in this.
Defend: the idea here is to prevent theft from happening by putting security measures in place. Examples of measures include cable/lock for stock, refund control procedures, secure display fixtures and armored car pickup for cash deposits.
There interaction of these programs with the loss prevention results is quite complex. Retailers find it difficult to isolate the value of a single program. It is even more difficult to figure out how much of a change will occur when a program is discontinued due to budgetary pressures.
Luckily though, all these programs generate data points over time and organizations can harness the power of analytical techniques to effectively manage their resources.
Analytics in loss prevention:
Report: Retailers tend to have systems in place for in-house reporting to track losses. These have to be consolidated using LP scorecards and Exception reporting. LP managers use these reports to rank stores based on the LP metric. Analytics can help in better understanding where shrink occurs and in tracking various LP programs.
Analyze: Once managers know how much and where losses happen, the next step is unearthing the root causes. Exploratory data analysis (EDA) is used by professionals with extensive experience in the industry and a deep understanding of the current market conditions. Regression is normally used across industries and business functions for impact analysis
Predict: Finally, there is a need to anticipate problems within specific areas in a store or a region to allocate resources efficiently. Depending on data availability, we can perform prediction by-
- Judgement (expert opinion using historical data)
- Time series (trend extrapolation)
- Multivariate analysis (using models and neural networks)
It’s time you utilize available data resources effectively to prevent loss in retail, by building systems to report, analyze and predict losses accurately.