Retailers who want quick wins that increase sales should do more with their data.

In the past 20 years, I have worked with leading retailers who had reasonably good data and analytics, great processes and smart teams. Can a retailer like that still see value in artificial intelligence and advanced analytics? I believe that the answer is ‘yes’, because, through the use of an AI solution, retailers can do more with data they already have.

There are several opportunities for an AI data analytics solution to take a retailer to the next level of sales and profitability:

1. Extracting more opportunities from existing data: a. Retailers are documenting and handling vendor claims made at the store, but do they really analyze this data? Do they know if an increase in claims happened because of vendor performance or because the store is trying to compensate for poor shrink or damage rates? Will they even know that claims were recently increased in volume, are they monitoring trends and benchmarking stores and regions? b. Operational and loss prevention teams are monitoring POS refunds for customer and cashier fraud, but are they measuring the impact of customer returns on damage and shrink? Do they have practices in place to triangulate correlate these data points? c. Inventory is closely monitored to assure accuracy, but do retailers use the data that they are collecting through cycle counts and inventory adjustment to predict shrink? d. SKU level sales information is available to operational and commercial teams, but is it used to detect and predict on-shelf availability and order integrity?

2. Increasing the efficiency and effectiveness of your team: a. Broaden the range of data in use, but insist to also gain access to SKU level views quickly and easily when required. b. Automatically pinpoint and push opportunities to store and HQ associates. c. Focus on high risk, use ranking and prioritization mechanisms to support decisions and allocation of resources. d. Retain and distribute “local” knowledge and best practices. e. Formalize and document follow-up on the actions following the insights.

3. Focus your actions on what the data is telling you: a. You found an anomaly in inventory behavior? You found an anomaly in cycle count trends? Always check if it also has a potential to impact profits (through sales increase, shrink/damage reduction) and act to implement preventive actions. b. Identify the best practices in your organization that may have a direct impact on sales, shrink and damage. When you identify non-compliance, these best practices must be in your top priority in audit, training and general awareness activities.

Improving these 3 key areas will build capabilities for sustainable performance improvement, sales and profit increase.

Data Driven Investor

from confusion to clarity, not insanity

Omer Matityahu

Written by

Twenty years of entrepreneurial and business experience, an expert in retail technology, retail analytics, retail operations and execution, loss prev

Data Driven Investor

from confusion to clarity, not insanity