Summary

The Supply Chain group at Meta is in charge of sourcing and maintaining employee devices, such as cell phones, and was charged with deciding whether to lease or buy these devices from the manufacturers. With DataChat, the group was able to discover the repair window that needed to be covered by new leases as well as improve the sustainability of the supply chain by recommending the longest-lasting devices to employees.

Challenge

Meta purchases cell phones for their employees in bulk from three large brands and handles the repair process internally. With data for 200,000 phones over the past five years, of which about 50,000 will approach the end of their service in the near future, the group needed to investigate which factors influenced device life, which devices lasted the longest, and decide whether to switch to a leasing paradigm for new devices. With over 10 years of device data, the group was searching for a powerful yet simple data and analytics platform to answer their questions.

Approach

With DataChat’s platform, the Supply Chain group was empowered to address their questions on their own while working collaboratively amongst themselves and across departments more quickly and easily than they could with traditional tools, such as Excel, SQL, and Python.

DataChat’s no-code platform helped our group think like data scientists and collaborate to quickly create robust, transparent, and repeatable data science solutions to business problems. - James Paul, Supply Chain Product Lead

DataChat allowed the Supply Chain group to independently construct robust data science pipelines and workflows to analyze their device data. They were also able to leverage DataChat’s explainable AI and machine learning tools to quickly create models that revealed that the time between purchasing a device and the first repairs was the primary factor of device life, which would help inform the terms of new leases. 

Results

The group identified millions of dollars in potential savings by identifying the average time to first repair for each brand. With this information, they could then select optimal warranties and other lease terms. The group was also able to identify that one particular brand had superior longevity compared to the others, which helped the company promote their environmental, social, and governance (ESG) goals by recommending those devices to employees.