HIGHLIGHTS
- The transformation of the supply chain to a digital environment is necessary
- Another element driving firms to shift to data analytics is the lack of storage space at stores.
- Walmart has aggressively embraced these tools as it shifted from spreadsheets to web-based and data science modules at the back end, and is developing web-based scenario-planning functionality.
FULL ARTICLE
Brian Hecht, supply chain specialist at Kroeger, says that human experience and historical data used to support planning decisions are not enough. The transformation of the supply chain to a digital environment is necessary and it is beginning to help develop many other capacities of individuals. AI replaces humans in some jobs, and humans can do many others.
Another element driving firms to shift to data analytics is the lack of storage space at stores. Storage space at the back of stores has largely disappeared over the years, leaving retailers with no redundancy to hold stock there.
Bill Mines, SVP finance, logistics & supply chain at Walmart, said the retailer did not want to build up redundancy. Instead, it aims to leverage AI and data science.
Walmart has aggressively embraced these tools as it shifted from spreadsheets to web-based and data science modules at the back end, and is developing web-based scenario-planning functionality.
One initiative has been the development of an in-house forecasting platform at the distribution center area level, which is used daily and weekly.
Jackie Guan, senior director data & analytics at the retail giant said ”It allows us to plan our labour more accurately. We were able to dramatically improve our forecasting ability.”
In response to the labor challenges the company has experienced, her team developed an optimization model and corresponding tool for labor recruitment and planning. In any of its distribution centers there are up to two million configurations of different applicants, job calls and schedules, so the tool helps make faster and better decisions.
Now Walmart is working on a tool, and the corresponding app, to give estimated arrival times for trucks, a project that involves investment in sensors, data technology and advanced analytics.
While data analytics and AI offer massive improvements, it is vital to start with the actual business problems and targeted outcomes a company wants to address, before getting to the data and the technology. Understanding the processes is of the utmost importance to get on the right track, said Mr Hecht.
Hong Dao
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