Bloomingdale’s uses machine learning to evaluate employee knowledge
Bloomingdale’s can now pinpoint which of its employee learning programs are generating results — and by how much in real dollars.
The Macy’s division has deployed Axonify Impact, (from Axonify), a learning attribution engine that uses machine learning to evaluate the data collected through training programs. Results reveal the direct impact that employee training programs are having on real business metrics, such as increases in revenue or decreases in expenditures.
As employees interact with the platform, the technology’s machine learning capabilities reveal which programs are generating the greatest impact, and how employee knowledge and participation influence business results. It also uncovers gaps, and makes real-time recommendations to frontline managers when a business target is at risk.
At Bloomingdale’s, the platform has played a large role in helping reduce safety incidents. The platform automatically ties the retailer’s training efforts to how well it is reducing its overall safety claims. Bloomingdale’s has attributed about one third of this safety claim reduction to training efforts on the platform, which translated to a savings of $3 million in one year.
“At Bloomingdale’s, we’re always digging deeper into the effectiveness of our training programs and content to understand exactly how they impact business results,” said Chad McIntosh,VP of asset protection and risk management of Bloomingdale’s. “For most companies, making these connections is incredibly difficult and time-consuming.”
Bloomingdale’s can now easily identify where “learning has benefited our company, because we can tie training efforts directly back to business results,” he added. “But what’s most powerful to me is that Impact shows us exactly what we need to do to drive a greater effect on our business. This just hasn’t been possible before.”
The Macy’s division has deployed Axonify Impact, (from Axonify), a learning attribution engine that uses machine learning to evaluate the data collected through training programs. Results reveal the direct impact that employee training programs are having on real business metrics, such as increases in revenue or decreases in expenditures.
As employees interact with the platform, the technology’s machine learning capabilities reveal which programs are generating the greatest impact, and how employee knowledge and participation influence business results. It also uncovers gaps, and makes real-time recommendations to frontline managers when a business target is at risk.
At Bloomingdale’s, the platform has played a large role in helping reduce safety incidents. The platform automatically ties the retailer’s training efforts to how well it is reducing its overall safety claims. Bloomingdale’s has attributed about one third of this safety claim reduction to training efforts on the platform, which translated to a savings of $3 million in one year.
“At Bloomingdale’s, we’re always digging deeper into the effectiveness of our training programs and content to understand exactly how they impact business results,” said Chad McIntosh,VP of asset protection and risk management of Bloomingdale’s. “For most companies, making these connections is incredibly difficult and time-consuming.”
Bloomingdale’s can now easily identify where “learning has benefited our company, because we can tie training efforts directly back to business results,” he added. “But what’s most powerful to me is that Impact shows us exactly what we need to do to drive a greater effect on our business. This just hasn’t been possible before.”