Businesses have long had a range of data that could improve business performance but no way to channel that information into concrete actions.

Opus Training, the training operations system trusted by hundreds of multi-unit brands, today announced the launch of Opus Recommendation Engine, a product that does just that, turning operational data, guest feedback and other signals into specific, actionable recommendations for franchise and multi-unit operators.

By channeling data that franchises and multi-unit businesses already generate, Recommendation Engine creates actionable steps that drive consistency and operational excellence. This includes using internal data, guest reviews, outside platforms like Google Reviews, operational metrics, and a growing set of third-party signals.

A persistent problem for many businesses has been that the data is disconnected from action. Recommendation Engine is the first product of its kind in the training and operations space to turn these insights into clear actions.

For example, a recurring customer complaint around order consistency can be turned into a series of steps for managers to reinforce best practices. Recommendation Engine can also use data to modify training or recommend other actions, like acknowledging a team’s growth and excellence. It then tracks whether those actions change outcomes for businesses, improving accountability.

Opus now offers Recommendation Engine to all of its customers, including more than 500 multi-unit groups in the U.S., including household names like Bonchon, Smash Burger and Craveworthy Brands.

Recommendation Engine builds on previous product innovations at Opus, and expands them to include a broader range of operational and third-party signals for franchises.

"The tools for the frontline have always been an afterthought, built by copying what worked for a desk job. We think that's backwards," said Rachael Nemeth, founder and CEO of Opus Training. "Every guest review, every missed order, every signal a business already has, most of it just evaporates. Recommendation Engine exists because we don't think data should evaporate. Every business already has the signal. We just built the part that was missing."

One early example, has been Newk's Eatery, which used the product in beta to build its own "Perfecting Order Accuracy" initiative, reassigning training to the stores with the most guest feedback around missing items. The result was a 10% net improvement in missing-item incidents.

“Recommendation Engine, including its Guest Feedback Integration, drives consistency in our business which is ultimately one of the most important drivers of success,” said Jessica Drahem, Director of Performance, Development & Culture. “We’ve been able to use it to focus our efforts on stores that need the most support and our business is benefiting from that.”

Opus Recommendation Engine is available now to all Opus customers. More information can be found here.