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Improve customer service, respond faster to demand fluctuations, offer integrated supply and new pricing models, and achieve greater automation

With Infor AI, 99% faster detection and diagnosis of failure lowers rejection rate and improves OEE and asset utilization

“Infor as a partner is allowing us to move from paper to mobile to sensors. It allows us to move from being reactive to proactive to predictive.”

Hotel revenue management has expanded in the last few years, with more factors to consider, and more data for which to account to get the clearest picture. Sometimes, intelligent solutions and automation still feels like giving up decision-making power for a lot of hoteliers. But the exact opposite is true. Here’s why that is.

Read about how a modern data architecture is one of the most overlooked drivers of analytics adoption

Read why in-context industry-specific analytics embedded into the workflows of business users speeds up time to insight and increases analytics adoption

Despite the usefulness of automation and algorithm-based functionality, hesitancy around AI technologies has been common in the hospitality industry. Some organizations have been wary of turning over hotel revenue management forecasting and price adjustments to these features. But are the contributions of machine-learning functionality and human expertise around strategy mutually exclusive? The short answer is no. For revenue management activities, It’s more useful to look at the relationship between AI and human leadership and how one enhances the efforts of the other. Here’s what we mean.

Read this blog to see how industry-specific analytics can boost your analytics adoption and time to value.