The latest episode of the Restaurant Technology Guys podcast dives deep into the world of data-driven decisions in the restaurant industry. Jeremy is joined by Mike Lukianoff, a seasoned veteran in restaurant operations and technology, currently spearheading SignalFlare.ai. This insightful conversation covers Mike’s career journey, the evolution of data analytics in the restaurant industry, and the groundbreaking methodologies SignalFlare.ai is bringing to the table.
A Journey Through Restaurant Technology
The Genesis of Mike Lukianoff’s Career
Mike Lukianoff’s career spans 25 years in restaurant technology, with roots in restaurant operations. Mike initially aimed to re-enter restaurant operations after completing his graduate studies, only to be drawn into the quantitative side of things. His career trajectory took a significant turn when he began focusing on pricing, analytics, and data during a time when these concepts were foreign to the industry.
“Nobody was really pulling data out of point of sale,” Mike recalls. He started working with a pioneering company in analyzing restaurant data and building price elasticity models to understand consumer behavior in response to price changes. This venture led to a successful partnership with McDonald’s, rapidly transforming his small outfit into a multinational entity.
Building on Data and Analytics
The financial collapse of 2008 provided an unexpected opportunity for Mike, leading him to bootstrap his own company focused on promotional analytics and social media analytics. As an early adopter of AWS Cloud, he could run elaborate algorithms cost-effectively. His innovative approach during challenging times allowed him to navigate the complexities of data and pricing efficiently.
Enter COVID-19: Rethinking Methodologies
Mike’s latest venture was born out of necessity and innovation during the COVID-19 pandemic. The traditional methods of relying on stable periods of demand were no longer viable. Mike had to rethink everything about data analysis, integrating new datasets like mobile data, credit card data, and local economic indicators to understand consumer behavior better.
“We had to start with completely different datasets,” Mike explains. The new models could predict demand patterns accurately even before receiving point-of-sale data, showcasing the robustness of these advanced methodologies.
The Emergence of SignalFlare.ai
Redefining Data Utilization
SignalFlare.ai emerged as a solution to make sophisticated data analytics accessible to even smaller chains. By leveraging extensive datasets and advanced algorithms, SignalFlare.ai can assist in understanding local demand, customer behavior, and economic factors affecting restaurant performance.
“Now you can get all of this kind of information,” Mike emphasizes, highlighting the importance of integrating diverse data sources to build predictive models.
Practical Applications for Restaurants
Jeremy and Mike delve into the practical implications of these analytics for restaurant operators. SignalFlare.ai offers insights into optimal pricing, demand patterns, and promotional effectiveness that can drive significant business improvements. By providing tailored recommendations and probabilistic simulators, SignalFlare.ai empowers operators to make informed decisions.
From Data Science to Real-World Impact
The conversation underscores that while SignalFlare.ai’s foundation is built on complex data science, its ultimate goal is to deliver simple, actionable insights to operators. “They need to know what to do and how it’s going to affect their business,” Mike asserts.
The Future of Restaurant Pricing: Beyond Dynamic Pricing
Rethinking Dynamic Pricing
The term “dynamic pricing” often stirs controversy and skepticism in the restaurant industry. Mike clarifies the misconceptions, suggesting that the focus should be on overall menu management and value-driven decisions rather than constantly fluctuating item prices.
“Dynamic pricing has a specific meaning… constantly changing,” Mike explains. Instead, strategies should emphasize creating value and improving operational metrics without alienating customers.
Conclusion: Embracing Data-Driven Decisions
The podcast concludes with a compelling message: the importance of starting down the path of data-driven decision-making. Mike warns that delaying this adoption could leave operators behind competitors who are already leveraging these tools to gain a competitive edge.
“If you’re not doing it, likely your competitor is,” Jeremy echoes.
For those interested in exploring SignalFlare.ai and the transformative power of data analytics, visit their website at SignalFlare.ai, or reach out directly to Mike Lukianoff at mike@signalflare.ai.
Jeremy’s concluding thoughts resonate with restaurant operators and tech enthusiasts alike: “We know you have lots of choices. Thank you for spending time with us, and make it a great day.”
This episode provides a rich, informative look into how data analytics and intelligent decision-making can revolutionize the restaurant industry, making it a must-listen for anyone passionate about restaurant technology and operations.
