In this episode of Data Alchemy, we are joined by Frank Corrigan, Director of Customer Success at Lyric and seasoned analytics professional, to discuss how to implement a truly data-driven organization. Frank has experiences at both small and large organizations taking data and helping business leaders derive actionable insights. In this episode, we’ll discuss how to position teams in any industry to better leverage data, how to choose the right data and BI tools, and walk through a real example of analytics at work.
From Data Overload to Data Empowerment
It is quite often to hear or read these days that businesses need to “be more data-driven.” But the phrase itself can feel a bit overwhelming. Does more data automatically equal better decisions? Not necessarily. In talking to Frank Corrigan, Director of Customer Success at Lyric and an analytics expert, his journey into the world of data is a great reminder that it’s not just about the numbers, it’s about how one thinks about them.
Frank’s early career involved a series of humbling and relatable job interview experiences. Motivated to sharpen his analytical thinking, he immersed himself in the world of data science. What he discovered wasn’t just technical prowess – it was a new way of approaching problems. “Data is there to help you think and get different perspectives,” Frank emphasizes.
One of Frank’s anecdotes from Wayfair illustrates this perfectly. A warehouse manager was urgently warned about critically high inventory, but the data report suggested otherwise. Trusting his gut, Frank dug deeper, spending the weekend wrangling SQL queries. The report was flawed. It overlooked outliers and key data, providing a false sense of security. The lesson? “Data is only half the story,” says Frank. “You’ve got to be listening all the time to the people and what’s going on around you.” Data, paired with analytical thinking and real-world context, becomes truly empowering.
Taking Action: Practical Steps to Become More Data-Driven
Building a truly data-driven organization doesn’t require a complete overhaul overnight. Instead, as Frank emphasizes, it’s about taking a strategic and manageable approach, focusing on building lasting habits throughout teams.
“Don’t try to do too much at once,” Frank advises. Start by encouraging your team to dedicate even just 10 minutes each day to reviewing a few key metrics related to their roles. This consistent exposure helps make data analysis feel less intimidating and more ingrained in daily workflows. Instead of solitary number crunching, make data review a regular team activity. Discuss observations, brainstorm solutions, and encourage diverse perspectives. This collaborative approach fosters comfort with data and helps everyone feel more confident interpreting insights.
So which metrics should we actually be looking at? Don’t get bogged down trying to track every single data point. Focus on the ones that directly impact your bottom line and align with specific business goals. Luckily, there is no need to reinvent the wheel. Plenty of resources, like industry benchmarks and competitor analyses, can help guide metric selection. And yes, even a quick Google search or a query with ChatGPT can provide valuable starting points. For example, in the restaurant industry, metrics like food cost percentage, table turnover rate, and customer satisfaction scores should be top of mind. By zeroing in on the data points that matter most, businesses can gain clearer insights and, ultimately, make more impactful decisions.
The Secret Weapon in the Data Revolution
The rise of AI might seem like another layer of complexity in an already data-saturated world. But Frank is a firm believer that AI, particularly tools like ChatGPT, can be incredibly valuable even without a data science background. “Don’t let the technology intimidate you,” he advises. “Think of it as a powerful assistant ready to help you unlock the full potential of your data.”
One way to leverage AI is by using it to generate synthetic data so quickly mocking up a dataset that mirrors real-world information. ChatGPT can do just that, allowing anyone to test hypotheses and experiment with different analytical approaches before diving into the actual numbers. AI can also help one communicate data findings clearly by offering suggestions for refining data visualizations, even recommending specific chart types that resonate with the target audience.
But perhaps the most powerful use of AI is its ability to enhance one’s own thinking process. ChatGPT excels at brainstorming, helping uncover new perspectives and explore innovative solutions. Stuck on a particular business challenge? Try bouncing ideas off ChatGPT and see what creative solutions emerge. The point is AI isn’t about replacing human intuition or expertise. It’s about augmenting those capabilities and making data analysis more accessible and impactful for everyone.
