Most business leaders have fallen into the same trap at some point. They collect mountains of data, create impressive dashboards, and then wonder why their decisions still feel Like guesswork. The problem isn’t the data itself, it’s how companies approach it from the start. Chad C. Paris has watched this play out countless times during his 15 years in sales leadership, particularly while working with private equity firms that acquire growing companies.
Setting the Right Data Foundation
Paris has seen the same mistake repeated across organizations: companies rush to analyze data before they have figured out what they are actually trying to measure. “One of the things I have seen that is overlooked is the way we set up the correct data that we are trying to achieve,” he explains. “Data is used a lot and it is a very powerful tool, but it is important that you set the correct playbook and define what you are trying to accomplish with that data.” It sounds obvious, but Paris points out how often this step gets skipped. Teams inherit systems from previous employees or follow outdated directives without questioning whether they are measuring the right things. “Oftentimes we look past the blocking and tackling, the foundation of what we are trying to accomplish, before we start pulling data,” he notes. Without this groundwork, even flawless data becomes useless for real decision-making.
Paris also diverges from the “data-driven everything” mindset that has become popular. He is convinced that numbers alone cannot provide the full picture. “Data tells part of the story. I don’t know that I would sit here and say the data tells the whole story,” he says. “There are tangible, human elements to what you are trying to read.” That perspective comes from years of working with sales teams, where relationships and personal connections matter enormously. Paris treats data as supporting evidence in a courtroom rather than the final verdict. “I use it as a supportive element to a decision being made, not the only way of making the decision,” he explains. The human element fills in the gaps that spreadsheets cannot capture.
Hiring by Blending Data and Intuition
When Paris recruits new team members, he begins with a clear framework of what success looks like in each role. Once he has identified the key characteristics and performance indicators, the data from candidates’ backgrounds becomes far more meaningful. “Then it makes it very easy when you analyze and are talking with people, to look at their history of what they have done, where they have been, and what they have accomplished,” he explains. But there is a catch that many hiring managers miss. “Very often people interview very well,” Paris cautions. “So when you have one interview, you could be fooled, you could be misled very quickly.” That is why he combines data-backed criteria with human assessment. Together, they provide a much more complete picture than either approach on its own.
Presenting Analytics Without Intimidation
One of Paris’s biggest challenges is helping relationship-focused team members embrace analytics without feeling threatened. “In a lot of organizations there is this fear that data sits over here, the human is over here, and they do not want to cross paths,” he observes. Many salespeople worry that focusing on numbers will diminish the personal connections they have built their careers on. Paris addresses this by reframing how he presents data. “The data only tells half the story,” he tells his teams. “Data tells a side of the story, the human fills in the gaps.” This perspective helps people see that their relationship skills and industry knowledge are not being replaced. Instead, they are being enhanced by stronger insights and better information.
Filtering Actionable Data from Noise
With so many metrics available, Paris has learned to separate actionable data from analytical noise. “What is actionable data? Input A, outcome B, it is actionable,” he explains. These are the metrics that show clear cause-and-effect relationships his team can actually use. For example, tracking the number of cold calls, meetings, and follow-ups that lead to predictable outcomes gives salespeople concrete actions they can take. “Now they have this: if I do X, Y, and Z, I am going to have this result,” he notes. The other data points may be useful for leadership analysis, but they do not help individual contributors improve their daily performance.
As workforces evolve and technology advances, Paris sees data becoming even more important for effective leadership. “Today’s younger workforce is totally different than the workforce was five years ago. We have way more technology at our fingertips,” he points out. Yet the core principle remains the same. “I am a firm believer in having really good data to analyze and making sure that what we are analyzing speaks to us and helps guide our decisions,” Paris concludes. “But we also need to understand that there is a human element to it, and we must marry the two.”
Connect with Chad C. Paris on LinkedIn to explore more insights on sales leadership and data-driven strategies.
