After decades of helping organizations understand and apply analytics to business performance, Analytic Translator Founder Wendy Lynch has seen the same data mistakes appear repeatedly—regardless of company size or sector. From poor integration to misplaced faith in technology, Lynch says the biggest problem isn’t a lack of data, but a lack of strategy in how it’s used.
Having spent over 35 years in data analytics, mostly in the business setting, Wendy Lynch has seen the good, bad, and ugly of how companies use data. Unfortunately, examples of ugly have outnumbered examples of good by a large margin.
Below are five common missteps Lynch says are holding organizations back from realizing the full potential of their data.
Resisting Integration
Lynch argues that many companies underestimate the importance of connecting their data sources. “Every company above 500 employees would benefit from internal analytic expertise about their own business,” she says.
“I believe running a company without an integrated data platform is corporate malpractice. It is the same as piloting a plane on a cloudy night without instruments. Perhaps you know the general direction you’re headed and where you hope to land, but you remain under-informed about the current status of the flight or what problems you might have.”
In her view, companies that lack integrated systems are essentially guessing—operating on instinct rather than insight.
Relying on Industry Trends and Benchmarks
Another common pitfall, according to Lynch, is relying too heavily on external trends or benchmarks. “Those who rely on industry trends often prefer the comfort of authority to the uncertainty of what they might uncover when they dig in,” she says.
“It requires a certain level of courage to actively understand problems that may not have an easy answer. While some leaders say they want to be data-driven, not all of them mean it.”
She believes the most successful organizations are those willing to examine their own data first, even if what they find is uncomfortable.
Allowing Artificial Separation
Departments that function in isolation can prevent organizations from seeing the big picture. Lynch says, “It is only through integration that companies learn just how interconnected everything is. Turnover is a function of work schedule, culture, engagement, compensation, and performance. Absence and injury are a function of health, burnout, training, experience and policy. Net revenue reflects how people are performing as well as how they use benefits. It’s one big puzzle, not a collection of little ones.”
This fragmented approach, she notes, limits an organization’s ability to identify systemic issues or opportunities that span multiple departments.
Asking the Wrong Question—or Assuming the Usual Answers
Even when companies collect the right data, Lynch warns they often fail to ask the right questions. “Once data is integrated, the investigative team should include many stakeholders around the business plus people who have seen some of these sorts of connections before,” she says.
“Don’t just ask benefits professionals about benefits and operations managers about operations. Ask bigger questions across stakeholders.”
By involving multiple perspectives, organizations can uncover relationships that single departments might overlook.
Falling in Love with Visualization Tools
Finally, Lynch cautions that technology alone won’t fix data literacy or decision-making problems. “Don’t assume you, or your clients, will be able to make use of them easily,” she says.
“I estimate that over 90% of hands-on tools that I’ve seen sold to leaders have sat unused and/or were assigned to their direct reports to figure them out. Pretty pictures are secondary to having solid skills and systems.”
While modern dashboards and visualization platforms can make analytics more accessible, they’re no substitute for strategic understanding or the right expertise.
Lynch’s message is clear: meaningful use of data requires integration, curiosity, and collaboration—not just software. Companies that resist these fundamentals risk flying blind in an increasingly data-driven world.