As data practitioners, our ability to spot patterns and extract insights can become our greatest weakness when overconfidence overrides curiosity. This article explores how even experienced analysts can fall into the trap of drawing sweeping conclusions from limited data, missing crucial business context that completely changes the story the numbers tell.

Drawing from real-world examples of analytical missteps—from misreading Adobe Analytics data to celebrating traffic that actually harmed conversions—we examine the warning signs of data overconfidence and provide practical strategies for building a more curious, empathetic approach to analysis.

Disinformation is not confined to politics or public health, it lives wherever data can be bent to serve an agenda. Analysts hold a unique responsibility as translators of data into action.

When we strip away context or selectively frame numbers, we risk becoming part of the same machinery that erodes public trust.

At 33 Sticks, we believe ethics cannot be optional. Our manifesto commits us to objectivity, transparency, and context because without objectivity, the true value of data is lost.

For the past fifteen years, i’ve worked with data practitioners across industries, retail, healthcare, tech, finance, entertainment. Different businesses, same story. Teams feel frustrated and underappreciated. They’re buried in requests for reports and dashboards, treated as service providers, and excluded from strategic conversations.

The complaints are familiar:

• “We don’t have a seat at the table.”

• “The business doesn’t respect us.”

• “Leadership ignores our insights.”

Yet beneath the frustration lies a paradox. The very behaviors and beliefs that define how most data teams work are the same ones sabotaging their influence. We want respect but avoid accountability. We want to be strategic, but we refuse to step into the role.

Earlier this month, Cracker Barrel unveiled a new brand identity. The familiar imagery of a man leaning on a barrel disappeared. Within hours, social media lit up and headlines followed:

• “Board member under fire for DEI background after restaurant ditches traditional logo”

• “Conservative activist slams Cracker Barrel; company left reeling after logo redesign”

• “Marketing fiasco shows investors are making ‘woke’ a massive risk factor”

The narrative was clear, the redesign wasn’t about business strategy, it was about politics.

Analytics teams will always be understaffed, that's not a problem to solve, but a reality to work with. This article explores how analytics leaders can build powerful virtual teams through evangelism and relationship building rather than waiting for budget approvals.

At 33 Sticks, we believe the most fascinating insights often emerge when we apply analytical rigor to unexpected datasets. Recently, we discovered a treasure trove of human behavior patterns hiding in plain sight: LinkedIn professional responses to a policy analysis scenario.

Until we bridge the gap between data and felt experience, our dashboards will remain beautiful, sophisticated, and ultimately ineffective displays of information that change nothing.

The digital analytics industry stands at an inflection point. As generative AI and automation sweep through organizations, promising to handle everything from data collection to basic analysis, we face a fundamental question: What becomes of the digital analyst?

The answer isn't found in fighting the tide of automation or doubling down on technical skills. Instead, it requires us to acknowledge an uncomfortable truth that digital analytics, as we've known it, is already obsolete. Not because the work doesn't matter, but because the name itself has become too small for what we must now become.

What emerges from this disruption isn't the death of a profession but its radical evolution from mechanical data workers to what we call "organizational anthropologists," practitioners of Human-Centered Analytics who help businesses see the humans behind the data.

There’s a moment in every analyst’s career when they stop just reading data and start questioning it.

We’re not talking about being cynical or skeptical for the sake of it. We’re talking about curiosity-driven, clarity-seeking, insight-focused critical thinking.

Take U-Haul’s 2024 “Growth States Report.” It ranks U.S. states based on one-way U-Haul rentals, suggesting where people are moving to and from. At a glance, it’s a tidy list with intuitive appeal. But scratch the surface, and it becomes a perfect teaching tool, not because the data is “bad,” but because it invites better questions.

So let’s use this dataset not as something to critique but as something to practice on.

Ad agencies are buzzing about Meta’s new Incremental Attribution model with some calling it a breakthrough in “real” measurement and the end of vanity metrics.

But here’s what we’re not seeing: Critical discussion from a data perspective.

The rapid rise of Generative AI has raised serious questions about the future of digital analytics. Tools that were once positioned as analyst accelerators now appear to be replacing the need for analysts altogether. With platforms like Amplitude, Adobe Analytics, and GA4 embedding natural language querying, anomaly detection, and AI-generated insights directly into their workflows, some enterprise leaders have begun to ask an uncomfortable question: Do we still need analysts at all?

A friend once remarked to me that "unintentional evil is still evil," referencing how social media platforms might not have been designed with malicious intent, yet their engagement-obsessed algorithms often create harmful outcomes. Sometimes it's not evil but simply unethical, disrespecting humans, breaking trust, or manipulating behavior.

Migrating to the webSDK doesn’t mean giving up on implementation methods that scale. Adobe provides a little-known “Update Variable” mechanism in Launch that allows you to build a scaleable, maintainable implementation with minimal redundancy.

In both espresso-making and data analysis, the magic happens not when we automate away complexity, but when we master it. The perfect shot, like the perfect analysis, comes from understanding each variable, each step, each potential pitfall in the process.

33 Sticks is thrilled to announce the launch of our first ever internship program, developed in close collaboration with East Tennessee State University (ETSU). After over a decade in business, we have decided to create a robust internship experience to provide meaningful opportunities for the next generation of data and analytics professionals.

At 33 Sticks, we're proud to be the artisanal option – crafting unique, high-quality solutions for clients who value a more personalized approach to analytics consulting.

The organizational positioning of analytics teams represents one of the most consequential yet frequently overlooked strategic decisions in modern enterprise structure.

The digital analytics industry is facing significant issues as major platforms like Google and Adobe push for migrations to GA4 and Customer Journey Analytics (CJA). These migrations have been plagued by poor implementation, largely due to over-reliance on large consulting firms and subcontractors lacking expertise. This has resulted in frustrated clients, failed projects, and a tarnished industry reputation. However, smaller agencies have an opportunity to step up by focusing on quality, transparency, and client education. The industry must realign incentives, demand transparency, and foster innovation to create a client-first ecosystem that prioritizes genuine customer success over vendor-driven sales goals. This is a call to action to reclaim the industry from monopolistic practices and build a better future for digital analytics.

From an early age, children are naturally curious, asking questions, observing patterns, and trying to make sense of the world around them. In our modern, data-driven society, this innate curiosity can be nurtured through tools that teach them how to think critically, analyze information, and draw meaningful conclusions. This is why we created A is for Analytics—to make the world of data accessible to kids in a fun and engaging way.

Critical thinking and skepticism are not just optional tools for data analysts—they are essential. Without them, we risk allowing flawed, biased, or incomplete data to influence important decisions. In a world where data is used to shape narratives and drive opinions, our responsibility is to approach it with a healthy dose of doubt and a commitment to uncovering the full story.