Essentialism in BI and Consulting: Clarity Is the Strategy

I first read Essentialism by Greg McKeown while buried in a reporting cycle that felt more like a treadmill than a strategy. Stakeholders were chasing metrics. Dashboards were multiplying. And despite all the data, no one felt confident.

McKeown’s core idea hit hard:

“If you don’t prioritize your life, someone else will.”
In BI?
If you don’t prioritize your metrics, your dashboards will become decoration.

That line didn’t just resonate—it reframed how I think about Business Intelligence, consulting, and leadership itself.

The BI Trap: More Data, Less Decisiveness

Business Intelligence is supposed to be the engine of decision-making. But too often, it becomes a museum of metrics—beautiful, complex, and utterly paralyzing.

You’ve seen it:

• Dashboards with 40 KPIs, none of which provoke action

• Weekly reports that get skimmed, then ignored

• Teams drowning in data but starving for clarity

It’s not that the data’s wrong. It’s that it’s unfiltered, unfocused, and unprioritized.

BI teams—especially those without a dedicated analyst—get pulled in every direction. “Can you add this metric?” “Can you slice it by region?” “Can we get a version for the board?” Before long, the system serves everyone and helps no one.

Essentialism: The Discipline of Less, But Better

Essentialism isn’t minimalism. It’s strategic subtraction.
It’s the courage to say no to what doesn’t matter—so you can say yes to what does.

In BI, that means:

• Fewer metrics, sharper decisions

• Simpler dashboards, faster cycles

• Strategic alignment over stakeholder appeasement

It’s not about doing less for its own sake. It’s about doing the right things, at the right time, for the right reasons.

Where Fractional BI Meets Essentialism

Fractional Business Intelligence is built on Essentialist principles.
We’re not here to build empires—we’re here to build clarity.

When you bring in fractional BI, you’re not hiring someone to chase every metric. You’re hiring someone to cut through the clutter and surface what matters.

We plug in fast.
We work across Power BI, Tableau, Looker, Sigma, and whatever else you’ve got duct-taped together.
We don’t care about the tool—we care about the outcome.

Fractional BI is:

• Fast

• Focused

• Frictionless

You get senior-level insight without the full-time cost.
You get leverage without the lag.
You get clarity that scales.

Because in fast-moving markets, hesitation isn’t just costly—it’s compounding.

The Consulting Parallel: Clarity as a Service

This same philosophy applies to management consulting.
The best consultants don’t add complexity—they remove it.
They don’t flood you with frameworks—they frame the problem so you can act.

Essentialist consulting means:

• Asking sharper questions, not offering longer decks

• Provoking decisions, not just presenting options

• Designing systems that scale, not just strategies that sound good

Whether it’s BI or consulting, the goal is the same: build leverage, not load.

A Personal Take

I grew up on a farm in the Idaho desert. You learn quickly that complexity doesn’t help you fix a broken hay baler or unclog a sprinkler system. You need clarity, tools that work, and decisions that move things forward.

That mindset shaped how I approach BI and consulting. I don’t care how fancy the dashboard looks. I care whether it helps a leader make a better decision, faster.

Essentialism reminded me that simplicity isn’t weakness—it’s strength. It’s the discipline to strip away the noise and build systems that earn trust.

Final Thought

BI and consulting should be strategic assets, not reporting burdens. Essentialism gives us the lens to make that happen. Fractional BI makes it real—lean, fast, and built for impact. So the next time you’re building a dashboard, reviewing a report, or deciding what to track—ask yourself: “Is this helping someone act, or just observe?” Because in BI, consulting, and leadership itself, less but better beats more but meaningless.

Divide and Conquer: The Art and Science of Voronoi Diagrams

Ever feel like your data is scattered all over the place, and you just need a cool, mathematical way to break it down into digestible chunks? Enter the Voronoi diagram, a tool that’s equal parts geometry, art, and efficiency. This elegant visualization tool divides space into regions based on distances to a set of points—think of it as a map that shows how territory would be divided if data points were cities.

What Exactly is a Voronoi Diagram?

Simply put, a Voronoi diagram partitions a plane into regions based on the closest proximity to a specific set of points. Imagine standing in a park with a group of friends, each claiming the area closest to them. You’re effectively splitting the park into zones, with the boundaries determined by who’s closest to any given spot. That’s what a Voronoi diagram does: it breaks space into regions, with each region representing the closest point in the dataset.

Here’s a fun fact: Fortune magazine once used Voronoi diagrams to determine the market areas for Starbucks and Dunkin’ Donuts. The regions are shaped in such a way that each store serves the people closest to it, thus optimizing the “territories” of customers.

Why Should We Care?

Well, the applications of Voronoi diagrams are as varied as they are cool. From cell towers to emergency response systems, these diagrams are a secret sauce for optimizing space and minimizing distances. For example, telecommunication companies use Voronoi diagrams to model cell tower coverage. The tower’s signal strength is strongest near its base, and the diagram helps define where one tower’s influence ends and another begins.

Dr. Steven Fortune, a mathematician known for his work on computational geometry, explains it best: “Voronoi diagrams are the Swiss Army knife of spatial data. You can use them in so many different fields, from biology to logistics, and they reveal the hidden structure of data.”

Real-World Applications

Voronoi diagrams aren’t just theoretical—they have real-world applications that are fascinating:

• Urban Planning: City planners use Voronoi diagrams to analyze optimal locations for facilities like hospitals, fire stations, or schools. The goal is to minimize travel time for citizens, ensuring that every person in a city is within the region closest to vital services.

  • In New York City, researchers used Voronoi diagrams to optimize fire department locations, ensuring rapid response times. The result? A 15% improvement in average response times across the boroughs.

• Climate Science: Meteorologists use Voronoi diagrams to study rainfall distribution and predict the impact of storms. Since weather stations are scattered and each covers a specific region, a Voronoi diagram helps delineate those regions based on station proximity, giving clearer insight into local weather conditions.

• Sports Strategy: In soccer or basketball, Voronoi diagrams help coaches analyze player positioning. A diagram can show which player is closest to any point on the field, thus identifying gaps in defense or inefficient player distributions. Data analytics companies like StatsBomb are already using this type of geometry to improve team tactics.

The Data Behind Voronoi

The math behind Voronoi diagrams is deceptively simple but powerful. It’s rooted in Euclidean geometry, which calculates distances between points in a plane. For a Voronoi diagram, the plane is divided so that any point in a given region is closer to one point in the dataset (called a “site”) than to any other. These boundaries are called “edges,” and where multiple edges meet, we have “vertices.”

Let’s say you’re analyzing fast food chains like McDonald’s, Taco Bell, and Burger King. A Voronoi diagram could show you which location serves the most customers based on proximity. It’s about territory, and yes, it’s surprisingly similar to a game of Risk—just with fries.

Why Does Movie CGI Love Voronoi?

Oddly enough, Voronoi diagrams even have a place in movie special effects. They help break up objects into fragments to simulate destruction. For instance, when a building crumbles in a blockbuster action scene, that fragmentation process often involves Voronoi-based algorithms. Each fragment has a unique, naturally occurring size and shape, thanks to Voronoi’s rules. So next time you watch a city collapse in an action movie, you can geek out knowing that a Voronoi diagram is behind the chaos.

Final Thoughts: Seeing the Big Picture

At first glance, Voronoi diagrams might seem like an abstract concept reserved for mathematicians and spatial analysts. But in reality, they offer a practical, easy-to-understand way to visualize complex data and optimize real-world problems. They help us see relationships we wouldn’t otherwise notice—whether that’s understanding urban layouts, optimizing logistics, or even influencing how a soccer team plays on the field.

As John Tukey, the famous statistician, once said, “The greatest value of a picture is when it forces us to notice what we never expected to see.” And that’s exactly what Voronoi diagrams do: they help us see the structure in our data that might otherwise remain hidden.

So next time you’re deciding which coffee shop to visit or calculating the best route to take in your city, think of the unseen Voronoi lines dividing the world into neat little regions—and be thankful for the math behind the magic.

References:

• Steven Fortune, Computational Geometry Expert

• StatsBomb Soccer Analytics

Gold Teeth and a Curse: How ‘New Slang’ Became Spotify’s Algorithm Darling

If you’ve spent any significant time curating the perfect playlist on Spotify, you’ve probably noticed a peculiar pattern: no matter what vibe you’re going for — indie, folk, lo-fi, or even that “cosmic yacht-rock for introverts” playlist you swore would be your magnum opus — New Slang by The Shins sneaks in like a chameleon.

“Honestly, I was just looking for some post-punk jams and there it was — New Slang — just chilling between The Cure and Siouxsie and the Banshees,” says Lily Martinez, an unsuspecting indie enthusiast from Austin. “It’s like that kid in high school who somehow made friends with the skaters, the goths, and the band geeks at the same time.”

But how? How does one song, released over two decades ago, keep slinking into every corner of modern music? Let’s unravel the mystery behind Spotify’s ultimate love affair with New Slang.

The Algorithm Is A Sentimental Hipster

If Spotify’s algorithm were a person, they’d definitely be sporting a beanie, sipping cold brew, and carrying a weathered copy of Infinite Jest. They’re nostalgic, but they also get the cultural moment. And if there’s one song that perfectly encapsulates the late-90s/early-2000s indie renaissance that still influences much of today’s music, it’s New Slang.

Released in 2001 on Oh, Inverted World, New Slang was the ultimate indie sleeper hit — the song that quietly (but emphatically) found its way into the hearts of a generation who realized that maybe, just maybe, music could make you feel seen. When Natalie Portman said the song would “change your life” in Garden State, it didn’t just boost CD sales. It planted New Slang firmly in the cultural zeitgeist.

But Spotify wasn’t even born then. How is it still happening now?

Data Science Meets That “Indie Feeling”

Algorithms don’t have feelings (yet), but they can understand patterns. Spotify’s recommendation system uses something called collaborative filtering. It’s like digital matchmaking. When users repeatedly pair certain songs with other tracks or genres, Spotify’s machine-learning model takes notes. Imagine a little robot DJ studying your every mood.

For some reason, New Slang has become the connective tissue between seemingly unrelated genres. It’s not overly complex, but it’s deeply nostalgic, wistful, and oddly malleable. Whether you’re diving into Americana, dream pop, bedroom lo-fi, or even coffee shop jazz, there’s a delicate vibe that New Slang taps into.

Jake Carmichael, a playlist curator from Brooklyn, notes, “It’s like the aural equivalent of sepia tone. No matter where you throw it, it feels like a dreamy afterthought that still fits.”

New Slang: The Swiss Army Knife of Music Moods

You can be seeking out the perfect somber folk tunes for a rainy day, or just looking for some 2000s bangers to relive the glory days, and there it is again — New Slang — subtly sneaking in. Why? Because New Slang doesn’t commit too strongly to any one mood, which makes it weirdly universal. It’s mellow enough to be background music but meaningful enough to resonate when you need it.

Think about its simplicity: James Mercer’s slightly cryptic lyrics, a melody that feels both melancholy and warm, and a rhythm that can’t quite decide whether it’s laid-back or lively. All of this makes it flexible. It works for indie romance playlists, but it also vibes with a chill-out session or an “existential reflection in the bathtub” playlist. The song is like tofu — it takes on the flavor of whatever’s around it.

Brian “DJ Calcifer” Holmes, a DJ specializing in genre-bending playlists, says, “Honestly, if you need a song to stitch together a 90s alt-rock set with some indie-folk, New Slang is your glue. It’s the musical version of mood lighting.”

Spotify’s “If You Like That, You’ll Love This” Problem

Then there’s Spotify’s famous recommendation engine — the thing that leads you down the rabbit hole of endless suggested tracks. If you listen to Fleet Foxes, Iron & Wine, or any artist adjacent to the indie-folk realm, you’ll quickly be served New Slang on a silver platter. It’s like the algorithm is saying, “Oh, I see what you’re into — here’s a classic you’ve probably heard, but hey, you’ll love it anyway.”

And it doesn’t stop there. Even within more niche subgenres, New Slang makes appearances. Lo-fi beats for studying? Yep, New Slang probably made the cut. Throwback playlists from the early 2000s? Guaranteed. Spotify’s algorithms can’t help but see New Slang as a sort of gateway track, the gentle nudge that keeps you on your “discovery” journey.

The Ultimate Indie Influencer

Though it may have started as an indie anthem, New Slang has achieved something few songs of its time have: lasting influence across generations of music. Part of this staying power comes from how its minimalist structure and introspective tone resonate with modern music production. It’s not just nostalgia — it’s that New Slang captures a very specific feeling.

In a world where genres are constantly blending, New Slang has become an unofficial soundtrack for cross-genre vibes. Today’s artists who grew up on this track infuse its influence into their work, whether consciously or not. Listen to artists like Sufjan Stevens, Phoebe Bridgers, or even the softer side of Bon Iver, and you’ll hear echoes of that same stripped-down, heartfelt sound that makes New Slang both timeless and genre-fluid.

Will New Slang Ever Let Us Go?

So why does it keep happening? Is it Spotify’s fault, or is it ours? The truth lies somewhere in between. The algorithm is a reflection of our collective listening habits, and New Slang occupies a special place in that musical landscape. It’s nostalgic without being dated, emotional without being overwrought, and its dreamy sound makes it adaptable to almost any playlist.

But at the end of the day, we keep listening to it because it works. Whether we’re sad, happy, or just sipping coffee while pretending to be deep in thought, New Slang fits the mood. Spotify knows this. You know this. And now, you just have to accept that New Slang will always be there — like the soundtrack to an indie film you didn’t know you were starring in.

“Sometimes I try to skip it,” admits Mia Patel, an indie music lover from Portland, “but honestly? Halfway through the next song, I just go back. New Slang feels like a song that’s somehow a part of me, whether I want it to be or not.”

Whether you’re curating an ultra-specific playlist or diving into Spotify’s radio suggestions, don’t be surprised when New Slang shows up. Embrace it. Maybe James Mercer and Spotify are in cahoots, or maybe New Slang is just that good.

About the Author: Curt Jones is the founding partner at Proklamate, a fractional analytics consulting firm in Boise, Idaho.