After a recent presentation to senior and C-suite leaders across multiple industries on how AI is re-shaping work I find the conversations lead to extremes… From we are all in to>>> we do not know how to get started👣.
It’s also ( yes, still surprising) when I hear people with the attitude that AI will NOT CHANGE HOW I WORK. AI will not initially replace… but it will separate and re-organize those that leverage this advantage and those that do not.

The disruption rarely looks like replacement anyway. It looks like compression. Tasks that took a week take a day. Teams of five become two. The people who don’t adapt don’t get fired immediately — they just become visibly less productive relative to peers who are augmenting aggressively.

There’s also a status dynamic worth naming: for knowledge workers, the process of work has always been tied to professional identity. Admitting a tool can do in 20 minutes what took you two days is psychologically costly. So people find reasons to discount it.

The people most confident AI won’t change how they work are often constructing the most elaborate reasoning to avoid finding out.

And when entire leadership teams share the hallucination? You get companies treating AI as a productivity “side hustle” — tools at the margins, workflows unchanged — while competitive exposure quietly accumulates.

Remember the telephone game as a kid?

One person starts with a simple phrase…
“Butterfly.”

It gets whispered from person to person…
slightly altered each time.

By the end of the line?

“Whitewall tires.”

Same starting point.
Completely different outcome.

That’s exactly what happens to data inside many organizations.

We start with a single source of truth — the ERP.
But as it moves across functions…

Finance adjusts it.
Sales reshapes it.
Supply chain redefines it.
Marketing reinterprets it.

Each step makes sense locally.
But collectively?

We’ve turned “Butterfly” into “Whitewall tires.”

And now…

• Revenue doesn’t match across reports
• Volume tells a different story depending on the team
• Trade spend and margin are constantly debated
• Meetings shift from decisions → to reconciliation

This is the translation layer problem.

Not a data issue.
A consistency issue.

Because every transformation layer — no matter how well intentioned —
introduces drift between the business and the truth.

The organizations that break this cycle focus on:

✔ Shared definitions across functions
✔ Governed semantic layers (not just raw data)
✔ Alignment on metrics before analysis begins
✔ Reducing “local logic” in favor of enterprise logic

Because the goal isn’t just a single source of truth…

It’s a shared understanding of that truth.

Otherwise, you’re just playing telephone —
and wondering why your “Butterfly”
turned into “Whitewall tires.”

#DataGovernance #DataStrategy #Analytics #BusinessIntelligence #Leadership #DataGene #BeCurious

In my experience, as an analyst, tool builder, sales person and data visualizer, I have seen this one component make such a huge difference. Information intimacy is the term I use to describe the series of insights (intimacy) you gain from the entire data exploration journey. From data collection, cleansing, organization, observation, analysis, metric development, statistical evaluation, cognitive inquiry to eventual data visualization, this “journey” sets the backbone for a high impact narrative.

Key Learning: Presenting insights from data that your audience is already aware of can initially help your credibility.  It let’s them know that you know a little about what they know.  THAT”S IT!!!  However, presenting information/insight they don’t know  really grabs their attention. People really listen when you say what they don’t expect to hear. Not my quote but incredibly accurate at describing interactions between presenters and presentees.

While you can always take a few select members of your analyst team with you (PLEASE DO THIS), the Sales Person is still responsible to tell a compelling story that keeps the audience engaged, interested and intrigued.  Just as you would not want a traditional sales person running your SPSS or SAS model you probably do not want your analyst talent being your sales person.  

So how do you transfer this intimacy from source to seller?

The model that’s evolving to meet this need is really blurring the lines of traditional roles. I’ve seen analyst/statisticians that are extremely savvy when presenting information to clients and influencing opinions.  Sales people who are not content in being handed a power point  a few days before a presentation.  They will sit with the analyst team and get below the obvious observations and into the information relationships that aid in exploiting the provocative.  Plus the double threat, individuals who have formally held one role then transitioned into another. How many places have you actually seen this happen?

In the opening for this post I mention how important the data exploration journey is in the development of a high impact narrative.  I recently participated in a session at a conference  on “presentation skills using story telling.”  Remember NOT everyone absorbs information in the same way.  Your ground breaking, animated bubble quadrant with live data streaming theme clouds won’t always reach everyone.  But a data visualization with PUNCH, plus a great story creates an ideal landscape for comprehension.

 

 

 

 

 

 

Looking forward to providing a “view from the trenches” on analytics, business intelligence, reporting and BIG DATA throughout the coming weeks.  The first rule of blogging… stay current, blog often and be disruptive.  More to come…