Over time, I’ve checked out lots of numbers. Far too many truly. Like many people, I’ve struggled to maintain my head above the floor of huge swimming pools of information, desperately attempting to grasp what the floating numbers are attempting to inform me. Excel straining, my sense of self dissolving, the what is usually staring me within the face, however what I’m lacking is the so what?
The elemental problem of the trendy office is that knowledge, in its uncooked kind, is mute. A quantity on a display screen has no context, no historical past, and no motivation. But we venture onto it the load of being an “reply.” We current these silent numbers in conferences and anticipate them to drive sensible choices, however they typically fall flat, creating extra confusion than readability.
The DNA Philosophy: Each Dataset Has a Narrative
It took me far too lengthy to understand that the reply was not within the numbers, however within the story they instructed. All knowledge, when given context, can inform a narrative and at coronary heart, I’ve at all times been a narrative teller.
The Dynamic Narrative Analytics (DNA) philosophy is constructed on this single, foundational concept. Whether or not it’s a quarterly monetary report, a person suggestions survey, or a fancy A/B take a look at, there are hidden forces at play—constructive and adverse, connecting all of that knowledge right into a story. Our job is to uncover it.
The philosophy proposes that to do that, we should interrogate our knowledge with a disciplined, holistic, and constantly human-centric set of questions. As an alternative of simply asking, “What occurred?”, we should act as skeptical investigators.
It isn’t an algorithm for analysing knowledge, fairly a story layer on prime of the information that follows 4 key guidelines or inquiries to current the story to the top person.
As a result of I like a barely contrived framework, the DNA philosophy has a really on model acronym to cowl the 4 questions. AGCT: Assurance, Acquire, Readability, and Risk.
The Query of Belief (Assurance): Can I even belief this data? That is the bedrock of any credible story. Earlier than we imagine the narrative, we should validate the supply. Is the information clear? Was the gathering methodology sound? Is there a hidden bias? There isn’t any story with out belief.
The Query of Alternative (Acquire): What’s the excellent news right here? Each story wants a constructive pressure. What on this knowledge represents progress, success, or alternative? The place is the upward pattern? This provides us the measure of the entire potential upside.
The Query of Focus (Readability): Did we obtain our main goal? Within the midst of all this chance and threat, what was the one central plot level we should take note of? Each good story has a focus, and it’s our job to seek out it within the knowledge.
The Query of Threat (Risk): What’s the dangerous information right here? A narrative with out battle is a fairy story. We should actively search out the villain, the friction, or the problem. What represents a loss, a value, or a hazard? Being hyper-aware of threat is the idea of mature, defensible decision-making.
As I say, this can be a layer, a psychological mannequin for important pondering. It’s a manner of seeing. And its energy is greatest demonstrated by making use of it to fully totally different worlds.
Placing the Philosophy to the Check
Let’s see how this would possibly work in some sensible functions.
Utility 1: The A/B Check (A Formal Evaluation)
Think about AGCT is constructed into an automated DNA engine for presenting analytics for A/B assessments.
Assurance: The engine asks, “Was visitors break up pretty? Did the take a look at run lengthy sufficient? Was the amount adequate?” If not, the story is fiction, and the evaluation stops.
Acquire: It appears to be like in any respect metrics that moved positively, weights them by enterprise significance, and compiles a single rating for the entire upside.
Readability: It isolates the first purpose and asks with laser focus, “Did we obtain this particular factor with excessive statistical certainty?”
Risk: It pessimistically hunts for any metric that moved in a adverse course, particularly important “guardrails” that shield the enterprise. It’s hyper-sensitive to hurt. Did we see a drop in AOV? Did bounce charge go up?
From this structured inquiry, a wealthy narrative verdict is born: “Dangerous Winner”, “Internet Loser”, “Stable Alternative”. And from there an entire story might be born, not only a single inexperienced arrow.
You aren’t simply the purpose metric, you’re looking on the full image, weighing up the general threat and reward of the take a look at. “While we noticed a rise within the purpose metric of conversion charge, we noticed a big drop on income and aov. Cease the take a look at and re-evaluate the speculation.
Utility 2: The Annual Report (A Philosophical Evaluation)
Now, let’s depart the world of p-values and apply the very same pondering to a shiny, 80-page company annual report. This isn’t a proper engine, however a manner of studying and deciphering.
Assurance: Earlier than studying a single headline, we ask concerning the supply. “Has this been audited by an unbiased agency? Are there footnotes detailing modifications in accounting strategies? Are they counting on obscure ‘adjusted’ metrics?” That is the mental equal of the Assurance rating; it establishes the report’s credibility.
Acquire: That is the story the report needs to inform. “Headline income is up 20%. Internet revenue is at a document excessive.” We collect all these constructive factors to grasp the scope of the acknowledged success.
Readability: Final 12 months’s report acknowledged the #1 precedence was “sustainable, natural progress.” We should now ask, “How a lot of that 20% progress got here from an acquisition versus natural gross sales? Is that progress sustainable if it required chopping R&D spending?” This assessments the headline declare in opposition to the acknowledged strategic purpose.
Risk: Now we grow to be a skeptical analyst. We hunt for the counter-narrative. “Why is our market share down in a key area? Why is worker turnover up by 25%? Why has our debt-to-equity ratio worsened?” Actively looking for this data is essential for a balanced view.
One Philosophy, A Universe of Understanding
And take a look at that, with one framework consisting of 4 easy questions, we’ve remodeled a passive studying of an annual report into an energetic, important evaluation. We now have moved past merely accepting the headline numbers and have constructed a deeper, extra sincere narrative.
As an alternative of claiming, “It was an ideal 12 months with 20% progress,” our story turns into:
“The corporate delivered spectacular top-line progress, however, we did see the next than ordinary worker churn”
We’ve taken uncooked knowledge and turned it right into a easy, however way more human pleasant narrative. We now have taken the total context of all of the information, not simply the headline knowledge, and constructed a simple to grasp window into the true which means of all of it.
This looks like a super use for Generative AI in case you ask me 😉
