Happy Triple Threat Thursday.
Here’s one Signal to notice, one thing to Spark growth and one Shift to consider.
This week's theme: Most operators already have the data. They just never interrogate it.
Every business generates revenue data, marketing data, and pipeline data. Most of it sits in dashboards nobody opens, reports nobody questions, and exports nobody analyzes. AI changed what is possible with that data. Most leaders haven't noticed yet. That gap is the opportunity.
📡 Signal — What’s Changing
Why Are Most Growing Companies Still Making Decisions Without Using the Data They Already Have?
The data problem most leaders think they have is not the one actually slowing them down.
The assumption is that better decisions require more data, better tools, or a dedicated analyst. None of that is true anymore. Modern AI systems can deal with unstructured or incomplete data sets much more easily than previous software. Businesses can now use AI without the cost and complexity of a complete overhaul of their systems.
The real problem is that most leadership teams have never been taught to interrogate their data. Reports get reviewed. Dashboards get opened. Numbers get nodded at. Conclusions get drawn based on what leadership already believed before the file was opened. That is not analysis. That is confirmation.
74% of organizations are hoping to grow revenue through AI in the future, compared to just 20% that are already doing so. The gap between those two numbers is not a technology gap. It is a behavior gap. The organizations in the 20% are asking their data questions. The other 74% are still waiting for the data to tell them something on its own.
72% of small business leaders believe AI can offer a competitive advantage. Believing it and doing it are different things. The ones doing it are pulling exports from tools they already use, running them through AI with a specific question attached, and making decisions differently as a result. The ones who aren't are still watching dashboards and calling it data-driven.
Why it matters now: The window for competitive advantage here is real and it is not staying open. Every month a competitor figures out what their data is actually telling them is a month they make a better call than you do. Most industries still have more leadership teams in the 74% than the 20%. That ratio is changing.
What to do this week: Before the next leadership meeting, ask whoever owns your reporting to pull one export and run it through AI with a specific question attached. Revenue by customer. Pipeline by stage. Marketing spend by channel. One question, one export, one answer. The output will be more useful than any dashboard reviewed in the last 90 days.
⚡ Spark — What to Try This Week
How Can Leaders Use the Data They Already Have to Get a Competitive Edge?
Most leadership teams don't push on data because nobody has framed what the right question is. The tool linked above was built to close that gap.
Whoever owns your reporting can add up to three data sources, describe the decision you are trying to make as a business, and get back the key pattern across all of them, what is missing, and three questions to take into the next leadership conversation.
It works with whatever your team already exports. Clean data is not a prerequisite. Label each source, paste the data, set the mode to show cleansing steps if you want to see what got fixed, or insights only if you want to go straight to the analysis.
One thing worth noting before your team uses it. The output is a starting point, not a final answer. The more context your team gives it, the sharper the analysis. Every recommendation should be verified against business knowledge and experience. AI analysis does not replace judgment. Data is processed in real time and is not stored or accessible by anyone.
Why it works: Smaller firms can now potentially access world-class analytics once reserved for large corporations. A leadership team that spends one afternoon interrogating its own data with AI has access to a quality of analysis that used to require a consultant engagement. Most businesses are not doing this yet. The ones who start now build a compounding advantage the ones who wait will spend months trying to close.
🔄 Shift — How to Rethink It
Is Reviewing Reports the Same as Understanding the Business?
Default belief: If leadership looks at the numbers regularly, they understand what is happening in the business.
Flip: Looking at reports tells you what happened. Interrogating data tells you why, and what to do about it.
A $23M distribution company reviewed a weekly sales report every Monday morning for three years. Revenue was growing. The leadership team felt informed. When a new operations lead joined and asked AI to analyze two years of transaction data, the output revealed that ~60% of revenue was coming from ~8% of customers, three product lines were producing negative margin after fulfillment costs, and the highest-growth customer segment was being ignored by the sales team because it didn't match the historical customer profile.
None of that was hidden. All of it was in the data the team had been looking at every week. Nobody had asked the right questions.
Why it matters: Companies using AI to drive growth and innovation are nearly three times as likely as others to redesign workflows and realize meaningful business impact. That redesign starts with knowing what the business is actually doing, not what the reports suggest it is doing. In most companies the gap between those two pictures is significant, and nobody at the leadership level has named it.
Pick one decision leadership has been making on instinct for the last six months. Find the data that should inform it. Have your team run it through AI without anchoring on the current assumption first. Compare the output to what leadership believed before the analysis ran.
Identify the one report the leadership team reviews most consistently. Ask what question that report cannot answer and what data would be needed to answer it. That gap is where the next insight lives.
Build one hour per month into the leadership calendar for data interrogation, not data review. The difference is asking a specific question before opening the file, not after.
The business that knows what its data is actually saying has already lapped the one that is still watching dashboards.
📚 Worth A Look
What Should You Be Reading About AI and Data-Driven Decision-Making This Week?
The World Economic Forum piece on why AI levels the playing field for companies without enterprise data infrastructure. The point about AI handling incomplete and unstructured data is the permission slip most leadership teams need.
Most leadership teams are hoping AI will help their revenue. A small group is already using it to do exactly that. This report explains what separates them.
The finding that AI high performers are nearly three times as likely to redesign workflows is buried in this report but worth pulling out. The data interrogation habit is a workflow change, not a technology change.
📈 TL;DR
The data to make a better decision than your competitors is already in your business. AI is how you ask it a question.
📈 One Question
When did your leadership team last ask your data something specific instead of just reviewing what it showed you?
Thanks for reading Triple Threat. See you next Thursday with another Signal, Spark, and Shift.
— Alexandria Ohlinger
p.s. If this helped you think sharper or move faster, share it with someone who builds the way you do. And if you want more practical insight between issues, connect with me on LinkedIn or schedule a strategy session.