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Stop Working Harder: Use the Theory of Constraints to Finally Get ROI From AI
Key Takeaways:
- Most AI initiatives fail to show ROI because teams apply AI “everywhere” instead of fixing the single biggest bottleneck in the system.
- The The Goal insight is simple: improving anything that isn’t the constraint doesn’t help—and can make the system worse by creating more work-in-progress.
- Use the traffic-jam test: if a five-lane highway narrows to one lane, widening any other section just creates a bigger pile-up—marketing workflows behave the same way.
- Constraints in marketing often hide in approvals, unclear strategy, overloaded creatives, broken intake, rework loops, and slow reporting—AI only helps when it targets the true choke point.
- Step zero matters: align on the goal of the marketing system (awareness, pipeline, retention, conversion). If the goal isn’t shared, constraint-finding and AI investment become guesswork.
- Identify the constraint by asking: Where does work wait the longest? Where do tasks pile up? Where does rework repeat? If one step sped up, what would unlock everything else?
- Before adding new tools, “exploit” the constraint with low-disruption moves: clear intake requirements, define ready/done, streamline reviews, remove distractions—then use AI for targeted support (first-pass checks, feedback summaries, standardized briefs).
- Subordinate the system to the constraint: stop launching more work than the bottleneck can handle and prevent work from boomeranging back through the choke point.
- Only then “elevate” the constraint with bigger changes (hiring, automation, AI agents, removing steps)—treat it as precision tuning, not a sledgehammer.
- Constraints never disappear; they move. Repeat the cycle—Identify → Exploit → Subordinate → Elevate → Repeat—to stop chasing AI hype and start getting compounding ROI.
Here’s a depressing stat for you: 95% of executives say they’re struggling to see any ROI from their AI initiatives.
That’s not because AI doesn’t work; it’s because most organizations are applying it in the wrong place.
They’re working harder. They’re buying tools faster. They’re automating everything they can touch.
And yet… nothing really changes.
If that sounds familiar, the solution isn’t another shiny AI platform. It’s a systems-thinking concept from a book written in 1984.
Yes, really.
It’s called the Theory of Constraints, and once you understand it, you’ll never look at your marketing workflow – or your AI roadmap – the same way again.
Why Working Harder Is Often Making Things Worse
The Theory of Constraints comes from Dr. Eli Goldratt’s book The Goal. It was originally written for manufacturing, but don’t let that fool you. The ideas apply beautifully to modern marketing, especially now that our systems are more complex than ever.
The core premise is that every system has at least one constraint at all times.
A constraint is the single biggest thing limiting your ability to achieve your goal. And if you don’t identify and address it explicitly, the system will never improve.
Here’s the part most teams miss:
Improving anything that is not the constraint does not help. In fact, it can actually make the whole system worse.
This is exactly why so many AI initiatives fail.
Teams add AI “where it fits,” or where someone got excited, or where a vendor demo looked impressive.
But they never stop to ask: Is this where our system is actually stuck?

The Traffic Jam That Explains Everything
Let’s make this concrete.
Picture a five-lane highway that suddenly narrows down to one lane.
Traffic backs up. Cars crawl. Everyone is frustrated.
That single-lane section is the constraint.
Now imagine trying to fix the problem by:
- Adding more lanes before the bottleneck
- Making cars go faster after the bottleneck
- Improving literally anything except the single lane
None of that helps – it just creates more pile-up.
Your marketing workflow works the same way.
Your process is only as fast and effective as its slowest point. Until you fix that point, nothing else matters.
Where Constraints Hide in Marketing Teams
In marketing, constraints show up in lots of places. Here are some of my least favorite:
- Slow or painful approval processes
- Unclear strategy or shifting priorities
- Overloaded creatives
- Broken intake systems
- Endless rework and revision cycles
- Reporting that takes longer than the work itself
AI can help with many of these, but only if you apply it at the actual bottleneck.
Slapping AI into a random step of the process is like widening the wrong part of the highway. It looks productive. It feels busy. And it accomplishes nothing.
So, what do we do instead?
Step Zero: Define the Goal (Yes, This Matters)
Step 1: Identify the Constraint
After identifying your actual goal, this is the most important step. So do not rush it.
Ask questions like:
- Where does work wait the longest?
- Where do we see the most delays?
- Where does rework happen over and over?
- Where do tasks pile up?
- If I could speed up one step, which one would make everything else easier?
That spot – the place where work consistently slows down – is your constraint.
And here’s the hard truth: Working harder anywhere else will not help.
It may even make the constraint worse by pushing more work into an already jammed lane.
Step 2: Exploit the Constraint (Without Burning People Out)
“Exploit the constraint” is a terrible phrase, so let’s start by clearing something up: It does not mean chaining someone to their desk.
It means making the constraint as efficient as possible without changing the system yet.
Some low-disruption ways to do that:
- Remove distractions from bottleneck roles
- Clarify intake requirements
- Define “ready” and “done” clearly
- Reduce unnecessary meetings
- Streamline reviews
This is often where AI can help – carefully.
For example:
- AI can do a first-pass review so humans only do final checks
- AI can summarize feedback to reduce back-and-forth
- AI can standardize briefs so work arrives complete
The goal here is simple: The bottleneck should only be doing bottleneck-specific work.

Step 3: Subordinate Everything Else to the Constraint
This is where systems thinking really shows up.
Once you’ve identified the constraint, the entire system must support it.
That means:
- Stop launching new work if the bottleneck is backed up
- Don’t create more campaigns than design can handle
- Don’t flood the system with requests that can’t be processed
- Do everything in your power to avoid sending work back to the bottleneck after it’s left
Everyone benefits when the bottleneck moves faster, so everyone has to adapt their behavior.
There’s nothing that’s “the bottleneck’s problem.” If it affects the bottleneck, it’s the system’s problem.
Step 4: Elevate the Constraint (Now You Can Add Muscle)
Only after you’ve exploited and subordinated do you move here.
Elevating the constraint means changing the system itself. We do this last because it’s usually the most expensive and the most disruptive, and we want to make sure we try the easier stuff first.
This could include:
- Hiring or contracting additional help
- Adding automation
- Introducing AI agents
- Removing steps entirely
This is where AI often shines, but only because you’ve done the thinking first.
Good AI use cases at this stage include:
- Drafting content so humans focus on refinement
- Triage and prioritization of incoming requests
- Automated reporting that flags only meaningful anomalies
- Agents that handle repetitive back-and-forth without fatigue
Remember, in this and all use cases, we aren’t wielding a sledgehammer. We should consider systems adjustments a precision exercise.
Make small adjustments, see what happens, and then move forward from there.
Step 5: Repeat (Because There Will Always Be Another Bottleneck)
Once you fix one constraint, another will appear.
That’s not failure, that’s progress.
You’re not trying to create a perfect system. You’re making it less broken, one bottleneck at a time.
Over time, you also get better at this process. You learn where AI actually helps. You stop chasing hype. And you start seeing real ROI – because you’re applying effort where it matters most.

AI Isn’t a Flying Car. It’s a Wider Bridge.
AI doesn’t eliminate constraints. It shifts them.
Think of it as widening a bridge to ease traffic – not magically teleporting everyone to the other side.
Once you fix your current bottleneck, new ones will emerge:
- You fixed the design process, now the holdup is in content review
- Reporting isn’t a struggle anymore, but the briefs are holding everything up
- Intake and prioritization used to be a nightmare, but now we can’t seem to get feedback once the work is underway
- You finally have stakeholder alignment, but the higher volume of work has revealed a lack of execution capabilities downstream
The good news is, you already know what to do about these new bottlenecks.
- Identify.
- Exploit.
- Subordinate.
- Elevate.
- Repeat.
That’s how you build a marketing system that actually improves over time, and avoid becoming another cautionary tale of expensive AI tools with nothing to show for them.
Topics discussed
Andrea Fryrear is a co-founder of AgileSherpas and oversees training, coaching, and consulting efforts for enterprise Agile marketing transformations.
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