Two New MVPs: Minimum Viable Process and Planning
Innovation doesn’t scale. Stop trying to make it.
You’ve heard of Minimum Viable Product—Eric Ries coined the term to describe a version of a product that offers maximum learning at minimal effort.
Here are two more MVPs: Minimum Viable Process and Minimum Viable Planning.
Most companies get MVP culture right at the beginning. Then they grow, add systems, and accidentally kill the thing that made them successful in the first place.
Innovation Doesn't Scale Well
Most companies get MVP culture right at the beginning. Then they grow, add systems, and accidentally kill the thing that made them successful in the first place.
The rule of 3 and 10.
I’ve worked with companies at every stage—early startups to Fortune 50 enterprises. There’s a framework that helps explain what happens as companies scale: the rule of 3 and 10.
Hiroshi Mikitani, CEO of Rakuten, observed that as companies grow in multiples of 3 and powers of 10, systems and processes start breaking down. What works with 3 people doesn’t work at 30. What works at 30 doesn’t work at 90, 270, and so on.
I generally agree with this for most functions—finance, operations, sales, marketing. These areas need systems to scale.
But there’s one exception: innovation.
The startup phase: chaos works.
Startups have one job: find product-market fit with minimal distraction. That means failing fast, shipping MVPs, absorbing customer feedback, and iterating without overthinking it.
There’s no time for elaborate planning. Expensive tech stacks, formal processes, hierarchies—all of that can wait. You’re moving too fast to build scaffolding.
The scale trap: growing up too fast.
Once companies find product-market fit, sign initial customers, and start growing, basic systems get implemented. This is necessary—without some structure, profitability becomes unreachable.
But here’s where it goes wrong: there’s a gravitational pull to add process, planning, and technology too soon. Companies start building for future scale before they’ve proven current traction.
Scaling infrastructure prematurely overheats resources, burns capital, and distracts from revenue growth. Worse, innovation suffers because added processes create friction. The speed that got you here slows to a crawl.
The enterprise phase: the giant hairball.
Years of growth mean layers of products, businesses, technology, systems, rules, traditions, and processes. Gordon Mackenzie called this “orbiting the giant hairball”—an ecosystem that consciously or subconsciously wrings risk out of the organization.
Employees execute defined routines with little upside to innovate. Risk-taking gets punished. Mavericks get treated like viruses—corporate antibodies attack until the innovators leave or conform.
Innovation becomes incremental product improvements instead of disruptive new business models. Stage-gate processes with five layers of approval. Five-year plans that are outdated before they’re finished. Six Sigma rigor applied to exploring the unknown.
It’s all designed to reduce risk. And it works—by also eliminating the conditions that create breakthroughs.
The permanent MVP state.
Here’s my thesis: organizations should resist scaling processes and planning specific to innovation functions at all growth stages.
Minimum Viable Product, Minimum Viable Process, and Minimum Viable Planning should be the permanent state for new technology, product, and business model innovation.
Innovation culture should not grow up. It should maintain MVP vitality forever—regardless of whether the company has 30 employees or 30,000.
Why Elon gets away with it.
Love him or hate him, Elon Musk routinely wills a general concept into a billion-dollar business across industries. Ideas that would die immediately in most organizations.
Why? He thinks in first principles. He asks questions the way a child would—without baggage, without “that’s not how we do things here.” But he combines that childlike curiosity with advanced intellect and experience.
His other differentiator: bias for action. He ships. He tests. He breaks things and learns fast.
Most enterprises have the intellect and resources. What they lack is the willingness to stay in permanent startup mode for their innovation functions.
How to keep innovation wild.
Here’s how to maintain an MVP innovation culture as you scale:
1. Keep teams small.
Product development teams should stay under 10 people. Independent. Autonomous. Free to chase seemingly crazy ideas.
In my experience, five teams of five working on the same problem outperform one team of 25. Small teams move faster, communicate better, and don’t need three layers of approval to make decisions.
2. Go agile, actually.
Agile methodology is standard in startups, especially for developers. It’s less common in enterprises still clinging to waterfall processes.
Invest in real agile training across functions—not the bastardized “agile” that just means more meetings.
3. Use simple frameworks.
Business Model Canvas is visual and straightforward. It forces you to think through key assumptions on one page.
If your planning document is longer than one page in the early stages, it’s probably too much. You’re planning instead of learning.
4. Build internal VC funding mechanisms.
Many large enterprises have corporate VC arms to invest externally. Let internal innovation teams tap the same funding mechanisms.
Keep the process simple—no 47-slide decks to get $50K for an MVP.
5. Kill stage-gate processes for innovation.
This is hard for me to say—I’ve advocated for stage-gate processes most of my career. But they don’t work for early-stage innovation.
Develop a simple prioritization framework. Start working on the best ideas. Iterate based on what you learn, not what the stage-gate calendar says.
6. Stay horizontal.
Layers of hierarchy kill decision-making speed. Stick with horizontal org designs as much as possible for innovation teams.
If someone needs three approvals to run a $5K experiment, you’ve already lost.
7. Protect the mavericks.
I’ve heard the talk in large corporations about embracing risk-taking and entrepreneurial culture. I have not experienced it being real.
Risk-taking and failure lead to corporate exits—voluntary or involuntary. Mavericks get treated like threats. For every maverick pushing boundaries, there are ten employees rooting for them to fail so things can go back to normal.
In startups, everyone is a maverick—or they’d find less risky jobs that pay more. Enterprises need to create protected spaces where mavericks can operate without corporate antibodies attacking them.
8. Simple financial modeling.
I’m guilty of building complex financial models in early-stage product development. My learning: a simple model works just as well to determine if you’re on the right track.
You don’t need 20-year forecasts with sensitivity analyses when you’re testing whether anyone wants the product.
The takeaway.
Companies scale. They add systems, processes, technology, people, and planning. That’s fine—most functions need structure to operate efficiently.
But innovation is different. It’s an animal that needs to stay a little wild.
As companies grow, they try to cage the innovation function. Bring it under control. Make it predictable. Reduce the risk.
Resist.
Keep your innovation engine in permanent MVP mode. Small teams. Simple frameworks. Bias for action. Protection for mavericks.
Scale the parts of your business that benefit from systems. Keep innovation chaotic, fast, and a little bit dangerous.
That’s where breakthroughs come from.
Book a Call
If you like what you see, we think you’re gonna love what you hear. Book a first consultation with us, and together we’ll figure out how to make your life a little better.
Why Mastery Is Expensive But Competency Scales
Easy to do, hard to master.
I saw this phrase describing a SaaS platform. Simple. Layered. It stuck with me.
So I started applying it elsewhere—skills, workflows, career planning. It turned into a framework for thinking about where to invest time and what mastery actually costs.
Mastery isn’t the only path.
Social media makes it feel like deep expertise is the only winning formula. 10,000 hours. Become world-class. Own your niche.
And sure—mastery can lead to outsized returns. But there are plenty of paths to success that don’t require becoming the best in the world at something. You just need to be strategic about where you go deep and where you stay broad.
That requires thinking about commitment, risk, natural ability, value, and time. Not every skill is worth mastering. Some are worth knowing well enough to be dangerous. Others are worth automating entirely.
Mastery Is Expensive, Competency Scales
Mastery takes time, focus, and obsessive depth most people don’t have. Competency across a dozen high-value skills lets you diagnose fast, connect dots others miss, and know when to bring in experts.
Depth vs. range.
Genetic disposition plays a role here. Some people have the wiring for mastery—the obsessive focus, the tolerance for repetition, the ability to grind on one thing for years.
Others don’t. They consume breadth. They connect dots across domains. They’re competent in twelve things instead of world-class in two.
Neither is better. But you need to know which you are, because the strategy changes.
The framework.
Here’s how I think about skill development across four quadrants:
1. Easy to Do, Hard to Master
This is where I spend most of my time. CRM systems. Coaching. Consulting frameworks. SaaS platforms. Strategy development. Writing. Project management.
My approach: build a broad base of moderate skills with the ability to go deeper when a specific situation demands it. I’m not trying to be the world’s best Salesforce admin. But I can configure it, troubleshoot it, and know when to call in an expert.
Go-to resource: YouTube tutorials, vendor documentation, pattern recognition from repetition.
2. Easy to Do, Easy to Master
I minimize time here. Most manual, stepwise processes fall into this bucket—data entry, basic formatting, repetitive admin tasks.
My goal: automate or outsource anything in this category. If a process can be scripted, documented, or handed off, it should be. These skills don’t differentiate you. They just consume time.
Go-to resources: Scribe for documentation, Zapier for automation, RPA tools, virtual assistants.
3. Hard to Do, Hard to Master
I don’t claim mastery in anything here. Few can. But I maintain competency in several hard skills I’ve developed over my career—programming, sales, lead generation, financial modeling, design thinking, product development.
These require real commitment. If you start down one of these paths without a solid reason, you’ll burn significant energy for minimal gain. But if you choose wisely, competency in hard skills opens doors and commands higher compensation.
Masters in these areas are rare and expensive. Knowing enough to evaluate their work, brief them effectively, and integrate their output is often more valuable than trying to become one yourself.
Go-to resources: Networking, online communities, mentorship, paid courses with real feedback loops.
4. Hard to Do, Easy to Master
I struggled to populate this quadrant. Accounting, maybe? Skills with high barriers to entry but clear paths to competency once you’re in?
Honestly, I don’t invest here. If something is hard to access but easy to master once you do, it’s probably not a leverage point for me.
My personal thesis.
I aim for competency across the value stack of business transformation—enough depth in hard skills to diagnose opportunities, enough breadth to see connections others miss, and enough humility to know when to bring in masters.
The goal isn’t to be the best at any one thing. It’s to be dangerous enough in the right combination of things that I can rapidly assess what’s broken, what’s possible, and who needs to be in the room to execute.
I need to know what mastery looks like so I can help clients stitch together the right resources for ambitious projects. But I don’t need to be the one delivering that mastery in every domain.
The exercise.
Take fifteen minutes and map your own skills across these quadrants:
- Easy to do, hard to master — Where are you building broad competency?
- Easy to do, easy to master — What are you automating or outsourcing?
- Hard to do, hard to master — Where are you committing real energy? Is it worth it?
- Hard to do, easy to master — Does this quadrant even exist for you?
Then ask yourself:
- What’s your commitment level to each category?
- What’s your natural wiring—depth or range?
- What does your skill development thesis look like over the next three years?
This should be unique to you. Don’t copy someone else’s path because it worked for them. Figure out where you have leverage, where you have interest, and where the intersection of those two things creates value.
The takeaway.
Mastery is expensive. It takes time, focus, and often a specific genetic disposition for obsessive depth.
But competency is scalable. You can be competent in a dozen high-value skills and still have time to build a business, stay curious, and avoid burnout.
The trick is knowing which skills are worth going deep on, which are worth staying broad on, and which are worth ignoring entirely.
Most people never ask the question. They just accumulate skills randomly and wonder why nothing compounds.
Book a Call
If you like what you see, we think you’re gonna love what you hear. Book a first consultation with us, and together we’ll figure out how to make your life a little better.
How Legacy Infrastructure Kills New Ventures
Why your growth initiatives keep dying.
Most enterprises carve out capital for new ventures. They target high-growth markets that complement the core business. They staff up with smart people. They launch with fanfare.
Then the initiative dies quietly eighteen months later.
You can blame culture. You can blame execution. You can blame market fit. But there’s a deeper pattern: business model coupling. Companies try to run new business models on legacy infrastructure. Round peg, square hole. It doesn’t work.
Legacy Becomes the Liability
Most enterprises believe their infrastructure is an asset for new ventures. In reality, legacy systems create friction, bloated costs, and customer experiences that tank NPS before you hit year two.
The Widget CO problem.
Here’s the pattern. You’re a global construction widget company. Fifty years building market dominance. World-class at manufacturing, distribution, channel partnerships, and service. Strong margins. But growth has flatlined, and the CEO wants “innovation.”
A sharp team builds a cloud-based software stack. Game-changing product. The MVP crushes in early trials. So leadership launches it through the existing channel—leveraging fifty years of distribution muscle.
A year later, software revenue is 10% of plan. Leadership wants to kill it.
What happened?
You tried to sell SaaS like you sell widgets.
Widget CO is phenomenal at moving hard goods. They’ve optimized heavy tech stacks like SAP. Trained partners to maximize widget market share. Built supply chains that work at scale.
But SaaS is a different business model. Different economics. Different playbook. Different customer expectations.
Widget CO doesn’t know this playbook, so they customize a hybrid Frankenstein solution. The result: terrible customer experience, bloated costs, and unit economics that make no sense compared to benchmarked SaaS businesses.
The legacy becomes the liability.
Widget CO believes they’ll win because they have infrastructure, brand equity, and distribution. And sure—some of those assets help. But most create friction.
The legacy infrastructure was built to support channel partners, not sell directly to end users. Channel partners don’t know how to sell SaaS—they’re widget people. There are no implementation partners. Minimal tech support for customers. The service org can’t answer basic software questions.
NPS craters. The new product threatens the brand. Finger-pointing starts. Before long, the initiative gets shelved.
Fast forward three years: an external startup with an inferior product becomes a unicorn solving the same problem.
How to actually win at this.
Companies that approach new business models with humility can avoid this outcome. Here’s how Widget CO should’ve played it:
1. Use the actual playbook.
SaaS has well-defined business models. Don’t reinvent the wheel. Build from the ground up using proven SaaS economics—CAC, LTV, churn benchmarks, pricing models that work. Use frameworks like the Business Model Canvas to map it out before you build anything.
Don’t retrofit your legacy model and call it innovation.
2. Extract to survive.
New ventures need protection from the mothership. They can’t operate under the same KPIs, approval chains, and quarterly pressures as mature business units.
Create an internal or external venture structure with autonomy. Let them iterate and fail like a startup. Compensate for risk-taking, not for playing it safe. The good news: this can all be virtual. You don’t need a Silicon Valley office.
3. Build a modern tech stack.
Cloud platforms let you stitch together best-in-class capabilities with fewer resources. But don’t force new ventures to use legacy tech stacks designed for mature business models.
Your SAP instance is not the answer. Give new teams autonomy to build lean, proven stacks that match their business model.
4. Cherry-pick the good stuff.
Some legacy assets actually help. Brand recognition. Existing relationships. Distribution muscle—if used correctly.
Figure out which assets create value for the new model. Then structure internal systems to create win-win behaviors. Sales and channel partners can be useful if they’re designed into the business model with the right expectations and training.
Don’t assume everything transfers. Most of it doesn’t.
5. Study what actually worked.
Dig into the ventures that succeeded. What forces enabled those outcomes? What did leadership do differently? What constraints were lifted?
Repeat the elements that worked. Kill the rest.
6. Organize by business model, not business unit.
Some enterprises benefit from organizing around business models instead of traditional structures. Industrial products, retail, ecommerce, SaaS, services—each operates with different economics and different playbooks.
Forcing them under one P&L with shared KPIs creates misalignment and politics.
The takeaway.
Corporate ventures fail for many reasons. But business model incompatibility is the root cause nobody talks about.
Taking time upfront to research the business model and its requirements will save you eighteen months of expensive theater. You’ll either build something that works, or you’ll kill it early before burning capital and credibility.
Stop trying to force new business models into old infrastructure. It’s expensive, demoralizing, and predictable.
Book a Call
If you like what you see, we think you’re gonna love what you hear. Book a first consultation with us, and together we’ll figure out how to make your life a little better.