Broken from the Top to Bottom, Inside and Out

As a product marketer for over 15 years, I’ve had a front row seat to how companies really function. For some time now — years, really — I’ve been feeling something big is off in tech. I used to think it was just exec teams who didn’t understand product marketing was the issue. But the more I spoke with colleagues, the clearer it became: we were all witnessing the same fundamental breakdowns. Companies lack basic processes to move from idea to product to market, contracts are executed on Word docs, no consistent way to sell, and no differentiators anywhere in sight. And that’s for the product they sell. For their employees — no investment in developing the skills their people need to do a job well. Teams reinvent the wheel on every project because best practices are for someone else. No one knows how decisions are made — or who makes them. But it’s more than that. The problems I’ve been seeing and working on over the last 15 years aren’t just operational — they’re foundational.

Have you ever wondered why tech companies, lauded for their innovations and advancements, so readily accept an organizational structure that came about almost 50 years ago? Leadership designed for 20th-century hard goods is trying to run 21st-century software companies.

The current day C-Suite was born during the 1980s-90s for companies that made hard goods — like building railroads or manufacturing cars and appliances. What caused the CEO to need help? I won’t be so naive as to pin it on one thing, but let’s focus on something we can all relate to today: information explosion. Companies had to move from general managers making decisions to leaders who possessed specialized knowledge over a particular domain (think: finance, marketing, sales, etc.). And this made sense — someone who knows and is closer to the business of the department was the best person to provide insights to make better decisions.

You’re probably saying this isn’t any different from today, but this is where you’d be wrong.

The major difference between the last decades of the last century and where we are in the first quarter of the new century is speed.

The speed of information. The speed of technology. The speed of economic change. The speed of new competitors. The speed of AI.

All of this on top of globalization.

Consider that: 49% of companies missed H1 2024 revenue targets.

61% of companies failed to meet 2023 revenue targets.

75% of enterprise companies missed revenue targets.

95,000 tech workers laid off in 2024.

10 out of 13 industries saw big declines in CX scores.

Nearly ⅔ of software customers say their vendor is failing them after close of deal.

31.1% of software projects get canceled before they finish, and more than half (52.7%) are over budget — by a huge amount (189%).

And perhaps most shockingly, tech failures cost U.S. companies $2.41 trillion in 2022, including operational failures and software errors.

These statistics are not the signs of a healthy sector. Tech is hemorrhaging.

You would think any one of these factors alone would make the argument for doubling down on domain knowledge expertise leading the charge. But the current organizational structure doesn’t reward those with the most domain knowledge. To understand this, we need to look at where power is concentrated. Power lives at the top, somewhat divided between finance, marketing, sales, and if you are a larger company, operations. Even when domain expertise exists, the hierarchy slows the information flow as it goes up one side of the chain and back down. Yes, tech moves faster than traditional corporate structures, but it’s still slow compared to how fast the market is changing — plus you get the added bonus of some of the most detrimental elements to decision-making: “yes” men and “get in line” mentality. If I were a CEO and I heard only good news, I would be very suspicious that someone isn’t telling me the truth.

Old style organization and hierarchical management stifles innovation.

Pick a random tech company and check out the Leadership page. What do you see? Mostly white men with the token woman in HR or Marketing. The statistics bear this out.

“Ethnically and racially diverse executives are just 12.5% of CEO, CFO and COO positions in Fortune 500 and S&P 500 companies” according to a study done by CFO Dive. Qualtrics reported in “…2023, 37 of the top 50 Fortune 500 companies’ CEOs were white men.” We aren’t injecting perspectives of the world into solving world problems. The very problems tech promised it could solve. We are shown only one way to fix things.

Tech pays a lot of lip service to innovation and to being entrepreneurial, yet change is not welcomed. Those who don’t agree with management are typically silenced. Either suppressed or ousted. Employees are told to get on the bus or get off the bus. We are told culture is good. That culture “gets things done.” But this kind of “cult”-ure is just a form of control. Wear the free tshirt, show everyone free swag when coming on board, tell others about your #dreamjob. Not-so subtle forms of control. You are one of us now. And to remain one of us, you must comply.

Control remains in the hands of the few who are so removed from what happens in the trenches on the daily, it’s almost farcical. Somehow we have been led to believe the men at the top are the ones who have the more knowledge to make the decisions that are in the best interest of the company.

Think about the last time you brought up an idea or pointed out a problem. Maybe you told your boss. They might have said this is great, you should move it forward — or perhaps they offered to bring it forward themselves. If it was really good, they might have presented it as their own idea. If it was “too radical,” there was some calculation on how to present it as something to be flicked away and damage your reputation at the same time. Too harsh? You haven’t worked in tech.

And now, tech is betting the farm on AI. What could possibly go wrong?

Here’s the thing no one wants to admit: AI is in its infancy. Don’t believe the hype of funding rounds. The vast majority of Americans don’t know what AI is or recognize when they’re using it — yet they use it every day on their iPhones. It looks like pattern learning, like recommendations, like automations triggered by behavior. For tech, it’s the proliferation of LLMs and advanced automations. It looks like predictive analytics. It looks like firing your staff because now AI can do it. This is happening because the c-suite is out of ideas on how to squeeze more dollars — called productivity — out of their staff. It’s happening because many working in tech aren’t ready to see the problem — that the c-suite itself is the wrong approach for innovation and growth. Handing over the decision making power to a group of ego-centric people (not a dig, but IYKYK) who lack understanding of external market factors or refuse to acknowledge internal capability gaps is problematic enough. Add in poor process definition plus lack of data governance that skews the revenue picture, well, that’s a recipe for disaster.

Is there a way out? Yes. Is tech ready for it? That depends on the reason you got into tech in the first place.

The signs are clear: centralized decision-making creates arbitrary slowdowns, homogeneous leadership narrows perspective, and hierarchical chain of command suppresses the very innovation tech companies desperately need. Fixing the current system isn’t the solution — it’s adopting organizational models that were designed for distributed intelligence and rapid adaptation.

If you’ve read Glassdoor reviews lately, you’ve seen people calling out the lack of leadership, the deafness of the c-suite, the lack of innovation in the product, the lack of communication from the top down. These are all foundational issues causing a rift between those in charge and those charged to do the work, leading to dissatisfaction in the work, the job, the workforce — burnout. It’s time for a new model. A new way to bring ideas to the fore, a new way to lead, and a new way to respect the skills and perspectives of the collective.

Wait, what did you say? What’s a collective? Are you talking about a union? No.

Organizational models exist that prioritize psychological safety — being seen, feeling valued, and having a sense of purpose. You know this rampant burn out all tech workers are feeling? A new way to work might actually re-engage, even revitalize, your talent.

I’m talking about an egalitarian approach to managing a tech business. To apply proven models to tech that accelerate innovation without burning out your staff. Think employee cooperatives, sociocracy, and matriarchal leadership as foundational systems. These exist today and are working. The future of tech is companies who recognize the collective strength in the talent of their people and are able to create decision making structures that lift the organization rather than drive it into the ground.

These businesses have opted to put people first: Alvarado Street Bakery — generates $33M annually, bakes 50,000 loaves a day; successfully navigated several downturns without layoffs when they prioritized employment over profit.

Isthmus Engineering & Manufacturing — custom automation equipment; remained in business for over 30 years while automated manufacturing contracted in the US.

Namaste Solar — solar and electrification; grown to 220+ employees over 17 years, consistently awarded and recognized year over year by local, national, and industry groups.

South Mountain Company — architecture, building interiors, solar; in business for nearly 50 years, with 33 employees, certified B corp.

These companies are successful because:

Decision making is closer to the actual work.

Diverse perspectives are valued.

Power is distributed.

They have an agreed upon purpose that doesn’t revolve around cash only.

What’s most interesting about these companies is they chose to define success differently. They aren’t going for the unicorn valuation with a big ol’ payout. They operate with a fundamentally different measuring stick — one that prioritizes human flourishing over hypergrowth and extraction.

The traditional tech model demands that employees sacrifice family time, mental health, and work-life balance in pursuit of the next funding round or exit strategy. These cooperative models flip that equation. They ask: What if success meant your employees could afford a good life without working 80-hour weeks? What if it meant stable employment that survives economic downturns? What if it meant having real input into the decisions that affect your daily work?

The assumption is that treating people well means sacrificing business results. But what if that’s backwards? What if sustainable success comes from sustainable practices?

I can hear the critics. Being “nice” at work means people will slack off and you definitely won’t hit your goals.

Wrong — Alvarado Street Bakery generates $33 million annually and produces 50,000 loaves daily. Namaste Solar has installed over 3,100 solar systems and consistently wins accolades. Isthmus Engineering generates over $20 million in revenue in the demanding, and contracting, automation manufacturing sector. These companies are successful by any reasonable business metric. They just refuse to sacrifice their people on the altar of exponential growth.

The unicorn mentality has given us the current crisis in tech — the layoffs, the burnout, the features developed for a single client that are costing you more to support than the contract value, and let’s not forget the biggest lie of them all: equity. Maybe it’s time to ask whether the real disruption isn’t a new app or platform, but a fundamental reimagining of what business success actually means.

But how do you build a company that operates in a different way? How do you create the decision-making structures that enable this alternate definition of success?

The answer lies in organizational models that distribute power rather than concentrate it. Models that give employees genuine voice in the decisions that shape their work and their company’s direction. These aren’t theoretical concepts — they’re proven systems with names like sociocracy, holacracy, and democratic workplaces. Of these approaches, sociocracy offers the clearest framework for how decision-making could work in practice.

Sociocracy is a way to self-govern based on collaboration, equity, and distribution of power.

Endenburg Elecktrotechniek uses sociocracy as its foundational structure. This pioneering Dutch company organizes around circles and a consent model for decision making. Each functional area forms a circle with two people (double links) dedicated to decisions — one externally focused, one internally focused. These roles rotate to give others opportunities to lead. The key to decision-making is consent: instead of requiring agreement, it simply asks whether the collective can live with a decision.

With a foundation defined, now we need to talk about how we get work done. You’d think getting the information needed to make decisions in a tech company would be straightforward — after all, everything is digital. But in reality, work becomes an endless series of searches — where are the latest metrics, what was just released, what are we planning on releasing next, who are the top customers. And then you want to slice that data: top customers by product, by region, by segment. Each question spawns at least 3 more searches.

Perhaps one of the reasons we haven’t tried a new organizational format — besides the type of fear that makes you throw up — is our inability to solve for, and actually stick to, decision making frameworks and the governance of data. This is where AI comes in — with the help of Web3.

AI is being used as a crutch today. It’s being forced to take over the jobs of humans because CEOs are focused on growth at all costs, or they don’t understand the value of human insight. This is an abuse of AI. AI should be used as a strategic insight generator, a pattern spotter, a thing to assist humans. Instead of a product manager spending weeks interviewing customers, AI should be continuously monitoring and analyzing the data required to make strategic decisions. AI could identify when circles are working on overlapping solutions, preventing duplicate effort before it happens, or spot where features aren’t compatible in how they’re being designed or built.

It should be helping humans make better decisions. With data governance, clear roles and responsibilities, and defined processes, AI provides the backbone of a democratic decision making process. Every voice can bring ideas forward and every decision is permanently recorded — creating an historical view into what led to these outcomes.

I can hear the doubt. Let’s see what this looks like when we apply this structural organization and methodology to doing work.

Let’s take the product manager example I mentioned earlier. Today, it takes weeks of customer interviews, market research, internal interviews, and data analysis to arrive at what’s next. Frequently these steps are cut short or cut altogether. Many companies take the safe route and do incremental improvements that really do nothing in pragmatic terms except keep the team busy through their sprint cycles. Even when something interesting is proposed, it takes weeks to get through the research, proposal, and approval process before understanding if it’s even feasible or something that solves the problem. And if it gets built? It’s punted over the walls with little explanation of why it important or relevant — but you know, everyone will figure it out.

Bleak.

It doesn’t have to be this way.

With a sociocracy organizational model, AI, and Web3, companies can go from proposing the question to building a desired feature in 2–3 days. Don’t forget, a sociocracy uses defined roles and responsibilities and decision frameworks. The foundation required for success.

Here’s how it works: When a circle proposes a new feature, AI instantly surfaces relevant data across all domains — customer support trends, usage patterns, competitive intelligence, and technical feasibility. Each circle reviews the data through their domain expertise lens and uses Web3 governance for transparent decision-making so no one can influence the results.

Each circle has a voice. Consent is necessary to move forward. Instead of building consensus — which often feels like favor-building — you ask each circle if they have a principled objection to moving forward. This shifts focus from politics to sound decision-making based on data and expertise. Product now has the insights needed and (crucially) also has buy-in from the entire organization.

The decision, complete reasoning, dissenting views, and success metrics are permanently recorded. You can even use smart contracts to automatically trigger review cycles if adoption targets aren’t met within 90 days.

The difference between consent and consensus.

In the workplace there is an idea that everyone must get along and agree on everything is a healthy way to function — so when a decision needs to be made, you have to put your energy into persuading people (stakeholders) to see things your way. And while the intent might have been to understand the needs of another business unit, it’s more like building alliances on Survivor. With consent within a sociocracy, your ideas are researched, defined, and supported through a business case — everything you need to make an educated decision. Your colleagues are expected to voice improvements, dissent, or approval. Approval doesn’t mean they have to like or love the idea, it means they can live with it — they can continue to function in a healthy manner even with this decision in place. This works for companies, like tech, who need to move forward and maintain cohesion, while avoiding decisions that could harm relationships or derail the mission.

So what’s keeping tech from moving into the 21st century?

Well, I think we know the answer to that.