Patterns, Pitfalls, and Politics: How Your Company Really Works

We challenge the people-process-technology cliché and show how companies behave like living systems shaped by perception, connections, and constraints. Six dynamics reveal why effort often fails, where leverage hides, and how simple rules can trigger better self-organization.

• spotlight logic driving silo dominance and clashes
• nonlinear effects turning effort into leverage or waste
• connection chains creating virtuous, vicious, and neutralizing cycles
• dominance shifts moving priorities as constraints change
• latency causing overcorrections and instability
• self-organization emerging from simple rules and incentives

We give you a simple experiment or exercise you can do this week that can leverage the system for big outcomes.

Chapters

• 0:39 Welcome And Premise: Companies As Organisms
• 1:56 Spotlight Logic And Silo Dominance
• 5:31 Nonlinear Effects And Leverage
• 8:09 Connection Chains: Virtuous, Vicious, Neutralizing
• 13:47 Dominance Shifts And Constraints
• 16:57 Latency, Overcorrections, And Stability
• 20:29 Self‑Organization And Designing Simple Rules
• 25:35 Recap, Takeaways, And Next Guest Tease

Transcript

SPEAKER_05: 0:39

Let's push place right soda.

SPEAKER_03: 0:47

Hello, this is New School IT. How can I help you?

SPEAKER_00: 0:51

Hi everyone, and welcome back to New School IT. I'm your host, Roland Hoffman. This is the second episode of our special that debunks the old cliche that companies are made of people, processes, and tech because they're more like living organisms. In today's episode, I'll go through the hidden forces in your company that make it unpredictable, yet also very consistent in a strange way. I'll explain the six core dynamics that define how a company really works. By the end, you'll see how you can boost your results or your team's results with six simple try this experiments and approaches for each one of the dynamics. Okay, let's get started.

SPEAKER_01: 1:33

Please hold.

SPEAKER_00: 1:56

Your choices are optimized for what you can see and avoid decisions in the dark areas you can't see. Very rational. However, operating with that limited visibility doesn't just shape decisions. It also allows human nature to take over. Consider this. Studies of married couples found that when asked separately to estimate their share of the housework, the totals added up to more than 100%. We all tend to see our work as the center of it all. And this is made worse by spotlight logic. The real challenge here is that every team is doing it, and all of those smart isolated choices create unintended consequences when combined. In companies, that human nature allows the strongest silos to become dominant. Sales believes growth is the most important thing. Operations believes cost control driving profits is what makes the company successful. Both are right from where they stand. Given how deeply natural this behavior is, most organizations have evolved to operate that way unintentionally. We all overestimate our own contributions. When teams from different functions clash, it's usually not because the people can't get along, it's because their purposes compete. Sales makes promises that stretch what operations can deliver. Operations takes a budget hit. The real issue isn't the people, it's spotlight logic. Leaders in the highest performing companies understand this. Isolated excellence is less powerful than shared visibility. That transparency isn't about exposure or control. It's about putting a window in the walls between the spotlights so the circles of light overlap and teams stop tripping over each other. They can finally see how they fit together and build their objectives around a shared purpose. Try this. Before you kick off your next cross-functional initiative, run a pretend retrospective. With one person from each key partner, go around the room and ask everyone to answer. Imagine it's three months from now and we failed to meet our objectives. That failure has created a huge problem for your team. What specific, plausible thing caused it? This exercise shows each team's spotlight logic, in other words, their constraints, their goals, and fears, before work even begins. It's the fastest way to eliminate blind spots between teams.

SPEAKER_02: 4:35

Please hold.

SPEAKER_00: 5:31

Small actions can have a big impact, and big actions can simply fizzle. Your company isn't a machine that produces predictable linear results. It's a complex network of connections, workflows, and accumulations that can amplify or neutralize cause and effect. The same effort, say, we spend two weeks doing this, sometimes produces an output no one even notices, and other times creates massive momentum. The next four dynamics when we get to them will explain how that actually works, but for now, the key insight is this. Your impact isn't just about effort, it's about leverage. Results depend on whether you're applying that effort in the right place and time. Just work harder is usually terrible advice. What matters most is understanding how conditions will affect the outcome of your effort, not how many hours it burns. Think of pushing a car. If the brake is on, you can push it with all your strength and it won't move an inch. But the same car balanced at the top of a hill with the brake off. A light touch from you sends it rolling faster and faster downhill. Smaller effort, completely different outcome. The system state, resistance versus readiness, determined the result. Companies behave the same way. They amplify or neutralize the output from a team's work based on their current state. You can spend enormous effort across dozens of initiatives, but only the effort aimed at true leverage points actually matters. Everything else is just motion without momentum or busyness without results that matter. Try this. Add a short leverage review to your next retrospective to ask two questions. Where did our effort produce a bigger result than we expected? And two, where did we see almost no movement despite our effort? The answers reveal your company's leverage points for momentum, the places where a small push creates a big change. You could then consider this when you prioritize your work. And the one actually responsible for amping up or stalling the effects of everyone's work. Connection chains. Consider this research. Depending on their role, a typical employee takes part in over 50 workflow connections every day, using information, money, decisions, materials, and other resources to create their output. In a company of 1,000 people, that's 50,000 daily connections, over 12 million a year. In a company of 100,000, it's 5 million workflow connections in a day, or more than a billion in a year. Connections formed for workflows link up into chains that can multiply or zero out effects and carry them to unexpected places. Like a car pulled over on the highway. It looks important to rubbernecking drivers in the opposite direction and causes gridlock traffic even though it's not creating an obstacle in that direction. The same way, unexpected effects travel through invisible chains in the company. So what creates the chains? Purpose. A purpose like we sell tires creates objectives like keep the right amount of tires on store shelves. Those objectives define what gets measured, like how many tires did we sell, which then drives a decision about how many tires the manufacturer to restock inventory. The circular pattern, decide what to measure, adjust workflow, measure again, repeat over and over, in real life involves multiple teams and functions that work as a chain. Some chains amplify a virtuous cycle. Satisfied customers tell friends, sales go up. More revenue means funding better tire technology, even happier customers, even more sales. The chain reinforces itself upward. A vicious cycle works the same way, but unfortunately in reverse. Price cuts boost sales, margins shrink, less money for quality control, more defects, customers switch to competition, sales drop further, deeper price cuts. Eventually, a downward chain like this can reach a tipping point that causes real problems. If a chain's purpose is stability, it's called a neutralizing chain that eliminates any change to its target state. Let me explain. The tire company has a zero defect quality target. Quality control rejects defective tires and triggers automation adjustments until defects return to zero. This neutralizing chain restores equilibrium. When multiple neutralizing chains operate in sync with the company's greater purpose, they create resilience. Take inventory management. One supplier fails and orders route to backups, demand spikes and overtime kicks in to replenish the inventory. A product sells too slowly, and marketing runs promotions to clear the excess stock. Each chain moves at its own pace, but together they stabilize the system when it's under strain. The same neutralizing mechanisms can also fall out of sync with the greater purpose, and then they create resistance even when a change is necessary. Take a company that can't quit spreadsheets even after buying expensive dashboard software. First, there's a skills problem. Most people aren't data experts, so they build confusing dashboards. Now, everyone doubts the new system and retreats the spreadsheets for the real numbers. Second, there's a trust problem. The unreliable dashboards eroded executive confidence. So funding for data cleanup dries up and the data stays unreliable. Finally, there's an incentive chain. Bonuses and reviews still depend on the spreadsheet reports, so using them isn't resistance, it's rational. These aren't three separate issues, but an interlocking chain. The lack of skills feeds the lack of trust, which is reinforced by misaligned incentives. The root cause fix would be to close the skills gap, but spotlight logic pushes that solution outside everyone's purview. Try this. When you hit a block for a change you need, use a simple three-step audit to diagnose whether you're seeing resilience, which is good, or resistance, which is not so good. One, identify the rule or process that's blocking or reversing the change. Then ask the owner this investigative question. What valuable outcome is this rule actually designed to protect? When you discuss the answer, decide what to do. If it's something essential to the company's purpose, you found resilience. Don't break it, accept it, and redesign your process around it. If it's something that no longer matters, you found resistance. Align with the owner around a shared purpose and define a new target that aligns with the company's purpose overall. The simple audit shifts you from fighting the system to working with it, honoring the company's strengths and helping it evolve.

SPEAKER_01: 13:19

Please hold.

SPEAKER_00: 13:47

Suddenly you have to play by new rules. Dominance shifts slowly along a maturity journey. Whenever something new begins, a startup, a new team, or a new function, it moves from innovation mode to scale mode to efficiency mode. In the beginning, intensifying chains produce the most useful results. These connection chains fuel creativity, growth, and expansion. Energy builds fast. Small wins trigger big gains, and momentum compounds. However, as the innovation matures, neutralizing chains take over, bringing cost control, risk management, and process discipline. Dominance shifts quickly toward the resource that creates the biggest constraint. When a strained resource like capital, information, or talent becomes abundant, something else immediately takes its place as the new bottleneck. When revenue runs low, cost control dominates. When talent is hard to find, recruiting takes the center stage. When infrastructure can't keep up, capacity rules every conversation. External forces trigger shifts too, both slow and fast. Markets move, competitors advance, regulations tighten, technologies disrupt. While internal maturity and resourcing move leverage points and priorities, external events redefine what matters most. You might have a hiring freeze until a competitor launches a breakthrough AI feature, and suddenly recruiting a top data scientist becomes strategic. While individual teams and entire chains respond to their unique pressures, a single large enough constraint can redefine the center of gravity for the entire company for a moment or for a long time. That's why your company can feel completely different from one quarter to the next. Same team, same boss, same purpose. But dominance has shifted to a new chain. Try this. You obviously can't fix everything, and any leverage point you found won't survive the next dominance shift. This dynamic is exactly why adaptability must become a habit. In your next team meeting, I ask this what are we all waiting on right now? The answer most people share is your most constrained resource to leverage results. Track the constraint of the week regularly, and you'll start seeing the pattern. This awareness builds your team's reflex to adapt quickly. You just learned that something unexpected happened. How big should the ideal reaction be? The short-term answer is based on assumptions. The long-term answer is based on latency. To explain latency, let me start with what it's not. It's not the same as delay. Delays happen when an individual task takes longer than expected. Most companies already have neutralizing chains to handle them. If an order takes a few extra days to reach the warehouse, shipping schedules adjust, and inventory buffers absorb the delay. Customers won't notice. Latency is different. Even when every step runs perfectly, the orders received, processed, manufactured, and shipped, the full cycle might still take three months. The three months to complete the cycle, that's the workflow latency and the root cause of overcorrections. The longer the latency, the bigger the swing. Imagine a workflow with no latency between trigger and outcome. You act, instantly see the results, and adjust your next move right away. Your reaction is exactly right. Now add latency. You act. But the results aren't visible yet. You still need to keep moving. So you make assumptions and adjust your next action. And you repeat this until the day that the real data finally arrives. In a bad case scenario, by then your earlier assumptions may have been right at the time, but dominance shifted, and now all the smart moves made since then have quietly made the problem even worse that you didn't even know existed. Latencies are caused by unnecessary connections, waiting for others, rework, idle talent, and anything else that adds time without producing valuable results. This plays out across the entire company, so spotlight logic is flawless everywhere. But together, the extra time can create vicious cycles. Shortening the time between trigger and outcome has massive benefits and creates systemic stability, making your team, your function, and your company more resilient. Try this. Organize a time-to-outcome review. Stability comes from shortening the workflow time between trigger and result. So pick one critical workflow and map its latencies by asking first, what triggers the work? For example, the monthly sales report. Then how long does it take to make the decision and get the action approved? For example, four weeks to coordinate a response and get VP approval. Then there's the time to do. How long does it take to implement the action? For example, six weeks to hire a new person. And then there is the time to learn. How long before you know whether it actually worked? For example, three months before the new hire is productive. That total latency between trigger and knowing if it worked is your time to outcome. Find the longest step in the chain and design one experiment to shorten just that piece. Or pick the one that's easiest to change and start there. Any improvement will have potentially major benefits.

SPEAKER_04: 20:29

Connect the dots on the way, find the scene, calibrate, all moving away, let it be where a living stream, no school IT. Let's push more right place, right time, turn the plan into a cloud.

SPEAKER_00: 20:43

Many uncontrollable dynamics raise the final question about how your company really works. Who's actually running the company? Leaders steward its purpose, set objectives, track outcomes, and adapt strategies. But the organization's resources, workflows, connections, accumulations, and all the dynamics we've just explored here determine how that purpose and those objectives actually become results. So the answer to who actually runs the company is somewhere between leadership and the last dynamic called self-organization. Think of any company that has been around long enough, and not a single person who started it is still there. Yet the company is still operating. It acquires new resources, evolves its structure, and keeps pursuing its purpose, even as everything is constantly changing and evolving. You can see it in nature. Take a group of starlings, the swirling, shape-shifting pattern of thousands of birds flying as a single group. Each bird just follows three simple rules. Maintain a safe distance, match the direction and speed of your neighbors, and stay connected to the group. The birds can see the pattern, but we can from the ground. Complex, fluid movement of thousands of birds emerges from simple individual behavior. The same principle applies to a company's self-organization. You act from your own spotlight logic. You do what your manager prioritizes, you focus on the right metrics, you align with HR's expectations, and avoid whatever might get you in trouble. When thousands of employees do this simultaneously, patterns of self-organization emerge without a central authority having to design it. If a new rule is respond to complaints within 24 hours, a triage connection chain forms automatically. Before we wrap up, here's a thought about how self-organization affects office politics. If there is not enough transparency to avoid the pitfalls of spotlight logic, then turf battles, information hoarding, and credit claiming are predictable downsides of self-organization. It's like when budget cuts hit and everyone suddenly rebrands existing work as a strategic initiative. That competitive theater of advantage and positioning self-organizes, reacting to dynamic shifts and constantly repeating itself. A new shift emerges, new chains become dominant, old ones fade, and the cycle continues. And one last thought about change in general. If your company or your function is going through a transformation initiative, you might now understand why mandates, re-orgs, or new policies rarely make a lasting difference. This beautiful, dynamic, self-organizing company that employs you simply does what systems do, maintain stability through resilience, absorb the change, and snap back into a familiar shape. So how do you actually drive systemic change? You change the conditions to generate the right self-organization. The proven way to do this is what Soda formalizes. Create a genuine shared purpose, focus on outcomes that matter, and reduce latency to make better decisions. Now the company creates new patterns instead of defending old ones. So here's your last try this. Experiment with conditions for self-organization. Codify a new purpose in a few simple rules. Purpose is timeless, meaning it's true today and a year from now and remains true until it changed. The rules need to work like that too. Here's an example. A customer support team is buried under a thick process manual. To drive change, their leader establishes three simple rules. One, the person who takes the call owns the issue until it's resolved. There's no handoffs, no unnecessary latency. Two, solve the customer's issue first, then find the root cause and fix it. Immediate value for the customer and long-term benefit for the company. Our success will be measured by reducing recurring issues. A shift from closing tickets to real outcomes. The rules don't dictate how to work. So there it is. The complete picture of how your company actually works. Spotlight logic creates patterns and dominant silos. Nonlinear effects show how small shifts can create big results or waste enormous effort. Connection chains create virtuous and vicious cycles and build resilience and resistance. Shifting dominance moves short-term and long-term priorities. Overcorrections are caused by latencies. And self-organization is how the system actually gets it all done. These forces don't operate one by one. They're always on and constantly interacting. However, once you start seeing them, you can start working with the system instead of against it. Find the leverage points and the approaches that actually work. That awareness is a powerful tool to have. I hope you find this new lens useful and start recognizing the beauty and the patterns you'll begin to notice all around you. Our next episode will be a different format. My first special guest is joining me. Thank you for listening to New School IT. I'm long enough.