The Pattern Behind the Building Blocks: Why Each One Matters

In the first article of this series, I laid out the 5 Building Blocks of Connected Business: Operations, Customers, Products, Data, and Teams. Each one represents a critical component of how your company creates and delivers value.

But here’s what I didn’t tell you. These aren’t just convenient categories I pulled out of thin air. There’s a deeper pattern underneath this framework, and understanding it changes how you think about AI and transformation.

Each building block got shaped by a different technology wave. And those waves hit with remarkable consistency, roughly 20 years apart, each one fundamentally changing a different piece of how businesses compete. Michael Porter documented three of these waves over 60 years. The pattern tells us we’re experiencing the fourth wave right now.

That fourth wave is artificial intelligence, and it’s transforming Teams in exactly the same way previous waves transformed Operations, Customers, and Products. This isn’t speculation. It’s the continuation of a pattern that’s been reshaping business since the 1960s.

The Pattern You Already Know

Let me show you how this works. In my book Don’t Think So Much, I traced Porter’s three waves in detail. What makes them transformational isn’t the technology itself. It’s how each wave changed the flow of information through a specific building block.

The first wave hit in the 1950s and 1960s when companies started automating internal operations. These weren’t glamorous projects. We’re talking about replacing ledgers and pegboards with giant mainframes that handled finance, accounting, and supply chain planning. Over time, these systems grew into the Enterprise Resource Planning behemoths we know today.

Every facet of internal operations got digitized: Order to Cash, Purchase to Pay, Make to Ship, Record to Report. The goal was relentless: do more with less. This wave continued through the personal computer revolution of the late 1980s when email replaced printed memos and desktop tools gave people back some individuality after the rigid controls of ERP.

What really changed wasn’t just speed or efficiency. Information that used to live in people’s heads and filing cabinets got captured in systems. Implicit knowledge became explicit. Informal processes got formalized. That’s what made it transformational.

The second wave arrived around 2001 when Porter wrote about how the Internet was transforming strategy. This wasn’t just about having a website. The Internet created a two-way channel between companies and their customers.

Marketing teams could track what customers were actually interested in, not what they claimed in focus groups. Order configurators let customers build exactly what they wanted without talking to a salesperson. Mobile apps focused on specific customer actions, not comprehensive functionality. The real shift was design thinking – we started paying attention to how real human beings actually used our systems and consumed our information.

Again, the transformation wasn’t about the technology. It was about information flow. Customer insights that used to require expensive market research and months of analysis started flowing continuously and bidirectionally. Power shifted. The customer’s voice got louder and more immediate.

The third wave emerged in 2014 when Porter and Heppelmann published their work on Smart, Connected Products. This was the Internet of Things before it became a buzzword everyone got tired of hearing.

Products themselves became digital, sending telemetry back to manufacturers, optimizing their own performance, and transforming from hunks of machinery into self-aware components of larger systems. I saw this firsthand at IDEX Corporation when we looked at connected rescue tools. The Jaws of Life and other hydraulic rescue equipment from our Hurst brand could send performance data back through Captium’s platform.

Fire departments got maintenance alerts before equipment failed. Manufacturers learned how their products actually performed in the field, not just in test labs. The product itself became a source of ongoing value and insight. Once more, the transformation was about information flow – products could now communicate their own performance and needs.

Now You See the Pattern

Here’s what strikes me about these three waves. Each one hit roughly 20 years apart. Each one transformed a different building block. And each one fundamentally changed how information flowed through that specific component of business.

Wave one (1960s-1980s) transformed Operations by capturing operational knowledge in systems. Wave two (2000s) transformed Customer relationships by opening bidirectional communication channels. Wave three (2010s) transformed Products by making them intelligent and communicative.

Notice what’s missing? We haven’t touched Teams yet. Not really. Yes, we gave people better tools and faster communication. But we haven’t fundamentally changed how expertise flows through organizations, how decisions get made, or how knowledge moves from senior to junior team members.

That’s the building block that AI is transforming right now. And if the pattern holds – and I believe it does – this transformation will be as profound as ERP was for operations, the Internet was for customers, and IoT was for products.

Why Teams Is Different

Here’s where it gets uncomfortable for most executives. The previous three waves automated processes, opened channels, and connected devices. Those were hard implementations, sure. But they didn’t fundamentally challenge who controls information within your organization.

AI does. It challenges every assumption you have about knowledge hierarchies.

Think about how your company actually works today. Senior engineers know things that junior engineers don’t. Sales veterans understand customer nuances that newbies miss. Plant managers carry decades of operational wisdom in their heads. This knowledge hierarchy isn’t documented in any system. It lives in conversations, mentoring relationships, and hard-won experience.

AI makes that hierarchy optional. When a junior engineer can ask an AI assistant trained on your company’s entire engineering history, what happens to the knowledge hierarchy? When a new sales rep can get instant insights about a customer’s buying patterns and preferences, how does that change the relationship with the senior rep who used to be the only source for that information?

These aren’t technology questions. They’re cultural and organizational challenges that go deeper than anything we faced with ERP, Internet, or IoT implementations. And that’s exactly what makes this the fourth wave. It’s transforming how information flows through the Teams building block in the same way previous waves transformed information flow through Operations, Customers, and Products.

Data Connects Everything

Before we dive into what this means for each building block, let’s talk about Data for a moment. Data is the fifth building block, and it’s special. It doesn’t map to a single transformation wave because it’s the connective tissue between all the others.

ERP created operational data. The Internet generated customer data. IoT produced product data. AI creates and consumes team knowledge. Data mastery isn’t about any one of these. It’s about connecting insights across all of them.

That’s why the Data building block sits at the center of the framework. You can’t transform Operations without understanding operational data. You can’t transform Customer relationships without customer insights. You can’t transform Products without product telemetry. And you can’t transform Teams without making organizational knowledge accessible and actionable.

Data mastery became critical exactly because each wave generated new data streams that needed to flow between building blocks. The companies that figured out how to connect operational data with customer insights and product performance created massive advantages. AI just makes this more essential because it operates on all those data streams simultaneously.

What This Means for Each Building Block

In the coming articles, I’ll dig into how AI transforms each building block of business. Understanding the wave pattern helps you see what’s actually changing and why it matters. Here’s what’s ahead:

Operations: AI turns your operational data from historical reporting into real-time decision support that front-line teams can actually use, continuing the transformation that ERP started 60 years ago.

Customers: AI enables truly personalized relationships at scale by making every interaction feel like you know exactly what each customer needs right now, building on the bidirectional channels the Internet created.

Products: AI transforms products from smart and connected into adaptive and predictive, learning from every deployment to improve the entire installed base, extending the IoT transformation into autonomous optimization.

Data: AI makes data mastery non-negotiable by operating across all your data streams simultaneously, demanding integration and quality at levels most companies haven’t achieved yet.

Teams: AI democratizes expertise and accelerates decision-making by making your organization’s collective knowledge accessible to everyone who needs it, fundamentally transforming how information flows through people.

The Pattern Continues

Porter’s framework gave us a way to understand how technology transformed business over 60 years. The pattern is remarkably consistent: roughly every 20 years, a new technology wave hits and fundamentally changes how information flows through a different building block.

AI is that fourth wave, and it’s transforming Teams in ways we’re just starting to understand. But now you see why Teams matters so much. It’s not just another component to optimize. It’s the building block that hasn’t been fundamentally transformed yet. And the pattern suggests this transformation will be as profound as the three that came before.

The companies that get this right won’t just implement AI tools. They’ll rethink how information flows through their organization and challenge the cultural assumptions about who controls knowledge and expertise. That’s uncomfortable work. It’s also the work that determines who wins over the next 20 years.

In the next article, we’ll start with Operations and explore how AI extends and amplifies the transformation that ERP started decades ago. But I’d love to hear your experience: where are you seeing AI challenge knowledge hierarchies in your organization?

Join my mailing list at http://eepurl.com/gOBDBj to get notified when each new article in this series drops. Understanding the pattern helps you see what’s coming next, and the building blocks of business are shifting under our feet right now.