When technology leaders discuss managing their “technology portfolio,” they often borrow metaphors from financial management—weighing investments, balancing risk, and optimizing returns. This framing is intuitive and familiar, but it’s also dangerously incomplete. Unlike stocks and bonds, technologies don’t exist in relative isolation. They form intricate webs of direct dependencies, create and constrain immediate possibilities, and fundamentally shape what an organization can and cannot do.
In reality, managing a technology stack requires a different approach than portfolio management alone can provide. While traditional portfolio thinking focuses on planning, budgeting, risk assessment, and strategic alignment, it misses three critical dimensions that separate technology decisions from financial ones:
dependencies, the adjacent possible, and talent availability.
Every technology choice you make doesn’t just add or remove a capability—it also creates or removes constraints that can ripple through your entire stack. Consider the seemingly simple decision between SQLite and PostgreSQL for a database. SQLite cannot handle concurrent users but stores data in a single, easily portable file. PostgreSQL supports concurrency but requires a complex infrastructure. While different implementations of the SQL language are relatively standard, the infrastructure requirements of these two technologies are radically different. This is a fundamental constraint on future architectural options. Alternatively, compare PHP with JavaScript, one is a backend scripting language that requires a server, and the other is a client-side scripting language that runs in the browser. While the delivered UI may be similar, the dependencies are very different.
Every system, service, and software package connects to others in ways that may not be immediately apparent. Maintaining a comprehensive IT landscape map becomes essential—not as a bureaucratic exercise, but as a map for navigating change. When you understand these dependencies clearly, you can analyze risks, troubleshoot issues more efficiently, and make informed decisions about where to invest or divest. Any change to systems deep in the dependency hierarchy could have many contingent costs.
Here’s where technology portfolio management diverges most dramatically from financial management. When you buy a stock, it doesn’t unlock new investment opportunities. But when you adopt a technology, you fundamentally change what’s possible next.
Biologist Stuart Kauffman first introduced the concept of the adjacent possible to explain biological evolution and self-organization in complex systems. Steven Johnson later popularized it in his book Where Good Ideas Come From, applying it to innovation in technology and culture.
The core insight is elegant: at any given moment, only a limited number of options are available to you. But exploring one of these options—whether through systematic study or random discovery—creates a new set of possibilities that were previously unreachable. Each new development opens up the frontier of adjacent possibilities, expanding what you can conceive and build.
Understanding the adjacent possible transforms how you think about technology choices. You’re not just selecting tools for current needs; you’re choosing which doors to open and which to keep closed. A technology that seems perfect for today’s requirements might foreclose valuable options for tomorrow. Conversely, investing in a technology that slightly overserves current needs might unlock capabilities that become strategically crucial.
This is not a call to overengineer solutions. Selecting a technology because it offers more future possibilities need not cost anything or take any longer. It is, however, a strategy that exploits the fact that innovation doesn’t leap across vast chasms; it proceeds through incremental steps that expand what’s possible at each stage.
There’s another factor that distinguishes technology management from portfolio management: technologies require people who know how to use them effectively. Different technologies have vastly different adoption levels, which directly impacts the talent pool available to work with them.
A mature, widely adopted technology offers access to a large community, extensive documentation, and many experienced practitioners. An emerging technology might offer technical advantages but comes with the cost of limited expertise, smaller communities, and the need to train your team.
This talent availability intersects with all your other considerations. A technology with perfect technical fit and favorable dependencies might still be a poor choice if you cannot staff projects that use it effectively. Conversely, choosing a technology primarily because your team knows it well might constrain your adjacent possible in unacceptable ways.
Bringing these dimensions together, effective technology stack management must evaluate:
1. Intrinsic appropriateness: Does this technology actually solve the problem at hand? How well does it fit the specific use case?
2. Dependency implications: What does this technology depend on? What will depend on it? How does it constrain or enable other parts of the stack?
3. Talent availability: Can we find people who know how to use this effectively? What’s the learning curve? What does the community and ecosystem look like?
4. Adjacent possible impact: What doors does this technology open? What possibilities does it foreclose? How does it position us for future capabilities?
5. Expected lifetime: How long will this technology remain viable? What’s the replacement cost when it’s superseded?
When all these factors are understood, a Final Assessment of the cost, benefit, and risk of a new technology can be performed and a choice made.
The portfolio metaphor has served technology leaders well in establishing discipline around planning, budgeting, and strategic alignment. But it’s time to evolve our thinking to match the actual nature of technology decisions.
Your technology stack is not a collection of independent investments that can be evaluated in isolation. It’s an interconnected system where each component influences the value and viability of others, where choices constrain and create possibilities, and where the availability of human expertise matters as much as technical capabilities.
By explicitly considering dependencies, the adjacent possible, and talent availability alongside traditional portfolio management concerns, technology leaders can make more informed decisions that serve both immediate needs and long-term strategic goals. The goal isn’t perfect prediction—the adjacent possible remains inherently unknowable until you explore it—but rather building a framework for thinking through the full implications of technology choices.
In the end, managing a technology stack is less like managing a portfolio and more like navigating a complex landscape where every step you take reshapes the terrain ahead. The most successful technology leaders are those who understand this dynamic nature and make choices that keep the most valuable doors open while building the capabilities they need today.