One of the things I’ve noticed more and more lately is how long it takes companies to make technology decisions.
Not because they don’t care or because they aren’t smart; in fact, usually it’s the opposite. They care a lot! They’re thinking hard, and they’re trying to avoid making the wrong move.
But somewhere along the way, thoughtful evaluation turns into endless circling. More demos, more meetings, more comparisons, spreadsheets, debates….and eventually, the question becomes: is indecision becoming your decision?
Because while you’re analyzing, the problem you were trying to solve is still there. You may not have made a bad decision, but you also haven’t made a useful one.
That’s a problem too.
Over the years, I’ve found that the best way to avoid paralysis by analysis is to step back and ask a simpler question first:
What am I actually trying to solve, improve, accomplish, or change?
Not what features do I want or what did the software salesperson say I should care about, but focusing on the real problem. If you don’t get that part right, the rest of the decision-making process gets unnecessarily messy.
When I’m helping clients think through technology choices, there are six categories I tend to use to evaluate decisions. This isn’t an all-inclusive list, but it gives structure to the process and helps keep the discussion grounded in principle instead of emotion.
1. Pros and Cons
This sounds obvious, but it’s amazing how often people skip over it or do it too casually.
Every decision has pros and cons. The question isn’t whether the option is perfect. (Spoiler: it isn’t.) The real question is: can I live with the cons?
Sometimes an option has great benefits, but one downside is a dealbreaker. Sometimes the cons are inconvenient, but manageable. Sometimes people get so distracted chasing the perfect answer that they miss the good, workable one sitting right in front of them.
No technology choice is without tradeoffs. Being honest about them upfront is a lot healthier than pretending they don’t exist and acting surprised later.
2. The Near Picture vs. The Big Picture
A lot of technology decisions get made because they solve one immediate, finite problem for one group, one department, or one function. It’s quick, it’s easy, and it works well enough for now…great, right?
And then the company grows.
Then systems need to connect. Data needs to move. Teams need visibility. Processes need to scale. Suddenly the “easy” decision made two years ago has become the thing that needs to be unplugged and thrown away because it doesn’t fit with anything else.
I see this especially as organizations digitalize. The more you rely on technology and the more interconnected your operations become, the more those short-term, isolated decisions start costing you.
The question isn’t just, “Will this solve today’s problem?”
It’s also, “Will this still make sense as we grow, connect, and build on it?”
That doesn’t mean every decision needs to be designed for a Fortune 500 company on day one. But it does mean you should think a little farther down the road than next quarter.
3. Risk
There is no such thing as a risk-free decision. That’s true in technology, in business, and in life.
So when I evaluate a choice, I ask: what are the risks, and what will it take to mitigate them? Then I ask a second question: can I live with the ones that remain?
The goal isn’t zero risk; the goal is reasonable risk.
Too many companies act like avoiding the decision is somehow safer than making it. Usually it’s just a quieter risk, and a slower one. Manual processes, outdated systems, fragmented tools, and ongoing inefficiencies all carry risk too. It’s just easier to tolerate them because they’ve become familiar.
Familiar doesn’t equal safe!
4. Total Cost of Ownership
A lot of people focus almost entirely on price.
That’s understandable: it’s easy to compare, and it’s a visible metric.
But price and cost are not the same thing.
You can buy cheap software that requires a lot of extra labor, workarounds, manual entry, and internal maintenance. Or you can buy a more expensive solution that reduces complexity, saves time, automates tasks, and scales more effectively.
So the real question becomes: what is the total cost of ownership? What will it cost to implement, manage, train on, maintain, and work around?
There’s also a cost avoidance angle here. What work goes away if the right system is in place? What manual effort disappears? How many future hires might you not need because the process scales better? How much time are you saving, not just after implementation, but right now by making a decision instead of dragging it out for six more months?
Delayed decisions have a cost too. Lost efficiency has a cost. Ongoing uncertainty has a cost.
5. People vs. Technology
This one gets overlooked all the time. Who is working for whom?
I’ve seen companies implement systems that are so complex, so rigid, and so task-heavy that the people inside the business end up serving the technology instead of the other way around. That’s backwards!
If the system isn’t helping your people do their work more clearly, efficiently, and effectively, then it’s not really helping. I’ve seen detailed workflows where people have to click through a million steps just to make the technology “happy,” and at some point you have to ask whether the system is actually supporting the business or just creating more complexity.
Yes, some structure is necessary and some disciplines require more rigor. But if your team is spending enormous amounts of time maintaining information “just in case” they might someday need it, while very rarely ever using it, that deserves a second look.
6. Must-Have vs. Need-to-Have vs. Nice-to-Have
This distinction matters a lot, especially when working with IT teams, software vendors, or implementation partners.
I used to see this all the time: A non-IT team would go to IT and say, “Here is exactly what we want you to build. It must do A, B, C, and D exactly this way.”
The problem was that they were describing a solution, not the actual objective. They were so focused on what they thought they needed that they unintentionally closed the door to better alternatives.
That’s why I like separating things into three buckets:
Must-have: it must do this exact thing, this exact way.
Need-to-have: it must accomplish this objective somehow, but there may be flexibility in how it gets done.
Nice-to-have: it would be helpful if it did this, but we can live without it.
That clarity changes the conversation. It gives smarter people the chance to solve the actual problem instead of just building the first version of your assumption.
Technology decisions don’t need to be casual, but they also don’t need to take forever.
Thoughtful and thorough are good. But if analysis is preventing progress, then it’s no longer helping.
Start with the real problem, evaluate the tradeoffs, think beyond the near picture, understand the risks, consider the full cost, make sure the technology serves the people, and be clear about what truly matters…versus what just sounds nice in a meeting.
Because at some point, not deciding becomes its own decision.
And usually not a very good one.