Technology Agnostic, Outcome Obsessed: A New Rubric for Evaluating Infrastructure

So much of how we evaluate technology centers on a single principle: new = good.

I get it. In my 13 years designing infrastructure, I have seen new technologies come in and obliterate the structural limitations we had accepted. The smallest startup today has off-the-shelf capabilities that, as recently as five years ago, would have required months of dedicated investment.

But the longer I work in technology, the more skeptical I become of technology-led thinking. The more durable conversation, and the one that produces better strategic decisions, begins with outcomes. 

The goal isn’t to have the latest, fastest, best technology. The goal is to have the most successful business. When we evaluate emerging technologies, these are the questions we should be asking:

• What are we trying to improve? 
• What constraint are we trying to remove? 
• What risk are we trying to reduce? 
• What work should become easier?
• What opportunities should become possible?

The most hyped technology in the world still has to solve a problem at the end of the day. 

To put it another way: Does a foldable iPhone materially improve your day-to-day life? Or does it just … fold. 

Why your business doesn’t need an ‘AI strategy’

AI gives us a perfect example of this in action. Five years ago, AI would not have been on the radar for most businesses. If they had been asked to predict what capabilities would be available, which vendors would win out, how quickly adoption would occur, or precisely how AI would become integrated into everyday work, they would likely have been wrong. 

Ask those same leaders about their desired business outcomes, however, and most would have a detailed list at the ready, much of which would still be true today:

• Automate manual tasks
• Improve data collection and quality
• Increase time for strategic thinking
• Eliminate tedious data entry
• Capture and refine processes

The C-suites are echoing with calls for an AI strategy, but AI in and of itself doesn’t do anything for a business — as far too many early adopters are finding out. In a recent Accenture study, only 20% of AI tokens used were tied directly to business outcomes. The rest? Experiments and tech for tech’s sake. 

Technologists who focus on outcomes got to avoid this kind of wasted spend. Because they evaluate all new technologies against their ability to support specific outcomes, AI was deployed only when it could support a strategic priority and deliver an agreed-upon business value. 

Where to start the conversation about emerging technologies

As a technology provider, it’s my job to turn the focus to outcomes.  

Consider a familiar scenario. A customer asks why they should move a business application from infrastructure they operate themselves into a professionally managed hosted environment.

There is a technically correct answer to that question, and my knee-jerk reaction is to give it,  describing virtual infrastructure, storage architecture, backup systems, redundancy, security controls, remote access technologies, high availability, data center design, and every other technical capability. 

All of those things may be important, but none of them answers the customer’s question. 

The real answer is that employees need to reliably access applications at any time, from anywhere. Managed hosting delivers that far more reliably than the organization could. And it eliminates the need to maintain and staff a physical server sitting in an office. Employees spend less time on work that doesn’t differentiate the business. Technology costs become more predictable. Capacity can expand when the organization grows. Backup, security, maintenance, and infrastructure operations become the responsibility of people who perform those functions every day. 

Those are the outcomes. Technology is just the mechanism through which we create them. 

Moving the evaluation process from ‘What can it do?’ to ‘What will it do for me?’

That doesn’t mean we get to slack off on our technical knowledge. Instead, it’s the opposite. We have to know everything about the technology and enough about the business to understand if and how it can make a difference. 

When businesses approach Summit, they often have a specific capability in mind. It’s my job to bring the conversation up a level. 

• If someone asks about managed hosting, I want to understand how and where employees get their work done. 
• If someone asks about storage, I want to understand what changed to create the new need. 
• If we are discussing cybersecurity, I want to know which information, processes, and systems are truly critical. 
• If someone asks about AI, I want to know where better information, faster decisions, reduced manual effort, or broader access to institutional expertise would materially change performance. 

The technical questions still come, as they should. 

But they arrive after we understand why we are asking them. Knowing the outcome changes the answer. It tells us where additional investment produces meaningful value and where it merely produces additional capability.

Outcomes become the evaluation criteria

One of the most useful tests I know for a technology investment is whether I can explain its value without using technical language. 

• What becomes faster? 
• What becomes easier? 
• What work disappears? 
• What risk becomes smaller? 
• What cost becomes more predictable? 
• What constraint is removed? 
• What becomes possible that was not possible before? 
• And perhaps the most important question of all: how will we know whether the investment worked? 

Technological capabilities won’t answer any of these questions. And that’s why the questions work: They move the conversation from capability to accountability. 

Now there is something to measure.

Business objectives don’t have to be growth-oriented

That doesn’t mean that every answer has to be “number go up.” Sometimes, the best outcome is no change at all. 

One of the more useful examples of this came recently, when a manufacturing organization came to us with an aging Sage 300 environment. 

The obvious technical answer was to move the application into a managed cloud platform — something we do every day. But the technology problem was only part of what was happening.

New entities and multilingual operating requirements had been pushing the organization to a broader ERP reconsideration. The easiest, and most lucrative, path for us would have been to force it all into one transformation narrative. Modernize everything. Move immediately to the new platform. 

It’s not bad advice, but it would have misunderstood the business problem. 

What leadership needed was time. Time to evaluate and make a deliberate, long-term ERP decision. Moving the existing Sage environment into a managed cloud platform allowed them to think proactively instead of reactively. The technology created optionality. 

We tend to assume that technology creates value when it accelerates change, and sometimes it does. In some cases, though, slowing down is more cost effective. Here, we were able to create enough stability, resilience, and flexibility to separate an urgent infrastructure decision from a strategic business decision.

How outcomes future-proof your technology assessment

Technology changes every day. Outcomes don’t. If you want to build a long-term strategy, you need to understand the outcomes you’re trying to create. A strategy anchored to productivity, resilience, customer experience, decision quality, operating leverage, or risk reduction will stay relevant through multiple generations of technology. 

Even for those of us in the business, our ability to predict emerging technologies is much weaker than we often admit. Fortunately, we don’t need to know every technology that will exist five years from now. We just need to be ready to recognize when a new capability can create an outcome that matters.