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The half-life of a good decision is shrinking

Why tech buyers should care

Fifteen years ago, we were still comfortably in the era where enterprise software was expected to carry you for years, if not a decade plus. Yes, Agile was around, but major decisions (about CRMs, ERPs, etc.) took time. Ditto implementations and training.

That’s changing.

Today, the pace of technology development means the half-life of a good purchase decision is miniscule. Yes, that software you just demoed may meet your exact needs today, but what happens when a new regulation hits? What about when buyers start embracing screenless interfaces? Or when an LLM update brings new functionality into the mix?

In our current environment, tech buyers need a new skill: just-in-time decision making. They need to be able to assess a constantly shifting reality, learn fast, and make high-stakes decisions confidently. And then do it all again tomorrow. For many of us, that’s a big shift.

Luckily, you’ve probably already started to adjust. In this piece, I’ll offer some context around why this is our new normal and some tips for adapting faster and thriving in the era of just-in-time decision making.

You can get fired for buying IBM, actually

It used to be that going with the biggest name in the industry was a safe choice. Nobody would blame you for choosing IBM or Salesforce or SAP.

Maybe the software was expensive, maybe the contract terms were not ideal, but most organizations didn’t have an alternative. The products were effective. They delivered essential functionality. For a long time, the pain of switching to something else—never mind the pain of trying to build an alternative—was far greater than the pain of paying.

Increasingly, though, that’s changing.

Every few weeks, there's a headline about an executive who canceled a major software subscription to build an in-house alternative. As a spokesperson from one such company said, “AI changes the economics of building software.”

Note that this doesn’t mean anyone can just spin up an effective alternative to Salesforce. Compliance and security and privacy and interoperability are still important. Building and maintaining software to deliver the functionality you need while also meeting legal and contractual obligations isn’t easy.

What's shifted in the last few years is that, thanks to the way AI has changed the economics of building software, buying IBM is no longer the safe choice it once was. There's now a much stronger case to be made for a newer, leaner alternative. Or a homegrown product that’s built for exactly the use cases you need.

Just as important: the rate of change of available technology is increasing. As tech buyers consider a system of record, they no longer have the luxury of gathering requirements for several months, then considering solutions, then starting a three-year development or onboarding process.

Today, technical capabilities might evolve significantly in the time it used to take to gather requirements. If you’re following the old model, you’ll almost certainly invest in technology that meets the needs of your organization at some date in the past.

What this means for today’s tech buyers is that the skill set needed to make effective technology purchases has changed.


The new essential skill for tech buyers: just-in-time decision making

You can no longer assume that what was best for your organization last year or last week is best for it today. This requires a shift in posture and pace.

Where identifying technology needs and gathering requirements was once a cyclical process, now it’s becoming an almost ongoing practice. Leaders need to find ways to gather and process information faster, identify risk sooner, and make high-stakes decisions (e.g., about what software their organization might need) more frequently.

Let’s dive into that risk identification piece, which is hugely important.

Being able to quickly and consistently identify potential risks and eliminate or minimize them is essential to success. One of the most powerful resources organizational leaders have for doing this is their team. People see different risks based on the work they do and the perspective they bring to the table.

But getting people to speak up when they spot risk is its own skill.

Fifteen years ago, a leader might have said to a roomful of people, “Who thinks this is a bad idea?” And hoped to get a few insights.

In a world where the default answer (IBM) was pretty much always safe, it may not have mattered whether anyone raised their hand. Even if there were risks, nobody was going to lose their job for buying the industry standard.

In a world where we can’t default to established ways of doing things, we need to find a different way to seek out risks. Ideally, that should involve…

  • Removing the moral judgment from risk identification.

  • Eliminating the need for someone to go out on a limb to highlight risks.

  • Creating a sense of shared purpose around identifying and mitigating risks.

Some question formats that can work in this reality:

“What’s the big thing that has to be true in order for this to be successful?”

“What is the thing that is most likely to get us off track?”

“Where’s the hidden risk?”

When you use questions like these, risk identification becomes a group effort. The decision-maker can tap the wisdom of the team to surface risks, then use their judgment to assess those risks and make a decision.

Related: Strategic software investment: Maximizing returns through effective kickoffs

The new definition of expertise: how fast you can learn and apply new information

This all ladders up to what expertise means in our current moment. The old definition is about who knows the most, but when knowledge is immediately available to everyone via the internet and skills are increasingly available via AI, that definition doesn’t speak to what today’s experts need.

My take is that the new expertise is more about who can learn the fastest: who can navigate the overwhelming inputs available, extract insights from colleagues and partners, and make a confident decision on a tight timeline—and then repeat that over and over.

This isn’t to undermine the skills that today’s experts need: you need to know what questions to ask and how to frame them. You need to understand how accurate and trustworthy information is, how relevant it is to the decision you’re making, how fast information changes in the area you’re assessing.

In the context of tech buying: what does an expert do when someone flags a problem with the system of record? What follow-up questions do they ask? Who else do they consult? When do they know they have enough information to make a decision, and what decision do they make?

How do they assess whether they’re dealing with a training issue, a bug, or a bigger-picture shortcoming that should trigger the search for a new solution?

That’s the kind of thing required of modern-day experts. That, over and over and over.

Today’s experts have to make high-stakes decisions more often and more efficiently

In the not-so-distant past, enterprise software was the kind of purchase you expected to be durable. It required a decision-making process you only had to go through once every several years.

That’s changed. Now, tech buyers are expected to make high-stakes purchase decisions much more frequently.

By making the shift to embrace just-in-time decision making and learn-fast-and-decide expertise, you’ll be better positioned to react, adapt, and adjust to the accelerated pace of change that defines enterprise life today.


About the author

Gayle Silverman is a Principal Product Strategist here at TXI. Gayle leads product strategy and delivery for industrial clients, working with operations and technology leaders to close the gap between the data they're sitting on and the decisions they need to make. Her work often starts with one question: where does technology strengthen your competitive advantage? Known for saying “two things can be true at one time,” Gayle builds the kind of environment where the people closest to the problem are heard and teams can say the hard thing out loud.



Published by Gayle Silverman

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