Do You Really Need That New Tech?

Our expert explores the Shiny Ball Syndrome and offers four tips for deciding whether your organization actually needs that cool new tech.

Written by Cliff Jurkiewicz
Published on Jan. 22, 2024
Do You Really Need That New Tech?
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Artificial intelligence is on the minds of executives who can’t wait to jump on the bandwagon and see how the tech will boost profits, lower costs and help them leapfrog over competitors.

In fact, a survey found that nearly three-quarters of chief executive officers call generative AI a top investing priority, and more than half of them say they’re actually spending more money on new technology than training current employees. But what happens when you buy new technology as a quick-fix for an issue without an idea of its long-term value for your organization?

What is shiny ball syndrome?

The Shiny Ball Syndrome is the tendency to gravitate toward and spend money on new products simply because they’re new and exciting.

Other perspectives on new techStop Freaking Out About Generative AI

 

The Allure of the Shiny Ball

Corporate chiefs think they get it, but what’s really happening is that they have fallen under the hypnotic spell of what I like to call the Shiny Ball Syndrome: a temptation to buy something new that looks great without understand the impact it will have on their organization.

In 2023, it was impossible to read a business publication without another CEO singing the praises of generative AI. Yet, how many companies actually adopted the technology into their workplaces? A mere 10 percent. So, with flush budgets for 2024, C-suite leaders may be looking to spend big on the next shiny object.

Budgets create a false sense of urgency to spend what you have as soon as you can. Instead, leaders should be more concerned with spending at the right time — knowing when to adopt a new technology or when to take a hard pass. Here are three tips to guide executives in making those calls.

 

Understand Your Technology Ecosystem

Understanding your organization’s technologies and how they fit into its broader goals is the first thing to consider when deciding whether to adopt a new system. It can be tempting to solve an issue with the latest tech. But in reality, you might have a challenge that requires more brain power, not one that requires new technology. 

All too often, executives have the mindset: “What problem am I solving by implementing this technology?” Fair question. But what they should be asking is, “Where do I want to create value in the organization and how can technology help me demonstrate it?”

How well do your people engage with the organization’s technologies? Does the tech create efficiency, revenue and value, both for the company and individuals? Individuals need to see that their value is improved by the use of technology, not the other way around. Now is the time to reflect on your organization’s technology ecosystem.

 

Create a Process Around the Technology

I was a technology architect for a big insurance company years ago, and we were tasked with merging with a competitor that would have created a multi-billion dollar behemoth. Part of my job was to look at the entire technology landscape of the two companies, find out where there was overlap and where there were pieces missing. The goal was to create efficiency and value.

Between the two companies, we found that they were using hundreds and hundreds of systems. The analysis took almost two years, but we ended up cutting the number of systems by more than half. That practice taught a lot from a process perspective about how the business was supported by its technology ecosystem.

The reason we got bloated to almost three times the number of systems than we actually needed was because we were asking our tech questions in reverse — it’s not about how technology can support the process, it’s about creating a process around the technology. If the tech isn’t actually solving a problem and/or scaling innovation, it’s not creating value.

 

Form Partnerships in the Executive Conference Room

Value can mean a variety of things, such as generating revenue or enhancing efficiency. For example, in a human resources context, generative AI will create new value by redefining how recruiters and people managers work, such as how they create job descriptions. Executives should ask themselves what the organization’s value proposition looks like and whether their current technology stack supports that proposition.

But in three years, do you think you’ll still be using that tool?

In many organizations, there is limited partnership between chief human resources officers, chief information officers and chief technology officers. In part, this is due to market forces and the speed of innovation externally. The intention is there, but the information that drives good decision-making is scarce.

You really have to commit time and resources to perform technology due diligence. That depth of discovery is more art than science, requiring creativity that many leaders don’t often exercise. That is, they look at data while tuning out their intuition. This inhibits scalable innovation, a business process that leads to widespread adoption of an innovation.

Instead of the focusing on the greater good of the organization, executives are making impulsive decisions in silos. Short-term thinking in the senior leadership ranks — “I’ve got the budget, so now’s the time to snatch up that new tech I want!” — takes away from the organization’s long-term value. That’s why engaging in a full analysis of the whole tech stack is crucial.

More on keeping up with new techA Digital Adoption Platform Can Transform the Way You Track Software Success

 

10 Percent Better or 10 Times Better?

Ask yourself: Do you want to be 10 percent better at something or 10 times better? When a new tool goes live, in the short term it will make an organization 10 percent better. Guaranteed. If it didn’t, why would anyone buy it?

But in three years, do you think you’ll still be using that tool? Has the company it was purchased from demonstrated historical innovation and long-term value? Is that vendor financially stable and making the right investments into their products and services? Is it a point solution or is it a suite of technologies that are going to scale in its own domain and in others over time? These are the kinds of questions and conversations that should be taking place at the executive level.

Generative AI is an example of an unproven technology. There are no long term use cases and success stories because it’s so new. But based on previous innovations, if an organization has done their impact analysis, leaders will understand the value that the tool has because they understand how it affects work. That’s as effective a way as any to avoid the allure of shiny new things.

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