Don't modernize because you can. Modernize when it makes sense.

By Sam Shar / The Delivery Gap

One of the biggest things I learned from inheriting my father's business was that modernization isn't about adopting the latest technology.

For me, it's about looking at a business's day-to-day operations and finding ways to update its systems for efficiency and alignment with its current needs.

Enterprises often take one of two instinctive approaches: trying to catch up every ten or 20 years, or trying to implement every new piece of tech as soon as it hits the market. Neither is a sustainable method.

It should be a continual but careful process. Rather than being reactive, successful businesses continually identify where they can improve or solve a problem, then selectively adopt a technology once it's proven it can deliver results.

At Trend-Setters, we've made small steps towards modernization with automation and cloud upgrades, but it is only five years in that we are taking those significant steps to move the business forward.

I spent time understanding the business – what was working, what could be improved, and what was possible for the future. It's the same with cars: you wouldn't install a bigger engine before you've even sat in the driver's seat. 

You need to understand the fundamentals before you decide what should stay, what should change, and where upgrades can genuinely help.

Without taking the time to understand the gaps in your business, you could end up with a pile of unfinished projects. That's what many companies are experiencing now: 95% of enterprises have delayed or canceled AI projects over the past year.

This isn't a new phenomenon brought on by AI. In 2018, Lidl abandoned a $600 million SAP project after extensive customization failed to make the system compatible with its operations. It eventually reverted to its legacy system because the project focused on implementing SAP software, not on streamlining resource-planning operations.

This SAP failure shows the risk of adopting new technology simply because it's there.

Whether it's AI or SAP, prioritizing emerging tech over internal efficiency problems, especially without proper implementation planning, risks jamming that new tech into a system that can't support it. Time, money, and resources are all wasted, and the disruption can damage what was already working well.

By identifying the problem first, you can build an integration framework for new software that addresses it. That means testing whether existing infrastructure and data systems are compatible with the upgrades, whether adoption would have a tangible impact, and optimizing existing systems to make integration easier. Only then should you fully adopt the new technology.

That requires discipline about how and where you choose to grow, and UPS has already shown us how to do it well.

They developed, tested, and refined the ORION system using new analytics technology to address the high costs and environmental impact of inefficient route planning. The result? An estimated $300 million saved and 100,000 metric tonnes of C02 emissions reduced per year.

The lessons from UPS and Lidl are simple:

→ New technology should follow the problem, not the other way around.

→ Implementation should be gradual and continuous.

This is where I think consultancy firms can sometimes get it wrong. They arrive with a predefined solution for modernizing an enterprise before they've even begun to understand the business and its problems. If you take time, as I've done and as UPS did, to understand those fundamentals and focus on genuine opportunities for improvement, then you can build an effective, rolling modernization strategy and implement it over time.

Modernization isn't about being the first to adopt what's new. It's about knowing what needs upgrading, being selective about how to do it, taking time to implement it, and ensuring those upgrades make the business better.