Ready for What’s Next: Reflections from Our Customer Panel on Future-Proof Dealer Operations 

I had the privilege of moderating our recent webinar, “Ready for What’s Next,” featuring Keith Hernandez from Fairchild Equipment and George Bennett from Maverick Environmental Equipment. Most webinars about dealership technology feel like vendor pitches dressed up as education. This one was different. Keith and George didn’t sugarcoat their implementations or pretend everything went smoothly. They shared the real story—the painful rebuilds, the support ticket nightmares, and the hard-won lessons that actually matter. If you’ve ever inherited a messy ERP implementation or wondered why your reports don’t drive decisions, their candor will resonate. 

 
The AI Readiness Gap Nobody’s Talking About 

I came across a statistic that’s been on my mind: only 1% of companies worldwide consider themselves truly ready for AI. This isn’t about the technology being immature—it’s about most organizations lacking the foundational data infrastructure that makes advanced capabilities possible. The dealers who succeed won’t necessarily be the ones with the most sophisticated AI tools. They’ll be the ones who built clean data systems, established reliable processes, and created cultures that embrace continuous improvement. 

When Implementation Inheritance Goes Wrong 

George’s story at Maverick illustrates the difference between implementing software and actually transforming operations. When he joined in January, they had a system but no actionable insights. They couldn’t publish reliable financials or give department leaders the metrics needed to run their businesses effectively. The organization had become “extremely anecdotal and reactionary.” 

His candor was refreshing: “It was a nightmare at first, and I’m gonna be completely honest, it was not easy, it was not fun for anyone.” But the real lesson came in his diagnosis—they didn’t start with the end in mind. 

Instead of trying to recreate old reporting structures, George held week-long workshops with operational leaders from parts, service, rental, and equipment to define what success actually looked like. Not what IT thought they needed, not what finance wanted to see—what would enable their parts lead to stop calling 17 people across regions just to verify an inventory report. 

The result was a complete general ledger rebuild focused on the KPIs that actually drive their business: service crew utilization, parts absorption ratios, equipment age on yard, and working capital metrics. It took three months of intensive work, but now they have a system that serves the business rather than forcing the business to serve the system. 

The Power of Preventive Intelligence 

Keith’s approach at Fairchild demonstrates how business intelligence transforms daily operations when designed around real workflows. Their service teams can see WIP aging immediately, parts teams track open orders through automated alerts, and equipment managers monitor delivery delays—all without drowning in data. 

Keith referenced the Wolf of Wall Street scene where Matthew McConaughey explains that without proper validation, data is “fairy dust—it doesn’t exist.” This connects directly to that AI readiness challenge. Advanced analytics, predictive maintenance, and automated decision-making all depend on clean, accessible, validated data. You can’t skip this step and jump straight to AI. 

Testing as a Service: From 20 Tickets to 2 

Keith served as our beta client for Testing as a Service, one of our first machine learning models. When you’re managing 2,600 solution dependencies in a test environment, manual validation becomes impossible. Keith described the evolution: 10 solutions was manageable, 20 was fine, 100 started getting difficult, but 2,600? “There’s no way I’m going to allow this many solutions into our live production, but we also can’t hold it up because there are developments and integrations I’m waiting to implement.” 

The Testing as a Service approach transformed their deployment process. In their most recent implementation—956 solutions deployed over a weekend—they generated only 2 support tickets. Previously, deploying just 15 solutions would result in 20+ tickets the next day. That’s the difference between an IT team constantly firefighting and one that can focus on strategic initiatives. 

Data Visualization as the Great Equalizer 

One question from our marketing team really hit on something important: how do you deal with people who aren’t naturally inclined to work with these types of systems? 

George’s answer crystallized the approach that makes modern BI accessible: data visualization. He can create Power BI reports showing sales by delivery address for parts, service, and rentals. He doesn’t need “the family truckster deluxe of computer-savvy salespeople” to look at a map with bubbles and understand where they’re selling equipment and where they’re not. 

He doesn’t expect service technicians to become data experts—they’re experts in fixing machines, ordering parts, and selling equipment. He just wants them to see what they’re doing and monitor it. When utilization meters show service crew productivity below targets, the arrow speaks for itself. No complex analysis required, no Excel expertise needed—just clear, visual indicators that drive action. 

The Implementation Philosophy That Actually Works 

As we wrapped up, both leaders shared advice that transcends specific technology choices. George emphasized starting with the end in mind and building cross-functional teams with operational leaders who will actually use the systems. His warning resonated: “Don’t be afraid to ask for outside help. When you’re a small company and you’ve lived in a silo and you’ve always done it that way, well, there’s folks out there who have done it differently, and it may cost a little bit more money. But spend a little bit more money, because you’re going to spend it on the back end if you have to redo it.” 

Keith’s advice was equally fundamental: “Make sure your data’s clean before you adopt any new technology, even think about adopting any new technology.” If you have junk in the system, you’re going to get junk out. 

Looking Forward 

The questions from participants throughout the webinar demonstrated genuine hunger for these capabilities across the dealership community. These weren’t technology questions—they were operational questions from teams ready to transform how they work. 

The future of dealership operations is data-driven, automated where appropriate, and focused on exception handling rather than routine processing. The dealers featured in this webinar are building that future today, using current technologies to solve immediate problems while creating the foundation for tomorrow’s innovations. 

The 1% who feel AI-ready aren’t necessarily the ones with the most advanced tools. They’re the ones who did the foundational work: cleaning data, establishing reliable processes, building cross-functional alignment, and creating cultures that embrace continuous improvement. 

Watch the full webinar on demand to hear Keith and George’s complete stories, see their detailed discussions about BI implementation and testing methodologies, and catch the full Q&A session with dealership professionals. If you’re ready to explore how these approaches could transform your operations, reach out to your VitalEdge Customer Success Manager for a personalized demonstration focused on your specific operational challenges.