Unlike after-the-fact surveys, real-time customer conversations with support, success, or sales teams capture raw customer pain points. This data reveals what customers need, where operations fail, and what the business should do next, making it a richer source of intelligence than any dashboard.
Front's research reveals a hidden "coordination tax" where teams spend the majority of their time on operational tasks like managing handoffs and re-explaining context. This 3:1 ratio of coordination-to-problem-solving cripples efficiency, even if traditional metrics like response time look good.
Adding AI to boost individual speed can paradoxically create more team friction. Organizations with the most advanced automation often report the highest number of coordination issues because they fail to redesign the underlying collaborative workflows, optimizing individual tasks instead of the entire process.
Effective AI implementation isn't about automating entire human jobs. It's about re-architecting workflows to assign AI the research and analysis tasks it excels at, while preserving relationship-building, empathy, and high-judgment tasks for humans. This division of labor maximizes the strengths of both.
While 40% of organizations don't measure coordination, conquering its hidden costs requires tracking three specific metrics: the number of handoffs, total coordination time, and the amount of duplicate work. The 5% of companies that track all three are the ones who successfully reduce this operational drag.
The ease of creating specialized AI agents is setting the stage for "agent proliferation." Soon, companies will suffer from deploying multiple, uncoordinated agents that, while useful independently, will create a chaotic and fragmented experience for customers, leading to brand damage and operational messes.