How Hexagon scaled sales analytics capacity by 200% without adding headcount.

The sales analytics bottleneck

Hexagon's sales organization had a data problem, but not the kind most companies worry about. They had plenty of data—too much, actually. The problem was getting it into a format sales reps could actually use. With two analysts supporting 150 account executives, the math simply did not work.

Every rep had different needs. Enterprise AEs wanted account health scores and expansion opportunity tracking. Mid-market reps needed pipeline velocity metrics. SDRs cared about lead quality and conversion rates. Each request meant the analytics team had to build a custom dashboard, pulling data from Salesforce, the data warehouse, and various third-party tools. Six to eight hours per dashboard, minimum.

The backlog grew to three weeks. Reps stopped asking for data because they knew they would never get it in time to be useful. They made decisions based on intuition instead of analysis, leading to missed opportunities and inaccurate pipeline forecasts. The VP of Sales Operations knew this was costing them revenue but could not justify hiring four more analysts just to build dashboards.

Self-service analytics vision

The solution became obvious during a quarterly business review when the CEO asked why sales analytics was not self-service like their product analytics. The VP of Sales Operations had no good answer. They had looked at traditional BI tools, but those required SQL knowledge and weeks of training. Sales reps needed something they could use immediately without becoming data experts.

Lumis offered a different approach. Instead of requiring technical skills, the AI could understand what a rep was trying to accomplish and suggest the right visualizations automatically. The sales ops team could create templates for common use cases, and reps could customize them without breaking anything or creating nonsensical charts.

From bottleneck to strategic partner

The transformation went beyond just efficiency gains. With reps handling their own standard dashboards, the analytics team finally had time for work that actually required their expertise. They built a pipeline forecasting model that improved accuracy by 40%. They analyzed territory assignments and recommended changes that increased productivity 34%. They identified patterns in lost deals that led to product and pricing improvements.

Sales rep productivity improved measurably. With real-time data at their fingertips, reps spent less time guessing and more time acting. They identified at-risk accounts earlier, spotted upsell opportunities faster, and prioritized their time more effectively. The VP of Sales Operations calculated that the improved data access was worth roughly $2M in additional revenue in the first year alone.