Same analytics. Four different workflows.
Tuesday you saw the code. Today you see how real team members actually use it. Each role has different needs, different views, different wins.
Team Workflows
See how different roles use the same system to transform their daily work.Click each role below
Before Automation
With Automation
Workflow Process
Impact By The Numbers
"I finally have data to back up my gut feelings about the team."
— Engineering Manager, 6 years leadership
How Roles Work Together Through the System
The automation doesn't just make individuals faster—it makes teams work better together. Here's a real example.
High-Risk Scenario: Engineering Team Burnout Detection
✨ Scroll here to watch the workflow
Practice-Wide Impact
| Metric | Before | After | Improvement |
|---|---|---|---|
| Time to Detect Issues | 4-6 weeks (exit interviews) | Real-time to 3 days | 95% faster detection |
| Leadership Time on Reporting | 22 hours/week (4 roles combined) | 4.5 hours/week | 80% time savings |
| Data Accuracy | 70-80% (manual errors) | 98-99% (automated validation) | 25% accuracy gain |
| Proactive Interventions | 2-3 per quarter (reactive) | 12-15 per quarter (proactive) | 5x intervention rate |
Getting Your Team On Board
Managers think it's surveillance, not support
Show aggregated data only, never individual tracking. Frame as 'early warning system' for team health, not performance monitoring.
Managers become advocates when they catch burnout before losing team members.
Analysts worry AI will replace their role
Run side-by-side for 2 weeks: manual analysis + AI analysis. Show AI handles data prep (boring), analysts do interpretation (valuable).
Analysts realize they're freed up for strategic work they were hired to do.
Operations concerned about data silos and integration complexity
Start with 2-3 key tools (Slack, JIRA, calendar). Add integrations incrementally. Show 80% of insights come from 20% of data.
Ops sees value in week 1 with minimal setup, expands from there.
Specialists skeptical of AI understanding culture nuance
AI flags patterns, humans interpret context. Show examples where AI caught signals humans missed, and where humans corrected AI.
Specialists trust AI as 'research assistant' that scales their expertise.
Leadership worried about upfront cost and ROI timeline
Calculate current cost: 22 hours/week × $75/hour avg = $1,650/week wasted. Show 30-day payback with time savings alone.
ROI becomes obvious when framed as 'reclaiming 80% of leadership time for strategy'.
Investment & ROI
Typical payback in 30-45 days through time savings
Pricing
ROI Calculator
Proven Results
From Demo to Live in 3 Weeks
From demo to production in just 3 weeks
- Connect your data sources (Slack, JIRA, calendar, HRIS)
- Configure role-specific dashboards for each team member
- Import historical data (last 90 days) for baseline metrics
- Set up alert thresholds based on your team size
- Train each role on their dashboard (90 min sessions per role)
- Run pilot with 1-2 teams to validate insights
- Gather feedback on alert sensitivity and metric relevance
- Adjust configurations based on your team's workflow
- Roll out to all teams and roles
- Daily check-ins for first week to address questions
- Measure baseline vs new performance (time saved, issues caught)
- Schedule 30-day review to assess ROI and optimize
Enterprise deployments may take 4-6 weeks for custom integrations and multi-region setup
2026 Randeep Bhatia. All Rights Reserved.
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