Same disruption data. Four different workflows.
Tuesday you saw the automation code. Today you see how managers, analysts, ops coordinators, and specialists each use it differently. Same alerts, different actions, better outcomes.
Team Workflows
See how different roles use the same system to transform their daily work.Click each role below
Before Automation
With Automation
Dashboard Metrics
Impact By The Numbers
"I finally stopped firefighting and started actually managing the supply chain."
— Supply Chain Manager, 11 years logistics
How Roles Work Together on One Disruption
Watch how all four roles collaborate through the system to resolve a high-impact disruption in under 3 hours.
Semiconductor shortage detected at primary supplier
✨ Scroll here to watch the workflow
Practice-Wide Impact
| Metric | Before | After | Improvement |
|---|---|---|---|
| Disruption Response Time | 2-3 weeks average | 18 minutes to 3 hours | ↓ 99% faster |
| Suppliers Monitored | 50-75 (manual limit) | 247 continuously | ↑ 230% coverage |
| Team Coordination Time | 12 hours/week meetings | 2 hours/week reviews | ↓ 83% less meetings |
| Missed Disruptions | 15% slipped through | 0% missed | ↑ 100% visibility |
Getting Your Team On Board
Managers worry AI will replace their strategic judgment
Show that AI handles monitoring and data aggregation, freeing managers for actual decision-making. Run parallel for 2 weeks: managers see they make better decisions with AI insights, not worse.
Managers become AI advocates when they realize it amplifies their expertise instead of replacing it.
Analysts think automation will eliminate their jobs
Demonstrate time savings data: 6.5 hours/week freed up means more strategic projects, not layoffs. Frame as 'from data janitor to strategic advisor.' Show career progression opportunities.
Analysts see automation as career accelerator. They get promoted faster because they're doing higher-value work.
Operations coordinators don't trust AI to communicate with suppliers
Let them review AI-generated messages before sending for first 30 days. Show 92% response rate vs 65% with manual emails. Suppliers actually prefer consistent, timely automated requests.
Coordinators realize AI is better at routine communication than they are. They focus on complex negotiations instead.
Specialists worry AI can't understand nuanced supplier requirements
Run side-by-side test: specialist finds alternatives manually, AI finds alternatives simultaneously. Compare quality, speed, pricing. AI typically finds 2-3 options specialists missed.
Specialists use AI as research assistant. They make final decisions but with 4x more options to choose from.
Leadership concerned about upfront investment and ROI timeline
Calculate current cost of disruptions: $2.3M average exposure × 15% missed = $345K annual risk. Show automation ROI: $60K/year subscription saves $890K in faster response + eliminates $345K risk exposure.
ROI becomes obvious: 18x return in year one, 2-week payback period on first prevented disruption.
Investment & ROI
Typical payback in 14-21 days through prevented disruption costs
Pricing
ROI Calculator
Proven Results
From Demo to Live in 3 Weeks
From demo to production in just 3 weeks
- Connect ERP, TMS, and supplier portals (API integrations)
- Import supplier database and active POs
- Configure role-specific dashboards and alert thresholds
- Set up monitoring rules for your critical suppliers
- Train each role on their workflows (3hr sessions per role)
- Run pilot with 5 users and 25 suppliers
- Test disruption scenarios with historical data
- Gather feedback and adjust configurations
- Roll out to all users and suppliers
- Daily check-ins for first week (30-min standups)
- Measure baseline metrics vs new performance
- Document processes and create runbooks
Enterprise deployments with multi-region rollout typically take 6-8 weeks. We can run parallel with existing systems during transition.
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