DMAIC project reducing sales proposal cycle time by 15% — enhanced with a live Databricks monitoring pipeline for real-time process KPI tracking in Tableau.
Gentech, a $60B multinational, faced stagnating growth due to a sluggish Quote-to-Tender process. Goal: Reduce proposal cycle time by 15% using DMAIC methodology.
The control phase is powered by a Databricks + Tableau live monitoring pipeline ingesting CRM data daily and surfacing SLA breaches in real time — no manual reporting needed.
| Phase | Key Action | Outcome |
|---|---|---|
| Define | SIPOC map, defect definition (>35 days) | Baseline: 31.6 days avg, sigma 2.08 |
| Measure | Tableau control chart by brand/region | DPMO: 281,053 |
| Analyze | Fishbone diagram — approval loops, manual entry, sequential reviews | 3 root causes identified |
| Improve | RPA for standard bids, Poka-Yoke CRM validation, parallel reviews | Projected -4.7 days |
| Control | Databricks → Tableau live SLA dashboard | Automated breach alerts |
| Metric | Before | After | Improvement |
|---|---|---|---|
| Avg Cycle Time | 31.6 days | 26.9 days | -15.2% ✅ |
| Sigma Level | 2.08 | 2.78 | +0.70 |
| DPMO | 281,053 | 158,655 | -44% |
| Rework Rate | 12% | 2% | -83% |
Salesforce CRM (daily export)
→ ADF → Databricks Delta: proposals_raw
→ dbt: proposal_kpis (cycle time, sigma, SLA status)
→ Tableau: real-time SLA monitoring + trend alerts
→ Email alert when 7-day avg > 30 days
| Category | Tools |
|---|---|
| Methodology | Lean Six Sigma DMAIC, SIPOC, Fishbone |
| Monitoring | Databricks, Delta Lake, ADF, dbt |
| Visualization | Tableau control charts, Draw.io |
| Statistics | Minitab (normality tests, sigma calculation) |
git clone https://github.com/omkarpallerla/Lean-Six-Sigma-Process-Analytics.git
cd Lean-Six-Sigma-Process-Analytics
pip install -r requirements.txt
jupyter notebook notebooks/01_Baseline_Analysis.ipynb
Built by Omkar Pallerla · MS Business Analytics, ASU · BI Engineer · Tableau | Databricks | Azure Certified