Author: Rijo Mathew John
Role: Business Development Manager & Data Analyst
📍 Dublin, Ireland | 📧 rijomj008@gmail.com
This project models how small operational tweaks can create measurable business impact across two restaurant branches — Lucan and Liffey Valley — of the Sheela Palace Group, operated under Blue Sapphire Tech Ltd.
It simulates three real-world business levers:
- €2 Customer Spend Increase (Pricing Optimization)
- Rain Penalty Reduction (17% → 10%)
- Staff Efficiency Improvement (+10%)
All analysis was done using PostgreSQL (SQL Views) for data modeling and Power BI for interactive visualization.
The project covers an 8-month operational window (Jan–Aug 2025) and demonstrates how minor adjustments can yield over €90,000 in potential annualized gains — without any capital investment.
| Layer | Tools Used | Purpose |
|---|---|---|
| Data Modeling | PostgreSQL (SQL Views) | Build reusable marts & scenario simulations |
| Visualization | Power BI | Create executive dashboards & scenario simulations |
| Documentation | Markdown / GitHub | Transparent business storytelling |
Operations-Scenario-Model/
│
├─ README.md # Project overview & instructions
├─ LICENSE # MIT license
├─ .gitignore # ignore cache/temp files
│
├─ /sql # PostgreSQL data modeling & scenario scripts
│ ├─ 00_run_all.sql # executes all scripts sequentially
│ ├─ 01_schema_setup.sql # base schema creation
│ ├─ 02_params.sql # global parameters (price uplift, rain penalty)
│ ├─ 03_ref_branch_meta.sql # reference metadata per branch
│ ├─ 10_base_channels.sql # split dine-in vs delivery, compute RPV/RPO
│ ├─ 20_scn_price.sql # €2 RPV uplift scenario (Lucan)
│ ├─ 30_scn_rain.sql # rain penalty reduction (17% → 10%)
│ ├─ 40_scn_staff.sql # +10% staff efficiency model
│ ├─ 50_scn_all_summary.sql # consolidated branch comparison summary
│ └─ 90_exports.sql # export templates (safe, no sensitive data)
│
├─ /PowerBi # Power BI dashboard, visuals, and measures
│ ├─ Operations_Dashboard.pbit # dashboard template (no data)
│ ├─ Measures.md # all DAX measures used
│ ├─ Visuals_Layout.md # visual design documentation
│ ├─ Dashboard_Overview.png # full dashboard screenshot
│ ├─ Price_Scenario.png # €2 RPV uplift visualization
│ ├─ Rain Penalty.png # rain impact reduction chart
│ ├─ Staff_efficiency.png # staff productivity scenario
│ ├─ Efficiency_Contributions.png # donut: scenario contribution analysis
│ └─ Profitability_Timeline.png # simulated vs baseline profitability trend
│
└─ /Docs # documentation and metadata
├─ Overview.md # executive summary (business insights)
└─ data_model.md # schema documentation (marts, joins, lineage)
Lucan’s buffet is priced at €20 versus Liffey’s €22.
If Lucan recovers that €2 gap through delivery pricing, premium combos, or value-add promotions, the branch can generate an additional €53,430 in 8 months (~€6,700/month) with zero increase in fixed costs.
Strategic Takeaway:
Optimize delivery pricing and perceived-value menus to align Lucan’s RPV with Liffey’s without deterring demand.
Weather-related slowdowns cost both branches roughly €35,000 in potential revenue (Liffey ≈ €21k, Lucan ≈ €14k).
By mitigating the impact through targeted rainy-day offers, loyalty incentives, or delivery boosts, the group could reclaim that lost revenue.
Strategic Takeaway:
Treat rainy days as promotional opportunities, not slow days — 7–10% sales recovery potential per month.
Improving staff productivity by 10% would save approximately 150–170 labour hours/month at Liffey and 60–80 hours/month at Lucan, equating to €2,000–€2,500/month in labour cost savings.
Lucan is already operating close to optimal efficiency, while Liffey holds the largest improvement margin.
Strategic Takeaway:
Focus efficiency training and smart scheduling at Liffey to unlock the highest ROI from labour optimization.
| Scenario | Description | Potential Gain (8 Months) | Key Action |
|---|---|---|---|
| Price Uplift | €2 spend increase at Lucan | €53,430 | Optimize pricing & perceived value |
| Rain Penalty | Reduce rain loss from 17% → 10% | €35,000 | Launch rainy-day promotions |
| Efficiency +10% | Smart scheduling & training | €20,000 (annualized) | Focus on Liffey training ROI |
💰 Total Potential Gain: Over €90,000/year
⚙️ Investment Required: None — purely operational optimization.
The Power BI dashboard presents a single executive view:
Top KPIs
- Total uplift (€)
- Monthly revenue recovery
- Labour hours saved
- Branch-level RPV comparison
Main Scenario Panels
- Left: Price Uplift (€2 Scenario)
- Center: Rain Penalty Reduction (17 → 10%)
- Right: Staff Efficiency (+10%)
Bottom Summary Visual
- Donut chart showing contribution of each scenario to total uplift (Price 59%, Rain 25%, Efficiency 16%)
- Profitability Timeline
# Clone the repository
git clone https://github.com/<rijomj008-create>/Operations-Scenario-Model.git
cd Operations-Scenario-Model
# Run setup
psql -U <user> -d <database> -f sql/00_run_all.sqlData note: This repository contains only SQL logic and Power BI templates — all sensitive business data has been excluded.
- Built modular SQL pipelines (staging → marts → scenario views)
- Created parameter-driven models for “what-if” simulations
- Integrated SQL and Power BI to tell a financial impact story
- Demonstrated business acumen in pricing, weather, and efficiency levers
- Showcased how to operationalize analytics for executive decisions
Rijo Mathew John Business Development Manager | Data & Operations Analyst 📧 rijomj008@gmail.com 📍 Dublin, Ireland
www.linkedin.com/in/rijo-mathew-john-225403373