Roberto Carlos Tientcheu

Multi-site environment with strong demand volatility and complex coordination between production, inventory and distribution requiring a consolidated real-time view.

• Improved forecast accuracy from 85% to 93% (+8 pts) through ABC/XYZ segmentation, advanced statistical models and integration of promotional signals.
• Reduced stock-outs from 15% to 7% (53% decrease) by dynamically optimising safety stocks and implementing early warning alerts.
• Generated 59,000 € in yearly savings via Lean projects, transport optimisation and CO₂ reduction.
• Prevented 8 critical stock-outs, protecting 45,000 € of sales.

S&OP achievements

• Led 12 complete S&OP cycles: demand consolidation, sales history analysis, capacity simulations, production and inventory trade-offs.
• Designed 5 Power BI executive dashboards connected to SAP and Sage X3 (OTIF, logistics costs, stock rotation, stock-out alerts).
• Facilitated demand review meetings with sales and supply teams, adjusting forecasts with field feedback.

Continuous improvement

• Reduced CO₂ emissions by 12% through transport plan optimisation and reduction of empty trips.
• Increased truck loading rate from 68% to 85% (+17 pts) via flow analysis and delivery frequency adjustments.
• Cut order preparation time by 9% by reorganising picking flows and storage zones.

Manual reporting taking 6 hours per week, fragmented data between SAP S/4HANA and Sage X3 and no consolidated real-time performance view.

• Built 10 Power BI dashboards connected to SAP S/4HANA and Sage X3 through automated ETL flows.
• Designed a star schema data model (orders, stock, deliveries vs products, customers, time, sites) and advanced Power Query transformations.
• Developed complex DAX measures (time intelligence, rolling averages, anomaly detection, dynamic KPIs).
• Supported 6 S&OP cycles: MAPE tracking by product family, risk identification and commercial forecast consolidation.

Results: reporting time reduced by 70% (6 hours to 1 hour 30 per week), elimination of manual input errors and adoption by more than 15 users (management, supply planning, sales, finance).

Quantitative modelling of macroeconomic risks (inflation, exchange rate volatility, logistics disruptions) on humanitarian supply chains in developing countries.

• Analysed large international economic databases and UNDP operational data (purchases, lead times, inventory).
• Built composite risk indicators and impact scenarios (stress tests, Monte Carlo simulations).
• Produced 2 strategic notes with quantified results and operational recommendations.

Monitoring of vocational training programmes funded by multiple donors (total budget 1.2 M€).

• Designed relational Excel databases for 4 projects and automated 4 monthly reports via Google Apps Script.
• Defined financial and operational performance frameworks and supported steering committees with variance analysis and recommendations.