Case Study - Supervisor Content Talabat.pptx

The case study **“Supervisor Content – Talabat”** explores how effective leadership, communication, and performance management can transform a content operations team within a fast-paced food delivery platform. It highlights the supervisor’s role in aligning content accuracy with customer experience, ensuring that menus, promotions, and restaurant data are always up to date and error-free. The study examines challenges such as high order errors, slow content updates, and cross-department coordination gaps, and explains how structured training, data tracking, and accountability systems improved team productivity and quality. By introducing clear KPIs, coaching sessions, and collaboration tools, the supervisor achieved significant improvements in turnaround time, reduced content-related customer complaints, and boosted overall brand consistency across Talabat’s digital ecosystem.

1. Case Study - Supervisor Content Mohamed Younis

2. Root Cause Analysis (RCA)  and  Action Plan  using the  DMAIC 1. Define Problem : Low vendor satisfaction (VSAT) across several vendor contact reasons, especially related to operational and content updates. Goal : Improve CSAT and reduce DSAT for high-volume and low-performing contact reasons.

3. Measure Key Metrics : Contact reasons with  CSAT < 30% High  DSAT counts High  survey volume Root Cause Analysis (RCA)  and  Action Plan  using the  DMAIC

4. Root Cause Analysis (RCA)  and  Action Plan  using the  DMAIC Measure Key Metrics : Contact reasons with  CSAT < 30% High  DSAT counts High  survey volume

5. 3. Analyze Here are the top RCA candidates with CSAT < 30%: Root Cause Analysis (RCA)  and  Action Plan  using the  DMAIC

6. 4. Improve Action Plan Suggestions : Root Cause Analysis (RCA)  and  Action Plan  using the  DMAIC

7. Root Cause Analysis (RCA)  and  Action Plan  using the  DMAIC 5. Control Monitoring Tools : Weekly CSAT/DSAT dashboards SLA tracking for each contact reason Feedback loop with vendors post-resolution

8. Glide Path to Improve Vendor Experience Using DMAIC Phase 1: Define (Week 1) ✅ Finalize problem statement: Low CSAT in vendor interactions. ✅ Identify top contact reasons with high DSAT and low CSAT. ✅ Align with stakeholders (Ops, Tech, Vendor Support) on goals. Deliverables : Problem charter Stakeholder map Initial RCA list Phase 2: Measure (Week 2–3) 📊 Deep dive into survey data (CSAT, DSAT, volume). 🧾 Map current processes for top contact reasons. 🧠 Identify gaps in content workflows (e.g., menu updates, coverage area). Deliverables: Process maps Baseline metrics dashboard Vendor feedback summary Phase 3: Analyze (Week 4–5) 🔍 Conduct RCA sessions with cross-functional teams. 📉 Prioritize issues based on impact and effort. 🧪 Identify quick wins vs long-term fixes. Deliverables: RCA matrix Pareto chart of issues Prioritized improvement list Phase 4: Improve (Week 6–8) 🛠 Implement fixes (e.g., automation, UI enhancements, SOP updates). 🧪 Pilot changes with selected vendors. 📢 Communicate updates and gather feedback. Deliverables: Updated SOPs Pilot results Vendor communication plan Phase 5: Control (Week 9–10) 📈 Set up dashboards to monitor CSAT/DSAT weekly. 🧭 Define SLAs and escalation paths. 📚 Train internal teams and vendors on new processes. Deliverables: Monitoring dashboard SLA documentation Training materials

9. Glide path

10. ✅ Alignment Between RCA and Glide Path

11. 2- Rejection Rate

12. 2- Rejection Rate The Weight of the Rejection Reason Using parito chart

13. 2- Rejection Rate 🔍 Categorized Root Causes

14. 🛠️ B. Action Plan to Improve 1. Define Objective : Reduce rejection rates in new acquisition by addressing top rejection reasons related to content, documentation, and imagery. Scope : Focus on high-weight rejection reasons such as: Images Ratio Less Than 80% Wrong Legal Name Signature Mismatch Menu Description Quality Stakeholders : Content Team Acquisition Team Vendor Support Legal & Ops 2. Measure Actions : Audit 3 months of rejection data to quantify impact. Segment rejections by category (e.g., imagery, documentation, contract). Identify recurring patterns in vendor submissions. KPIs : Rejection rate per category CSAT/DSAT scores post-resolution Time to resolution 3. Analyze Root Cause Identification : Imagery : Vendors unaware of image ratio standards. Documentation : Manual entry errors in legal names and account details. Authorization : Missing or mismatched signatures. Menu Quality : Incomplete or poorly structured menu descriptions. Tools Used : Pareto Analysis Fishbone Diagram Vendor feedback loop 4. Improve Solutions : Imagery : Launch auto-validation tool for image ratio and resolution. Documentation : Pre-filled templates and dropdowns for legal fields. Authorization : Digital signature verification integrated with ID upload. Menu Quality : Menu builder with sectioning and description prompts. Pilots : Run pilot with top 10 vendors to test new tools and templates. Collect feedback and iterate. 5. Control Sustainability Measures : Weekly rejection dashboard by category. Monthly training for acquisition and content teams. SOP updates and version control for templates. Vendor onboarding checklist with mandatory validations. Governance : Assign QA leads for each rejection category. Escalation matrix for unresolved cases.

15. 🛤️ Glide Path for Improvement Week 1 – Define Finalize problem statement: High rejection rate in new acquisition. Identify top rejection categories (e.g., imagery, documentation, menu). Align with stakeholders: Ops, Vendor Support, Legal, Acquisition. My Role : Present content-related rejection trends and define improvement goals. Week 2–3 – Measure Audit rejection data by category and vendor type. Map current acquisition and content submission workflows. Identify bottlenecks and manual error points. My Role : Lead content workflow mapping and validate imagery/menu standards. Week 4–5 – Analyze Conduct RCA workshops with cross-functional teams. Use Pareto and Fishbone analysis to identify root causes. Prioritize issues based on frequency and impact. My Role : Highlight content-specific pain points and propose automation opportunities. Week 6–8 – Improve Implement: Image validation tool Menu completeness checker Pre-filled contract templates Signature verification system Pilot changes with selected vendors and acquisition teams. My Role : Oversee content tool deployment and vendor training. Week 9–10 – Control Launch rejection monitoring dashboard. Update SOPs and onboarding checklists. Conduct refresher training for acquisition and content teams. Establish feedback loop with vendors. My Role : Maintain content QA standards and monitor rejection trends.

16. 3- Bounce Rate 📊 Correlation Insights ✅ Top Factors Correlated with GMV (Gross Merchandise Value in EUR): ✅ Top Factors Correlated with Content Readiness: 🔥 Key Takeaways Hypermarkets  are strongly associated with  higher GMV . Vendors from  KSA and Egypt  tend to have  better content readiness . Content readiness positively impacts GMV , though not as strongly as account type. Regular Restaurants  show decent content quality but mixed GMV performance. Evaluate trends by correlating different data points (e.g., activation date, country, account classification, GMV, and item readiness) to uncover meaningful patterns and relationships.

17. 📈 Visual: Correlation Matrix Here’s a heatmap showing how all variables relate to GMV and content readiness:

18. Which vendors are showing poor content readiness (e.g., low active items with images, descriptions, or choices)? What’s the impact of this on performance? ❌ Vendors with Poor Content Readiness Criteria : Vendors with less than  30% completeness  across: Active items with  images Active items with  descriptions Active items with  choices Total vendors affected :  78 📉 Impact on GMV Performance Vendor Group Average GMV (EUR) ❌ Poor Content €4,861.46 ✅ Good Content €38,745.34 This shows that vendors with better content generate ~8x more GMV on average. Vendor ID Readiness % 727036 29.84% 727032 29.84% 727068 29.84% 727012 17.98% 751730 0.00% 753631 0.00% 758726 0.00% 722574 0.00% 722064 0.00% 761824 0.00%

19. Do vendors from specific countries or account classifications perform better or worse in terms of content quality or GMV? 🌍 Country-Level Performance

20. Do vendors from specific countries or account classifications perform better or worse in terms of content quality or GMV?  Insights Kuwait and Qatar  lead in GMV, with  moderate to high content readiness . Egypt  has  high readiness  but lower GMV — possibly due to market size or vendor type. Hypermarkets  dominate GMV despite  low content readiness , likely due to brand strength. Beauty and Pharmacy  categories show  very low readiness , suggesting a major gap.

21. Is there a clear relationship between activation timing and content completeness or GMV? What does this suggest about the onboarding process? Metric Correlation with Activation Timing Content Readiness Score −0.096 (weak negative) GMV (EUR) −0.040 (very weak negative)     Correlation Results   🔍 Interpretation The  negative correlation  means that  earlier-activated vendors  (lower vendor IDs) tend to have  slightly better content readiness and GMV . However, the relationship is  weak , suggesting that  activation timing alone doesn’t strongly determine performance . This implies that while onboarding may improve over time,  other factors  (like vendor type, support, or market) play a bigger role.