SayPro Begin applying the established data verification protocols to all new data collected throughout January.

Great! Here’s a practical and structured plan for SayPro to begin applying the established data verification protocols to all new data collected throughout January. This ensures a smooth rollout, consistency in implementation, and builds accountability from day one.

---

✅ SayPro: Applying Data Verification Protocols to January Data Collection

🎯 Objective

To ensure that all new data collected in January complies with SayPro’s official data verification protocols, maintaining data quality, credibility, and alignment with internal standards and reporting needs.

---

📅 Implementation Timeline: January Rollout Plan

Date Range	Action Item	Responsibility
Jan 1–5	Orientation & distribution of verification tools to all teams	M&E Team, Project Leads
Jan 6–31	Ongoing application of verification protocols to all new data collected	Data Collectors, M&E Team
Jan 15 & Jan 30	Mid-month and end-of-month data review checkpoints	M&E Coordinator
Feb 1–7	Compile verification logs and review compliance across projects	QA/Data Quality Lead

---

🧰 Tools and Resources to Use

• ✅ Data Verification Checklist (digital/paper)
• ✅ Source Metadata Template (to capture data origin, collection method, timestamp)
• ✅ Verification Logbook (tracks who verified each dataset and when)
• ✅ Quality Scoring Matrix (rates each dataset by accuracy, completeness, consistency, etc.)

All resources should be made available on the SayPro Shared Drive or internal system.

---

🔄 Step-by-Step Process to Apply the Protocols

🧾 1. Pre-Collection Setup

• Review updated data collection tools to ensure they match verification criteria.
• Train data collectors and M&E staff on:
  • Filling out verification checklists.
  • Recording metadata (who, where, when, how).
  • Common red flags to watch for (incomplete responses, duplicates, etc.).

📥 2. During Data Collection

• Apply verification steps as data is collected, not just after.
  • Example: If using mobile survey tools, enable real-time flagging for missing fields or out-of-range values.
• Field staff submit data along with:
  • Completed verification checklist
  • Metadata form describing the collection context

📊 3. Post-Collection Review (Weekly or Bi-weekly)

• M&E team conducts a spot-check on at least 10–20% of submitted datasets.
• Use the scoring matrix to rate:
  • Accuracy (e.g., does this match other data we know?)
  • Completeness (are required fields filled?)
  • Consistency (do timestamps and formats align?)

🧾 4. Documentation

• Log all verification activities in the central Data Verification Log:
  • Dataset name
  • Date verified
  • Name of verifier
  • Notes or actions taken (e.g., returned to field for correction)

📤 5. Feedback Loop

• If any dataset fails verification, return to the field/data source team with comments.
• Track these cases in a “Returned for Revision” sheet for accountability.

---

📈 Monitoring and Reporting

• Conduct a mid-January verification status review with all departments.
• At the end of January, produce a summary report including:
  • Number of datasets verified
  • Common issues found
  • Corrective actions taken
  • Recommendations for February improvements

---

✅ Benefits of Starting in January

• Sets a strong precedent for all 2025 data practices
• Builds muscle memory for verification processes early
• Identifies real-world gaps in the verification protocol
• Increases accountability and improves overall data quality

---

Would you like help setting up the actual verification log, reporting template, or a January tracking dashboard to help SayPro monitor this rollout in real time?