When creating a #datacollection system for your #MonitoringEvaluation activities there are 7 steps you can follow to ensure you are building an effective system. Here they are:
Step 1: Map the information flow in your organization & programmes.
• List all actors involved in reporting
• Add those interested in the activities' progress
• Map out how information flows from each department, field office or colleague to another & eventually to you
Then, find out:

• Where each type of information resides
• Who is responsible for providing it

Tip: If you find out that there are various different systems storing information you can consider replacing them with one so as to streamline the overall #datacollection process.
To reach quick conclusions out of multiple sources of data you need to have in your hands #qualitydata in structured formats at designated times. Save time & reduce friction by using a common #datamanagement system for all data collection needs.
Step 2: Create an indicators’ inventory

• Examine your #Logframe or #ResultsFramework
• Detect high-level #indicators and analyze them further
• Identify percentages
• Narrow it down to the exact numbers you need to track

Add the related Activity next to each indicator.
The hierarchy of information in Logical/Results Frameworks is top down. In data collection, we need to approach the process bottom-up.
To complete the indicators’ inventory, choose the breakdowns you will use (e.g. frequency, location, demographics). Keep in mind:
• The objectives of your M&E programme
• The interest of all involved actors
• Confidentiality issues

Tip: Use the mapping exercise from Step 1.
Step 3: Decide on the structure of the #datacollection plan in relation to your team size and M&E plan.

• Incongruous #indicators?
You might need multiple forms.

• Similar indicators & small team? Maybe it’s best to go with one flexible #form.
Step 4: Bring your M&E data collection system to life.

Decide where the data collection system will reside. Think of:

• Ease of use & flexibility
• Users’ access
• Offline & mobile availability
• Validation rules & reporting locks
• Audit logs

And of course data security.
Step 5: Empower the data collection process.

Support your team & help them address data entry challenges such as internet limitations & field constraints. Offer:

• User-friendly tools
• Mobile apps working online & offline
• Inclusive training sessions
• Supportive material
Step 6: Monitor the data collection process.

Once data entry starts, keep an eye on the process, detect unsolicited changes and enhance data quality. Use:

• Locks on reported data
• Validation rules
• Reviewing sections
• Audit logs
Step 7: Evaluate progress & build rapport by sharing results internally and externally when possible. How?

• Publish reports, dashboards & maps to inform stakeholders on the progress of your activities.
• Combine results with evaluation conclusions, insights & recommendations.
Finally, after all these steps, don’t forget to congratulate yourself on putting together such a demanding #datacollectionsystem!

Want to learn more? Read the full guide: bit.ly/MandE-data-col…

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