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Enhancing Agricultural Productivity with the MDS Digital Field Worker Application

The MDS (Minimum Data Set) application, designed for field workers in Lusaka, aims to improve agricultural productivity and profitability through digital solutions. Managed by Shaun Ferris from CRS Agriculture, this innovative platform enhances skills, asset management, and provides critical data for over 200 farmer groups and 5000 field agents. It supports efficient data flow by implementing a parallel system that ensures high data quality. Through effective monitoring and evaluation, the MDS application empowers farmers, strengthens market chains, and enhances access to services.

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Enhancing Agricultural Productivity with the MDS Digital Field Worker Application

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  1. Digital Field worker and the “MDS” application Lusaka, 30th April Shaun Ferris

  2. CRS Agriculture aims to Enhance • Productivity • Profitability • Skills • Asset management

  3. Digital Fieldworker Platform ( Current Series data flow) Project manager Theme leaders Master trainers Diseases Seeds/ inputs Production Finance Marketing CRS Project Field staff Project staff Project staff Project staff Project staff Project staff Local Partners Partner Staff Partner Staff Partner Staff Partner Staff Partner Staff Partner Staff Partner Staff Partner Staff Field Extension Agents 200 + Farmer Groups 5000 +

  4. Digital Fieldworker Platform (Parallel data flow) Accelerate Data Flow by replacing Series data mapping with parallel data flow With data quality checks Project manager Theme leaders Master trainers Project staff Partner Staff

  5. Field Agent Training Kit agro-enterprise course for field agent Supply and demand What is the market chain?

  6. Main Technology Input devices

  7. Minimum Data Set (MDS) First Phase is to complete the first three forms Form 2. Biz Plan ………………………………………………….. Form 1. Farmer Group Registration………………………………………………….. Form 3. Profitability calculator GM…………………………….. • Form 6. • Baseline • Sentinel Impact Δ Income Δ Assets Δ Food security Δ Trading relations Δ Income options Δ Service access Form 4. Production Profile Rains Date planted, seed type Date weeded Date fertilized Date harvested # bags kept, # bags sold Form 5. Visit Log Date Duration Purpose Outcome

  8. MDS Registration Page

  9. Gross Margin Analysis

  10. MDS Profitability calculator

  11. MDS Business Planner Key Activities Customer relations Customer segments Key Partners Value proposition Key Resources Channels Cost Structure Revenue

  12. MDS Business Planner

  13. Rethinking - M&E What do we need to measure to support 100 enterprises? Are we on track? Year 1 Year 2 Year 3 Year 4 Year 5 Frequent Data flow M&E systems

  14. Air Adobe Architecture Data • Reports • Field Agent • Supervisor • Program manager • Country • Global Database 1 May 31st Air Adobe Database 2 August 31st Database 2 iforms August 31st

  15. Pilot testing Timeline Feb 2011 Launch 1. May 2011 Launch 2. Jan 2012 Version 2.0 MDS ICT4D India / Phil Amazon cloud hosted SaaS with partner CRS focused and supported SARO 5 countries AFG GMCR ICT4D

  16. Conclusion • Develop a system to collect basic project data • Provide information that helps farmers • Use that process to gather M&E data • Analyse the data for both farm and project performance monitoring and upgrading • Share data with other projects and partners

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