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IT in M&E

IT in M&E. Not (always) a bad idea. Alastair “Bell” Turner Khulisa Management Services. What are these things?. “Database” Repository Capture Tools Reporting Tools. Why do we do it?. Immediate feedback Rapid communications Structure Versioning Distributed Capture.

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IT in M&E

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  1. IT in M&E Not (always) a bad idea. Alastair “Bell” Turner Khulisa Management Services

  2. What are these things? • “Database” • Repository • Capture Tools • Reporting Tools

  3. Why do we do it? • Immediate feedback • Rapid communications • Structure • Versioning • Distributed Capture

  4. Some cheese with that …? • “It was so much easier/quicker without a database” • “We spend our lives pushing stuff into this system and we never get anything out again” • “It suits x’s needs fine, but does nothing for me”

  5. Why are they so unhappy? • Navigation / process intensive interfaces • Inflexible • Insufficient meaningful extraction • Broad programme / donor relevant indicators • Long data periods

  6. What computers do well • Arithmetic • Big numbers • Lost of numbers • Fast • Repetition • Comparison and matching • Accuracy

  7. How does this help us? • Aggregate at all levels • Aggregate in all possible combinations • Multi Dimensional Analysis • OLAP

  8. Illustration • Impact on new car sales • Gas guzzlers and small passenger diesels • Manufacturers • Inland / coastal • Provinces

  9. AUDI GP JAN 173 14 94

  10. 260 25 104

  11. 564 79 58 267 60 43 348 37 103 89 7 29 300 88 40 220 79 58 700 200 165 99 16 27 447 89 103 75 12 30 700 200 165 560 200 55 320 44 38 608 400 50 155 75 28 405 165 37 99 23 25 700 200 165 520 30 120 230 88 77 75 10 14 450 150 77 270 99 45 157 11 50 571 88 99 880 78 200 602 67 77 99 24 17 462 157 68 133 56 14 440 79 33 568 46 33 430 79 67 500 120 78 345 100 90 456 78 56 345 99 120 320 78 99 789 300 54 120 88 20 550 125 70 340 56 44 340 45 100 600 57 138 77 11 24 99 10 30 700 200 165 420 88 57 557 99 145 444 22 64 570 125 33 230 150 44 700 200 165 790 400 210 688 67 92 53 2 20 607 300 157 88 15 27 183 5 30 654 54 33 176 33 5 244 67 45 700 200 165

  12. Organisation Time Indicator

  13. Getting data in easily • Import sources are not always stable • Extension of the organisation hierarchy during import • Atomic data makes time aggregation possible

  14. Time based aggregation • Discrete • Just add/compare numbers over time • Continuous • Generally “Continuing” + “New” • When aggregating over time “New” has some important qualifiers

  15. Old fashioned data capture • Tally sheets or registers • Order of fields/columns • Produce registers or forms from system

  16. In summary • Multi Dimensional Analysis • Reporting flexibility • Capture system / Import flexibility • Cascades • Subdividing dimensions • Time is the tricky one • Capture from paper • Watch the order • Print them from the system

  17. A word from our techies • Exceptions are the enemy of reliability • Not complexity Thank You

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