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October 29, 2018
•ACF collects systematic data through
SMART surveys
•Data is processed via validation program
but not aggregated in one place
•SMART staff and others have no access
to aggregated data and analysis
•Web-based dashboard system would
serve both aggregation and analysis
•We must understand users to create
system that decreases workload
•Third-parties conduct SMART surveys
and send the data to ACF
•SMART team adjusts methodology and
analyses data
•Other researchers need access to
aggregated data
•If technology is a burden on its users, it
will not be used.
•Design must reflect existing user
workflows, not force them to change
•Data must be kept secure and
anonymised to protect respondents
•Dashboards must be easy to use and
intuitive
•Data must be stored systematically for
analysis and possible future AI use
•Use open-source data collection software
– don’t reinvent the wheel
•Build-in APIs to share data with other
platforms
•Considerations of field teams paramount
– without them there is no data
•Do not force use of Excel, pull from data
collection – no extra steps for users
•Dashboards should answer questions
analysts have, not just present data
‘because it’s there’
•Design thinking can prevent existing
software from being unused and
neglected
•Systems should reflect users’
understanding of their work, not force
them to learn the system’s
•Data is only powerful when standardised
and aggregated
•The potential for data should not be
overstated, but organisations should
strive to realise potential that is there

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一比一原版(harvard毕业证书)哈佛大学毕业证如何办理
 
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataPredictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
 

Approach to Challenge 2 - Global Nutrition Dashboard

  • 2. •ACF collects systematic data through SMART surveys •Data is processed via validation program but not aggregated in one place •SMART staff and others have no access to aggregated data and analysis •Web-based dashboard system would serve both aggregation and analysis
  • 3. •We must understand users to create system that decreases workload •Third-parties conduct SMART surveys and send the data to ACF •SMART team adjusts methodology and analyses data •Other researchers need access to aggregated data
  • 4. •If technology is a burden on its users, it will not be used. •Design must reflect existing user workflows, not force them to change •Data must be kept secure and anonymised to protect respondents •Dashboards must be easy to use and intuitive •Data must be stored systematically for analysis and possible future AI use
  • 5. •Use open-source data collection software – don’t reinvent the wheel •Build-in APIs to share data with other platforms •Considerations of field teams paramount – without them there is no data •Do not force use of Excel, pull from data collection – no extra steps for users •Dashboards should answer questions analysts have, not just present data ‘because it’s there’
  • 6. •Design thinking can prevent existing software from being unused and neglected •Systems should reflect users’ understanding of their work, not force them to learn the system’s •Data is only powerful when standardised and aggregated •The potential for data should not be overstated, but organisations should strive to realise potential that is there