1.1 Define your data problem

Clarifying the issue or challenge that your data-driven work is designed to solve

Why should I do this?

To articulate and document a shared understanding of the data problem being tackled. Articulating and sharing it with others in your investment can help ensure there is alignment on what various partners are working to solve.

1) If you are a Program Officer (PO), you may want to share this page directly with your grantee, so they can act on it.

 

2) You can use the workbook (and supporting factsheet) for Step 1 here. We recommend using the same document throughout this step, so you have a single document that captures all your workings. The workbook contains guiding questions to help you formulate your data problem statement.

 

3) Use the guiding questions below to help you get started on defining your investment’s data problem statement:

 

  • What is the data problem the investment is trying to solve?
  • How did this data problem arise?
  • How would the beneficiary describe the data problem?
  • What evidence is there that this is a data problem?

A project team might identify their data problem as ‘limited access to real-time soil health data for smallholder farmers in remote regions’. This challenge impacts farmers’ ability to optimize crop yields due to lack of timely, localized soil condition information.

 

4) Refer to the investment type examples below while formulating your data problem statement.

 

5) If the investment has already developed a data problem statement that both the grantee and PO are aligned on, populate the template with the existing problem and move on to the next activity.

©Gates Archive/Mansi Midha ©Gates Archive/Mansi Midha

Every investment project is unique

The application of the six steps will vary accordingly. To provide examples that align with your project, common characteristics of AgDev investments were researched and three ‘investment types’ were developed.

©Gates Archive/Alissa Everett

AgriConnect’s data problem statement

The lack of an integrated, accessible platform for agricultural data that smallholder farmers can use to improve decision-making.

 

Background: There are inefficiencies caused by scattered data sources, making it difficult for farmers and stakeholders to locate relevant information. Beneficiaries, such as farmers, describe the problem as a barrier to improving productivity, as they currently rely on outdated or incomplete information. From earlier engagements, AgriConnect collected evidence through surveys that shows that farmers face challenges in accessing reliable data.

©Gates Archive/Thomas Omondi

AgroThrive’s data problem statement

In Datapur, government departments lack access to cohesive and actionable agricultural data to inform policymaking and attract private investment.

 

Background: This problem emerged from initial consultations with government officials who noted the difficulty of sourcing and using data for policy development. For beneficiaries like Datapur officials, the issue is one of disconnected data sources, making it hard to take informed policy decisions. Through desk research, AgroThrive found several government reports that highlighted gaps in available agricultural data and provided validation to the data problem they had articulated.

©Gates Archive/Esther Mbabazi

NourishGen BioTech (NGBT) data problem statement

The scarcity of climate-resilient crop data that can be used to support smallholder farmers in Datastan.

 

Background: The problem stems from the lack of comprehensive, locally relevant agricultural data, which limits NGBT’s ability to make informed decisions on crop development. Farmers and local stakeholders describe this as a missed opportunity to improve food security and productivity. NGBT has gathered evidence from its research showing that available data is insufficient for the specific needs of Datastan’s farmers.

While the FAIR Process Framework focuses on data, it is beneficial to link the data problem you are trying to solve to the larger problem your investment is addressing.

For example, if there are data blockers that are too resource-intensive (or even impossible) to overcome, having a clear vision of your main objectives will allow you to refine your work and use the data that is available to meet those objectives.

Guiding Acid Soil Management Investments in Africa (GAIA)

We want data, in the end, to assist smallholder farmers in making decisions.

Christian Witt, Program Officer, Bill & Melinda Gates Foundation

Watch the full interview
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