Data Readiness Toolkit (Beta)


An overview of data readiness

In the Red Cross Red and Crescent Movement context, data readiness is the ability of National Societies to use quality and timely information in humanitarian operations and programs.

Intro video

Why it matters

The IFRC and National Societies are thinking critically about data and how to leverage it better to improve our work. Through data readiness, organizations will be better equipped to respond to, recover from, and prepare for disasters.

How to get there

There are many paths to becoming a data ready organization. This toolkit outlines an easy-to-follow roadmap to data readiness. Whether you are learning about data readiness for the first time, developing a strategy for your team, or putting together a project proposal, follow the steps below and get started!

Learn the basics

Learn more about data readiness and how it applies to humanitarian operations and programs.

Assess your priorities

Using the assessment framework, identify where your team falls in terms of data readiness and where your team needs to improve.

Plan your learning experience

Plan how your team will meet your data readiness goals and explore Movement resources.

Data readiness one-pager

Need a short one-pager on the roadmap to data readiness? Print this.

Learn the basics

What is data readiness?

In the Red Cross Red Red Crescent Movement context, data readiness is the ability of National Societies to use quality and timely information in humanitarian operations and programs.

Below describes the three main components of data readiness: (1) data literacy, (2) data preparedness, and (3) data-driven decision making.

Data literacy

Data Literacy is the basic skills, knowledge, attitudes, and social structures required for different populations to use data.

Data preparedness

Data Preparedness is the ability to responsibly and effectively use and manage data-related tools, methods, and strategies.

Data-driven decision making

Data-driven decision making is the ability to use data for decisions, having reliably integrated analytic thinking into both design and implementation.

Theory of change

All the components and related competencies are part of a broader Theory of Change (ToC) on data readiness for operations and programs. If you're interested, go ahead and review the ToC. You can use it as a reference for learning more about data readiness, strategy development, project proposals, or other data needs.

Assess your priorities


The assessment phase aims to help you identify your data readiness goals. The framework guides you through the data readiness competencies in humanitarian response and programs alongside a maturity matrix. Using this resource, you can identify where your team falls in terms of data readiness and learn what it means to increase your capacity in those domains.

Recommended steps

There is no "right" way to identify your teams' priorities. There are many considerations, including broader strategic initiatives, project needs, time limitations, and funding opportunities. This section outlines the main steps to help you be successful in this journey. Read the descriptions and tips below as you work through this phase.

1. Select your team

The first step is to identify the appropriate people to be involved in this diagnostic. Who should be included will depend on your goals, but generally, you'll want to identify a team or department.

For example, you can identify a team working on a specific program (such cash or community health surveillance) or a team/department that regularly works with data (such as response or PMER).

2. Assess your team

With your team, go through the framework and rate yourselves from 1 (does not exist) to 4 (high performance). Use the descriptions to rate yourselves as objectively as possible. You may find you belong in two categories; if this happens, choose the level that represents your team most of the time.

As you score yourselves, note why you chose that level. This can help you decide which areas to prioritize and later on, shape your learning experience.

3. Identify which competencies to prioritize

Depending on your broader objectives, there may be critical data readiness competencies needed for your team to be successful. Review your results and objectives to identify which areas to prioritize.

This stage takes a bit more thought and creativity — which competencies are key to the success of your program or department? Where is there the most room for improvement? In additional, you may want to consider your National Society's strategic priorities, funding opportunities, and any time constraints.

Plan your learning experience

Set your goals

Now that you’ve considered your priorities from both a programmatic and diagnostic perspective, the next phase is to plan your learning experience. To do so, consider your audience, prioritized competencies, and minimum standards you want to achieve.

Review the learning objectives

Under each competency are several sub-competencies and indicators. These may can be considered the “learning objectives” as you create your road map. To move up in your competency rating, all sub-competencies should be considered.

Write your curriculum

The next step is to consider how your team will learn and practice the competencies. You will need to consider a number of factors (time, number of people, synchronous vs. asynchronous learning, remote vs. in-class sessions, etc.) to plan how your team will learn. In particular, consider, which resources, teaching tools, activities, and assessments you will need.

Find the resources you need

There are plenty of existing resources across all data readiness competencies. As a starting point, the toolkit has identified resources from the IFRC, National Societies, and external organizations to help you get started. Take a look on the resources tab of the framework and a complementary toolkit, the Data Playbook.