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First steps with program data toolbox

3.1 The scope of Information Management for NGOs


3.1.1 What exactly is Information Management?

Information Management (IM) in the humanitarian and development sector relates to the processes that use data to promote evidence-based decisions. IM includes all stages of the ‘data management cycle’, which effectively outlines the processes required to produce and use data for NGO programs (as seen below). Therefore, IM can also be called ‘program data management’, and strong IM systems facilitate improved activity outcomes for beneficiaries.

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As seen in the diagram, IM for NGO programming requires a breadth of steps. To summarize:

  • First, it must be determined what program data is needed for programs in terms of both outputs and outcomes, similar to with monitoring and evaluation.
  • Then, IM includes the process of planning how to collect this data, as well as the subsequent data collection (including using different Mobile Data Collection tools).
  • Once data is collected, it must be processed in a way that ensures data quality (data cleaning and validating).
  • Using a breadth of possible software solutions, data can then be analyzed through a variety of techniques to determine the progress made in projects, including in terms of outputs and outcomes.
  • Findings from analysis must be shared to promote evidence-based decisions based on knowledge produced through data. Findings should also be shared with beneficiaries for grounding the conclusions in feedback from the communities in which we work.

Thanks to technological development during the last decade, there are many digital technologies available that can offer very cost-effective solutions for big and small organizations in the sector. Examples include technology for mobile data collection (MDC), database creation/management, data analysis, and business intelligence (such as through developing dashboards).

3.1.2 What things do I need to keep in mind when I’m starting a project in relation to data?

Information Management (IM) systems are needed to manage program data, while also providing the opportunity to adapt program activities to better suit the needs of beneficiaries. IM allows for program approaches that can be adapted through feedback loops resulting from timely and quality program data. Further, IM systems are needed to provide information needed in accordance with the reporting requirements for your programs.

Managing data through IM systems is linked to the project monitoring and evaluation (M&E); M&E stipulates what information is needed, but IM includes the ways in which teams interact with the data (collect, store, analyze, etc.). For M&E to be effective, program data management systems (IM) need to be in place, regularly updated, and accessible.

When starting a project, keep in mind the basic data needs for both external reporting and internal uses. Reflect on the objectives of what you want to achieve through data collection and analysis, allocating only the resources needed to achieving them. For example, in humanitarian programming, data collection tools should be designed only in relation to data that will be used by the operational teams. Questions posed should also be coherent with the indicators put forward in the project’s logical framework. Data collection should only be conducted when connected directly to activities.

If possible, indicators and questions should be standardized within the program (and the organization) to allow for comparison of outcomes; only through doing so can we compare outputs and outcomes before and after activities, or across different types of support or geographies.

Most importantly, it is essential to make sure that the people involved in your team understand why and how the IM systems will operate so you can ensure that your program data is used to its potential. Program teams need to understand what information is needed to influence their activities (and how it can be used).

Dashboards are an example of an accessible tool for fields teams that can promote reflection on results, thereby also increasing ownership and promoting reflection through their use in coordination meetings.

For more details on dashboards, please see the question below, “3.4.3 Automatic dashboards updated in real time: what are the first steps to know?”.

3.1.3 What’s the difference between IM and program data management?

CartONG uses the terms Information Management (IM) and program data management interchangeably. Program data management is not widely used in the development or humanitarian sectors, but if used interchangeably as IM, it allows us to understand more easily what is included in and meant by IM (that can otherwise be understood as a much broader notion).

Data management refers to the full range of processes, methodologies and tools needed at various stages of data analysis (collection to analysis to decision making). Program data refers to all operational data related to population needs, project implementation, and M&E related field activities.

3.1.4 What’s the difference between IM and Monitoring & Evaluation?

IM and M&E have the same purpose: to help operational teams achieve the best possible data quality for appropriate decision-making that ensures the smooth functioning of a project (steering, learning, and accountability). M&E focuses on supporting continuous and ad hoc measurement of changes to which the programmes contribute. However, IM focuses more on processes, such as the organization of data processing procedures through the use of specific IT tools and methodologies.

Thus, IM and M&E are complementary: for example, both IM and M&E are required to design a comprehensive survey. As such, many organizations consider IM and M&E within the same realm and do not clearly distinguish the terms and/or roles- which can be problematic, as the two require very different skill sets.

3.1.5 What’s the difference between IM and IT?

IM relies on IT infrastructures and services (networks, security systems, services, media, software, etc.). Managing IT services requires a very different skillset to IM.

Basic skills required for management of IT systems are often already present in organizations, or can easily be hired externally. As such, it is possible for organizations to opt for a few – rather easy to implement – IM solutions that require little to no added investment. However, when IM gets more complex, IT infrastructure would have to adapt to meet the new requirements. In this circumstance, making the right choice in terms of IT infrastructure will require a structured approach, often requiring hiring experts alongside additional financial and human resources dedicated to IT/IM.

3.1.6 What’s the difference between IM and ICT4D?

According to ICTWorks, a community dedicated to the topic, ICT4D (Information Communication Technology for Development) can be defined as “the use of digital solutions to magnify the intent of communities to accelerate their social and economic development”. To add to that in the words of CRS, it concerns “information and communications technology used during interactions with - or directly by - beneficiaries, with the technology helping to manage key information relating to those interactions” (further information found here and here).

As such, ICT4D is geared towards external users, whereas IM is limited to the internal scope of the organization. ICT4D is a broader term where the digital solutions can also be the project activities, whereas IM focuses purely on data management for improved internal processes.

3.1.7 Who’s responsible for Information Management within my mission / organization?

Firstly, we can mention that this is very rarely formalized, except in bigger organizations. However, almost all organizations are already conducting some form of information management, such as project managers receiving feedback from field teams or field teams enacting instructions from management with regards to distributions. As such, IM is not just the realm of M&E and/or IT teams, but all staff should have some competencies allowing them to interact with program data (see discussions of the difference between IM and M&E/IT above). Addressing or improving IM is often based on formalizing and improving already existing processes. For example, program managers need to be able to read, work, analyze and use data to a certain extent to make evidence-based decisions.

Effective IM systems, therefore, require a wider perspective on data literacy within the organization (see CartONG’s blog posts on the topic, here).

CartONG has produced a HR Pack focused on the staffing requirements in relation to data literacy for different responsibilities and levels of positions within NGOs (‘Program data management for humanitarian aid and international development CSOs’, found here). Focusing on data literacy needs, the HR pack provides support in relation to how to structure an internal review, identify training needs, launch a recruitment, or even strengthen an organizational strategy.