3.2 Building organizational capacity in Information Management

TABLE OF CONTENTS

• 3.2.1 My organization is undergoing a digital transformation: what about program data in all that?
• 3.2.2 What are the benefits to investing our resources towards improving IM?

3.2.1 My organization is undergoing a digital transformation: what about program data in all that?

More precisely, what are the key things to keep in mind through this process with regards to our program data?

According to the ICRC, Digital Transformation can be defined as follows:

“Digital transformation is a disruptive or incremental shift that allows us … to pursue new ways of humanitarian assistance by transforming current practices and developing new digital humanitarian services. Utilizing data analytics digital technology – deployed by confident professionals, in service of people in need, and handling data responsibly – can improve relevance, speed, quality, reach, accessibility, resilience, and sustainability of services” (ICRC 2021, pp. 6).

Inherent in the definition are the key principles of staff capacity (“deployed by confident professionals”) with the objective of improving program outcomes (“in service of people in need”), and under careful observation of data protection (“handling data responsibly”).

Digital transformation requires systemic changes at all levels of the organization. However, digital transformation is not only a ‘top-down’ approach, but also allows organizations to be more in line with the context and needs of beneficiaries through enabling regular feedback loops of data and information. Effective digital transformation favors solutions that are managed and promoted by field staff in line with the context in which they work (local adaptation) in order to be the most impactful and sustainable. ‘Data that is used locally’ should be a primary concern of IM; local ownership and feedback to communities can greatly contribute to overall program quality.

With these key principles in mind, digital transformation requires planning for systems to be put in place in relation to all stages of the data management cycle (see diagram in response to the question, ‘What exactly is information management?’). The first step of digital transformation is to set up the fundamentals, including the availability of basic IT infrastructure, digital applications and network systems, and skills training. Further steps are then to use these systems to improve effectiveness in humanitarian services.

Finally, it’s worth keeping in mind that digital transformation is “as much about people and culture as about leveraging data and technology” (ICRC 2021, pp. 7). Digital transformation cannot happen without staff experienced in managing the technology, and without a culture that promotes organizational change through adapting to using the new solutions.

3.2.2 What are the benefits to investing our resources towards improving IM?

There are multiple benefits to investing time and resources into improving Information Management within our organization. First and foremost, strong IM systems provide program data to operational teams with improved relevance, speed, quality and accessibility; data can then be used as the basis for feedback loops to subsequently improve programming. In sum, improved IM can have a positive impact on the program outcomes for beneficiaries.

Additionally, strong IM systems allow for accurate and timely reporting. As such, investing in IM not only has the power to improve program outcomes, but also saves time on resource heavy reporting requirements, which can sometimes take time away from resources being focused on program activities.

Mobile data collection (MDC) is an example of a time saving IM exercise that can also improve data, and therefore service provision. Whereas before local teams would face a number of issues associated with collecting data on paper and entering it correctly into higher level reporting, the use of MDC can remove a significant human resource burden. As such, investment in MDC can make the process of collecting, aggregating, cleaning data and analyzing data much easier and less time intensive (see more detail on this here).