Harnessing the Power of Financial Data


Harnessing the Power of Financial Data

By Erin Byrne

Officer, Research, Evaluation & Learning Unit IRC

Getting to Cost-Informed Decision Making

I remember, as a teenager, sitting in the passenger seat of our family Chevy Caprice, struggling to navigate road trips using a foldout map that stretched wider than my arm span. Unsurprisingly, this resulted in many wrong turns, or worse, getting stuck in traffic because the “shortest route” turned out to be anything but.

Today’s teenagers don’t face the same struggles. Google Maps has made the old family arguments over which route to take redundant. Instead, access to data made available by an app guides us more efficiently to our destination.

I work in the humanitarian sector, where worldwide conflicts have caused refugees to flee conflict in unprecedented numbers, resulting in immense strain on humanitarian resources.  The key to meeting this widespread need is not just more resources, but also more efficient and effective use of existing resources.

Thankfully, technology can play a major role in helping humanitarian organizations do just that. Just as GPS technology improves the accuracy and accessibility of location data, tools that improve accessibility and accuracy of cost information can help us better navigate the path toward achieving our humanitarian goals.

During a recent trip to Pakistan, I worked with members of the International Rescue Committee’s (IRC) country team to pilot a new application that provided insight as to how resources were being used. In the past, the time and expertise it took staff to generate data for answering cost questions was prohibitively high. But instead of weeks or months, it now can be generated in a matter of hours using the Systematic Cost Analysis (SCAN) Tool.

SCAN allows users to estimate cost per output by answering a series of simple questions about their expense reports. It then presents results on a dashboard that staff can use to identify cost drivers and compare across programs. The tool draws on existing financial data and allows users with all levels of expertise to generate and reflect on cost data.

Just as modern drivers use GoogleMaps, the Pakistan team used this application to identify current resource use and course correct. Combining finance and monitoring data to look at the cost per person served helped explore key questions related to implementation: How should we select our partners, activities, and locations of operation to help as many people as possible? Were any costs observed in the first phase of the project higher than expected? Can we adjust the scale of the program so it becomes more resource efficient?

This creation and use of cost per output data is a major step forward in the humanitarian space. For the most part, non-profits do not routinely gather evidence on the costs their projects in relation to outputs (cost efficiency) and outcomes (cost effectiveness) because it is time consuming and difficult. When it is done, it is usually in response to donor requests. This is a missed opportunity, because this sort of cost analysis has the power to be transformative: using resources more efficiently and effectively allows non-profits to help more people in distress.

So how do non-profits make the shift from reactively answering donor questions about cost to proactively generating and using cost data insightfully as an organization? Technological innovations like SCAN that automate our access to cost data play a major role. But data is only as important as what we learn from it; it is the routine use of cost information to shape our decision-making processes for the better that will make tools like SCAN game changing.

Another example from Pakistan demonstrates how cost data can be used to inform decisions. Cash assistance is one of the fastest growing methods for assisting people affected by crisis, thus designing cash interventions to be cost effective is important. But past analysis shows that the cost per dollar delivered to beneficiaries can vary widely across projects.

So in 2016, our economic recovery team in Pakistan tackled this question by piloting two different approaches to see which delivered cash with the lowest operational costs, fastest response time, and highest client satisfaction. One strategy identified recipients using a community-based targeting strategy, while the other used a pre-positioned database to identify vulnerable households. While both methods were comparable in cost for a small-scale pilot population, the analysis showed how the pre-positioned data is likely to be significantly lower cost at large scale.

As we’ve seen in Pakistan, harnessing the power of existing financial data to generate cost evidence provides valuable insight for making programmatic decisions. Eventually, we will be able to interpret and compare cost data across the humanitarian sector. This will enable us to answer questions such as: Is this cost too high for my context and sector? What program components are driving my results? Are costs dictated by external factors such as high security needs or long travel distances?

To answer these questions systematically, collaboration by humanitarian actors is essential. Through events such as the Cross-Operational Roundtable recently hosted by Humentum, tools such as SCAN are being shared across organizations. As other actors being using SCAN, the quality and quantity of cost evidence available will skyrocket.

Just as applications like Google maps revolutionized how we get about, technology can greatly improve the way humanitarian organizations deliver aid. But such applications are not sufficient in themselves: true innovation will be when the cost data created by tools such as SCAN is systematically considered in the design, implementation, course correction, and scaling of programs. 

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