Full Report PDF & Overview: Using Data to Power Scale

Find the full PDF report of “Scaling Pathways: Using Data to Power Scale” here.

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Drawing on the perspectives and experience of some of the world’s leading social enterprises, these articles lay out key strategies and advice on how to use data to more effectively and efficiently scale impact. Our interviewees’ advice was three-fold: 1) to lay the foundation for data efforts by carefully considering equity and client voice; 2) to set the data building blocks — the how, what, and who of data — that will be critical for driving scale; and, with all that in place, 3) to pursue more advanced data approaches that align with the specific scaling strategies that you are pursuing.

Organizations and funders always want to go for the new shiny tools. But my advice would be: don’t start the conversation focused on machine learning and artificial intelligence. Instead, start by asking ‘what is the question that we want to answer?’ Then determine what data you have and what the right methodology and tools are to move us toward an answer. — Sharmi Surianarain, Chief Impact Officer, Harambee Youth Employment Accelerator

1. Lay the Foundation

Ensuring data efforts drive toward equity and inclusion.
In order to unlock the potential of data to scale impact, your approach must be grounded in equity, ensuring that all stakeholders have a voice and that you are not scaling bias as you go. This means engaging stakeholders in determining what gets measured, identifying biases in how data is collected, and empowering diverse stakeholders to access, interpret, and act on the data.

2. Set the Building Blocks

Answering the how, what, and who of data for scale.
Once the equitable foundation is laid, there are critical building blocks — the how, what, and who of data — that will power your drive to impact at scale. These two-page memos will give you the top tips to get it right:

1. Create a learning culture as you scale. The road to scale is rarely linear, therefore, enterprises must create a learning culture that uses data to adapt along the way. This means shifting the purpose of data from accountability to learning; routinely interrogating findings; ensuring “bad data” is learned from (and not disincentivized); and, embracing data-driven experimentation.
2. Decide what data to collect to drive action. The wrong data can stifle a leader’s abilities to make decisions — or worse, lead to poor decisions. Therefore, prioritize a limited number of key performance indicators; monitor the tension between impact, cost, and reach; collect quantitative and qualitative data; and identify data that will drive scaling decisions — not merely satisfy funders.
3. Determine how to collect data with scale in mind. More manual or resource-intensive data collection may work well in early stages but will be inefficient as the work scales. Scalable data collection finds the balance of being simple and repeatable while still equitable. This approach often means leveraging technology or other partners to make data collection more efficient.
4. Build data infrastructure to bolster scale. Data infrastructure — particularly the systems that store and communicate data, ranging from excel files to enterprise-wide data systems — can help manage data for scale. Building data infrastructure for scale means starting scrappy while also considering future needs; seeking out dedicated capital; creating platforms that go beyond one organization’s needs; and ensuring data privacy and security.
5. Engage the right people to support data goals. Data is only as good as the people that collect, analyze, and maintain it. Deep and broad people strategies may be required (e.g., hiring technical experts and people with experience in different methods to dive deep in to data), while also integrating data broadly across the organization through ongoing trainings and open dialogue.

3. Power Scale

Using data to drive specific scaling strategies.
With the foundation and building blocks in place, more advanced data approaches can be layered on. Depending on the scaling strategy you are pursuing, consider the following approaches. Each memo includes a framework to follow as you use these approaches to superpower your scaling strategy:

1. As You Grow: Activate data use at all levels. As organizations grow, the number of people that can (and should) collect, analyze, and use data increases. Empower these users by designing processes that provide the right data at the right time, often facilitated by technology; incentivizing data collection and communication through tailored dashboards; and ensuring users are equipped to take action (often through regular trainings and automation).
2. As You Partner: Adapt your approach to data. Achieving impact at scale often involves various types of partnership, all of which will inevitably diminish the level of control over what data is collected and how it is collected. Therefore, approaches to data must adapt for partnerships: working to set a shared intention for data learning and improvement; aligning on what to collect and how; and promoting streamlining and simplicity in shared data efforts.
3. As You Drive to Systems Change: Shift your conceptions of data. Systems change efforts require a different data approach. Track data related to critical systems change levers, such as FSG’s Six Conditions for Systems Change: policies, practices, resource flows, relationships, power dynamics, and mental models. How that data is measured must also change: prioritizing contribution over attribution; being bold in selecting long-term measures; working with and through partners; and going beyond counting to identify meaningful outcomes.
4. As You Have More Data Available: Consider advanced data methods like machine learning. Machine learning can be a powerful tool, but first determine if it is the right tool for the problem. If so, you must have some high quality outcome and reliable predictor data in place. From there, make sure algorithms are not set up to perpetuate inequity and the right people are in place to drive success.

Within each of the sections outlined above, the social enterprises we interviewed share tactics and tips they have applied in their work — or learned through the wisdom of hindsight.

Read next: Ensure Data Efforts Drive Toward Equity and Inclusion, Create a Learning Culture as you Scale, or return to see all articles in Data for Scale. You can find the full PDF report of Using Data to Power Scale here.

This article was written by Erin Worsham, Kimberly Langsam, and Ellen Martin, and released in June 2020.