(Chapter 1 of 5)
Welcome to the first in a series of five posts on taking a new approach to thinking about nonprofit capacity building. Capacity building is an investment in the effectiveness and future sustainability of a nonprofit. The funding landscape is in total disruption, therefore, it is crucial for nonprofit leaders to think about novel techniques and processes in order for their missions to compete and thrive.
If you’re a nonprofit working on capacity building strategies, you know how difficult it is to grow effectiveness and be more efficient in key areas such as communications strategy, volunteer recruitment, leadership succession, technology implementation, measuring outcomes — ultimately being continuously better at delivering on your mission. You need to bring your mission to the next level of maturity so it can survive into the future, but too often the cards are stacked against you. Under-funded, under-staffed, under stress from an increasingly crowded and noisy nonprofit landscape.
While I offer no silver bullets, you might do well to take a page out of Uber’s playbook. Certainly, most of us have opinions about some of the technology-driven transformation our society is experiencing — seemingly at light speed. But there’s no denying that companies like Amazon, Netflix, and Uber are altering traditional industries and delivering services at costs that are orders of magnitude more efficient than the old-school incumbents. And the scary thing is, they are continuously getting better at it.
You see, companies like Uber leverage their own mundane, operational data to continuously improve efficiency and customer value. They have created closed-loop feedback mechanisms which not only inform decisions by team members, but improve their services in near real time as well.
For example, Uber can use real-time data in a given city to optimize operations to match supply with demand — all while pricing appropriately for the micro-market that exists in a given area at a given time of day. Better value for the customer. Better outcomes for the company.
However, most nonprofits are not technology companies. How can you expect to relate to — let alone take a page from these Silicon Valley tech firms to improve your own outcomes and capacity? Believe it or not, there are lessons that can be applied to your own efforts without having to hire top-shelf data scientists and without purchasing bank-breaking software. Once applied, you’ll have the opportunity to transform your mission for the better — now and into the future.
Our goal here is to help you create a closed-loop, data-driven feedback system for your nonprofit operation.
In this series, we’ll take a look at five action items that help set you on a path of transforming the business model of your mission into becoming a continuously improving value delivery engine. These include:
1. Understanding what data you should capture (today’s post) — Helping you to think differently about what data you should be collecting in the daily course of operations.
2. Having a good way to capture and store the data — Learning about the mission-critical importance of swallowing that big horse pill called “consolidation” when it comes to data storage — and taking a look at democratizing data collection in everyday processes.
3. Accessing and digesting the data — What’s the point if you can’t leverage the data? We’re not really talking about 1990’s-era reporting, but about leveraging data as feedback for continuous improvement in real time.
4. Creating a “feedback loop” culture — We’ll look at the three critical components of a holistic process evident in those organizations who have a good “feedback loop” culture.
5. Questioning everything — including your entire mission model based on the closed-loop feedback you’ll be getting.
Ready? Let’s get started with today’s topic, understanding what data you should capture.
When you think about Uber and what’s going on there that enables them to transform the way the industry helps a person gets a basic job done, i.e. getting from point A to point B in the city, you have to understand that it’s all about the data.
1. Understand what data you should capture.
Of course, Uber knows which data matter to them — demand (riders), supply (drivers), drive-times, etc. You, too, should consider what data matters to your operation. It may not always be what you first think of, i.e. meals served, or children attended, or shots given. These are important, but they are outcomes — a grade card on your current capacity.
You should also think about the data that can give you grade cards on mundane, operational activities and assets — data that can even suggest micro improvements which, over time, noticeably and continuously increase capacity and value. Here are some examples of the kinds of data that can be golden to a nonprofit operation:
This is the data generated by the work-a-day business you and the team are conducting with each other, board members, committees, volunteers, community partners, government officials, grant makers, etc. Not so much about marketing and donor engagement (important), but about literally everything else.
- Emails opened by person, by committee, by hub or group, by type, etc.
- Shared files opened by person, by committee, etc.
- Replies to emails or messages
- Files uploaded
- Tasks or action-items volunteered
- RSVPs for events or meetings
- Published content or reports opened
- Website visits
- Donations pledged
This is data generated when people take direct action or follow through based on prior commitments or calls-to-action.
- Attendance at events or meeting
- Tasks or action-items completed
- Introductions to new, important connections completed
- New or repeat donations delivered
This is data generated by your mission. You are hopefully already tracking this, but just in case.
- Meals served
- Patients seen
- Rides given
- Beds filled
- Jobs placed
Why is this mundane data so important? Because you can’t improve at the macro level if you can’t improve at the micro level. Most nonprofits are “data driven” for evaluation and reporting, as many funders require it, and it is becoming an increasingly common requirement from funders. The next level of “data-driven” means using data for continuous improvement, which will put you in a better position to be attractive to funders that are requiring better outcomes per funded dollar.
One way to think about your organization is as an aspiring athlete who is training to win the Boston Marathon. The athlete is a multicellular, complex organism with countless attributes and working parts. You can’t ask them to go straight from simply being able to jog for 20 minutes a day, to running competitively at peak performance for 3+ hours straight. There’s a journey. A process that involves a plethora of little, mundane items that must be monitored and continuously improved — from diet to physical strength to mental clarity and fortitude.
Think of your organization as a multicellular, complex organism. In order to improve the whole, you must understand and address what’s going on at the cellular level. The ultimate goal is to train your organization using continuous feedback from the mundane data (cellular) to iteratively improve everything you do and perform at the highest level.
In the next chapter, we’ll address helping you find ways to capture and store this so-called mundane data by consolidating storage and democratizing data collection.
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