This is our third and final post in this series. We believe outcome statements should be meaningful, measurable, and manageable, and we recommend that organizations evaluate their outcomes against those criteria in that order, because each serves as a more narrow filter than the one before. The universe of meaningful outcomes is big, complex, abstract, and ill-defined. The subset of those meaningful outcomes that can be made measurable with available research, tools, and resources is much smaller. Lastly, the subset of meaningful and measurable outcomes that your organization can measure in manageable ways with the technology, workflows, and staff capacity that you have is smaller still. In this post, we’re going to focus on the last criteria in our list – manageability.
Making Measurement Manageable
The IllumiLab recommends a few tried and true strategies for making measurement manageable.
- Design a measurement plan that is uniquely suited to your needs. There is no one-size-fits-all approach to outcome measurement. Not everything has to be measured with a survey or standardized assessment, or as a pre-test and post-test (check out this alternative). Familiarize yourself with different data collection strategies and choose the ones that best suit your data needs and your context.
- Integrate your measurement into existing workflows and tools. If your measurement plan requires a separate, extra set of forms or steps, it will feel like (and be!) a burden, which your team will resent. Instead, look for ways to collect the data you need in the course of delivering services. For example, add a couple questions onto an existing form or include the survey in the enrollment packet. Not only does this increase efficiency by reducing duplicate data entry and effort, but it also bakes evaluation into everyday practice. This builds your team’s evaluative capacity. (Think of it like sneaking zucchini into your kids’ blueberry muffins or putting kale in your smoothie!)
- Aim to make your data multi-purpose. When designing your measurement strategies, see how many birds you can kill with one stone (so to speak. No actual birds should be harmed in your evaluation efforts!). Aim to align your promises across multiple funders. It drives me up a wall when I see organizations have different sets of outcomes for each funder! Also, think about what data might satisfy your funders’ accountability needs while also supplying you with data you need to learn, improve, and make decisions.
- Consider your technology and tools. I am guilty of this mistake myself, so I have to warn you, too. When designing your measurement strategies, you must consider the data collection and management tools you have. How customizable and sophisticated are they? Is it very difficult or expensive to make changes to them? Can they capture the kind of data you’re considering? Can they aggregate, compare, analyze, and report the data in the way you’re imagining?
Why Manageability Matters
The expectation that meaningful outcomes be measured in manageable ways may seem like a bit of a buzzkill, but it is as essential as the first two criteria. Here’s why. If the process of gathering, analyzing, and using data related to your oh-so-meaningful and clearly measurable outcomes is at all redundant, inefficient, or burdensome – that is, if your plan is not manageable – your data will never be complete, accurate, or timely enough to be meaningful.