Could you benefit from a free data audit?

No longer can anyone use the excuse that it’s “too hard” or “too expensive” to refrain from collecting the kind of feedback that you will actually use to improve performance.

We built the Feedback Commons to provide a platform that any organization could use to collect, analyze, and respond to feedback from the people they work with at low cost, and with minimal effort. It’s free and simple. Anyone can design a survey – using questions that others have used before, and we will collect the feedback data for you. We can then analyze the data and provide benchmark scores to you, that you can then use to operationalize and plan corrective action.

We help you send it out over several channels and provide analysis tools to make sense of the responses. But there’s another way Keystone Accountability can help that you may not have known about – free data auditing. The same technology Keystone created to merge surveys and data sets to build sector benchmarks can also be used to compare your data with the data others have collected.

This is how it works. First, you send us a survey you’ve used in the past. We’ll extract the questions and run them through a system that compares each question with the thousands that others have asked. Then we’ll send you a report showing which of your questions are close enough to other questions allowing you to compare your results with the benchmark on our platform. Many organizations don’t realize they already have data that can reveal more insights, but only when contrasted with external data on the commons.

‘Likert’ and scaled questions tend to be the easiest to merge. We use a 0-10 scale for all our surveys, but if you’re using a 1-7 or 1-5 or even multiple-choice answers along a spectrum, they can all be converted. Our question bank mainly consists of questions about a person’s perception of impact, and about attitudes and feelings. If a project is going poorly, these answers tend to be similar regardless of the exact wording of the question, so long as it is close.

A data audit is less about quantitative rigor because we’re helping organizations get a real world perspective here. Are they doing better or worse than others doing similar work? We’re not trying to prove that a dollar spent in some way yields a 14 percent increase in some outcome using self-reported data. But people are great at self-reporting their feelings. In fact, they’re the only ones who can judge their work from their perspective.

Our purpose here is to illustrate that organizations are not so far apart in their approach to feedback. It also reveals how slight changes to your approach could unlock deep insights and establish what “good performance” is for your organization. This would shift you from defining success as “impact” – which you ultimately don’t control and cannot manage – to “performance” – defined by what’s feasible to accomplish, given your current resources and time frame.

Framing an organization’s success as “we accomplished what we could”, better than our peers did, liberates us from the mindset that anything less than saving the world is success. It also helps us refine how we work to do more with less, and how we can do it better.

That’s what we do, and why we think it matters. Our world is ready to take a step forward in listening and responding to the people who matter most – beneficiaries. Isn’t it time you let us take a hard look at your past data, to see if there’s insight to be gained from benchmarking it?

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