We've covered a lot of ground in this module. I hope that what you take away from this module is that measuring impact is important and useful. The most rigorous assessments, those establishing causality, that's level four, and establishing replicability, that is level five, are especially time consuming and costly. But rigorous assessments like these provide the clearest and best evidence that your business or organization has real and scalable impact. Still, you can learn a lot from less rigorous and therefore less costly ways of measuring impact. You learn a lot by thinking through and writing down your logic model, that's level one. You learn a lot by examining your output data, that's level two. While output can't tell you whether you're producing the outcomes and impact you hope, output data is helpful in knowing the scope of your activities, and unless you have outputs, well, you really can't have outcomes and impact. You learn a lot by looking at outcomes over time, that's level three. And maybe you are usinga lean data strategy to tap in to your customer's or client's perceptions and experiences. That's great for learning about your possible outcomes and your impact. You can't make causal claims from that kind of data, but still, you get a lot of insight. Of course, level four, randomized control trials, and level five, replication, give you the greatest rigor. When your organization or business is the focus of rigorous examination like this, you gain a deep, deep knowledge of your impact, and we hope the data, the impact evidence, to fuel the growth of your business or organization, and the scaling of your social and environmental impact. And last but not least, SROI, social return on investment. I've called this level q to emphasize that the rigor of this assessment, this analysis, is a question mark. It depends on the rigor of the data that you use that feeds into your SROI analysis. Still, the process of calculating SROI gives you tremendous insight into the costs and benefits of your activities. What are the social or environmental returns, the benefits in dollar terms, for every dollar you spend in creating impact? How is your social return on an investment changing over time? How can you get even stronger returns for your inputs? My bottom line for those of you leading or working in purpose-driven organizations is measure something. Get started, write out your logic model, consult with your many stakeholders about the outcomes they experience from your operations, your products and services. Track your outputs and get as much insight into your outcomes and impact as possible. For those of you who are donating to or investing in or even shopping at purpose driven businesses and other organizations, ask about their logic model. Be appropriately wary of broad claims and no data. When you hear about outputs, products sold, customers served, ask about outcomes and impact. Your questions will improve the organization's effectiveness and your own thoughtfulness in donating and investing or simply shopping. So, assessing one company or organizations impact is hard and it's a detailed process, as we've explored. Comparing different organizations impact is really hard, especially when they have very different business models and impact targets. Certainly, I'd be quite wary of comparing the social return on investment of organizations and businesses pursuing different strategies and different kinds of impact. Impact measurement is a work in process. The non-profit sector is more advanced, or at least more experienced in many ways, in measuring social impact than the for-profit sector. So impact investors are exploring how best to assess impact and quantify impact as they pursue financial returns alongside social and environmental impact. So, many impact investors are focused on outputs, products sold, customers served. When we know the impact of our products and services, when we know energy saved by using our products, for example, then we have a clear line of sight from outputs to outcomes. But often we don't, we don't know how much impact are products and services have. So as the field evolves, as impact measurement evolves, as impact investing evolves, we will have more and better impact measurement, and that will help impact investors achieve the financial returns and the impact gains that they seek. So I'm looking forward to the next five or ten years to see how impact measurement strategies involve. For example, we'll see more and more use of information technologies, I'm sure. Things like machine learning as well. So I'm looking forward to what comes, and how we get better at measuring impact. And all that said, I'm betting that the logic model is here to stay, that output data will always be easier to collect than outcome data, that randomized control trials will remain the best strategy to establish causality, and that impact measurement will help leaders, employees, donors, investors, and even shoppers make smarter choices and achieve the impact they seek. So I wish you good luck in measuring impact and making impact. Thanks for listening.