[MUSIC] Once you've decided what to measure. The next step is getting your tools and processes into place. So that SDG impact measurement and management is truly integrated into your operations. Our checklist for integration has three parts. Create your SDG data collection plan. Choose a data management system. And assign roles and align incentives among your team for continuous decision making. We recommend that if you're starting from scratch, you develop a first year operational plan that you can improve and revise in future years. If you already have an impact data collection process, your plan can describe what you're adding and testing this year. First, create your SDG data collection plan. Once you know what data you want to collect, you need to figure out how to collect it. This is a big part of the process and there are a number of things your team will want to discuss, such as, what method will we use to bring in SDG related data? Consider your data needs for each SDG outcome separately, paper surveys, interviews, text messages, sales receipts. There are a lot of ways you could collect data which are the most efficient and reliable. If surveying, what is your target response rate? The impact management project peport, using self reported data for impact measurement, discusses the strengths and weaknesses of stakeholder surveys and is listed as an additional resource. Can collecting this data be added to an existing process or do you need to create a new process? For example, data about how well a product functions for customers after sales could be integrated into a customer support process. User demographic data could be integrated into a warranty, application or registration process, wherein the firm's operations might this best fit? Can you collect the data yourselves or do you need the neutrality of a 3rd party? Consider this carefully for deeper who data at the stakeholder level and for all of your C-level outcomes where you might want 3rd party validation or peer benchmarking of your contribution. How much SDG impact data is enough? You identified in the last lesson the five dimensions of data that are possible to collect for each SDG outcome. Now, consider on what frequency you could collect data for each metric. Will you sample everyone or use representative samples? Are there other ways to lower costs but maintain credibility? How will you design for disaggregation of data, such as, by income, sex, age, ethnicity, geography or other factors relevant to your impact goals to align with standards like the fundamental principles of official statistics. Or to get more granular with what you're learning. How do we ensure data is high quality and free from bias? How will you assess risks associated with the resources, methods and limitations of your data collection process? How will you actively combat racial or power bias in data collection, storage, analysis and use? For more on this, C-cases scaling pathways guide to ensure data efforts drive toward Equity and Inclusion. Which stakeholders do we need to engage? Are there stakeholders you need information from but do not have direct contact with? How could you get to them directly or indirectly? Do you have effective processes for sharing data back with the stakeholders who are most affected? Internally, how do you efficiently get data to the people making decisions about it? Do you have funder or customer stakeholders asking for certain kinds of data as well? Agree with them on the hypotheses you're testing and the trade offs are making and why? As you develop plans to address these issues, keep some fundamental questions in mind. Does the data collection process you're planning align with the importance of the decisions that need to be made with that data? Are you starting to hear more about lessons learned by the teams who have made the most influence on outcomes? Have you created a strong culture of impact iteration and learning? Second, choose the right data systems. You want your data to be longitudinal, analyzable, actionable, comparable, and shareable. You want the impact measurement you do to be easily transferred to others as your team changes. So you want to consider the best data platform for your needs. There are many third party platforms for impact data collection. Some are listed here and we have links to each in the lessons resources. Using a platform like one of these may save you time and may make rolling up information easier. A potential drawback is that they are not necessarily tailored to the specific impact questions your enterprise is asking. In our experience, most organizations start with a spreadsheet or online database for data management. After working with a customized system for a few years, they may work to find ways to make it more automated or standardized. Some may do this alongside a platform that provides industry wide benchmarks for comparison, such as the B Impact Assessment. Our SDG outcomes map is a tool you can start with and customize to your needs. Regardless of the data system, you need to determine your data privacy and security needs. How will you adhere to company, national and international privacy and human rights standards around data gathering use and disclosure. Consider permissions, access policies, how you'll back up your data, keep it secure, etcetera. Third, assigned roles and align incentives among your team. As you determine the ways in which you'll bring in data, you need to allocate internal resources, assign responsibility and align incentives for this work. How do you assess skills and knowledge? Different organizations come to this work with different levels of familiarity and sophistication. One way to motivate your team to get ready to implement the plan is to let them assess the capacity needed to carry it out. In a toolkit produced by the Social Policy Evaluation and Research Unit of the New Zealand government called, getting your organization ready to do evaluations. Authors recommend having a discussion with key personnel and focusing on participants perceptions of the organization's current level of evaluation capacity. Then you can figure out what would be a realistic development goal for the organization for the next 1-2 years. This resource includes a very detailed checklist for staff capacity assessment. Which roles could be assigned? Taking on SDG related impact data management may require specialist expertise and you may need to hire or engage with others to fill gaps. At minimum, your team members may need additional training to develop their skills. Here are some of the key impact management functions you may consider. Data infrastructure, defining the most important goals in hypotheses of the data collection process for each SDG outcome and getting collection mechanisms in place. Data gathering, ensuring the data prioritized in the management systems is reliably and accurately gathered, managing costs and processes as things evolve. Interpretation and analysis, making sense of the data coming in and packaging insights and resulting new questions at the right time and in the right way for others to review and use in decision making. Resource allocation, deciding what intellectual human or financial capital will be applied to address the decision at hand. And line management, implementing the new actions and updating ongoing data collection processes to align with them. How do you develop milestones and align incentives? Well, you determine as a group are in your work teams, how the implementation plan can become a reality, identify action milestones, timeframes, and resources. You can also incorporate SDG impact management responsibilities into job descriptions, as well as key performance indicators. To recognize the importance of this work, consider how staff at different levels can be incentivized to support your SDG impact plan, such as through bonus or other incentive pay for impact milestones achieved and opportunities to collaborate a network with other groups across the firm. Here's an example of putting all these steps together. Grace's clinic chain has started to combine patient intake, patient treatment, and patient outtake data to create a full picture of the end-to-end experience and results for her pregnant mother customers. Previously, all of these were managed by separate groups and they had no way of tracking an individual patient to see if different prenatal treatments actually lead to better outcomes at or after birth. Her team adopted an off the shelf health data platform which tracks patients through all of their touch points with the clinic and manages patient identity information with privacy controls in accordance with national standards. Grace hired a new Director of Impact whose job it is to support everyone in overseeing data collection, integration with other processes and analyzing trends for regular meetings. The Impact Director created a customized version of the SDG outcomes map to track key SDG outcomes that go beyond what is tracked, mainly outputs in the patient health data platform. The patient coordinator and care team meet monthly to review current output numbers related to patient visits. They discuss possible collective solutions for patterns in missed appointments or other patient issues. The care teams have been empowered by management to try new actions within a certain budget allocation and know they are encouraged to fail fast and adapt if something doesn't seem to work. Quarterly, patient output and SDG outcome data is rolled up to the clinic level. The Director of Impact leads each clinic team through a process to brainstorm hypotheses that explain what their data shows. What's working and impeding them from reaching their goals and what actions they could take to solve them. In addition, the management team meets with each clinic manager to review lessons learnt and decisions made based on driving performance to the SDG targets. To align incentives, there is bonus funding for all clinics that meet or exceed their C-level SDG targets, both for the clinic as a whole and for individual staff. Getting to this process took several quarters. But the results of their analysis and decision making cycle are starting to show in their SDG outcomes. Next year, they're considering hiring a third party to do mobile surveys of their patients identified as high risk to the intake process. They're trying to pinpoint why these mothers miss so many prenatal visits. Since this seems to be correlated with later health problems experienced in both the clinic and post natal care phases. Making it real, decide on the right periodicity of your most important data and dimensions. Create an overall data collection and decision-making plan for each of the key dimensions underlying your SDG targets that you identified in the last lesson. Assess your team's ability to take on different parts of your impact management practice. Provide training and incentives to equip your team for success. Evaluate the different data management platforms available, will simple software like Excel or Google sheets meet your needs for analysis, collaboration, and security. Or do you need a platform specifically designed for impact management? Consider how you will evolve your impact measurement practices and get more sophisticated over time. Focus on continuous learning. Judge the success of this work not by how much time and money you spend, but by seeing the lessons learned by the teams who have the most influence on outcomes. Have you created a strong culture of impact iteration and learning? At the end of this step, you should have an articulated SDG impact data collection process for the next year alongside allocations for financial and human capital needed to carry it out.
