Building a Data Culture: Lessons Learned
Research has shown the value of building a data-informed culture. If used properly, the knowledge gained from data can deepen relationships with key stakeholders and improve program implementation. Indeed, knowledge-centric organizations shift key practices within their organization:
- They shift data to be forward, rather than backward looking.
- They shift from having a select group handling all data collection to involving all staff in data use.
- They shift from collecting data primarily to measure impact to putting data in the hands of practitioners to strengthen impact.
You might be thinking, this all sounds great, but how does my organization make this happen? Without question, there are significant challenges facing organizations trying to engage in this type of work.
And consultants don’t make it any easier. For every consultant, there’s a new framework. Strategic planning consultants encourage you to set SMART goals and priority objectives. Program evaluation consultants encourage you to determine measurable indicators aligned to program outcomes. Design thinking consultants encourage you to plan with the intended user in mind and iterate on program design and corresponding measures of success. And operational planning consultants support you to set manageable short-term goals to monitor and maximize team performance. Organizations are left swimming in graphic organizers with differing – and worse, sometimes conflicting – terminology and priorities.
If you’re an organization navigating this maze, we recommend you keep three questions top of mind.
First, what data do you need? Data should help you get better at what you do. While data can be used for monitoring and compliance (often by funders), as organizations establish a culture of learning, it’s important that staff don’t think about just meeting requirements but aspire to look at data as a source of knowledge for getting better at what they do. This means that you don’t have to track everything. Just what helps you get better.
Second, what stage of data use are you in as an organization? From our experience, organizations are at three stages:
- The first level is an Emergent Stage. In this stage, the organization wants to use data but doesn’t know where to start. Data collection may occur from time to time, but there is no formal reporting and data isn’t tied to strategic goals. Or alternatively, the organization may have more data than they know what to do with, which means very little gets used and it falls to the bottom of staff’s priority list. Organizations in this stage should prioritize a few key indicators and data collection methods and start using them well to demonstrate the value of data first before scaling up. In short, start small before going big.
- The second level is the Developmental Stage. In this stage, the organization is regularly collecting data, but it is stored across different spreadsheets and collected by different people or departments. Data may sometimes be linked to strategic planning goals and is periodically discussed in staff meetings, but these conversations and processes are not strategic or institutionalized across the organization. Organizations in this stage should prioritize developing a dashboard that pulls together key indicators across programs and determine a schedule for regularly checking in on progress over the year.
- The final level is the Institutionalization Level. In this stage, there is an organization-wide system and dashboard for collecting data that are shared with different departments. There is a staff position/s responsible for setting the overall agenda for data collection and reporting, helping staff understand data, and assuring that systems and timelines are successful. There are periodic check-ins to evaluate what is working and what isn’t. Organizations in this stage should provide professional development for staff to learn how to use and apply measurement tools to their work and provide opportunities for staff across departments to share knowledge and prioritize action.
Third who needs to know what? Despite conventional wisdom about transparency, not everyone needs to know everything. There should be different views or levels of detail in a data dashboard for senior leaders, program staff, board members, or other stakeholders. As you’re building your strategy for data use, think about who needs what and why.