Your Data Ducks Are Wandering All Over the Place. Get Them Lined Up To Maximize Your Technology Resources
You want data at your fingertips, when you need it, in the right format. Who doesn’t? But often when you go to get reports, the data is siloed and you can’t bring it together, or some of it’s missing, or it’s not accurate, or you don’t know what to make of it.
Maybe you think technology is the answer. It’s understandable. Machine learning. Artificial intelligence. Big data. There is all this amazing technology out there that can make cleaning, analyzing and reporting on data so much easier. Data warehouses, data lakes, and pipelines make it easier to bring all those siloes together into one place without making everyone use a new data system. While these tools can do amazing things, if you don’t have your ducks in a row in terms of your data governance, implementing any of these can be a waste of time.
Any nonprofits that are considering investing in big data solutions must ask themselves some fundamental questions.
1. What are we collecting and storing?
Make sure that the data you collect and store has a purpose. Often we experience “unsightly data build-up”. Stakeholders or constituents keep asking for more information, but that person moves on and the data we started collecting for them sticks around. Program close up, funding changes, and boards get their questions answered, but all the data we collect related to that closed program, old grant, or board meeting three years ago sticks around, using up time and money. Conduct a basic data inventory and archive unused data at least once per year to make sure you have what you need, but nothing more. As Einstein said, “everything should be as simple as possible, but not simpler”. Keep that in mind.
2. Who has ownership of the data?
Depending on the size of an organization, a single person or a cross-functional team may be appropriate to act as data owners and stewards. In this role, they periodically review data quality and practices, set goals for organizational data quality or usage, and provide guidance and leadership to other organization members around all aspects of data governance. If you have a small organization with a single person responsible, then it is helpful if they are in leadership or at least have a direct line to leadership. If you have a medium or larger organization and share the data ownership across a team, it is helpful to have a cross-functional team with at least one member of senior leadership involved. This diversity helps to ensure that the policies and practices developed by the team are both practical and strategic.
3. Who has access to our data?
Inherently, this question also gets at the idea that you should be clear on who SHOULD have access, and to what data. Have clear policies about data encryption, storage and transmission of low-risk data, personal information, and data covered by HIPAA or other regulations. Some of this involves user management, documenting what lives where, and understanding what the protocols are for accessing, sending, and receiving data.
4. Why do we have missing or inaccurate data?
If your data is missing, no high tech solution will solve that. It might make it easier to identify, but policies around how to manage data will help you have more accurate data, and reduce missing data. Make sure you have clear documentation and training materials related to data entry. It’s not a no-brainer to enter data and there can be a surprising amount of interpretation involved. Have your data owners and stewards develop quality assurance protocols for data entry and clearly document them.
5. How do we measure and improve our data quality and practices?
Implement effective ways to hold the people who collect, access and analyze data accountable. This doesn’t have to be finger wagging, and can even be turned into a game or competition between colleagues or departments. Measure or estimate a baseline of your data quality, change your practices, and then measure or re-estimate your data quality. Keep the people who have an effect on data quality informed of how it changes. Be sure to acknowledge and even reward them as your data quality improves, and ask them for input on how to make further improvements or address challenges. While you may have assigned data owners or stewards, everyone must understand their own part in the responsibility for your organization’s data.
When you have solid data practices such as a tidy data model, clear policies on access, and well defined and documented protocols around data cleaning and quality assurance, you can have good results that you can act on, no matter what technology you use.
At Inciter, we work with organizations to tackle tough questions related to data governance, as well as building data systems. So we make sure that you are aware of the organizational data management issues that need to be in place before we throw you into a high tech data management system. If you need warehousing, pipelines, data cleaning or reporting help, but you aren’t sure your organization has the policies and practices in place to take advantage of the new tools that are available, we can do a data assessment for your organization at a very reasonable cost. With the data assessment you can put in place the right technology for your organization, no matter what system you choose, and now that you can get the most out of it.
To see how Incite can help your organization get the most out of its data, contact us at firstname.lastname@example.org, or at (410) 366-1779.