Estimated reading time: 3 minutes, 43 seconds

In part 1, we discussed the growing amount of data created by not-for-profit (NfP) organizations every day. Along with copious amounts of data, stakeholders and donors expect to receive timely information when asked for. It’s important that, with the profuse number of guidelines, standards, codes and more that govern data management, NfPs make sure the organization meets all the requirement in order to drive the organization forward.

A Concrete Step: Building Data Governance

There are five dimensions that are mutually dependent on each other and together, each play an important part in the governance of your data.

  1. Strategy

Your data strategy lays out your data vision. A maturity model can help you decide where you are now versus where you want to be. Here’s a good starting point to help determine where you stand:

  • Data foundation – There are basic data standards with manual reporting in place.
  • Emerging – Organizations are aware of the importance of data strategy and are developing their skills and tools.
  • Competent –Organization have established formal data roles and capabilities which are benefiting decision making and compliance.
  • Data driven - Data is embedded in all processes and decisions to optimize performance.

This will help you diagnose and prioritize your issues, and opportunities and build awareness of what it takes to move to the more advanced end of the maturity model.

  1. Policies

Data Policies are the essential tool for explaining the principles that underpin how we manage and use our data. Going beyond compliance and a set of rules, they pave the way to achieving strategic data capabilities.

Policies need to be joined up, consistent, up to date, accessible and readable, and most importantly, aligned to your strategy.

  1. Procedures

Covering anything from how to dispose of sensitive data to how to write and publish a report, procedures tell anyone handling your data how to ensure both compliance and best practice. How for instance, should employees use social media engagement to encourage donations? What works and what doesn’t? 

Often forgotten, procedures need to be complete and constant, and if accurate enough can underpin compliance.

  1. Data architecture

It is an essential tenant of data governance to know what data you have, where it is and where it needs to be to support operational processes and reporting. Data architecture is how your data is collected, stored, arranged and integrated. 

To establish a baseline for your organization, there are a range of tools to help you audit and map your data. These same tools can also be used to design your optimal architectural environment. By going through this process, you agree the data standards for metadata or controlled vocabularies. This ensures that your data is consistent for reporting purposes because it is interoperable across systems both within and beyond your organization.

  1. Culture

Finally, data culture glues everything together. It is about your people and helps establish the roles and behaviours required to deliver your data vision.

It is also about who owns the data and what is happening on the ground. By focusing on data culture and stakeholder engagement, you can identify the barriers and levers that effectively manage the change brought about by proper governance.

The Outcome

There are powerful benefits of proper governance in a sector so reliant on data and information. Rather than looking at data generation and requests in isolation, with proper data governance, NfPs become part of a holistic picture that benefits donors, employees and beneficiaries. Increased efficiency means NfP orgs can divert time and activities that improve services on the frontline. Improved reporting means these organizations can demonstrate a clear audit trail of improved provision. This builds the reputation and trust needed to increase donor confidence and funding.

Excitingly, and alluded to above, the next stage, introducing digital technology aligned to your data governance, can turbo-charge your organization. One version of the truth becomes more achievable, automatically delivered to those that need it in a timely fashion. Microservice architecture and artificial intelligence will help the sector keep up with industry regulation and data proliferation. More though, they will introduce science to the data so that we can really understand what happens and works both within our organizations and out in the field. In short, rather than looking in the rear-view mirror, we will have our eyes firmly fixed on the road ahead.

While this may sound complex, the results will ultimately improve the payback of increasingly generous donors by continually improving the outcome delivered to those in need.

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