- Last Updated On
February 1, 2022
A data strategy lays out your approach to using data at your organization, including what data capabilities you want to have and how you’ll collect and manage your data. Executing your data strategy may involve building new data collection and management systems, as well as hiring new data talent. Importantly, your strategy will also help you identify where you need to make behavioral or cultural changes at your organization so that your staff is all thinking about and acting on data in ways that support your strategy.
In data.org’s Data Maturity Assessment (DMA), you’ll see three dimensions that define a strong data strategy: Purpose, Practice, and People. If you’re looking to improve your organization’s use of data, these three dimensions can be helpful for thinking about what you need to change. If you haven’t already taken the DMA, we encourage you to do so in order to get a sense of where you may have opportunities for improving your data capabilities.
In this Guide
- Learn about getting started with data strategy and how to implement it in your organization.
- Read about the three dimensions that define a strong data strategy.
- Assess your organization’s data journey through the Data Maturity Assessment.
The most important part of any data strategy is to identify what it is you actually want to use data to do. It’s no use creating a new database for storing data if you haven’t already established the ways you’ll use that data. The uses of data are numerous, ranging from reporting output numbers to funders, to feeding data-driven algorithms that speed up your work, to persuading people to join your cause. If you’re at the beginning of your data journey or are considering a new strategy at your organization, it may be a good time to assess what outcomes you want to achieve with data.
Here are some resources to help you determine your purpose:
Once you’ve determined the outcomes you want to achieve with data, you’ll next want to think about how you’ll go about achieving them. The data practice at your organization encompasses all of the stages of the “data value lifecycle”, i.e. how you manage data from collection to analysis. There are many considerations to make in this phase, so we’ve interspersed overall guides with our favorite resources on specific stages of the data use pipeline.
You may have your Purpose and Practice mapped out, but data strategies don’t run themselves. You’ll need our third P, People to make your work come to life. You’ll want to consider three types of personnel factors: technical skills, workflow changes, and cultural changes. Technical skills are the most straightforward—you’ll need people who know how to collect and use data to execute on your strategy and may have to train or hire staff to succeed. Workflow changes take into consideration the changes your staff will have to make for your data strategy to succeed, even if they’re not the “tech people” or “data people”. For example, in order to analyze the operations of your online mentoring program, you may now need tutors to log how much time they spend with each student. Lastly, cultural changes refer to the changes you’ll need to make in peoples’ mindsets and behaviors around data generally. For example, decision-makers may nod along with a data strategy but secretly resent having a computer “tell them” what to do and thus undermine the strategy in practice. If you are looking for more data capabilities on staff or are considering a substantial change to your data strategy that will require workflow and mindset shifts, this section may be a good place for you to start.
We hope this guide helps you on your data journey, whether you’re just taking your first steps or lacing up for your next marathon. No matter what, remember that building your data strategy is an ever-evolving process that you’ll continue to nudge, mold, and tweak as you find what works for you. Don’t be deterred if you need to keep experimenting, since change is really the only constant when it comes to data. Keep going and good luck on your data journey! Please feel free to suggest any other guides you found helpful by contacting us and we may incorporate them.
Our report on the Inclusive Growth and Recovery Challenge is available: data.org, with generous support from the Mastercard Center for Inclusive Growth and The Rockefeller Foundation, issued a $10M Inclusive Growth and Recovery Challenge. The Challenge solicited proposals for scalable and sustainable data science solutions from and for every part of the world, with… Read more