Guide Objectives
- Define your organization’s objectives for becoming more data mature in the short term
- To develop a list of prioritized activities to meet the objectives with limited resources
Social impact organizations (SIOs) are often challenged with limited staff, resources, and expertise. While there is usually an understanding that becoming “data mature” is valuable, it is often difficult to know where to begin. The truth is, there are almost always a myriad of paths to improve data maturity, so determining the one to take can seem daunting.
This guide is meant to support organizations along this journey by sharing how to develop objectives and prioritize efforts when becoming more data mature as an organization.
Guide Specific Disclaimer
Each organization has different priorities, risks, values, and resources available. These differences will shape how they prioritize their journey to data maturity and what they envision as an ideal state. It is important to remember that data maturity is relative. What may be a priority for one organization may not be a priority for another.
While this guide will provide useful tools and approaches, each organization will ultimately have to look inward to find the best ways to adapt what is provided to meet their priorities.
Understand what data maturity means for your organization
The first step is to understand what data maturity means, and then what it means for your organization specifically.
For context, “data maturity” refers to how an organization:
1) uses data to meet its organizational and mission-based objectives,
2) develops and implements processes to collect, responsibly use, and manage data, and
3) embraces data in its culture.
In other words, purpose, practice, and people are all fundamental to developing data maturity.
If you would like more insights into your organization’s data maturity, you can use a data maturity assessment (DMA). There are several free DMAs from data.org, Data Orchard, or DataCamp , and others to get you started.
It is important to note that while a DMA is useful to develop a general understanding of where your organization exists in the spectrum of data maturity, it is rarely tailored to your organization’s priorities, activities, and critical needs. Given this, to make meaningful progress in data maturity, you should first define your organization’s ideal state of data use, relative to its mission, resources, and needs. This will be done in the next step.
Define your organization’s ideal state objectives
Now that you are more familiar with the concept of data maturity, it is time to define what your organization’s ideal state looks like. To do so, you can download the Ideal State Action Plan.
On the Objectives Tab in the plan, you can write down the five most important objectives for your organization to be the data-driven organization you want to be, given your organization’s needs. For the purposes of this guide, we will focus on reaching your ideal state for the next year. When writing the objectives, we encourage you to reflect on the following question to visualize your ideal state: how would you want your organization to be using and managing data by the end of the year?
Consider the following questions, among others, in defining your organization’s ideal state:
- In what ways would you like to better collect, store, analyze, and communicate your data to further your mission?
- What, if any, critical security issues need to be addressed to more properly mitigate data breach risks with sensitive data?
- Do staff have the right skills in place to reach your goals, or is developing skills an objective itself?
- How would you like staff and leadership to better use data in decision making and communications?
Example:
The healthcare nonprofit, Give Health, has been hampered by the lack of a single storage solution for their data.
Their volunteers provide healthcare supplies to low-income clinics, but the tracking of what they have and where it was supplied is stored in all sorts of ways, on local computers, through Google Drive, in Box, and even just on paper. So, one of their ideal state objectives could be:
To store all of our data within one storage solution (Microsoft 365, Google Workspace, Dropbox, etc.)
(This, and the rest of the Give Health example items are listed in the Example rows of the spreadsheet.)
Define key activities and identify their value to the organization
Once you have defined your organization’s ideal state objectives, the next step is to define the activities needed to reach these objectives. To do so, go to the Activity Prioritization tab.
Within this tab, all the objectives you wrote in the Objectives tab are available within the dropdown menu in Column A. Select the appropriate objective, and then, fill out the associated activity in Column B. To keep things simple, we recommend you write up to three activities for each objective.
Knowing the need to prioritize efforts when one has limited resources, the next step is to identify the relative value of the objective to your organization. In Column C you will rank the relative value of the objective using the dropdown menu, and in Column D you can briefly describe why it is valuable.
Example:
Given its storage solution objective, Give Health, is focused on three key activities:
1) Develop an inventory of all datasets;
2) Decide which storage solution to use for data
3) Move all datasets to the storage space
The belief is that with these three activities, Give Health would have met its objective, created a more transparent, accessible place to house its data, reducing risk of data breaches in the process. Each activity provides a different value to the organization, and this is indicated as well in the spreadsheet.
Identify the resources and time required for each activity
While defining the value of each activity, it is important to balance the value with the costs required to reach each objective. Primarily, these costs include the resources needed and time required for each activity.
With that in mind, you can identify the intensity of resources required in Column E and provide a brief explanation of these resources in Column F.
Similarly, you can then identify the amount of time required to reach the objectives in Columns G and H. For this factor, it is important to consider the amount of labor time required to complete the activities, not the duration of time it will take to complete them.
Example:
With the three identified activities for Give Health, we can now identify how the time and resource expectations differ for each. For example:
1) Developing a dataset inventory is a resource heavy activity because they would need to collaborate with all volunteer healthcare suppliers to handle this work
2) Deciding on which storage solution to use for data requires relatively low resources in terms of time and energy
Prioritize objectives based on relative value, resources needed, and timeframe
Now that you have a balanced view of the value of each objective and the relative costs, you have what you need to prioritize your limited resources on the activities with the greatest return on investment (ROI) to your organization. When prioritizing, you should consider:
- Which activities make sense to start with, based on a logical order of activities, staff bandwidth, visibility to drive buy-in, and ROI
- Whether there are any activities that make sense to do simultaneously, rather than sequentially
- Are there any other factors to consider in the prioritization process (deadlines, bottlenecks, buy-in, etc.)
You can identify the relative importance for your organization in Column I.
Example:
For Give Health, given their staff is very much tied up with work over the next three months, the one activity they will prioritize at the moment is determining the storage solution.
After three months, when there is more time, they will focus on the other two activities, which will require more effort to wrap up.
‘So what’ and next steps
With the activities and reflection, you carried out in this guide you are now on your way to improving your organization’s data maturity.
Once your organization has carried out the activities and started to reach some ideal state objectives you can fill out a Data Maturity Assessment again to see how you have evolved. In the example of Give Health, they should see some improvement in the Practice section after reaching their objective.
To go further in your data maturity journey, you can check out our guide on building buy-in for data strategies.
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