Clear Impact Blog

By: Kayleigh Weaver
February 18th, 2023

Unified Data Management is a tool that can enhance a collaborative partnership’s alignment and accelerate its progress toward measurable results. There are three types of Unified Data Management. Partnerships should aim to engage in all three types for maximum impact.  Keep reading to learn what Unified Data Management is, why it’s important, and how Clear Impact software tools support unification efforts. 

In this blog, you’ll learn about the three types of Unified Data Management, why they’re important, and how Clear Impact software tools support each.

Table of Contents

1. Collaboration + Alignment + Unified Data Management = a Recipe for Impact

2. The Three Types of Unified Data Management

1. Utilizing the Same Data Management Frameworks

2. Utilizing the Same Data Management Software Systems

3. Utilizing Data Management Software Systems That Work Together

4. Aim to Engage in More Than One Type of Unified Data Management

5. The Best Unified Data Management Systems Do This

6. How Clear Impact Suite Supports Unified Data Management

7. Unified Data Management in Action

1. United Way of Central Iowa

2. SisterWeb

3. Health Resources and Services Administration Bureau of Primary Health Care

8. Helpful Links

1. Collaboration + Alignment + Unified Data Management = a Recipe for Impact

If you’re familiar with Results-Based Accountability, you probably understand “shared accountability.” This concept posits that no single person, agency, or organization can be held responsible for creating population-level changes. For example, a city health department shouldn’t be held solely responsible for improving health outcomes. Why? 

Social problems are complex and influenced by diverse factors. Think about the Opioid Epidemic in the United States. Opioid addiction is a health issue that any local, state, or national health agency should tackle. But the epidemic transcends what government can do alone. Overprescribing, economic upheaval, poor mental health, inequity, a lack of alternative pain management options, counterfeit pills, and irresponsible pharmaceutical practices are a few factors underlying this crisis. That means healthcare systems, insurance companies, pharmaceutical companies, law enforcement, and other regulatory and policymaking bodies (at the very least) share accountability in fixing the problem.

The nature of social issues necessitates collaborative intervention. Different sectors (schools, businesses, government, philanthropic organizations, etc.) all have unique strengths, influences, and resources to contribute to a collaborative effort. 

Collaboration is essential, but it is not an end in itself. You can have cross-sector partners who want to make an impact, but that doesn’t mean they’re working together effectively. Partnerships must work in alignment to make measurable progress on community outcomes. Alignment means partners share a Common Purpose and engage in mutually reinforcing activities that advance that purpose. Alignment gets everyone working together and moving in the same direction so that the entire collaboration can accelerate measurable progress.

Unified Data Management Helps Aligned Partners Get Where They’re Going Faster

When added to collaboration and alignment, Unified Data Management is another essential ingredient in the recipe for impact. Once all partners are “moving” in the same direction with aligned strategies, Unified Data Management can help them get where they’re going faster.

2. The Three Types of Unified Data Management

Engaging in Unified Data Management can accelerate a partnership’s mission and maximize its ability to create measurable impact.

Unified Data Management can mean any of the following:

1. All partners in a collaborative effort use the same data management frameworks to make decisions and report progress (e.g., all partners use Results-Based Accountability to measure their performance and impact).
2. All partners use the same software systems to centralize data management and make more informed decisions (e.g., all of a funder’s grantees report their performance data to the funder using Clear Impact Scorecard). 
3. If partners use different data software systems for different purposes, these systems are designed to work together (e.g., an organization uses Clear Impact Suite to collect, analyze, and report its data in one unified system).

Type One: Utilizing the Same Data Management Frameworks

When partners use the same data management frameworks, it becomes easier to aggregate performance metrics, compare the performance of similar programs, and engage in effective performance dialogue.

Using the same frameworks helps ensure partners engage in consistent data-based decision-making processes. It also ensures that partners consistently format all information (numerical or contextual data). This consistency makes it easier to compile, aggregate, and analyze different kinds of information. 

For example, many organizations and partnerships use the Results-Based Accountability framework to make data-based decisions and solve entrenched social problems. The framework helps organizations design performance measures by answering three simple questions:

1. 1. How much are we doing?
   2. How well are we doing it?
   3. Is anyone better off?

The framework also provides a simple step-by-step process for getting from talk to action called “Turn the Curve Thinking.” This process produces a Turn the Curve Action Plan. Organizations can use this plan to report the progress of individual programs. Partnerships can also use it to report progress on a shared mission to stakeholders and the public. You can see examples of Turn the Curve Action Plans here. 

If an entire partnership designs its performance measures using Results-Based Accountability, it becomes much easier to aggregate performance across similar programs. Additionally, suppose everyone uses the same templates to present their data and performance (e.g., Turn the Curve Action Plans). In that case, it’s easier for funders and backbone organizations to engage in effective performance dialogue with partners and compare the effect of different programs.

Type Two: Utilizing The Same Data Management Software Systems.

When all partners are collecting and reporting data on the same systems, funders and backbone support organizations can easily aggregate data across similar programming to see progress on collective strategies.

A partnership will never know the latest version of its data if that data resides in multiple places. Using the same data management software systems helps backbone support organizations and funders standardize, centralize, and unify data across funding streams to make better investment and budgeting decisions. 

Similar to the benefits of unified frameworks, Unified Data Management systems allow partnerships to easily aggregate data across similar programming to see collective progress on impact strategies. Backbone support organizations, funders, and government agencies can make better sense of performance data if their partners collect it in the same way. 

If your partnership finds a system that you know will simplify data reporting, we suggest making its use mandatory rather than optional. Implementing a system will be a significant investment, so why not get your money’s worth and make it a condition of funding or partnership? Just remember that if you make any system mandatory, supporting partners through system training and capacity-building is a must. 

Type Three: Utilizing Data Management Systems that Work Together

When partnerships use data management software systems that work together, they save time and money and make fewer data processing errors.

There are several types of data management activities partnerships must engage in to make an impact. Some of these activities include collecting data, analyzing data, and reporting data. There are many software systems designed to help partnerships engage in these data management acitvities effectively.

Some software specializes in one activity (e.g., data collection), and other systems can do more than one activity effectively (e.g., data collection and analysis). For example, organizations can use surveying software to collect data from program participants. However, many survey tools lack the option to analyze data over time. Analyzing how data changes over time is critical for data-based decision-making. Therefore, an organization may need to purchase a separate data analysis tool if its survey tool cannot provide analytics over time.

When organizations or partnerships utilize non-complementary systems to collect, organize, analyze, and report their data, inaccuracies can run rampant. Imagine that an organization uses one tool to collect data via surveys and another to analyze how that data changes over time. If the tools are from different software vendors, they may not be compatible. This incompatibility would force the organization to manually cross-walk data from one system to the next. Manual data collection, synchronization, and processing take more time and leave more room for errors.

In contrast, when organizations use integrated data management systems, these are some benefits they can experience:

• • Data processing becomes more accurate.
  • People save time when they don’t have to process data manually data.
  • Purchasing integrated systems from one vendor — rather than multiple systems from multiple vendors — usually saves organizations money.