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Posted by on Mar 4, 2016

Visualization and Metrics: Using Data to Build High-Performing Organizations

Visualization and Metrics: Using Data to Build High-Performing Organizations

Data VisualizationI recently attended the Government Analytics Breakfast forum hosted by Johns Hopkins University where HHS’s Chief Data Officer Dr. Caryl Brzymialkiewicz discussed the impact of data science in the Federal government. The conversation included a wide range of topics from systems structure, performance improvement, and data mapping, yet two things in particular stood out: data visualization, and useful metrics. To use data effectively to understand program performance and allocate budgets, data visualization and metrics are important areas for every agency to invest in.

A data pictorial is good if it helps the end user understand and appreciate the story it tells. It’s not enough for data to be accurate and the analysis relevant—it must also be easy to interpret. This enables descriptive as well as prescriptive analytics to have a real impact. To address this, it’s important to be flexible. Agencies need adaptive systems that allow users to grab data visualizations in ways that maintain the integrity of the data but make it “pop” to the end user. Maps are a popular data visualization format, but different formats resonate with different users. There is no “one size fits all.” Regardless of what system or software your organization uses to visualize data, strive to make data analysis results available in a variety of visual formats.

In addition to good visualizations, ensure that your analysis tells a meaningful story by using the right metrics. Legacy metrics may have been shaped by what we were able to collect, so it’s important to make sure your data models and metrics reflect current agency priorities and needs. Consider the following:

Make sure your metrics are relevant. Do they reflect agency priorities? Are they based on meaningful things? Are they realistic—do they reflect what your data does/can assess?

Assess your metrics’ lifespan and be realistic. For how long do you want to use this metric? When will you need to retire it and replace it with something else? What are the drivers that affect when you’ll need this?

Consider your stakeholders. What does Congress require for program justification? What are your customer’s goals? Invite your stakeholders to be part of the process of deciding which metrics you use and what benchmarks shape your analysis.

The amount of data available to us increases daily, and it’s upon all of us—industry, government, and academia—to partner, continuing to improve data quality and empower high-performing organizations.

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