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Analytic Process Automation | A Case Study with Livable Communities

Andrea Steffes-Tuttle Marketing Analytics, Nonprofit, Predictive Analytics

The Client

Roughly 90 percent of adults age 65 or older, want to “age in place” in their homes and their communities. They want to remain close to their children and grandkids. Such connections are not just nice to have — they actually contribute to the health and well-being of older adults.

AARP Livable Communities supports the efforts of neighborhoods, towns, cities and rural areas to be great places for people of all ages. They believe that communities should provide safe, walkable streets; age-friendly housing and transportation options; access to needed services; and opportunities for residents of all ages to participate in community life.

AARP works to build awareness of and support for community-led efforts in the following ways:

  • Help communities examine their housing, transportation, and access needs through an age-friendly lens.
  • Work to support communities in diversifying their housing stock.
  • Educate communities and residents on how to determine the livability of their neighborhood.
  • Invests in communities to strengthen the quality of place and encourage citizen engagement.

The Challenge

An important part of the work that the AARP Livable Communities team performs is its efforts to influence decision-makers to enact policy and fund programs that improve city design.

These decision-makers require sustained, targeted resources and support to accelerate the pace of change towards more livable communities. The levers of municipal influence are complicated and require a detailed understanding of local circumstances.

Danville Kentucky Project City Heights California Project Cutler Bay Project

The AARP team had access to a lot of valuable and greatly needed information, but it was not centralized, easily found nor consistent. A data-driven approach was required to allow them to make stronger and more targeted cases when influencing and enrolling decision-makers in community decisions that support age-friendly decisions.

Before starting work with Lityx, the team had disparate data, in a variety of locations, some of the data unknown to members of the team. Additionally, duplicate efforts were being performed in each state and there was a lack of process in approach.

Additionally, in 2018 every state office prioritized the Livable Communities program and the enrollments in NAFSC increased rapidly. AARP had to figure out how to improve their data systems and processes to accommodate the demand and scale the program quickly.

The Solution

Leveraging the LityxIQ platform, the Lityx team was able to bring together all of the data from the different sources. Automated processes for data collection, warehousing, cleaning, and preparation were established.

This enabled uniformity of approach across states and empowered the teams in those states with a visual method to see and share the data in the form of dashboards that can be shared with the team, stakeholders, and community influencers.Automated End-to-End Dashboard

The Outcome

With the data organized and dashboards built to provide a better understanding of the work performed across states, the AARP Livable Communities team has experienced a variety of improvements in their processes and the work they are doing.

  • Automated insights. With 12 to 24-hour automated processing of each days data updates, the AARP Livable Communities team has nearly real-time access to the latest information and insights automatically.
  • Global understanding of the program’s contributions. The ability to access a holistic view of the data enables AARP to see the impact of the program in each state and determine future resource expenditures.
  • More effective and efficient use of employee time and talents. With the information organized, it’s easier for the Livable Communities staff to answer questions, with more confidence.
  • Increase data transparency and accuracy. The ability to access data empowers users to provide feedback to the data owners when there are gaps or when more data could be collected and used, enriching their insight.