Case Study

Modernizing a Legacy System


A public research university and one of the largest institutions of higher education by enrollment, featuring amongst the top 10 nationwide is home to over 54,000 students and over 5,000 staff. It offers more than 250 degree programs in over 100 fields of study spread across 10 academic schools and colleges. It’s also classified as an R1 Doctoral University with very high levels of research activity.


Within the university, the Department of Public Health has evolved and administers a program designed to help children in low-income, ‘at-risk’ families have a nurturing, safe and healthy home environment. This is an evidence based, behavioral parenting program adopted by a variety of systems and agencies to serve caregivers with different needs. Systems include county and state public health departments, child welfare systems (including family preservation, reunification, foster parents, and family drug courts), early intervention systems (home visiting programs, Head Start programs, programs serving parents with intellectual disabilities), and criminal justice systems serving parents released from jail. This high impact program influences thousands of families every year in 29 US States and 7 international locations.


This program was developed over 30 years ago and now, quite obviously, has begun showing signs of its age with systems developed in the past proving to be ineffective and incapable of addressing the growing complexity of needs and requirements from its varied and dispersed user base. There have been multiple attempts over the years to modernize the legacy system that acts as a backbone for program delivery but they have all failed to meet the current challenges.

  1. Lagging and obsolete technology have resulted in a large technical debt leading to  high maintenance costs and vendor dependence
  2. Multiple coding scripts and languages have been introduced over the years to grapple with increased demands from users and this has resulted in an increased need for technical resources with varied and specialized skills
  3. A lack of functional flexibility and a disconnect with emerging technology trends have led to insufficient support for evolving functional requirements, data and information craters and frequent commitment slippages leading to time and budget overruns

These seemingly disparate challenges have culminated in a loss of reputation and credibility for the program. Different agencies and providers have started implementing their own versions of the system leading to a loss of valuable research data. Delayed time-to-market has resulted in a 300% increase over budgets, sub-optimal hosting and license costs and high ongoing maintenance expenses.


After a thorough analysis and evaluation of available solutions, the university decided to adopt Stackyon’s Low Code Enterprise Application Hub to update and modernize their legacy system. It’s cloud-native and multi-experience development capability promised a highly improved ‘time-to-market’. This in combination with a powerful workflow and process automation engine and superior data management capabilities would provide improved responsiveness and flexibility to program participants. The key objectives jointly formulated for the legacy transformation exercise included:

  1. Shift from a code-heavy to a configuration based approach to reduce upfront capital investments
  2. Reduce technology and vendor dependence by shifting the focus from feature delivery to value delivered and optimize ongoing operational expenditure
  3. Enable Straight-Through-Processing (STP) for improved efficiency and effectiveness across the entire value chain


  1. The entire system transformation project, including over 50 prior change requests that had been pending for many months, was completed in 4 months
  2. Average time to incorporate changes requests from program participants dropped from 5 months to 4 days
  3. Initial CAPEX costs was slashed by 70% and ongoing maintenance costs were reduced by 30%
  4. Management oversight and time commitments to quality checks was reduced by more than 50 hours per week
  5. Dramatically improved satisfaction levels led to a significant uptick in the adoption and spread of the program across multiple agencies, states and countries


The underlying goal was to achieve not just scale economies but also scope economies. With Stackyon, the university is now in a viable position to not only scale its operations with quality and efficiency but dynamic workflow processing and automation capabilities have also resulted in multiple inefficient processes being either automated or completely eliminated.