Though AI can yield significant economic returns, many organizations still struggle to maximize its business value. Discover how Teradata ClearScape Analytics™ helped one company overcome common AI/ML barriers to improve productivity, increase revenue, and optimize customer journeys, ultimately driving more than $125 million in profits and a 244% return on its investment over three years.
AI represents an enormous opportunity for businesses. According to McKinsey, generative AI alone holds more than $25 trillion in total economic potential. But as we noted in the first part of this series, many organizations still face challenges that prevent them from realizing value from AI/ML initiatives, including poor data foundations, productivity bottlenecks, and costly data movement.
To answer this, let‘s explore one organization’s success story: a Teradata customer that generated considerable ROI and profits by achieving three essential ingredients for driving AI business value:
Scaling AI to drive ROI
Boosting data scientist productivity and time savings
Improving customer experiences
AI case study: A healthcare company’s challenges
In January 2024, Teradata commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study aimed at examining the potential AI business benefits of using ClearScape Analytics™, Teradata’s engine for deploying end-to-end AI/ML pipelines. As part of the study, Forrester conducted a three-year financial analysis of a current Teradata customer, a North American healthcare organization.
Prior to using ClearScape Analytics, the company struggled with expensive and complex data movement, exacerbated by the security risks and governance issues involved with moving sensitive, protected health information between systems.
They also had difficulty scaling machine learning models in production and keeping up with their maintenance and governance. In many cases, models were being trained on personal laptops, which further delayed processing.
Maintaining version control, preventing model drift, and updating feature banks also ate into valuable employee time. As a result, they hit a “model plateau,” unable to create new models without adding more employees.
Together, these issues prevented the company from generating business value from its AI/ML initiatives.
The ClearScape Analytics solution
According to the study, deploying ClearScape Analytics enabled the organization to:
Significantly boost ROI by efficiently scaling AI beyond existing machine learning models
Improve model performance
Enhance and accelerate security approval processes
ClearScape Analytics enabled the company to deploy more models into production more frequently and with fewer resources. It also powered more proactive project risk management and ultimately allowed the organization to leverage new AI/ML opportunities to drive business value. These improvements helped generate $125 million in profit from models enabled by ClearScape Analytics over three years. In addition, the study found that the company realized a considerable 244% return on its investment.
One Teradata customer’s results with ClearScape Analytics
Boosting data scientist productivity and time savings
Before using ClearScape Analytics, the company’s team of data scientists could run a maximum of 25 models. Post-implementation, that number increased to 80 models. At the same time, new model deployment became much more efficient: what used to take a team member up to 10% percent of their time now consumed only about 2%.
The study also revealed that labor associated with data preparation decreased by 15%, model training by 5%, and model operationalization and maintenance by 30%, representing $713,000 in savings over three years.
Ultimately, the research showed that ClearScape Analytics saved data scientists 50% of their total time and enabled a 3x increase in the number of models released by reducing manual tasks, limiting costly data replication and movement, and streamlining data analysis.
Personalized patient messaging and real-time content delivery: Patients who recently visited the emergency department were more efficiently identified and sent follow-up messages regarding ongoing care and treatment. The improved messaging also boosted marketing email open rates from 2% to 46%, marking a 23x growth in engagement.
Risk population management: Patients at risk of certain conditions, such as diabetes and hypertension, were identified and informed of providers at the point of care, proactively helping to manage risk.
Predictive supply chain management: The healthcare organization built models to optimize inventory supply chain efficiencies, such as measuring and reducing the time vendors took to deliver medical supplies.
Real-time recommendation engine for patient referrals: Patients also received customized outreach messaging to in-network specialists, improving network efficiency by 40% and delivering $80 million in margin.
Following the investment in ClearScape Analytics, the organization was able to increase machine learning models at scale while enjoying better performance, streamlined security processes, easier data preparation, and a consolidated data analytics environment. As a result, they boosted data scientist productivity and drove significant AI business value while improving overall patient outcomes.
TTo see all the results of the Forrester Consulting Total Economic Impact™ of ClearScape Analytics, download the full study.
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