New study shows how Teradata’s AI innovation and cloud analytics capabilities help drive profits, productivity improvements, and customer engagement
Teradata (NYSE: TDC) — Customers of Teradata’s ClearScape Analytics experienced increased profitability through a notable improvement in data scientist productivity, faster time-to-market, scaling of artificial intelligence/machine learning (AI/ML) model deployment, and more. Those were among the conclusions announced today in a Forrester Consulting Total Economic ImpactTM (TEI) study commissioned by Teradata.
The study, entitled “The Total Economic Impact™ of Teradata ClearScape Analytics™” explored findings gleaned through Forrester Consulting interviews with a North American healthcare organization with $5 billion in annual revenue and over 25,000 employees, and a ClearScape Analytics customer. Forrester then used the information to extrapolate and project a three-year financial analysis showing the 36-month, risk-adjusted present value (PV) benefits including the following:
- Improvements in data science operations directly attributed to ClearScape Analytics
- 50% improvement in cumulative time savings for data science lifecycle
- 3x more models managed by data scientists
- It took less than 6 months to achieve payback for the healthcare organization’s ClearScape Analytics investment with an ROI of 244% over three years
- Improvements in AI/ML projects enabled by ClearScape Analytics
- $125 million profit from models enabled by ClearScape Analytics
- Increase in email open rates from 2% to 46%
Before using ClearScape Analytics, the healthcare organization interviewed for the TEI study said it faced difficulties in scaling its AI/ML models, and experienced problems around managing model drift, updating its feature banks and more. Because of these issues, the organization struggled to identify which AI/ML work would deliver real business value. Moreover, the organization could not run as many models as it would have liked as their data science team was at capacity and struggled to find ways to create new business value with AI/ML. Deploying ClearScape Analytics helped the company to mitigate these obstacles, provide better customer service, and halving the team’s work time. The company has now increased its data science team by 50%, tripled the number of models it was able to develop and deploy, and has freed up time to explore additional AI/ML use cases.
The Forrester study noted, “Investing in a solution like Teradata ClearScape Analytics is crucial for enterprises as it enables them to responsibly build and maintain machine learning (ML) models for their custom AI/ML solutions.”
“The important short- and long-term benefits cited in this study, as noted by our healthcare customer, can be experienced by companies across a broad spectrum of industries where there is a need for robust, open and connected AI/ML capabilities,” said Jacqueline Woods, Teradata’s Chief Marketing Officer. “ClearScape Analytics illuminates this transformative potential, not only delivering these capabilities at scale but also empowering organizations with unparalleled autonomy and seamless access to deliver near real-time insights and optimize business results.”
The study also identified additional benefits from ClearScape Analytics:
- “The SVP of enterprise data and analytics told Forrester that adopting ClearScape Analytics was cheaper, easier to justify to internal security and IT stakeholders, and faster to implement than alternatives.”
- “ClearScape Analytics allowed the interviewee’s organization to reduce manual tasks, increase productivity, and successfully scale models into production …”
- “ClearScape Analytics enabled the SVP of enterprise data and analytics … to deploy more models into production more frequently and with fewer resources.”
- “Models built with ClearScape Analytics improved patient population health and outcomes through personalized messaging, proactive and relevant follow-ups, a better understanding of population health, and more.”
- ClearScape Analytics’ powerful AI engine empowered the customer to quickly scale end-to-end AI/ML pipelines with accountability, security and trust — all while controlling costs.
Forrester’s TEI methodology is designed to enhance technology decision-making processes and assists vendors in communicating the value proposition of their products and services to clients. The TEI methodology helps companies demonstrate, justify, and realize the tangible value of IT initiatives to both senior management and other key business stakeholders.
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