Forrester Total Economic Impact™ study highlights faster time to market, improved decisioning and cost savings brought by SAS and Microsoft partnership
Organizations deploying SAS Viya, SAS’ cloud-native AI, analytic and data management platform, on Microsoft Azure can see benefits including a 204% return on investment over three years, according to a new commissioned Total Economic Impact™ study conducted by Forrester Consulting. Additional study results further emphasize the value of customers’ investments in SAS Viya on Azure, including millions of dollars in net present value and a 14-month payback period.
Forrester interviewed nine decision makers at six customer organizations using SAS Viya on Azure to understand the benefits, costs and risks associated with their investment. The customers spanned industries, including government, manufacturing, financial services, IT professional services and banking.
Prior to implementing SAS Viya on Azure, interviewees noted that barriers to data access and disparate data sources made it difficult and time-consuming to build, deploy and manage AI models. Other issues they faced included the inefficiencies and high costs of on-premises analytics infrastructure.
After their investment in the product, interviewees addressed these challenges and saw improved overall productivity and performance, according to the study. Quantified benefits included faster time to market for analytics insights, improved operational efficiency in model building and testing, and cost savings from retiring on-premises analytics infrastructure. With a strong three-year, risk-adjusted total present value of these benefits alongside numerous unquantified benefits, the investment plays a key role in improved organizational decision making and overall success according to customers.
“Many organizations today experience a multitude of friction points on their path from data to decisions. Our strategic partnership with Microsoft aims to simplify this process to improve trusted decisions and accelerate innovation,” said Jay Upchurch, Executive Vice President and Chief Information Officer at SAS. “This study shows we are jointly delivering on our promise and providing immense value to our customers, including cost reduction, increased time to value and improved productivity for data scientists and analysts across industries.”
Since SAS and Microsoft announced a strategic partnership in 2020, the companies have continued finding new ways to serve joint customers’ cloud migration and modernization needs.
From harnessing streaming IoT data and advanced analytics to help maintain COVID-19 vaccine integrity to providing fast, personalized customer service based on real-time analytics, joint customers are addressing their most complex challenges with SAS Viya on Azure.
The companies have also launched new industry-specific solutions, like SAS Cloud for Intelligent Planning as a part of the Microsoft Cloud for Retail, and SAS for Improved Manufacturing Quality for the Microsoft Cloud for Manufacturing. These powerful solutions help industry leaders remain resilient among today’s rapidly shifting markets.
New SAS Viya on Azure integrations include SAS Event Stream Processing, Azure IoT Edge and Azure IoT Hub to act on real-time insights; SAS Intelligent Decisioning with Power Automate to empower enterprise decisioning; and SAS Model Manager with Azure Machine Learning to remove barriers organizations face as they put more AI models into production.
These continued benefits of the partnership were also highlighted by the TEI study interviewees who shared positive feedback about feature integrations, including SAS Model Manager and Azure Machine Learning, SAS Intelligent Decisioning and Power Apps and Power Automate, and the ability to score models in-database in Azure Synapse Analytics.
“SAS Viya on Azure gives customers better insights with less time, cost and complexity to help accelerate time to value,” said Alvaro Celis, Vice President of Global ISV Commercial Solutions at Microsoft. “This enables Azure customers to address their most critical analytics challenges to drive innovation.”
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