How Can You Improve the Successful Deployment of AI Optimization Projects?
Before an AI Optimization project starts, can you systematically identify and prepare for potential risks? For projects in progress, how can you overcome challenges to deployment? Introducing “The Princeton 20,” a framework to assess and overcome risks in AI, optimization, and advanced analytics.
All AI projects come with risk and many fail to progress from exploration into fully deployed production. For your projects and opportunities, leverage best practices to research, discuss and address risks. Princeton Consultants has distilled 20 scorable factors that describe the core challenges to successful AI deployment.
The Princeton 20 is divided into 10 business risk factors, such as the sponsoring executive and decision support culture, and 10 technical risk factors, such as the application novelty and speed. In every project, identified risks call for explicit, planned mitigation—Princeton Consultants will work with your team and provide proven strategies and techniques, based on more than 1,800 projects. Contact us for an AI project risk assessment at your organization.
Recorded webinar: Steve Sashihara on the Princeton 20
Assess and Reduce AI Optimization Project Deployment Risk
Request a complimentary AI Optimization project risk assessment.
Princeton leaders will meet with your key stakeholders to review your current AI, optimization, or advanced analytics initiative and identify the business and technical risks most likely to affect successful deployment.
During the assessment, we can explore areas such as:
- Business readiness and executive sponsorship
- Decision support culture and stakeholder alignment
- Technical complexity and application novelty
- Data, systems, and implementation risks
- Deployment barriers and adoption challenges
- Risk mitigation strategies to improve project success
Following the assessment, Princeton will provide initial recommendations and outline practical next steps for reducing risk and improving the likelihood of successful deployment.
Contact us to schedule your complimentary assessment.
Read “The INFORMS Analytics Framework™: A Road Map for Success with Analytics” co-authored by Princeton Consultants Optimization Principal Irv Lustig, PhD, a former IBM ILOG CPLEX executive and Princeton University professor, award-winning computational mathematics expert, and renowned leader in optimization best practices.
Reference
White Paper: Assessing and Reducing Risks for AI Projects with the Princeton 20
About Princeton
Princeton Consultants helps improve operational performance through applied optimization. Since 1981, we have delivered more than 1,800 successful projects, including the design and implementation of custom AI Optimization systems for many of the best managed companies across a variety of industries.
Our assessments are led by Founder and CEO Steve Sashihara, author of The Optimization Edge: Reinventing Decision Making to Maximize All Your Companies’ Assets, www.optimizationedge.com, which describes his experience and study of optimization at many of the most successful and innovative companies; and by Optimization Principal Irv Lustig, PhD, an internationally recognized leader in operations research and advanced analytics, author of more than 30 articles and scientific papers, winner of the Beale-Orchard-Hays Prize for excellence in computational mathematical programming, and longtime active member of INFORMS, INFORMS Fellow, and Certified Analytics Professional-Expert.
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