First Name
Jean

Last Name
Essila

Email
[email protected]

Picture

Title
Associate Professor

Office
SCB 3109

Phone
(616) 331-7475

Department
Management

Expertise
• Management Information Systems • Enterprise Resource Planning (ERP) and SAP Systems • Artificial Intelligence for Business • Autonomous AI Agents and Digital Employees • Multi-Agent AI Systems for Business and Operations • AI-Driven Inventory, Operations, and Supply Chain Management

Biography
Professor Jean C. Essila, PhD, DBA, is an Associate Professor of Management Information Systems at Grand Valley State University's Seidman College of Business. He earned a PhD in Engineering Management from the School of Engineering and Applied Sciences at George Washington University and a Doctor of Business Administration in Business Management from California InterContinental University. He also holds certificates in Higher Education Pedagogy and Business Analytics from Harvard University. Professor Essila is an SAP-certified consultant and an ERPsim-certified instructor. He is a Certified Supply Chain Professional (CSCP) and holds the Certified in Logistics, Transportation, and Distribution (CLTD) designation from APICS/ASCM. Before returning to GVSU in 2020, Professor Essila was on the faculty at Northern Michigan University from 2016 to 2020. During his time there, he earned three major academic honors: the Outstanding Research Award, the Outstanding Graduate Faculty Award, and the Excellence in Scholarship Award, which is the university’s highest recognition for scholarly achievement. This award recognized his contributions to discovering, sharing, and applying knowledge, along with his influence on student learning. Prior to his academic career, Professor Essila held senior leadership roles in global and Fortune 500 companies, including Perenco Oil and Gas and Johnson Controls North. America, and ExxonMobil. Over more than 15 years in the industry, he led initiatives in operations, enterprise systems implementation, process optimization, and technology-enabled decision-making across complex organizational environments. His current research and applied work focus on designing, implementing, and governing artificial intelligence systems for business, with particular attention to autonomous AI agents, multi-agent AI systems, and digital employees integrated into organizational workflows. He collaborates closely with the business community to identify operational and strategic challenges and to develop AI solutions, including AI-driven inventory and materials management, intelligent process automation, ERP and CRM enhancement, and decision-support systems for operations and supply chains. His work explores how agentic AI architecture, AI-enabled robotic process automation, and intelligent enterprise systems enhance efficiency, resilience, and decision-making in small and mid-sized organizations. Professor Essila has authored multiple books, book chapters, and peer-reviewed journal articles and has presented his research at leading national and international conferences.

Education
PhD, Engineering Management, George Washington University (2018) DBA, Business Management, California InterContinental University (2013) Certificate in Higher Education Pedagogy, Harvard University (2018) Certificate in Business Analytics, Harvard University (2020)

Teaching Areas
Management Information Systems Artificial Intelligence for Business Autonomous AI Agents and Digital Employees Multi-Agent AI Systems for Business and Operations ERP Systems and SAP Systems Operations and Supply Chain Management

Publications
Essila J.C., Motwani, J. (in press, 2025). Efficacy of Seasonal Factor-Adjusted Naïve Forecasting in Operations Management: Insights from a Simulation Study. Operations Management Education Review, 18. Essila, J. C. (2024). A Regression Model to Identify Supply Chain Cost Drivers in Healthcare and Make Cost Predictions. International Journal of Business Innovation and Research, 35(4), 497-516. Essila J.C., Motwani, J. (in press, 2025). Efficacy of Seasonal Factor-Adjusted Naïve Forecasting in Operations Management: Insights from a Simulation Study. Operations Management Education Review, 18. Essila, J. C., Motwani, J., Hassana, A. K. (2024). Investigating ERP Systems Adoption by Medium-sized and Large Companies in Developing Countries. International Journal of Business Information Systems. Essila, J.C. (2023), "Strategies for reducing healthcare supply chain inventory costs", Benchmarking: An International Journal, Vol. 30 No. 8, pp. 2655-2669. Essila, J. C., Motwani, J. (2023). Unmasking Health Care Supply Chain Cost Drivers in the United States. Benchmarking: An International Journal. Vol. 31 (4): 1350–1382. Essila, J. C., Alhourani, F., Motwani, J. (2021). Using Concept Maps in Teaching Operations Management Courses. Decision Sciences Journal of Innovative Education, 19(1), 15-39. Alhourani, F., Essila, J. C., Farkas, B. (2021). Preventive maintenance planning considering machines’ reliability using group technology. Journal of Quality in Maintenance Engineering,