Director of the Leeds MBA, now ranked in the Top 75 globally in the QS MBA rankings 2026.
Applied AI, analytics strategy and decision intelligence
Dr. Richard Hodgett
Senior academic and data leader helping organisations turn complex analytics, AI and decision science into practical capability, clearer choices and measurable impact.
At a glance
Data, AI and decision leadership with applied industry impact.
Led analytics, AI and insight-driven projects with public funding and industry partners.
Collaborations spanning music, logistics, legal-sector intelligence, manufacturing, sustainability and engineering.
Recognised by Poets&Quants in the 2025 Best 40-Under-40 MBA Professors list.
About
A practical academic leader at the intersection of analytics, AI and organisational decisions.
Richard Hodgett is Director of the Leeds MBA and Associate Professor in Business Analytics and Decision Science at Leeds University Business School. His work sits deliberately between academic rigour and real organisational use: developing decision-support tools, shaping analytics strategy, and helping senior leaders make better choices when data, uncertainty and commercial priorities meet.
Across academic leadership roles, he has led programme strategy, cross-functional teams, executive-ready reporting, advisory relationships and substantial budgets. His experience includes growing the MSc Business Analytics and Decision Science programme, leading education strategy in a large academic department, and directing a globally competitive MBA programme.
Richard's research and industry collaborations are applied by design. Projects have used machine learning, artificial intelligence, forecasting, decision science and multi-criteria decision analysis to support organisations in music, logistics, manufacturing, legal services, sustainability and engineering. He also teaches analytics and decision-making to MBA, executive and professional audiences, with an emphasis on practical methods that non-technical leaders can use.
Impact / Work
Selected applied projects
Case studies drawn from funded collaborations and industry-facing research projects.
Machine learning and talent identification
Universal Music
- Context
- A Knowledge Transfer Partnership to support and enhance the identification of new musical talent using machine learning, AI and decision science.
- Actions
- Served as Academic Supervisor, recruited and managed the associate, and supported development of a decision-support system using public platform data and TOPSIS prioritisation.
- Outcomes
- Created a system to help A&R teams prioritise content more efficiently and reduce the volume of material requiring manual review.
Manufacturing decision support
Syngenta and Britest
- Context
- An EPSRC-funded project to identify optimal manufacturing routes across supply chain, sustainability, logistics, labour and other decision criteria.
- Actions
- Led the first work package, recruited and managed a research fellow and developer, and developed a cross-disciplinary decision framework incorporating uncertainty through SURE.
- Outcomes
- Produced research outputs and supported creation of Decision.Help, a browser-based decision-making tool for individuals and teams.
Predictive analytics and operational efficiency
Clipper Logistics / GXO
- Context
- A Knowledge Transfer Partnership focused on improving processing efficiency and reducing costs in product returns from fast-fashion e-commerce.
- Actions
- Served as Academic Supervisor, recruited and managed the associate, and supported predictive analytics work for returns handling and client insight.
- Outcomes
- Supported client returns analysis, identified resale recovery opportunities, and influenced the creation of an analytics team.
AI-enabled business intelligence
Katchr
- Context
- A Knowledge Transfer Partnership to enhance legal-sector business intelligence software with AI, machine learning and tailored analytics.
- Actions
- Served as Academic Lead, recruited and managed the associate, and supported the development of AI-driven analytical and forecasting capability.
- Outcomes
- Contributed to Katchr Assist, an AI-driven assistant for analysing company data, making recommendations and improving payment and work forecasting.
Sustainability and industrial uptake
Project SPRING
- Context
- An EU-funded project designed to increase industrial uptake and impact from sustainability-focused SPIRE projects in process industries.
- Actions
- Acted as academic lead / Leeds Principal Investigator, recruited and managed a research fellow, and provided academic input on decision support and impact reporting.
- Outcomes
- Helped shape guidance for project participants, industry decision-makers and stakeholders on articulating project value, barriers to uptake and policy recommendations.
Recognition & Publications
Academic credibility, executive relevance and practical tools.
Selected links for more information and to demonstrate impact.
Poets&Quants 40-Under-40 MBA Professors
Recognition for teaching, applied research and business school leadership.
Smart Decisions textbook
A structured approach to decision analysis using MCDA, published by Wiley.
Decision.Help
A browser-based decision-making tool for individuals and teams.
Google Scholar
Research profile and academic publications.
University of Leeds profile
Institutional profile at Leeds University Business School.
Contact
For collaboration, AI projects or anything Leeds MBA.
Richard is available through direct email and professional networks.