Human-centric analytics: collaborative design for mathematics, AI and data-driven insights

Phillips, CJ ORCID: 0000-0001-5221-210X (2026) Human-centric analytics: collaborative design for mathematics, AI and data-driven insights. IMA Journal of Management Mathematics, 37 (3). pp. 737-766. ISSN 1471-678X

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Abstract

This paper introduces human-centric analytics (HCA) as a design paradigm for integrating mathematical models, data and human judgement into management decision-making. HCA addresses situations in which analytics must be understood, adapted and used within complex organizational settings, rather than treated as standalone technical artefacts. While human-centred design (HCD) offers useful principles for usability and participation, HCA addresses a different design problem. It focuses on the practical design and adaptation of analytical artefacts, techniques and processes, including the negotiation of model assumptions and appropriate levels of granularity. Drawing on a longitudinal case study in a pharmaceutical supply chain, the paper examines a series of analytics interventions involving forecasting, simulation, statistical analysis, visualization and data blending. Analysis of both successful and unsuccessful interventions shows how mathematical tools gained traction when they were developed through iterative engagement with users’ work, expertise and constraints. The paper presents HCA as an empirically derived and theoretically grounded design paradigm, supported by an umbrella framework organized around four recurring design activities: structuring perceptions, structuring empirical data, overcoming resistance and evolving solutions. The framework supports flexible combinations of tools and techniques, enabling analytics to become technically grounded, contextually meaningful and integrated into organizational practice. As data-driven systems and AI become increasingly embedded in management, HCA offers an approach for designing analytics that augment human practice rather than bypass it.

Item Type:	Article
Uncontrolled Keywords:	human-centric analytics; AI; pharmaceutical supply chains; decision making; analytics framework; 4901 Applied Mathematics; 49 Mathematical Sciences; Bioengineering; 8.1 Organisation and delivery of services; 0102 Applied Mathematics; 1502 Banking, Finance and Investment; 4901 Applied mathematics
Subjects:	H Social Sciences > HF Commerce > HF5001 Business Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Liverpool Business School
Publisher:	Oxford University Press
Date of acceptance:	14 May 2026
Date of first compliant Open Access:	28 August 2026
Date Deposited:	28 Aug 2026 12:14
Last Modified:	28 Aug 2026 12:14
DOI or ID number:	10.1093/imaman/dpag018
URI:	https://researchonline.ljmu.ac.uk/id/eprint/29219

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