Dr Christina Phillips
- Position: Lecturer in Business Analytics/Statistic
- Email: C.Phillips1@leeds.ac.uk
- Phone: +44(0)113 343 6850
Diploma in Physics and Mathematical Modelling, Open University
BSc Joint Honours in Mathematics and Physical Oceanography, Bangor University
PhD in Operations Management and Business Analytics, Bangor University
Current Position at Leeds University Business School
Lecturer Business Analytics/Statistics
Visiting Researcher, forLAB, Bangor Business School (forlab.eu)
Business Analyst/Researcher, Siemens Healthineers, Gwynedd
R&D Manager, forLAB, Bangor Business School (forlab.eu)
Awarded the Siemens/CoBLESS PhD Studentship
Dr Christina J. Phillips has an eclectic background from tutoring in Physics and Statistics to running her own art and design company. Her specialism has always been in Mathematical Modelling but through recent in-industry research this has been extended to include ways to facilitate and maximise benefit from participative modelling and design.
Her work has helped to improve operations and promote cultural change in a multinational organisation. Leading to substantial savings across the organisation and moving it toward a more questioning data driven culture.
Christina also worked for four and half years as a Business Analyst and Researcher at Siemens Healthineers, providing senior management and staff with Business Intelligence and improving their data management. In this work she gained an understanding of the analytics needs of businesses and experienced first-hand many of the difficulties faced by organisations in moving toward a data driven culture.
In 2015 Forbes predicted that embedded analytics could save US companies $60 B by 2020 but, in order for companies to leverage the full capabilities of analytics in their organisations, the human analytics interface must be robust and fit for purpose. This is especially so in uncertain environments where the reliance on human decision making and management is high, but how can we achieve this?
Dr Christina Phillips research into reducing uncertainty in human processes via analytics has led to the development of a multi-methodology approach called Human Centric Analytics (HCA) . By coupling various methods she has illuminated how participative analytics development has the power to facilitate change and alter perceptions as well as provide decision tools. By putting humans at the centre of analytics development we can augment their work, enhancing productivity and increasing efficiency.
Using this HCA approach in a complex semi-process industry, during a longitudinal case study, Christina was able to augment lean development and facilitate an iterative process of production smoothing. This led to productivity savings and a shift in perceptions enabling a more inquisitive and data enabled culture. It also provided insights into the use of lean in non-discrete environments.
Dr Phillips is the first researcher to have explicitly used an Action Research approach to improve forecast use and understanding throughout the operations and supply chain of a global manufacturer. In a complex business setting it is sometimes difficult to capture all of the relevant information in our data systems and there is a tendency for individual units to silo. Under these conditions models which only capture process and data can fall short of expectations and miss nuances which are held implicitly by the organisation. Using methods such as Action Research together with contextualised explanatory models we can enhance engagement and create new organisational pathways to understanding.
Dr Christina Phillips has over 15 years teaching experience in subjects ranging from Physics and Fluid Mechanics to Statistics and Business Analytics. She has taught at all levels and abilities and is an evangelist for STEAM (Science, Technology, Engineering, Art and design, and Mathematics) having volunteered for many years as a STEM ambassador.
At Leeds Christina teaches Business Analytics and Statistics at both undergraduate and postgraduate level. Bringing to bear her experience working as an analyst and helping students to get the most out of critical thinking and applied mathematical skills.
Module leader for;
LUBS2920 Advanced Analytical Methods
LUBS5308M Business Analytics and Decision Science
LUBS1525 Analytical Methods
LUBS5582M Research Methods
Christina also remains a visiting researcher at forLAB and gives guest lectures at other institutions.
Reducing uncertainty in human processes via analytics