A WICKED approach to retail sector energy management

Panel: 1. Foundations of future energy policy

This is a peer-reviewed paper.

Authors:
Kathryn Janda, Energy Institute, University College London, United Kingdom
Julia Patrick, University of Oxford, United Kingdom
Ramon Granell, University of Oxford, United Kingdom
Susan Bright, University of Oxford, United Kingdom
David Wallom, University of Oxford, United Kingdom
Russell Layberry, University of Oxford, United Kingdom

Abstract

The UK retail sector is vital to the economy, diverse, and facing a number of challenges. Retailers range from multinational corporations to small independent stores. Across the sector, energy costs and requirements for understanding, displaying, and reporting energy use are increasing. Meanwhile organisations face competing pressures to “go local”, support staff development, and keep prices down. Because of this diversity, retail energy management creates a “wicked” problem, where solutions to challenges are contentious and multi-faceted. The Working with Infrastructure Creation of Knowledge and Energy strategy Development (WICKED) project provides energy solutions for different retail market segments. Through cooperative research, WICKED investigates clusters of technical, legal, and organisational challenges faced by retail groups, including those with smart meters and energy managers (the “data rich”) and those without (the “data poor”). In partnership with stakeholders, WICKED develops actionable insights by combining (1) top-down big data analytics, (2) middle-out organisational research, and (3) new bottom-up data. Building on this interdisciplinary evidence base, WICKED co-designs market-ready energy strategies to fit the retail sector’s diverse needs. The project uses a segmented socio-technical model to explore challenges faced by 6 different types of stakeholders in the retail market: data rich and data poor owner-occupiers, landlords, and tenants. This paper presents data from 3 different organizations: a European electronics retailer; a multi-national full-service department store; and a budget shopping centre with 91 units. These cases show that one size does not fit all: the data rich and poor will need different energy management solutions. Smart meters will not solve everything: further analysis is necessary to turn numbers into knowledge. Changes to legal infrastructure (e.g., leases) will be needed to assist tenants and landlords in sharing data to enable both groups to monitor, measure, and report energy use. Additionally, how organisational cultures frame employee duties, behaviours, and expectations requires further investigation.