Promotion Optimisation at Harrods

I spearheaded a Proof of Concept project aimed to optimise promotion thresholds during Harrods’ January sales. This initiative was designed to enhance the effectiveness of their promotional strategies, resulting in a significant annual revenue increase.

Problem

Harrods faced challenges in maximising revenue during their January sales due to suboptimal promotion thresholds. The existing strategy did not fully leverage data-driven insights to enhance promotional effectiveness, leaving potential revenue on the table or resulting in unsold stock.

My Contributions

As a Senior Data Scientist, I developed a model that identified optimal promotion thresholds. This solution provided actionable insights for retail teams that informed strategic shop-floor decision-making.

Outcomes

The project led to an impressive £500,000 revenue uplift, demonstrating the power of data-driven strategies in retail promotions, and was taken to production the following sales period.

Unstructured Data Management for Lloyds Banking Group

I led the unstructured data agenda for analytics and machine learning at Lloyds Banking Group. This initiative aimed to enable data scientists and analysts to access unstructured data in a safe and secure way following the migration of the machine learning platform to Google Cloud.

Problem

Lloyds Banking Group had vast amounts of unstructured data, which was siloed, not well documented and yet crucial for informed decision-making and maintaining a competitive edge.

My Contribution

As Engineering Lead, I spearheaded the unstructured data initiative, working with the Cloud Migration team to define functional and non-functional requirements for unstructured data management and analytics.

Outcomes

By driving the unstructured data agenda early in the cloud migration process, Lloyds Banking Group were able to leverage this data in time for the ChatGPT and Generative AI boom, gaining critical insights whilst ensuring data governance and security

Promotion Optimisation at Harrods

I spearheaded a Proof of Concept project aimed to optimise promotion thresholds during Harrods’ January sales. This initiative was designed to enhance the effectiveness of their promotional strategies, resulting in a significant annual revenue increase.

Problem

Harrods faced challenges in maximising revenue during their January sales due to suboptimal promotion thresholds. The existing strategy did not fully leverage data-driven insights to enhance promotional effectiveness, leaving potential revenue on the table or resulting in unsold stock.

My Contributions

As a Senior Data Scientist, I developed a model that identified optimal promotion thresholds. This solution provided actionable insights for retail teams that informed strategic shop-floor decision-making.

Outcomes

The project led to an impressive £500,000 revenue uplift, demonstrating the power of data-driven strategies in retail promotions, and was taken to production the following sales period.

Background

This project involved designing and implementing a comprehensive AI strategy for Pandora Global. The goal was to transform their AI capabilities across various domains including machine learning, infrastructure, and analytics, while enhancing team capacity, governance frameworks and company-wide AI literacy.

Problem

Pandora had a plethora of proprietary data, from manufacturing to marketing, but without an effective strategy to leverage this resource to optimise their operations and bottom line.

Contributions

As Global AI Director for a 14-month contract, I crafted and executed a strategic AI roadmap which aligned with Enterprise goals, covering products, infrastructure, governance, team and literacy. I also led the evaluation and adoption of generative AI tools and established governance frameworks.

Outcomes

Over $3M in increased revenue through AI-driven marketing optimisations, a 160% growth in the AI team, and development

AI Transformation and Strategy

I led a comprehensive AI transformation assessment for Hey Savi, focusing on evaluating resources, architecture, solutions, and governance. The goal was to develop a robust long-term AI strategy to boost their AI capabilities and improve business outcomes.

Problem

Hey Savi needed to enhance their AI capabilities to stay competitive. They lacked a cohesive strategy and faced challenges in resource allocation, architecture optimisation, and solution deployment.

My Contribution

I conducted a thorough technical and team audit, resulting in a detailed SWOT analysis, risk assessment and 5-year AI strategy. I used skills in Agentic AI, machine learning, data architecture, team and stakeholder management.

Outcomes

The creation of a clear SWOT analysis, risk assessment and 5-year AI strategy refocussed and aligned the Founders and technical teams, significantly enhancing Hey Savi’s AI capabilities and positioning them for future success.