The Challenge

Our client, a FTSE-250-listed e-commerce company, relies heavily on data to navigate highly seasonal, peak-driven trading periods. While the organisation boasts a strong, data-driven culture and a robust underlying technology platform, the Director of Data commissioned a comprehensive capability assessment to uncover performance gaps, benchmark against industry peers, and secure a framework for future investment.

The assessment quickly revealed a core friction point: a "two-speed" organisation. The central data team operated with a structured, platform-led culture, whereas the business teams were highly agile, chaotic, and trading-focused. This cultural clash left the Business Intelligence (BI) and Analytics teams trapped in a reactive cycle of ad hoc requests, leading stakeholders to view the data function as an unresponsive "black box".

Adding immense complexity to the engagement, the client announced an impending major reorganisation during the audit. The plan was to move the Business Analytics and BI teams out of the central data function and into the Finance organisation. This shift threatened to create "finger-pointing" silos, misaligned data metrics, and a fractured operating model.

Our Approach

To solve these challenges, we conducted a rigorous, architecture-led review, encompassing over 30 hours of interviews with 38 cross-functional stakeholders. Rather than just evaluating the technical estate, we benchmarked the client against major retail peers to provide actionable, industry-tested operating models. We immersed ourselves in the client's business, mapping the end-to-end data value chain from data ingestion to stakeholder value creation.

Strategic Recommendations

We provided the client with a strategic roadmap designed to modernise their service model and drastically de-risk their impending reorganisation. Key interventions included:

• Embedding "Business Partners": We recommended dismantling the centralised "concierge" service model for analytics. Instead, analysts would be embedded directly within commercial and marketing teams to establish deep business context, actively manage backlogs, and shape stakeholder demand.

• Curated Data Products Over Dashboards: To fix the broken self-serve model, we advised the team to stop building endless ad hoc visualisations. Instead, the focus was shifted to partnering across teams to build a shared semantic layer of curated data products, empowering business units to confidently answer their own queries.

• Peak Trading "War Rooms": To manage the immense pressure of seasonal trading peaks, we introduced a benchmarked "war room" model. During peak events, long-term engineering projects are frozen, and data resources are dynamically reallocated to provide real-time commercial responsiveness.

• Navigating the Reorganisation: To ensure the split of the data teams succeeded, we outlined a strict engagement framework. This included establishing clear hand-off boundaries, shared SLAs, and transitioning reporting toolset ownership to the newly formed Finance BI team, ensuring that both halves of the data ecosystem remained tightly aligned.

• Pivoting to Customer Centricity: We provided a framework to shift the business away from purely short-term trading metrics by investing in a robust Single Customer View, unlocking predictive modelling and deep personalisation.

Impact and Client Feedback

The engagement successfully provided the client's leadership with a transparent, actionable framework to restructure their teams, secure targeted headcount investments, and bridge the cultural divide between technical and commercial units.

The effort was highly praised for its deeply collaborative and empathetic approach. The client’s Director of Data commended the value of the partnership, stating: "Thank you for really immersing yourselves... spending the time with the team, surrounding yourselves with all our inner context, and properly walking the path in our shoes. That’s been hugely appreciated". The engagement was described as a "genuine pleasure" and a "great experience" that fundamentally repositioned how the business will leverage its data assets going forward.