Transforming Data and Analytics with Robust Data Architecture
We supported a chemicals company through their data and analytics transformation with a focus on building a robust Data Architecture.
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Situation
Our client faced several critical challenges: • Reliance on highly manual, desktop-based processing. • Aging legacy systems with limited integration and scalability options. • A highly fragmented data landscape, resulting in a lack of trust in data accuracy. • Limited organizational capabilities to meet data and analytics (D&A) needs. • Functions operating in silos with minimal transparency, integration, and governance. • A high volume of fragmented D&A initiatives, lacking clarity and direction.
Approach
• Conducted a current-state D&A maturity assessment of nine functions (e.g., finance, procurement, sales), covering data architecture, technology, and capabilities. • Designed a best-in-class future-state Modern Data Architecture, Data Operating Model, and Governance framework. • Facilitated workshops to define processes, policies, and governance, establishing a D&A Centre of Excellence (CoE). • Refreshed and prioritized the D&A portfolio based on desirability, viability, and feasibility. • Developed a D&A learning curriculum tailored to the needs of over 130 employees. • Delivered a D&A portfolio, including MVPs such as PowerBI dashboards and a target data model.
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Impact
• Implemented a fit-for-purpose Modern Data Architecture for full enterprise-wide roll-out, including a pragmatic roadmap for execution. • Established a D&A CoE with clearly defined roles, responsibilities, and an agile VC funding model. • Created a PowerBI dashboard with a transparent and prioritized D&A portfolio of 150+ initiatives, complete with a 3-year delivery roadmap. • Achieved an 80% uplift in understanding of agile methodologies across mid-management through agile coaching. • Significantly improved data accuracy, integration, and organizational transparency, driving more informed decision-making and operational efficiency.
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