Creating a Data Unification Foundation for Lean Management and Operational Efficiency

Context & Problem

The organisation faced fragmented data across manufacturing systems, limiting visibility, slowing decision-making, and constraining operational efficiency. Heavy reliance on Excel and disconnected sources made it difficult to scale data-driven practices.

In the discovery phase of the project, we focused on setting the foundation for structured data unification to align stakeholders, prioritise use cases, and define a scalable data architecture.

The result is improved visibility, faster decision-making, and a clear path toward measurable OEE improvements and increased manufacturing throughput.

Facts & Figures

The initiative established a foundation for improving Overall Equipment Effectiveness (OEE) by an estimated 3–11%, enabling increased output and better utilisation of existing assets. This creates the potential to defer capital expenditure by producing more with current infrastructure.

Through centralised data access and near-real-time visibility, teams can significantly reduce the time required to identify root causes and resolve production issues, improving responsiveness across manufacturing operations.

The discovery phase identified 43 potential use cases and 13 key challenges, enabling the creation of a prioritisation framework that focuses efforts on high-impact opportunities and quick wins to accelerate adoption.

Business Challenge & Why Accesa

Manufacturing operations relied on multiple disconnected data sources, including SAP systems, Excel files, and various applications. This fragmented landscape made it difficult to obtain a consistent and accurate view of performance across production lines.

Excel had become the primary tool for processing and visualising data, leading to siloed workflows, duplicated effort, and limited transparency. At the same time, the lack of real-time data availability limited teams' ability to respond quickly to operational issues or optimise production processes effectively.

Beyond technical challenges, the organisation faced the complexity of aligning multiple stakeholders with different perspectives and priorities. There was no clear overview of use cases or systems, nor a structured approach to prioritisation, making it difficult to define where to start and how to scale a data unification initiative.

Our first objective was to bring clarity to this complexity by structuring the data landscape, aligning stakeholders around a shared vision, and defining a practical roadmap for implementation. The focus was on enabling sustainable, organisation-wide data-driven decision-making rather than isolated technical improvements.

Solution & Impact

We established a strong foundation for data unification through a structured discovery phase and targeted initial implementations.

A key step was aligning business and technical stakeholders around a common vision for how data should support manufacturing and operational excellence. Through workshops and analysis, the initiative clarified objectives, identified pain points, and defined how data could be leveraged to improve decision-making and performance.

In parallel, we automated data extraction across multiple systems, reducing reliance on manual processes and enabling more consistent, reliable data flows. This laid the groundwork for centralising data in a unified repository that supports analytics and reporting across the organisation.

To ensure focus and momentum, a prioritisation framework was developed based on identified use cases and business impact. This allowed the organisation to target quick wins while building toward a scalable, long-term data strategy.

The resulting roadmap provides a clear path for implementing data engineering capabilities tailored to the organisation’s needs, supporting use cases such as supply planning optimisation, KPI dashboards, and productivity analysis.

Operationally, this approach enables faster issue identification, more consistent performance tracking, and improved decision-making across manufacturing teams. It also supports the adoption of Lean Management practices by providing reliable, timely data for continuous improvement initiatives.

Applicability & Current Status

The data unification foundation is designed as a scalable approach that can be extended across manufacturing sites, business units, and additional use cases. It provides a repeatable framework for organisations facing fragmented data landscapes and seeking to enable data-driven operations.

This approach is particularly relevant for manufacturing organisations with complex system environments and a strong reliance on manual data processing. By combining stakeholder alignment, use case prioritisation, and technical roadmap development, it ensures both strategic clarity and practical execution.

Future steps focus on implementing prioritised use cases, expanding data integration, and further embedding data-driven decision-making into daily operations.

By moving from fragmented data sources to a unified and structured data foundation, the client has taken a critical step toward more efficient, data-driven manufacturing operations. The initiative enables better visibility, faster decisions, and improved utilisation of existing assets.

If you are looking to establish a clear path toward data unification and unlock operational value from your manufacturing data, our specialists are ready to help.