Engineering Consultancy Recovers to £80M in 12 Months, Goes Paper-Free in Production

Context

A global engineering consultancy with significant manufacturing operations set out to establish a new AI-driven Industry 4.0 practice focused on rapid diagnosis of shop-floor challenges and a structured transformation to paperless systems and real-time data capture and analysis. The organisation operated multiple production lines in series manufacturing and had not invested adequately in frontline digital systems for over a decade. The objective was to combine PLC-connected data capture, augmented frontline applications and AI analytics to create a repeatable transformation model that delivered operational clarity, regulatory compliance and a turnaround in financial performance.

Challenges

Data quality and accessibility were the primary obstacles. Scrap, work-in-progress (WIP), quality checks and logistics were recorded on paper across multiple shifts and sites. Where data existed, it was often inaccurate and stale by the time it was collated, preventing timely decisions and masking root causes of losses. This lack of reliable production data undermined pricing accuracy, margin analysis and supply chain responsiveness.

The business also faced strict industry regulation and customer security requirements that demanded stronger information security and traceability. A long period of underinvestment left IT and maintenance teams underscaled, with limited career progression and insufficient capability to support a modern, connected factory. Finally, the organisation was operating on a deteriorating financial trajectory and needed a transformation that could deliver measurable recovery and sustainable profitability within a short time horizon.

Implementation

The programme began with rapid diagnostic workshops on the shop floor to prioritise pain points and identify quick wins. Frontline operational systems were implemented that connected directly to PLCs and augmented human inputs with barcode scanning, digital checklists and operator guidance. This enabled automated capture of scrap, cycle times, quality defects and logistical movements in real time. Data streams were normalised and fed into live dashboards and reporting tools to give leaders and shop-floor teams immediate visibility.

AI was used in two complementary ways: to accelerate development and iteration of frontline applications, and to analyse noisy legacy and new data to reveal patterns. Algorithms were built to cross-match disparate sources — PLC telemetry, manual inputs, ERP records and inspection logs — to create a reliable master data set. That master data set supported accurate cost-to-produce calculations and informed revised pricing structures. AI also mapped recurring causes of downtime and quality escapes, guiding targeted kaizen activities.

Governance and compliance were addressed through coaching and implementation of standards-based documentation. The programme implemented recognized security and information assurance frameworks, including TISAX and ISO 27001, and used AI to accelerate the generation, review and maintenance of policies, risk assessments and evidence packs. This reduced the administrative burden while improving audit readiness.

A strategic plan for IT and maintenance teams was developed: headcount growth, clear career progression, and skills development aligned with the new Industry 4.0 stack. The programme acted as a board-level champion to secure funding and organisational space, enabling existing heads to obtain the resources they had lacked for a decade. Operational migration included moving from an on-premises CRM to an AI-driven cloud CRM platform to improve customer insights and sales operations.

Results

Within 12 months the transformation contributed to a dramatic financial turnaround: the company moved from a -£20m loss to an £80m recovery. Reliable, real-time production data and the master data set enabled accurate pricing and margin decisions that directly improved profitability. Cross-matched algorithms exposed hidden cost drivers and supported corrective actions that reduced scrap and rework.

Production became fully sustainable and paper-free in series manufacturing, with PLC-connected data and operator-driven digital inputs forming the single source of truth. Real-time dashboards empowered frontline supervisors to act immediately on quality and logistics issues, reducing lead times and improving on-time delivery.

Compliance posture was strengthened through the implementation of TISAX and ISO 27001 aligned documentation and controls, supported by AI-assisted risk management. The IT and maintenance functions were scaled and professionalised, with clearer career pathways and capability to support ongoing digital initiatives. Migration to an AI-driven cloud CRM improved customer data quality and commercial responsiveness.

Overall, the integrated approach—combining rapid diagnosis, PLC-connected capture, AI analytics, standards-based governance and team scaling—reversed the company’s financial trajectory and established a repeatable Industry 4.0 practice capable of sustaining profitable, paper-free manufacturing.