Modernizing Data and Analytics for a Manufacturing Software Platform

The client is an industrial software provider delivering a manufacturing execution platform used by operators, supervisors, and plant leadership. As customers increasingly demanded real-time visibility, configurable reporting, and actionable insights, the organization recognized the need to modernize its data and analytics capabilities.

The platform’s existing analytics experience was outdated and misaligned with modern manufacturing needs. Customers were limited to a small set of static KPIs with no interactive dashboards or self-service reporting. As a result, many relied on spreadsheets or third-party BI tools, creating fragmented data sources, slow decision-making, and inconsistent insights across roles.

From a technical perspective, the analytics architecture had not kept pace with evolving expectations. Front-end technologies required modernization, data models limited flexibility, and the platform lacked a clear path toward advanced analytics and AI readiness.

Key challenges included:

• Static KPIs with no interactive, role-based dashboards

• No self-service reporting or configurable analytics

• Poor user experience across operator, supervisor, and manager roles

• High reliance on manual exports and external BI tools

• Limited readiness for predictive analytics or AI-driven insights

Connective partnered with product, engineering, UX, and business stakeholders to lead a focused discovery centered on data and analytics modernization.

The engagement followed a structured, multi-week discovery process that included:

• Stakeholder interviews across shop-floor operators, supervisors, plant managers, and leadership

• Current-state assessment of analytics architecture, data flows, and front-end capabilities

• Definition of a customer-driven, role-based KPI and dashboard framework

• Discovery of self-service reporting needs, templates, and usability expectations

• Exploration of real-time alerts and notifications tied to KPI thresholds

• Evaluation of data quality, structure, and accessibility to assess AI readiness

The goal was clarity—aligning business value, user needs, and technical feasibility before moving into delivery.

• A role-based KPI and dashboard framework tailored to operators, supervisors, and managers

• Defined requirements for interactive dashboards and self-service reporting

• An expanded KPI library aligned to real manufacturing decision-making needs

• A modernized analytics architecture vision, including HTML5 front-end considerations

• Clear requirements for real-time alerts and performance notifications

• An AI-ready data foundation to support future predictive and anomaly-detection use cases

• A phased roadmap outlining MVP analytics capabilities and future enhancements

• Strong alignment across stakeholders on analytics priorities and scope

• Reduced reliance on spreadsheets and third-party BI tools

• Improved clarity on how analytics should support real operational decisions

• A scalable foundation for advanced analytics and AI-driven insights

• A shared, actionable roadmap guiding future development investment

By focusing on user-driven discovery and pragmatic architecture, Connective helped the client transform analytics from a static reporting function into a strategic capability—positioned to drive better decisions today and enable AI-powered insights tomorrow.