Case: Product Information Management and Lifecycle Management Development Project

At an industrial technology company, our R&D MDM department was responsible for leveraging and refining industrial data. Key focus areas included process data analytics, Industrial IoT (Industrial Internet), predictive maintenance, and advancing the intelligence of automation systems. We developed and maintained automation and Industrial Internet solutions that collected and analyzed production data from plant sites. 

The challenge 

Different teams operated from different definitions. Engineering, R&D, manufacturing, supply chain, sales, and service used inconsistent structures, names, and versions. Bills of materials, specifications, and configurations changed slowly and without clear traceability. The result was repeated rework, compliance gaps, and delayed time to market. 

What Ikoni delivered

Ikoni helps to build Product Data and Lifecycle Management capability to align data and processes. We helped to develop and maintain data on current and upcoming systems to keep the organization synchronized through transitions. The program focused on three sub-capabilities and delivered four core capabilities that removed friction and restored control. 

1. Product data lifecycle management 

Ikoni established and maintained a unified product data model, making product information structured, validated, and accessible across systems. Engineering artifacts and downstream systems were aligned, so manufacturing and customer channels used the same authoritative data. Product information became auditable and available to R&D, Engineering, Operations, Sales, and Service. Ikoni maintained global dataset across both current production systems and systems planned for rollout, ensuring continuity during migrations and upgrades. 

2. R&D and engineering change management 

Ikoni modeled engineering changes, including product structures, bills of materials, and specifications, inside an end-to-end change workflow. Approval and deployment processes routed changes to the right stakeholders and systems. Version control, traceability, and impact analysis ensured every change carried context and history. By maintaining change data on both active and upcoming platforms, Ikoni reduced risk when shifting systems and preserved traceability across transformation waves. 

3. Standard product data governance 

Ikoni applied and maintained R&D & engineering and governance rules, templates, and classification models to standardize product variants, attributes, and metadata. Stewardship responsibilities and quality controls enforced uniformity across product families, reducing ad hoc variation and data drift. Governance extended to datasets used by future systems, so templates and classification models remained consistent as the technology stack evolved. 

Key capabilities delivered:

• Unified product data model that created a single source of truth and eliminated conflicting definitions. 
• End-to-end master data and lifecycle management workflows, from proposed changes to approved deployments across PLM, ERP, CRM, and manufacturing systems. 
• Data governance framework that enforces standards and reduces variations in product metadata. 
• System data integrations and synchronization that validate data across PLM, ERP, CRM, manufacturing, and upcoming platform landscapes. 

Business outcomes 

The results were practical and measurable without bespoke metrics. Operational errors caused by inconsistent product data declined because teams referenced a single, governed model. Controlled engineering change workflows reduced rework and approval delays, shortening time to market. Improved traceability and version control strengthened compliance and audit readiness. R&D, Engineering, and business operations aligned more closely, enabling faster, safer decisions. 

Why it mattered 

The program did more than tidy data. It created predictable pathways for change. Engineers could propose and assess modifications with immediate visibility into downstream impacts. Manufacturing and supply chain teams received consistent specifications. Sales and service teams delivered accurate information to customers. By maintaining product data across current and upcoming systems, Ikoni ensured that change management practices and data integrity survived platform transitions. Change ceased to be a disruptive event and became a managed, auditable process. 

What success looks like going forward 

With a governed product data backbone, the company can scale product complexity without multiplying risk. Standardized templates and stewarded metadata reduce onboarding friction for new products and suppliers. The established change workflow supports continuous improvement while preserving traceability for audits and regulatory requirements. Keeping data current on both existing and planned systems reduces migration risk and accelerates adoption of new tools. In practice, product development and operations move faster, with fewer surprises. 

Conclusion 

Ikoni’s Product Data and Lifecycle Management capability united people, processes, and systems around trustworthy product data and roadmaps for system change. By combining a unified data model, rigorous change management, effective governance, and maintenance of data on current and upcoming systems, the client reduced errors, accelerated time to market, and improved compliance, enabling aligned, confident decision making across the organization.