DataNovata Enables Digital Threading Across Manufacturing BOMs

Manufacturers Struggle to Implement Digital Thread

In 2023 Gartner analysts revealed that 91% of manufacturers surveyed claim to have either implemented, are implementing or plan to implement digital threads*.

However, Gartner predicted that “By 2024, 75% of CIOs at asset-intensive manufacturing firms engaged in digital thread programs will face delays due to BOM challenges encountered during the implementation program.” This prediction reflects the disillusionment IT teams are feeling as their digital threads fray.

Why is Digital Thread a Priority?

A digital thread is an end-to-end data view of any tool/process/role that connects related part and product data from across the entire lifecycle, from design to production, delivery, maintenance and retirement. It also connects any associated data points, whether due to sensors, financial information or customer engagement. The goal is to create a transparent view of any part to manage its lifecycle and deal with issues effectively when they arise.

Why are Digital Thread Implementations Failing?

The difficulty lies in stitching Bills of Materials (BOMs) across various systems, to connect all the data pertaining to a specific part together.

1. Interoperability

   The multiple operations within a manufacturing process operate their IT independently and BOMs will sit on different types of systems, which may not be fully integrated.

   Additionally, manufacturing departments reference BOMs with styles and terminologies that best suit the way that department interprets and uses the data. This makes it difficult for digital threads to gather relational data when there are no related terms between departments.

2. Legacy Silos

   Parts with long data lifecycles may have some or all of their data stored on systems that are no longer in use at the company. This means a part could still be in use, and therefore new data is being generated based on sales or repairs, but the early data needed to get a full picture of that part is locked in an archive that is not compatible with current systems. This makes it difficult to maintain an efficient and compliant PLM strategy.

To illustrate:

A piece of heavy machinery currently in use is in need of repairs and replacement of parts. The piece entered its service life 15 years ago and the parts needed are no longer in production, requiring a redesign. The BOM data from 15 years ago is locked within a legacy system.

Not only is there no easy way to bring up historic BOM data against current data, there is no clear path between engineering, lifecycle, and other necessary BOMs. This impacts decision making, compliance and service delivery as the best way forward is obscured.

Essentially, manufacturers don’t have enough thread to patch their BOMs together. As such, most digital threads are relegated to connecting BOM data within a single department. Hardly the end-to-end visibility CIOs were hoping for.

Yet Gartner still rates the benefits of digital threads highly, as they are a huge aid to decision making and compliance and streamline processes across the board. They are also essential to creating digital twins which allow for modeling and experimentation.

How Can Manufacturers Achieve their Digital Thread Goals?

Manufacturers need to level the playing field in 2 directions:

1. Establish a common data platform to break down the barriers between application silos
2. Link all databases to the data platform and index the search capability to enable threading of any data relationship between parts at any point in the life cycle through dynamic inquiry.

DataNovata has Successfully Modernized Access for Large Manufacturers

In one instance, we helped IMI Precision Engineering, a world leader in fluid and motion control technologies with customers spanning decades of service, who faced this problem when Microsoft shut down support to WS2008, threatening secure access to their historic BOMs. It used DataNovata to migrate and re-engineer access to 20 years of BOM history for parts tracing and maintenance for continued service delivery.

In another case, DataNovata rescued 20,000 BOM data files across multiple systems for a leading aerospace manufacturer. Their compliance and access security was at risk as their legacy systems were going out of service.

Both of these manufacturers have used DataNovata to scale the solution across multiple systems as a common data platform. Both achieved smooth, referential access to their historic BOM data that can now be threaded to their live systems.

Gartner research has already recognized DataNovata's capability as a digital thread vendor. You can read more about that here.

Continuous Value Through Connected Data

Digital Thread is one case where DataNovata provides continuous value for manufacturers. DataNovata is a web-enabled data access solution that:

1. Breaks down application silos

   DataNovata can access and interpret data from practically any system and present multi-database data within a single view regardless of the source.

2. Has contextual search capabilities

   DataNovata recognizes the relationships between your data sets. The smart search functions will account for variations in data semantics. You can personalize search capabilities to create relationships with the terminologies used across departments.

3. Eliminates Technical Debt

   DataNovata replicates all data tables and relationships within a new server so that the legacy systems can be retired.

With DataNovata, manufacturers are better equipped to build digital threads that interpret data meaningfully across their BOMs across active and nonactive systems. This supports the end-to-end view of the parts lifecycle, empowering decision-making, compliance, and customer delivery.

Find out what DataNovata can do for your manufacturing company by booking a free demo today.

For more information about this article, you can contact our Press Office.

*Gartner Inc “Top BOM Practices for Building Digital Threads in Discrete Manufacturing Industries” Published 23 February 2023 - ID G00736769 By Analyst(s): Marc Halpern, Sudip Pattanayak, Christian Hestermann, Rick Franzosa