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Data Management Definition in Your Workflow Process IP

Published Date
Author Cadence PCB Solutions

Key Takeaways

  • A data management system helps you track product documentation and important data for a new design.

  • Electronic products contain diverse sets of data that need to be tracked and managed.

  • Data management systems for electronics are used as part of product lifecycle management (PLM).

Data management definition

Electronics engineering teams at large companies achieve product dominance through their design data management strategy and the intellectual property they create. Not only is product design data a form of intellectual property, but so are all the processes that exist to enable manufacturing, distribution, simulation, testing, and much more for a new product. In today’s environment of digital transformation and integration across enterprises, manual processes of the past are being fully digitized into a centralized, integrated workflow that comprises a company’s IP.

The workflow and design process you use to develop and market your products is just as important as the products themselves. Some product data management systems provide a front-end interface for accessing product data and defining process IP, but these tasks are always part of a larger objective: product lifecycle management, or PLM. To ensure you can effectively implement PLM in your organization, there should be a clear definition of data management objectives and processes within and across business units.

Data Management Definition in Workflow Process IP

The definition of data management for electronics engineers spans far beyond electrical drawings and physical layout files. The data these teams have to manage will need to be accessible by multiple parties so that an entire product can be designed. Similarly, other teams may need access to electrical and physical layout data so they can engineer their portion of the product. Data management software solutions intend to enable the processes that teams will implement to comprehensively move through product development and execute a go-to-market strategy.

Electrical design
  • Compile all design files into a single location with a part/document/drawing numbering system
  • Link all components in the design to procurement information

Mechanical design
  • Product enclosure details, the completed assembly, mechanical models, and 3D model files need to be created for any important project elements

Manufacturing data
  • Manufacturing files should be available in the same system alongside all the design data so that the files can be directly compared as needed
  • Data management platforms should allow defects or errors from production to be indicated directly in the design files and documentation

Product documentation
  • Includes datasheets, application notes, block diagrams, functional diagrams, and even marketing/sales collateral like presentations and webinars
  • Users should have the ability to make specific pieces of data customer facing or internal only to support enterprise-wide processes

Application code
  • Products that include an embedded application, web application, downloadable resources, or other software should have the software available in the data management system

Revisions and version control
  • Change orders and tracked changes for each revision should be accessible
  • Version control systems are normally used to track revisions, clone projects at specific revisions, and track changes throughout project histories

There are plenty of goals to accomplish in the above list, so how can engineering teams ensure they hit all of these points as they define their design data management process? The answer depends on the defined scope of data management tasks to be performed, which will often scale with team and company size.

Data Management Processes Should Scale

As a company scales and encounters growing pains in its data management and product development processes, the scope of data management tasks within a PLM strategy must also scale. Smaller companies and individual designers will implement data management practices that are very different from large enterprises. Very large companies may have multiple product lines, multiple business units collaborating with each other, and stakeholder interests to consider. This all requires a comprehensive data management strategy that centralizes data and enables a PLM strategy. If implemented correctly at each level, companies can stay efficient and ensure their products are competitive as their products reach the market and the organization grows.

data management definition

Individual engineers do implement a data management strategy, but it generally rests in a particular place: the engineer’s hard drive. As designers scale their project count and the amount of customer data they need to store, they might use a cloud file storage service. However, they are typically not granting external file access to anyone and will not have access to those files in any other design or management software.

At the SMB level and enterprise level, things are very different. Stakeholders will need to access data, including internal stakeholders that will perform other important business functions required to take a product to market. SMB’s will usually find that they are great at handling and tracking design data in their workflows until other stakeholders need to access data to perform their business functions. At that point, it may be time to graduate to a defined data management system that enables a full PLM strategy.

The Heart of PLM Is Data Management

Data management solutions are part of an important business process: PLM. Every business that creates products, whether they are physical or digital, needs to ensure alignment among product data packages, stakeholders, and business processes that will execute a go-to-market strategy. Throughout the product data management process, companies need to accomplish three goals in their PLM strategy:

  1. Manage development tasks and continuously improve a product throughout its lifecycle
  2. Ensure stakeholders can access and view the product data they need
  3. Guide a product’s journey through the marketplace and eventually into retirement

Innovative companies define their data management processes and tasks as part of their PLM strategy so that they can remain competitive. As your organization grows, you’ll eventually need a comprehensive data management system like Allegro Pulse from Cadence. The PLM features in this platform help electronics development teams move through the entire development process, push products to production, and access data needed to distribute and maintain products while monitoring obsolescence and the supply chain. Keep your products competitive and maximize your product lifecycles with the industry’s best PLM solution.

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