Savvy organizations refuse to underestimate the value of the data they generate from the CAD process.
Even though most designers re-appropriate ideas from designs they’ve worked on in the past, these efforts rarely translate into a systematic approach the entire company leverages.
This leads to duplicated efforts and inefficiencies, especially in larger organizations in which one design team may not be aware of what others are working on.
Some designers and engineers would be reinventing the wheel before they realized that someone in another department has already solved the problem.
To avoid such inefficiency, organizations need to consider design data as an asset. To heighten the value of said data, the key is to put systems around its reuse.
Data reuse allows designers and engineers to leverage information from existing designs in new product development to create better products while maximizing value with minimal resources, cost, and effort.
Strategic reuse of design data can help organizations achieve the following:
An increase in design rapidity and continuity, which has a direct impact on time-to-market.
Improvements in product quality and reduced errors by using designs you’ve already tested.
Lowered costs through reducing the number of simulations and tests required to validate a new design or component.
For product data reuse to deliver organization-wide benefits, companies need to have the necessary software, training, and support. These five best practices highlight the ways companies can glean solid results from the dedicated use of design data management software:
In traditional design and engineering practices, each project carries its own cost.
Design teams tend to set up the data in a way that’s most convenient for them, rather than taking the extra effort to structure it for expedient reuse.
To facilitate design reuse, establish company-wide systems and protocols so teams can share and communicate information effectively.
That means you’ll want to extend ownership of data from each program or project to the entire enterprise, where appropriate, and as such you can distribute costs. Keep in mind, this approach requires an enterprise-wide data governance protocol.
To optimize the ROI of data reuse within the organization, create a systematic approach to the product development process.
Start by developing a framework for data reuse – retrieve, reuse, repair, and recover – and instill it as part of the company culture.
In particular, encourage data reuse when conducting new product development initiatives. A formal approach to conducting data reuse can help increase adoption throughout the organization.
One of the challenges of reusing data is matching a customer’s specifications to existing designs. Establishing a searchable knowledge base can help facilitate effective data reuse across design teams.
The design and engineering industry is fast evolving, so it’s important to develop a system that allows design teams to evolve and adapt existing data to take full advantage of changes and improvements where they make the most sense.
Having the ability to apply specific coding to parts and assemblies so you can retrieve and reuse the design data efficiently is the key to creating the agility an organization needs. This will help you adapt design data as you strive to meet new technological requirements and market needs.
Product design data is only as good as the access and ease of adoption it provides design and engineering teams.
Consider setting up a centralized location for available design data, which all designers and engineers can reference. With the right design data software, you can apply access controls as needed.
In addition, it’s important to support the collection of design data with robust search functionality so design teams can easily retrieve the most relevant information as quickly as possible.
To understand the success of your data reuse system, improve its performance, and get support from leadership, be sure to measure benefits in terms of time, cost, and quality.
For ongoing success of this system, a best practice is to continuously maintain the data by managing changes made to the reused data and update the links between the original and evolved data.
For example, when a user proposes a change to a block of common data, you can conduct an impact analysis and obtain approval from all the impacted data consumers within your organization.
A robust product data management software application is the key to effective data reuse.
There are many software applications available, and each offers a variety of features and functions to meet the needs of companies in different industries.
To choose the right data management software, the first step is to clearly define your needs. To get the greatest ROI from investment in design data software:
seek assistance in finding the right solution
plan and implement the software
train your teams
create comprehensive documentation, and
get follow-up support.
Hagerman Data Management professional service offers a customized approach to helping companies solve data management challenges and assist with implementation and documentation.
Request more info to see how we can assist you.