Breaking Down Data Silos

Connecting data across the entire product development process is the key to meeting growing demands | LEARN MORE

Data fuels innovation in the product development process and crosses organizational bounderies

Data is the lifeblood of the product development process, enabling the right design decisions at the right time. When used correctly, this data fuels innovation, allowing engineers to explore multiple design iterations and gain further insights into the best approach to take. This data often crosses organizational boundaries, giving global collaborators access to the most up-to-date information.

While the benefits of data sharing are clear, there are also challenges to overcome. In particular, data can quickly and easily get out of control, becoming isolated in silos. When this happens, stakeholders may start to make decisions without the best information to hand. Poorly informed decisions not only lead to design errors and disruption for your business, but it also devalues data because decisionmakers can no longer make the right decision at the right time. This post addresses all of these issues in greater detail and how to overcome them.

1 - Automated vs. Manual Data Management

Data management is difficult and, thanks to the big data phenomenon, this issue is exacerbated by the high volumes of information most organizations now have to deal with on a day-to-day basis. As a result, you need to avoid effort-intensive data management at all costs.

Automation accelerates data management processes

While many systems come with some low-level data management capabilities, most solution providers did not design their tools with effective data management in mind. From a data perspective, these systems are not fit-for-purpose and often require users to manually complete a range of data management tasks. For example, an engineer may need to manually upload every design into such a system, wasting their time and expertise.

Now, consider the benefits of a system that automates data management tasks. A cloud-based computer-aided design (CAD) system, for example, automatically saves every change a user makes to a design. The user never has to hit ‘save’ or upload multiple files to the system. What’s more, no one must manually set up CAD because it runs on the cloud. There’s also no need for any maintenance because the software developer adds every new feature, bug fix, and update to the cloud. Users need not wait for their turn to access the model. Everyone can work concurrently, and there are no confusing duplicates of the design. What’s more, you can access cloud-based CAD from anywhere, giving every user limitless access to all models.

2 - WIP vs. Released Design Data

Work-In-Progress (WIP) and released design data management are both highly effective strategies, which are used at different stages of the product development lifecycle to share data. WIP data management helps engineers during the design exploration stages. Using this concept, engineers can understand the flow of the design process from one iteration to the next, providing them with insights into different design decisions and their consequences. Released data management provides your engineers with access to the relevant information for all of the company’s final designs.

Adopting WIP and released design data helps saving time

These two capabilities may be different in terms of when users use them. Still, companies can realize many benefits by embracing a system that offers both WIP and released design data management. By adopting both strategies in the same system, engineers won’t waste their valuable time searching for designs, copying designs, sending/receiving models, or trying to understand the reasoning behind individual design decisions. All this information is available in one place, not many. So, users do not have to switch between disparate systems, streamlining design data at every point in the product development lifecycle and making it easily accessible to all.

3 - Email vs. Cloud Sharing

Data sharing is a critical capability. You may need to share information outside of the organization when, for example, external engineers and manufacturing suppliers aid the design process. When sharing design data, you also need to not only ensure its safety as it passes across the network but also make sure data easily and quickly accessible to all necessary parties.

A cloud-based solution helps to strike balance between data security and accessibility.

A cloud-based solution can help strike this delicate balance between data security and accessibility. Most enterprise-grade cloud solutions come with disaster-recovery capabilities and security protocols as standard, including compliance with the relevant security standards and state-of-the-art encryption techniques. This approach is a more robust solution than simply sharing data over email, where version control and security are both difficult to maintain. It puts sensitive design data at risk of interception. Plus, attachment sizes are often limited over email, making it difficult to share large CAD files effectively. What’s more, when sharing data over email, your information could be forwarded on to multiple recipients. However, a cloud-based solution allows you to put user management measures to be put in place to provide complete control over who can access sensitive data and what level of access they have.

4 - Homogeneous vs. Multi-CAD Support

Most organizations now need to manage data across more than one CAD platform. For example, your company may need to work with external parties who use a different CAD tool than your in-house team. This reality could also introduce foreign design data into the organization, complicating matters further. What’s more, as more packages hit the market, a multi-CAD solution ensures you have the right tools for the job in hand.

A multi-CAD platform streamlines your product development process

Whatever your reasons for adopting a multi-CAD solution, it is imperative to have the right platform in place to manage this information. Migrating internal and external data into a multi-CAD solution is a complex undertaking, and not one anyone wants to repeat in a hurry. So, research is essential. For starters, this platform needs to be compatible with your current CAD packages. For example, your CAD platform may need to support both 2D and 3D models, across multiple formats and new technologies, such as augmented reality and artificial intelligence. A multi-CAD platform should also offer specific data management features and methods, allowing users to find and manage CAD files and information throughout the product development lifecycle. Once this is achieved, a multi-CAD platform streamlines and simplifies the product development process, improving your organizational productivity and transparency.

Summary

Digital transformation is a global phenomenon, helping businesses realize many benefits and widespread innovation. But you must proceed with caution to reap the full rewards of any digital changes.

Start at the end by defining your primary objective for your digital transformation initiative. This goal usually refines an existing business process and, once finalized, should be communicated across your organization to help buy-in.

Break your entire implementation into clear steps, identifying the value each one brings to the organization. If possible, identify metrics to measure this increase in value and define the criteria of success for each stage so you can clearly communicate both the added value and progress you are making during your digital initiative.

You must take into account the people, process, and technology changes to enable digital transformation. While technology is the key enabler to change, you need the right people and clear processes in place for your initiative to succeed.

Manufacturing productivity with data at the center

Connecting design and engineering with manufacturing putting data at the center is one of the most powerful ways to enable concurrent engineering and improve your manufacturing efficiency. This connected data approach breaks down silos from design through manufacturing and production for efficient product development so you can get products to market faster.

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