During the design of a single product, large amounts of data are generated. And if a company creates designs for new products every day, it becomes a huge number. Therefore, effective data management is needed, which brings many benefits to organizations. However, poor data management and chaotic peak systems cause errors and delays.
This article covers a step-by-step guide to effectively managing engineering data. If you need more information, explore data engineering services.
Engineering data management
Each product life cycle collects huge amounts of data. These can be descriptions, drawings, and other information.
Engineering data management is a set of different practices that govern the handling of collected data. The goal is to support the storage of documentation and processes related to the product life cycle.
6 steps to effective engineering data management
1. PLAN
The first step is to plan your data management. Elaborate on each step, consider how to organize your engineering data, and answer questions.
- How much data will you need?
- How will you analyze them?
- How will you organize them in the file?
- Who will be responsible for each stage of data management?
- How long do you intend to keep the data?
- How do you want to share data with your team?
Having a plan doesn’t mean you have to stick to it all the time. Perhaps there will be problems along the way that you need to solve, or you will come up with a better idea. Therefore, constantly review your plan and make changes if necessary.
2. COLLECT DATA
Collect all possible data, but in such a way that it will be useful in the future. You can create a temple to use while collecting data. It helps you to capture any relevant contextual data, especially when there are a lot of data collectors. You can anticipate what data you will need. To capture images, documents, descriptions – everything that you may need in some time. Ensure that your data is accurate and reliable during the collection, entry, and analysis. In addition, the data format should be consistent throughout the dataset. Make sure it is.
3. DESCRIBE YOUR DATA AND DEFINE NOMENCLATURE
If everyone in your team names files individually, it will create chaos. To avoid confusion, establish a standard way of labeling files. This makes it easier to determine what the document is for and whether it is up to date. In this way, engineering data management will be effective. Additionally, describe and document your data. This will help you understand how to detect, understand and, above all, use data effectively.
4. CENTRALIZE YOUR STORAGE
The next step is to choose a place where to store your data. You can use the tools to identify the best storage location. Choose one but a safe place.
Keeping your data in one place will allow you to work more efficiently. When everyone is working on one drive, no one will miss the updates of other team members.
5. PRESERVE YOUR DATA
It may happen that you lose your files. So it’s worth implementing a plan to protect them. There are many possibilities. One of them is cooperation with the data center or archiving service. Data centers will help you secure your data and choose the right file formats. In addition, they will provide the appropriate tools for data discovery, access, and dissemination.
6. SHARE DOCUMENTATION
Make sure everyone on your team has access to the documentation. Share it and provide appropriate education on data management. Every member of the organization needs to follow the same guidelines for engineering data management to be successful. Establish a set of standards for everyone to follow and provide easy access to this document.
Why is data management important?
As we know, data is very important for every organization. They help to gain new customers, improve customer service, or reveal sales trends. However, to use them well, they must be managed effectively. Here are some advantages:
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Better productivity
Through data management, you and your employees will be able to find, understand, and communicate information more easily.
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Saved time and money
Data management saves time searching for data. And because you and your team are more productive, costs also decrease.
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Faster reactions
The data management process reveals trends so that you can act sooner than your competitors.
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Smarter decisions
With data management, you and your employees are always using the most accurate information.
The negative effects of poor data management generate many errors and problems that significantly reduce productivity and competitiveness.
Conclusion
Effective management of engineering data has a positive impact on the work with data generated during product design. It is especially helpful for organizations that design new products every day. Centralized, well-organized files can increase efficiency and productivity. It also reduces the time spent searching through documents.
We hope this guide will help you manage your engineering data effectively.