Engineers are detail-oriented; it’s the nature of the job. But there are times when it is good to think about the bigger picture. Whether the “big picture” is establishing best practices, launching a Six Sigma review of engineering or business processes, or calculating return on investment (ROI) for new products or services, establishing the big picture first is a very good way to make sure the right details are being accomplished.
Despite having computers in the workplace for more than a generation, there are still many aspects of business where the full utilization of digital technology is not happening. Many businesses, not just engineering businesses, are discovering new ways to fully realize digitalization in their businesses.
Google Chief Economist Hal Varian recently wrote an article for the International Monetary Fund on the importance of continually looking for “big picture” ways to increase and improve the use of computer technology in business. His audience was economists and politicians — definitely a “big picture” audience — but there are good lessons in his ideas for all of us.
Varian focused on five themes. Let’s take a look at his themes from the viewpoint of engineering data management.
Data Collection and Analysis— the push is on to make manufactured items Internet-connected. With this comes a new tidal wave of data, most of it unstructured. We will need to plan for giving this data structure; which makes it all the more important to have good systems in place now for managing and using engineering data.
Using Windows file folders and Excel spreadsheets to manage engineering data is electronic, but it is not digital. If your company is still manually searching for the right document and the right bits of information, you aren’t ready for the next wave of engineering data.
Personalization and Customization — the history of engineering data management (EDM) could best be described as one size fits all. But today’s technology makes it possible for every company to have an engineering document and data management system that is fine-tuned specifically for existing best practices and workflow. As companies work to be more responsive to customers, it will require data systems optimized for new transactional paths.
Continuous Improvement — implementing new technology is not a process with a beginning and an end. The most efficient use of digital technology comes from constant refinement based on new capabilities and new demands. When Innovative Steam Technologies (IST) in Cambridge, Ontario, decided to improve its engineering data management, it selected a group of individuals to be responsible for the whole process from software evaluations to implementation. They were drawn from key areas of the company, with a wide variety of skill sets, and were dedicated to the planning, designing, migrating, and training for their EDM system. They also had the important task of testing the EDM solution’s capabilities to make sure the software did what the company wanted it to do. Testing turned out to be more important than initially realized; it not only told them if the new software was working correctly, but also pointed out new areas and ways to take advantage of the software.
Contractual Innovation — Varian wrote about contractual innovation in regards to product sales and other economic transactions. But contractual innovation is a key in supply chain management, especially in how two engineering companies share valuable intellectual property. There are ways to fully digitalize the workflow, but no two situations are alike.
Coordination and Communication — Digital technology has given rise to a new business phenomenon, the micro-multinational company. Working on a global scale is no longer the sole enclave of Fortune 500 companies, thanks to the affordability of Internet-based communications services. Mobile is becoming ubiquitous, giving companies of all sizes new challenges for creating, using, and managing data.
These five themes form the backbone of any successful implementation or upgrade of engineering data management systems. By keeping the big picture issues in mind, there are fewer mistakes at the implementation level. Smoother implementation means faster payback and lower costs.
The Synergis Software white paper “Leveraging Your Engineering Data” has good tips and insights from Adept users who have been through the process.
Randall S. Newton is the principal analyst and managing director at Consilia Vektor, a consulting firm serving the engineering software industry. He has been directly involved in engineering software in a number of roles since 1985. More information is available at https://www.linkedin.com/in/randallnewton.