Transform Manifesto Principle #7: End Duplicative Work. Create Reusable Data Objects

by | May 4, 2024 | Digital Transformation, Model-Based Enterprise

Data contained in documents must be available as authoritative and reusable data objects.

This is the seventh and final article in a series about the principles of the Transform Manifesto. If you want to start at the beginning, go here.

A young cousin of mine graduated recently with a Masters degree in aerospace engineering and went to work for a large aircraft manufacturer. He was quickly surprised and disappointed by how much manual labor was required of him – manual labor that didn’t add value and didn’t require the skills he had learned in school.

One of his jobs was to create work instructions containing information from company specs and industry standards. He spent hours a day copying, pasting, and when necessary, manually rekeying content (like requirements, tables, equations) from PDF files into Word documents and into requirements management systems. He said that whenever he manually rekeyed an equation, he couldn’t help but think of the potential disaster if he got it wrong. And months later, if changes were made to any of his sources, he repeated the manual process again to create updated materials. 

Any data extracted and used in other applications is tracked for its location, usage, and status with a live dynamic link back to the authoritative source.

Transforming documents into digital model data bestows each individual data object with its own immutable “address” in the knowledge graph which can then be embedded into other applications or documentation. In the SWISS platform, this is not a copy-and-paste process, but rather “incorporation by reference,” and the process is as easy as drag-and-drop. Any number of authors can use consistent, authoritative data objects to create new compositions (like a set of assembly requirements). Updates or modifications to the individual requirements automatically propagate throughout the digital thread and notify downstream users. This not only minimizes the risk of errors, but also enhances collaboration, reduces manual labor, prevents duplicate work, and eliminates delays.

Importantly, any data that is extracted and used in other applications is tracked for its location, usage, and status with a live dynamic link back to the authoritative source. Including proprietary or copyrighted data in work instructions, test plans, or other documentation no longer means that it disappears into the ether, but instead it remains a part of the larger network of authoritative data.

Most great innovation is built on the shoulders of giants. In the context of engineering, most requirements, work instructions, test plans, and compliance checklists consist of data from multiple internal and external specs and standards. In other words, engineers create new ideas from old ones. But doing so shouldn’t involve such tedious, time-consuming, and risky manual labor. It’s up to information publishers and technology providers to build workflow solutions to solve these problems.

What do you think? Do you spend too much time copying, pasting, and manually rekeying data? If you want to reduce manual labor, errors, and frustration, let’s talk.

If you want to read all seven principles of the Transform Manifesto, start here.