At Autodesk, we're researching how people learn because we want to make our software easier to learn. We have found that people want to do to learn instead of learn to do. In other words, they don't want to spend weeks or even hours learning something and then weeks or years applying what they've learned. Instead, they want to try to do something and learn what they need to know as they go.
So what do people in your industry need to learn? Is there someone in another industry that already knows how to do that? Could someone in your industry do it the same way? If so, could that someone learn it the same way it is learned in the other industry?
We ask these questions because, so far in our research, here's what we've found:
As processes become more digital, more and more data is collected. This data can be analyzed by machine intelligence to reveal patterns in how the data is used. Once these patterns become known, the processes around the data became less siloed. In other words, people work together across disciplines when they realize that they are connected by data.
Being connected through data causes processes (that were once separate) to merge as they become more digitized and automated. From a cost, quality, and time perspective, it makes no sense to have two separate ways of doing the same thing. Why start from scratch when the output of one process can be the input to another? As a result of these merging processes, the linear chains of value (i.e., benefits derived from the work) are being reshaped into interwoven systems. We refer to this as convergence.
Convergence generates new kinds of social, technological, economic, and cultural value by driving far-reaching integration across sectors, disciplines, scales, and demographics. People work better together when they share data and common processes.
Autodesk software serves three industries:
- Architecture, Engineering, and Construction (AEC)
- Product Design and Manufacturing (PD&M)
- Media and Entertainment (M&E)
We're working to make our software easier to learn by anyone in any of these industries. The industries themselves are converging as part of the future of work:
- Customers who make buildings (AEC) are starting to behave more like customers who make things (PD&M). Whereas buildings used to be one-offs, more and more, parts of buildings (e.g., trusses) are being constructed offsite in environmentally-controlled warehouses, brought to the construction site, and assembled into position. AEC customers are suddenly concerned with mass production and quality control.
- Customers who make things (PD&M) are starting to make more bespoke items. Instead of setting up huge factories to make thousands of identical items, manufacturers are becoming more agile, configuring microfactories to make small runs, more like one-offs, of personalized items.
- Both AEC and PD&M customers see the benefit in showcasing what they make via Augmented Reality and Virtual Reality that has been a mainstay of the M&E industry for years.
As part of that, learning in these industries is converging too. For example: Architects can learn to create beautiful renderings the same way that special effects artists do. Factory floor workers can learn techniques for swift assembly-line construction and deconstruction. Entertainment developers can learn to use photogrammetry to include real-world objects in video games. The best practices from one industry can be applied to the other two.
So I will ask again:
Given that processes are converging, what do people in your industry need to learn that is already known and practiced somewhere else? Can people in your industry learn it the same way that they do?
Autodesk has always been an automation company. Today, more than ever, that means helping our customers automate their design and make processes. We help them embrace the future of making, where they can do more (e.g., quantity, functionality, performance, quality), with less (e.g., energy, raw materials, timeframes, waste of human potential), and realize the opportunity for better (e.g., innovation, user experience, efficiency, sustainability, return on investment). Software that is easier to learn is part of providing the opportunity for better.
Thanks to my colleague, Randy Swearer, for some of the content for this blog post.
The study of learning is alive in the lab.