The recent rise in interest in digital twins for industrial applications reminds of medieval seafarers navigating unchartered waters in search of fame and fortune. Their charting maps showed “Here be dragons” at the edges which meant dangerous or unexplored territories, in imitation of a practice of putting illustrations of dragons, sea monsters and other mythological creatures on uncharted areas of maps where potential dangers were thought to exist.
Industry analysts like Gartner, Forrester, and the ARC Advisory Group who survey a broad spectrum of the industrial market, all agree that digital twins will proliferate over the next couple of years.
Digital twins have attracted wide-spread attention and are considered to be the key to smart manufacturing and other industrial applications that are embracing large scale digital transformation initiatives.
In this 3-part series, we will present a methodology to create digital twins in a simplified, systematic and problem-to-solution approach.
The Challenge and How Do We Want To Solve It?
Because digital twins are digital representations or software design patterns, we look to existing software development practices and approaches for guidance.
There are multiple different software development approaches and our aim is not to review all the alternatives to determine best fit. We will focus on applying the principles that are used by many software startups that have vague requirements, limited resources and funding, and first need to find “product/market” fit. The approach used by many of these startups is described as “The Lean Startup”.
The Lean Startup Methodology
Silicon Valley entrepreneur Eric Ries first introduced the term Lean Startup in 2008 and published his best-selling book titled The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses in 2011.
The initial concept was aimed at helping startups take an agile and customer-centric approach to product development. The Lean Startup Methodology has since been widely adopted by startups, government organizations and global enterprises as a framework for creating innovative products and business models. For example, GE FastWorks launched 100 projects globally by using the Lean Startup approach. The results GE has achieved include: half the program cost, twice the program speed, and products selling over two times the normal sales rate.
In the following section, we’ll cover the elements of the Lean Startup Methodology that are most applicable to creating Digital Twins:
Minimum Viable Product
Eric Ries defines a minimum viable product (MVP) as a version of a product that enables you to learn enough to test your current assumptions with the least amount of development effort.
A common misconception about building an MVP is that it is simply a paired down version of the ultimate solution you aim to create. This approach overlooks the philosophy underpinning the MVP concept, which is to aid in validating your assumptions as fast as possible by getting user feedback.
In our experience, designing high-fidelity mockups and interactive prototypes have been powerful tools for generating the initial MVPs for digital twins. Because there is no development involved in this initial phase of experiments, we are able to rapidly turn around revisions of the prototypes and get multiple rounds of feedback.
The Lean Startup approach draws on the Scientific Method by recommending that practitioners conduct falsifiable experiments to inform their decision making. This is in stark contrast to the traditional approach of creating a comprehensive one-off plan before embarking on the development phase of a project.
For most industrial companies, creating digital twins is still uncharted territory. This is why an approach originally designed for startups can be useful in navigating the process of innovating in the midst of uncertainty.
By running small experiments with measurable outcomes, you are better able to make constant adjustments based on real user feedback, rather than on your initial assumptions (which are often incorrect).
Using the rigorous Validated Learning approach prevents the misfortune of perfectly executing a plan that produces an obsolete solution.
The Build-Measure-Learn feedback loop is a core element of the Lean Startup methodology. It consists of turning your ideas into an MVP, getting feedback from users and then making decisions based on what you learned.