A couple of months ago, David Socha proposed at the end of his initial trilogy of blogs on Digital Twins that there was, in fact, more to come. It’s a broad-ranging and complex subject after all.
Here we are again talking about Digital Twins. But since it’s been a little while, let’s do a quick recap. So far, I’ve discussed the concept and the history of Digital Twins and even introduced a Maturity Model for the analytical capabilities a comprehensive Digital Twin can deliver. If that stuff sounds interesting, please do take a few minutes to go back and take a look at those blogs. I’ll still be here when you get back, I promise.
However, all that said, I’ve yet to discuss the coverage of Digital Twins in the business. How do we actually deploy Digital Twins across the relevant parts of the organisation? This is another critical point. After all, a really clever Digital Twin that beautifully models only a small subset of your assets or processes might already be doing a great job. It might even get you a nice speaking slot at an important conference in a happening location. But how much more could it be doing were it rolled out across a whole asset fleet or an end-to-end process? Let’s take a look at that today.
Capabilities, not apps
Unfortunately, such a rollout is not as simple as it sounds. Rolling out a Digital Twin is not like rolling out Microsoft Office. Applications like Office deliver value in and of themselves. Once your IT Department has deployed Office to users’ devices they can pretty much sit back and admire a job well done, knowing that people have what they need to get on and be productive. Not so with Digital Twins. Digital Twins are – and can only ever be – inextricably linked with the large and diverse data sets that allow them to deliver valuable insights. Without data – and lots of it – a Digital Twin is just a series of pretty screens that may look beautiful but can tell you…nothing.
Unless your business is confident that they already have a comprehensive, accessible integrated data platform that can provide lots of rich, diverse and reliable asset-related data to a Digital Twin, any rollout must consider more than how to get the application in front of users. In fact, that’s the trivial part. Much more critically, your business must understand what data sets are required and decide how to make those data sets available to ensure that new application actually delivers a new and valuable capability.
So, what are you trying to do?
Where to start? Well, how about determining what it is that you want to achieve with a Digital Twin? What business problems do you need to solve? What opportunities do you need to enable? Digital Twins already have impressive and growing capabilities in areas such as modelling, predicting, prescribing and of course simply presenting information. But it’s fantasy to believe you’ll be able to deploy all that functionality at once, or even that the business would know what to do with it all. Instead, we should concentrate on the most pressing of issues; the most valuable of opportunities and create what we might call golden threads for our Digital Twins.
Finding the golden thread
Perhaps safely and cost-effectively improving reliability in rotating equipment is the top KPI for the Asset Management division. Perhaps reducing maintenance costs while not compromising safety or uptime is the main driver for the Maintenance Department. Perhaps in a production environment, overall process efficiency improvements are this year’s focus.
In each case, Digital Twins can be a key enabler, helping to deliver the improvement desired. But in each case, instead of just rolling out an app and hoping for the best, we should consider how we can use Digital Twins to specifically address our issue or opportunity. For example, what are the most important influencers of reliability in our asset fleet? Do they vary by asset class; location; environment; burden etc? Then, how can we model those factors and operationalise the results in a way that makes sense to users and facilitates change and improvement? Via that Digital Twin perhaps?
In this example, our Digital Twin capability will be deployed with the specific purpose of addressing reliability issues. First, via trustworthy, comprehensive and easy to understand reliability reporting. But then, following the maturity continuum I published last time around, on to detailed analysis of past events affecting reliability and on later to predictive and prescriptive capabilities, while at the same time expanding reach from one asset, asset class or OEM’s products to also incorporate other OEMs’ equipment; other asset classes etc.
To infinity…and beyond!1
Later, the great foundation we have created by following the golden thread of (say) equipment reliability can be expanded to also support analysis of Total Lifetime Value; Quality; whatever other factors are most important to the business’ continued success.
For now though, I fear I am out of space. Next month, I’ll get into more detail of how we can pursue this concept of the golden thread in Digital Twins. I’ll give a few more examples of what those threads could be; how we could deploy them over a broad and diverse asset base; and how we can ensure that we do indeed create a foundation that can support expansion to cover many more aspects of the business. See you then!
1 The definitive Buzz Lightyear quote, from Toy Story
About the author
David Socha is Teradata’s Practice Partner for the Industrial Internet of Things (IoT). He began his career as a hands-on electrical distribution engineer, keeping the lights on in Central Scotland, before becoming a part of ScottishPower’s electricity retail deregulation programme in the late 1990s. After a period in IT management and consulting roles, David joined Teradata to found their International Utilities practice, later also taking on responsibilities in Smart Cities and the wider Industrial IoT sector.