In Who Doesn’t Want a Crystal Ball?, we introduced you to the concept of a digital twin for your organization (DTO). A DTO is a dynamic software model which describes how your business works today and how it will respond to change. A DTO gives you more control over cost, revenue, risk, quality, and compliance, so you’ll be able to run your operations better. You’ll also be able to change things more easily, because you’ll be better able to simulate, experiment, and evaluate.
Your digital twin will help you find the quickest, lowest risk path to your best future state. Increased resilience and agility will make you more adaptive, allowing you to maintain customer experience even in a volatile business environment. Simply put, you’ll get more of the right things done, regardless of what the world throws at you.
Although digital twin technology has been used in other contexts for years, its application to business service modeling and transformation is relatively new and organizations are trying to work out if it’s for them and whether it’s worth the effort. In our experience, the best approach to exploring unfamiliar terrain is to find a local guide who knows their way around. To help you with your first steps on the journey, we thought we’d share a little of what we’ve learned about delivering digital twins.
Is our experience worth listening to? Well, Gartner regards BusinessOptix as being at the forefront of this emerging market. Not only do we have one of the best platforms on which to build a digital twin, but we’ve also worked with numerous organizations, large and small, in a range of industries (including financial services, public sector, pharmaceuticals, telecoms, retail, engineering, construction, and business process outsourcing). Along the way we’ve learned how a digital twin generates value and the kinds of challenges you must overcome. As you can imagine, it’s a bigger subject than can be done justice in a single blog, but we can start the conversation with you by sharing three of the biggest challenges.
Job One is getting buy-in from your stakeholders.
As with all technology, some people will raise objections. Two of the most common are “Sounds like another bunch of snake oil salesmen wanting to sell the emperor new clothes” and “We’ve already got process documentation – we know how things work”. The answer to the first one is that if you’ve flown in a plane in the last ten years, you’ve already put your trust in digital twin technology. The response to the second one is “Are you sure?” Plenty of organizations are embarrassed to find their documentation is either incomplete or inaccurate. For many, ad hoc process changes mean their documentation is out of date even before the ink is dry. Not only is process documentation a static record, but also the individual elements are disconnected from each other and the whole is disconnected from real life. It tells you nothing about how your organization will respond to change or how to improve the way you do things.
Our advice is to seek out the people who own the problems digital twin technology will solve. They’re the ones responsible for running or changing your organization. They’re responsible for the cost, quality, and timeliness of your organization’s operations, for meeting future targets, for worrying about disruptive events and how to survive them. They’re responsible for business transformation and digital transformation. They own the change initiatives to digitize, standardize, or optimize your business operations. These people will want to hear what you have to say.
To accurately predict the future, any good crystal ball must first be able to describe the present. To do this your digital twin must be built from operational and contextual data. The good news is you can ingest this data using process mining tools. The bad news is that, at time of writing, these tools don’t give you 100% coverage (see our blog Stuck In The Mine – for more details). Our platform allows you to use a combination of data mining and data modeling to build the most complete, most accurate model of your organization, filing the gaps into which mining tools can’t reach, such as legacy systems and human interventions.
With your digital twin up and running, you can validate its accuracy by checking its values for key metrics against what your business systems are reporting. Once you know it’s an accurate representation of how your organization works today, you’ll be more confident to use it for predictive analysis.
Yes, it’s a cliché but that doesn’t make it any less true. Trying to eat an elephant in one sitting will just give you indigestion and overly ambitious scope is a common reason for DTO project failures. Start small – maybe a few key business processes or a single department. Ideally you want to capture enough of your organization so that you can use the DTO for meaningful “What if?” experiments and it can suggest improvements that deliver tangible value. After all, the best way of winning over any doubters is to demonstrate that the technology really does deliver competitive advantage.
Building a digital twin needs planning but isn’t hard, providing you eat the elephant in small bites and remember to chew. Get buy-in from the people who own the problems it can solve. Focus on accuracy at first, not scale. Get a pilot project up and running in a controlled area, progress in small sprints, and grow your twin at a pace that suits your organization.
You’re not the first to tread this path and there’s plenty of information, advice, and guidance available to help you. Based on our clients’ experience, building a digital twin on our platform will enable you to run your business better, transform it more easily, create better customer journeys and greater customer value. The question you should really be asking is “Can I afford not to?”
