Data for Digital Twins

Do I have enough data to implement a digital twin?

If you try to introduce any new technology to a boardroom - especially one that comes with as much hype and promise as digital twins - you’re bound to get pushback.

There’ll be people who are content continuing in the way they always have using the technology they and their teams understand. There’ll be people with an eye on the budget who are worried about just how quickly they’ll generate a return on their investment. And there’ll be others whose memories stretch back to the last time someone was pitching the next big thing in digital transformation and will be keen to slow things down.

When it comes to digital twins, overcoming these objections is relatively straightforward. The return on investment for a company that deploys digital twins is fast, sometimes recouping the entire investment within a financial quarter. As well, the potential positive impact of a digital twin on the company's bottom line should encourage rapid adoption; it’s less a question of ‘should we move’ but rather ‘why aren’t we already moving when the competition already is’.

But there’s one objection that is often raised that is more pointed and deserves a more detailed response, and its this: do we have enough historical data to implement a digital twin program?

Luckily, with modern Enterprise Digital Twins, like those from Cosmo Tech, you don’t have to worry.

Digital twins and data

It’s undeniable: digital twins rely on models and those models need to be fed with data.

Fortunately, most companies are already rich with data.

For instance, take a utility company. Utilities already track and manage enormous amounts of data on everything from SCADA data to sub-meter data, data about outages, maintenance operations, and even the weather. The utility’s human resources department will have detailed data about each and every employee, the marketing team will gather data about utility customers, the finance team will have complex spreadsheets and market reporting data, and there’ll be data gathered in the field by utility workers using tablets and smartphones, and industrial internet of things (IIoT) sensors on lines, at substations, in vehicles, and across the utility's physical assets.

In short, utilities are not lacking data to feed into a digital twin model, which makes a response to the objection about enough data simple: we do have enough data.

But it also unlocks two additional questions that are more significant.

Have we got the right data?

When it comes to questions about digital twins and data, this is by far the more important question.

Having the right data, though, is essential. Without the right data, the digital twin will not generate the results you expect or provide the sort of added-value that you promised the boardroom.

Thankfully, digital twin vendors are experienced in identifying exactly what data is required to feed the digital twin, how to gather that information, and also how critical that data is in making accurate predictions, increasing efficiency and productivity, or optimizing business systems.

This third point is important: while there is some data that your digital twin cannot do without, there is also data that is less critical. Digital twin vendors like Cosmo Tech can help you to identify this data and determine the level of criticality that data presents.

Should historical data be missing or otherwise unavailable the intelligence of experts within the company can be encapsulated into the digital twin in its place. What’s more, because Cosmo Tech’s Enterprise Digital Twins are scalable, a business has the chance to deploy a digital twin in an area where all of the required data is available, then scale that deployment horizontally or vertically across the business, eventually reaching the digital twin of an organisation (DTO) level.

Companies can start with a digital twin using the data that they have, identify the critical data that they don’t, encapsualte their own expertise where data is missing, then scale the twin into other areas as they bring that critical data online and realize benefits across a broader and broader scope.

Is our data in a useable format?

Back to the utility and its wealth of data.

Even a quick review would suggest that this data exists in different formats depending on the division, department, or user. Data gathered from IoT sensors is not necessarily going to be in the same format as the financial data gathered by a CFO or the marketing metrics gathered by the company’s customer outreach team.

For a digital twin program to be successful, a company needs the data to be available and useful, and depending on the digital twin deployed that can raise issues.

Some digital twins can only accept data of a certain type or in a certain format. Choose one of these and your company might find itself having to invest not only in digital twins but also in a new data management and conversion tools, too. Other digital twins, such as those developed by Cosmo Tech, can integrate data from different sources and in different formats as standard.

Being certain that the data you have is usable in the digital twin, then, is often a more important question than whether that data exists at all. But there’s another question, too, that should give the boardroom pause.

Back to the boardroom

It’s not unusual that a push to adopt a new technology faces opposition from stakeholders inside and outside of a company, but having enough data is generally not of critical concern.

More important is having the right data in a format that will work with the digital twin that your company adopts. While some digital twin vendors impose constraints on end users in this regard, vendors like Cosmo Tech are capable of integrating data in a variety of formats and helping companies identify the level of criticality of their data for their chosen digital twin solution.

With Cosmo Tech’s Enterprise Digital Twin solutions you can start small with the critical data you already own, and then scale to a digital twin that unlocks value right across your organization.