If we think back to before the pandemic, many organizations were undertaking some kind of digital transformation or, if they weren’t doing it, they were at least talking about it. Typically, this was from a perspective of how to stay competitive: improve efficiencies, reduce waste, lower costs, etc. Some companies, especially those in industries that were ‘disrupted’ by unexpected entrants (think Uber, Amazon, Airbnb, etc., etc., etc.) were thinking beyond competitiveness. They were aligning digital strategy to business strategy and applying digital transformation to new business models and new digital revenue streams. Regardless of which strategy was driving change, companies were investing in technology like IoT, cloud computing and AI so that they could connect to, collect, and analyze data.
The global pandemic forced nearly all companies to reprioritize and reassess their digital strategies. In our analysis of the a recent Gartner report, 2021 CIO Agenda: Industry Perspectives Overview, 1877 CIO respondents across a variety of industries reported the extent to which the pandemic altered their IT strategies and for some, how it shifted their overall business strategies.
Not surprisingly, nearly all respondents reported significant impacts such as needing to shift to remote work, being forced to provide digital services, using digital channels to reach customers and digitizing processes to keep operations moving. CIO’s also reported that their business leaders began asking them for higher value and more strategic IT investments in 2020 (see chart: Changes in Business Leaders Asking IT for Higher-Value, More Strategic Things in 2020 below)
Almost all businesses were adopting new technologies, accelerating existing digital initiatives, and directing funding towards innovations that would help them survive or, for some, even thrive in the turmoil of the pandemic. Recognizing the need and the value of data, companies increased their investments in many productivity solutions along with IoT to gather more data. IoT spending actually increased in 2020.
As we return to more predictable business cycles, the question arises, how are these investments going to deliver value in the long term? An interesting finding of the report is that most companies are still focused on digital initiatives that affect operational performance, instead of innovating new business models. See 2021 CIO Agenda: Digital Journey Scatterplot
Only 11% of companies surveyed consider themselves to have sustainable, digital business models, deriving new revenue streams and achieving process optimization using digital technologies and data. Eighty-four (84) percent are still using technology predominantly for digital processes and 56% of businesses have fewer than 50% of processes digitized. It is understandable that the pandemic pushed a lot of investment in this direction. But success in the long term will require more innovation in digital business models.
One of the challenges companies will face is how to grapple with the many new data sources from devices, sensors, systems that they have invested in. The thing about data, and especially telemetry data from IoT devices, is that you don’t always have an immediate use for it. Sometimes that data needs to be understood in the context of the greater system or environment. So how can companies leverage all this new data and these new investments into more process optimization while also thinking strategically about long-term performance impact?
Digital Twins could provide the answer. Digital Twins are virtual replicas of physical world things, spaces, and people. They provide real-time visibility into current conditions and also insights into performance and utilization that can be harnessed for future planning. Here is how they do this:
- A digital twins platform like TwinWorx® built on Microsoft Azure Digital Twins connects disparate devices, IoT sensors, systems and then aggregates and normalizes the data into a Single Pane of Glass.
- Digital twins have attributes, properties, and relationships and can be defined using an open source standard language called Digital Twins Definition Language.
- Connecting digital twins to a data source animates the digital entity as a virtual mirror of the real thing. And, by connecting twins to each other, you can build a coherent, live and digital ‘system of systems’.
- As a dynamic model, digital twins can grow and evolve as more data is provided or as needs change. They do not have to be fully ‘developed’ from the very start.
- Building digital twins on industry standard ontologies such as Real Estate Core for smart buildings, NGIS-LD for smart cities and CIM for energy grids enables interoperability with digital twins from many vendors and sources. So you can now think about analyzing your environment in the context of other systems.
- Ultimately with a treasure trove of normalized, contextualized data spanning a vast ecosystem of people, spaces and things, powerful machine learning models can be used for insights and prediction. These models when applied to digital twins enable you to conduct simulations and scenario planning in the virtual realm instead of risking it in a physical setting.
As a business, having a platform that supports operational improvements while also enabling future capabilities is a powerful tool for ongoing innovation, risk management and overall business strategy. It is a on which to align your digital strategy to your business strategy, leveraging all the investments made over the past 12 – 24 months into formidable capabilities for long term success.
*Gartner, 2021 CIO Agenda: Industry Perspectives Overview, Jan-Martin Lowendahl, Brad Holmes, Chris Howard, Tomas Nielsen, Pete Redshaw, Andy Rowsell-Jones, Monika Sinha, 5 February 2021
Gartner clients can learn more about this research here.
To learn more about Azure Digital Twins visit https://azure.microsoft.com/en-ca/services/digital-twins/
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