The connectivity and interoperability of your data, itself, can make or break your digitalization
By Rod Walters, principal & global practice leader–enterprise technology with Kalypso
The most strategic modernization efforts depend on enhancements to underlying systems that support emerging technologies like edge computing and 5G. For example, edge computing is nearing the point where a full 75% of enterprise data will be created and processed at the edge by 2025. At the same time, 5G connectivity is increasingly coming to industrial settings as it grows toward becoming a $664 billion market by 2028. Companies that adopt both can see the value and agility of their edge technologies multiply thanks to 5G’s added bandwidth and reduced latency.
As this connectivity example shows, how an enterprise’s IT foundation is structured can be a critical enabler—or impediment—for the range of technologies available for enterprises seeking to modernize. But what about the connectivity of data itself? In other words, what can the organization do to ensure all data is strategically and accessibly stored for maximum accessibility and minimum silos across the enterprise?
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Too many companies fail to ask that question, even though data is exploding to the point where businesses generate more than 64 zettabytes (ZB) of data annually—as more corporate functions are digitized and remote work remains prevalent in a post-pandemic world. The truth is that, just the connectivity and interoperability of your data itself can make or break your modernization effort.
Let’s examine how companies can evolve toward what’s known as digital thread and digital twin technologies. It’s what happens when information silos are broken down to create frictionless, real-time sharing of data across the organization—strengthening the role of data for the entire modernization effort across operations, business processes, supply chain and more.
Taking on the barriers to data agility
A major issue for any company trying to plan and implement digital transformation is the massive struggle to connect, standardize, share and analyze data across what may be multiple, uncoordinated systems and operations across the enterprise. There are too many isolated teams working on isolated data sets that don’t talk to one another, making it difficult to get a clear and actionable picture of the organization as a whole and how it could be optimized.
Even the most impressive new technology acquisitions will be hobbled if fundamental barriers to data agility aren’t addressed. Otherwise, the transformation kickoff party will soon be cut short by some common pitfalls that arise as the project rolls out. For example, some companies suffer through what’s been called “proof-of-concept purgatory,” where multiple transformation teams work on various piloting efforts that are happening independently, sometimes totally unaware of each other.
Without any strategic alignment, multiple and splintered piloting efforts may reap limited insights into isolated functions within product development, manufacturing supply chain, operations or other business units; but there is no way to connect insights and capabilities together for larger gains. This makes it impossible to refine and scale the most successful approaches more broadly, or to settle on common standards and processes to better support emerging technologies that may be introduced as part of the broader transformation.
The flip side of proof-of-concept purgatory is the paralysis that comes with too much big-picture strategy and general vision, but not enough operational follow-through, including strategic piloting and scaling to create a baseline data architecture that organizations need to be successful with their digital transformations. This often happens when modernization appears on the C-suite radar and may get buy-in from the top—but without a consistent plan for implementation further down the org chart.
Throughout, there’s the risk of additional silos and barriers being introduced along with new technology investments that aren’t sufficiently strategized for data alignment, or that are too reliant on certain proprietary ecosystems that make best-of-breed interoperability and data-sharing difficult. These pitfalls typically arise when technology choices are made without positioning the business need as the driver of those choices—front and center in the planning and IT provisioning process.
Bringing enterprise agility and value to life with digital thread and digital twins
The good news is that there’s an approach organizations can embrace to remove all these hurdles and foster a more connected digital ecosystem to better support a range of modernization technologies. We’re talking about what’s known as digital thread—a well-integrated and cohesive flow of data that runs through the entire organization.
Digital thread allows access to the right data, in the right format, at the right time and in the correct business context. And given its growing adoption as more organizations realize the power of digital thread to unlock value from data and lay the foundation for the broader digital transformation, it has now evolved into an enterprise “must have” rather than a “nice to have.”
Digital thread becomes even more indispensable when you consider how it can bring digital twins to life. Digital twins are virtual replicas of as-built physical assets, processes, products and systems. These replicas are finely detailed and exact in mirroring and predicting impacts to changes in workflows, machinery, controls and systems. All of this translates into lower costs, reduced waste and vastly improved productivity.
An advanced ecosystem of digital thread and digital twins using data that can be accessed and analyzed anywhere across and organization’s IT or OT architecture can be a game changer—bringing about major reductions in downtime and providing the foundation for any number of modernization technology implementations. These include AI-enabled process control, business-health monitoring, proactive maintenance and a range of other data-driven tools.
The labor picture improves as well, given the ability that comes with digital thread and digital twins to optimize production scheduling, materials provisioning, smart shopfloor planning and allocation of resources. Digital twins also make global collaboration among teams much easier; and they provide an accurate and lifelike learning environment to train new hires or upskill current workers. These immersive simulations can teach skills mastery in a highly realistic environment, where knowledge-retention happens quickly and where mistakes are teachable moments that happen safely away from actual systems.
Throughout, digital thread and digital twins make scaling operations much easier, with continuous improvements in manufacturing processes, compliance, supply chain logistics and more. However, even if the desired end-state is an enterprise-wide digital transformation, the organization should put considerable thought into where to start.
Choosing the right use cases is key in modernizing the baseline data architectures that support digital thread and digital twins. For instance, consider focusing on Overall Equipment Effectiveness (OEE), which may already involve production systems with plenty of flow meters, sensors and related IoT devices. This provides a great deal of data volume, variety and velocity to feed digital thread and digital-twin models for real-time visibility and adjustments to maximize uptime and stave off breakdowns or equipment failure.
Other applications include field services, where original equipment manufacturers (OEMs) can use digital thread and digital twins fed by sensor data and other telemetry to run remote diagnostics, compare actual performance with design specifications or even guide remote maintenance and performance tuning. Sustainability is also a major use case, thanks to the ability to monitor and optimize energy usage and efficiency, not to mention the ability to simplify the process of regulatory reporting and compliance audits.
Conclusion
Every modernization effort must adequately consider the complexities of synchronizing data across systems and technologies that may have been historically siloed and disconnected. Fortunately, digital thread and digital-twin technology innovations can break down these silos, connect data across the organization, and support the broader transformation effort toward unprecedented efficiency and value for the enterprise.
