Skip to main content

How Digital Engineering Enables Resilient IT Decisions

Given the current economic environment, all business and technology decision-makers must come together in support of a cohesive strategy for ongoing information technology (IT) investment. In order to deliver custom digital products and services, resilient organizations will pivot from an 'operational mindset' to a more 'market-driven mindset'.

As IT and Operations Technology (OT) converge, companies will focus on using digital business capabilities to improve processes via better instrumentation, infrastructure, integration and insight.

To help organizations expand to the OT buyer and become resilient decision-makers, International Data Corporation (IDC) has published a new 'Future of Operations' (FoO) framework.

Digital Engineering Market Development

By 2025, intelligent enterprises will see a 100 percent increase in productivity, resulting in half the response time of peers due to the ability to anticipate market and operational changes and 25 percent increase in success rates of new digital product or service introductions.

IDC defines resilient decision making as having the ability to use all available data and information to rapidly and effectively make decisions that keep your operations aligned with customer expectations and demands.

Traditionally, operational data has been siloed by both technology and organization. Systems have typically been in place to pull critical financial and compliance information from operations by the IT organization.

And those same systems push down orders and demands as gathered by the IT systems. It is then up to the operation to have processes and systems in place to turn that flow into an executed business function.


"Digital Engineering is the piece that companies have been missing to become more resilient and to tightly align operations with their customers' needs," said Kevin Prouty, group vice president at IDC. "The convergence of IT and OT is the driving force behind digital engineering and the resiliency at its core."

To succeed with a market-driven mindset, IDC defines five key tenants:
  • Evolve beyond continuous improvement, lean, and six sigma to resiliency and market focus.
  • Embrace complexity in products, services, and markets while minimizing complications.
  • Adapting to changing markets and demands while keeping the core operational purpose.
  • Use digital capabilities to build a resilient organization and operation.
  • Develop a converged IT and OT function into Digital Engineering.

Outlook for Digital Engineering Methodology Adoption

According to the IDC assessment, forward-thinking organizations will leverage the Future of Operations framework to structure and scope their future of operations initiatives. Key decision-makers will be able to define the technologies and related services essential to the new market-driven operational models.

Furthermore, technology suppliers and IT vendors can use the framework to ensure their solutions are meeting the demands of the enterprises that are and will be undergoing operations transformation efforts. In summary, there is no digital transformation without IT operations transformation.

Popular posts from this blog

IoT Device Management Demand Gains Momentum

More forward-thinking CIOs and CTOs are focused on the adoption of the Internet of Things (IoT). Management challenges are top of mind for those who have already deployed a large number of sensors and associated network edge devices. Device management services are evolving in response to a greater breadth of new device technologies such as edge intelligence and related connectivity solutions, as well as the customer scalability and security of IoT deployments. But forward-looking suppliers are also preparing for a world where 41.3 percent of the connected devices will be using some form of Low Power Wide Area (LPWA) technologies by 2026. IoT Device Management Market Development Since IoT customers increasingly need to manage a larger fleet of connected devices, ABI Research now forecasts that IoT device management services will exceed $36.8 billion in revenues by 2026. Standardization is beginning to play a bigger role in device management services, as more connected devices use LPWA t

Anywhere, Anytime Workplace Demand for SASE

The ongoing adoption of flexible working models within the enterprise market has significant implications for typical IT organizations that must now support knowledge workers and front-line employees that operate outside the corporate network perimeter. The global COVID-19 pandemic created IT networking and security challenges. The expansion of the distributed workforce, an increasing reliance on cloud computing infrastructure, and the requirement to securely connect online employees -- wherever they choose to work, at any given moment in time. Legacy IT solutions that have rigid network underlays and a requirement for on-premises infrastructure cannot adequately deal with these trends. This 'Anywhere, Anytime Workplace' led to demand for new Secure Access Service Edge (SASE) solutions, with networking and security delivered as-a-service. Anywhere, Anytime Workplace Market Development   Although converging networking and security capabilities offer enterprises a promising solut

Cloud Edge Computing Demand Continues to Grow

Public cloud computing solutions are moving closer to the edge of networks where CIOs and CTOs are hosting new apps. The edge journey is well underway for forward-looking organizations as they seek to connect with customers, improve operational efficiency, and adopt digital business technologies to drive innovation. The latest worldwide market study by International Data Corporation (IDC) found that three-quarters of organizations plan to increase their edge computing spending over the next two years with an average increase of 37 percent. A combination of factors is driving this increased spending at the edge. Cloud Edge Computing Market Development The performance requirements of expanding workloads and new use cases that leverage artificial intelligence (AI) and machine learning (ML) demand greater compute capacity at the edge. In addition, the amount of data being stored in edge locations are rapidly expanding, and organizations plan to keep this data longer. As a result, the numbe