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

Industrial and Manufacturing Technology Growth

In an evolving era of rapid advancement, market demand for innovative technology in the industrial and manufacturing sectors is skyrocketing. Leaders are recognizing the immense potential of digital transformation and are driving initiatives to integrate technologies into their business operations.  These initiatives aim to enhance efficiency, reduce costs, and ultimately drive growth and competitiveness in an increasingly digital business upward trajectory. The industrial and manufacturing sectors have been the backbone of the Global Networked Economy, contributing $16 trillion in value in 2021. Industrial and Manufacturing Tech Market Development   This growth represents a 20 percent increase from 2020, highlighting the resilience and adaptability of these sectors in the face of unprecedented challenges, according to the latest worldwide market study by ABI Research . The five largest manufacturing verticals -- automotive, computer and electronic, primary metal, food, and machinery -

Rise of AI-Enabled Smart Traffic Management

The demand for smart traffic management systems has grown due to rising urban populations and increasing vehicle ownership. With more people and cars concentrated in cities, problems like traffic congestion, air pollution, and greenhouse gas emissions are pressing issues. Since the early 2000s, government leaders have been exploring ways to leverage advances in IoT connectivity, sensors, artificial intelligence (AI), and data analytics to address these transportation challenges. The concept of a Smart City emerged in the 2010s, with smart mobility and intelligent traffic management as key components.  Smart Traffic Management Market Development Concerns about continued climate change, as well as cost savings from improved traffic flow, have further motivated local government investment in these advanced systems. According to the latest worldwide market study by Juniper Research, they found that by 2028, smart traffic management investment will be up by 75 percent from a 2023 figure of

AI Software Market will Reach $251 Billion

The growth in Artificial Intelligence (AI) software could lead to many benefits. As more organizations adopt AI, they may become more efficient, productive, and able to offer improved products and services. The global job market could also expand, with demand growing for roles like AI engineers and technicians. Plus, AI apps could enable breakthroughs in fields like healthcare, transportation, and energy. The worldwide AI software market will grow from $64 billion in 2022 to nearly $251 billion in 2027 at a compound annual growth rate (CAGR) of 31.4 percent, according to the latest market study by International Data Corporation (IDC). AI Software Market Development The forecast for AI-centric software includes Artificial Intelligence Platforms, AI Applications, AI System Infrastructure Software (SIS), and AI Application Development and Deployment (AD&D) software (excluding AI platforms). However, it does not include Generative AI (GenAI) platforms and applications, which IDC recent