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The Virtual Enterprise: The spark of science and data-led innovation

The Virtual Enterprise accelerates innovation via openness, integrated communities, and exponential tools.

The COVID-19 crisis has changed businesses in profound ways, accelerating the pace of transformation across supply chains, manufacturing, distribution, workforce norms, consumer behavior, and more. This perpetual acceleration requires enterprises to be more agile and responsive than ever. The tools and approaches for managing this new condition are born from science—and will themselves amplify the acceleration.

Many businesses had already begun using analytics and AI to improve business processes prior to the pandemic. Those technologies and a growing focus on examining core enterprise data assets—such as user or transaction data or enterprise workflow patterns—have paved the way to remove, digitize, and automate tasks from production to billing.

The Virtual Enterprise takes these practices a step further, tapping into a wealth of external information— whether related to global health or climate or other ecosystem conditions—to guide decisions and adapt its operations and strategy.

Science and discovery drive innovation across industries—and constitute $52 trillion of the $88 trillion world economy.

Science and discovery drive innovation across industries—and constitute $52 trillion of the $88 trillion world economy.

Businesses need discovery tools to assimilate information from beyond the core—information on politics, the environment, social moments, and other industries—to protect and extend continuity and resilience. Science and data-led innovation is the instantiation of this process: The rapid collection of data informs decisions, with scientific rigor helping both identify knowledge and manage risk. Executives increasingly recognize the differentiation such innovation can provide, with more than three quarters saying their competitive advantage is based on utilizing discovery insights.

The emerging Virtual Enterprise is discovery driven, unlocking value-chain advantage. Science has long been core to sectors such as life sciences, chemicals, and materials. And other businesses rely on the results and outputs of science, such as those in the energy and utilities, healthcare, and technology hardware industries that are propelled by scientific advances in geology, medicine, physics, or other areas.

67% of executives understand the strategic value of data, while 58% access data in real time to create actionable insights.

Today, all enterprises need to become information driven. By applying the scientific method and experimentation at scale—and building on data and AI—they can gain new information about markets and management practices that can drive critical improvements in business strategy, product development, and operations.

What differentiates leaders

What does science and data-led innovation leadership look like? As enterprises become more discovery driven, transformations are required in the areas of culture, skills, business processes, tools, and platforms. For experimentation to be effective, it needs to be performed at scale and in a frictionless manner throughout the organization. A discovery culture is evidence based, which requires adaptivity and openness.

These transformations power enterprise discovery efforts; drive advances in domains such as climate, work, and health; and enable activities in accelerated discovery broadly. Beyond traditional AI tools, enterprises need hybrid cloud platforms to support experimentation at scale. And the injection of quantum computing will open even more new possibilities.

78% of CTOs say they use discovery-driven mechanisms to identify innovations across their broader ecosystems.

By examining how people work, AI can already help determine the most efficient or effective workflows. Tasks can then be routed to traditional or quantum systems—one or more quantum computers working with a classical computing system—depending on which is the best option. Once information technologists establish a workflow, a user need not know where or how the computation is being done, nor would any specialized knowledge of quantum computing be required.

To make the transformations necessary to cultivate a discovery culture that embraces science and data-led innovation, we suggest a focus on four leadership priorities:

Teamwork: 50% of executives in a recent IBV study cite the ability to collaborate in a team environment as a central workforce capability in a post-pandemic world.

Ecosystem focus: 78% of recently surveyed CTOs say they use discovery-driven mechanisms to identify innovations across their broader ecosystems.

Digitization: Executives predict the percentage of virtual workforce and customer engagement capabilities in their organizations in 2023 will be almost triple the percentage in 2017.

Data advantage: 67% of executives understand the strategic value of data, while 58% access data in real time to create actionable insights.

The Virtual Enterprise embraces these priorities, supporting science and data-led innovation and fueling accelerated discovery. Three key insights form the foundation of this support. They are focused on:

  • Virtualization and openness
  • Integrated communities
  • Exponential tools

Download the full report to see how science and data-led innovation can deliver a competitive advantage by dynamically uncovering new business opportunities.


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Meet the authors

John Granger

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, Senior Vice President, IBM Consulting


Teresa Hamid

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, Chief Technology Officer and Vice-President for Business Transformation Services, IBM Consulting


Tetsuya Nikami

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, Senior Partner and Japan Chief Technology Officer and Cloud CTO, IBM Consulting


Glenn Finch

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, General Manager and Global Leader, Cognitive Business Decision Support, IBM Consulting

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    Originally published 15 October 2021