An Intelligence Strategy for the Digital-First Era

Necessity is said to be the mother of invention. It is also the mother of adaptation. The world is adapting to the COVID-19 pandemic by using digital tools to survive and thrive—especially businesses and their customers, who still need the goods and services these enterprises offer, despite the restrictions of lockdowns, social distancing, and other public health protocols. More people are working from home, and these digital tools are their lifelines. This is where the Future of Intelligence report of IDC comes in.

Introducing the Future of Intelligence

IDC defines the Future of Intelligence as “an organization’s capacity to learn, combined with its ability to synthesize the information it needs in order to learn and to apply the resulting insights at scale.” It also takes the position that “the ability to continuously learn at scale – and apply that learning across the entire organization instead of in silos at a faster rate than the competition – is the crucial differentiator that will separate those with greater enterprise intelligence enterprises from their peers.”

IDC predicted that, over the next four to five years, enterprises that invest in future of intelligence capabilities effectively “will experience a 100% increase in knowledge worker productivity, resulting in shorter reaction times, increased product innovation, and improved customer satisfaction, in turn leading to sustainable market share leadership (or achievement of their mission) in their industry.”

These enterprises, IDC projects, will be able to:

  • Execute their responses to customers, competitors, regulators, and partners in half the time of their peers — often by anticipating situations in advance.
  • Increase their success rate of new product introduction by 25%.
  • Expand their scope by offering a wider variety of experiences and increase their Net Promoter Scores at a rate 1.5 times as fast as their competitors.
Targeted Investments in Intelligence

“In 2019, enterprises globally spent $190 billion on data management, analytics, and AI technologies and services—not even including labor costs or purchases of external data. How much of that spending generated intelligence and how much of that investment generated value are questions many executives are unable to answer,” IDC Group Vice President for Analytics and Information Management and Future of Intelligence Research Practice Lead Dan Vesset said.

The COVID-19 pandemic has highlighted organizations’ need to stay resilient, and many firms have been leveraging the benefits of becoming intelligent enterprises to future-proof themselves against further disruptions.

Marshall said, “organizations that are able to harness the power of their data-driven culture, the data literacy of their employees, and the processing power of their technology are showing greater resiliency in today’s pandemic-affected world and are also better positioned for the eventual recovery.”

Future of Intelligence Predictions

Some of the key Future of Intelligence predictions that will impact the IT industry and both technology buyers and suppliers in Asia/Pacific are:

  • By 2021, external shocks and resulting uncertainty will drive 40% of A2000 companies to discard existing decision models and focus on a new framework for decision environments to improve resiliency.
  • By 2022, driven by board-level agenda, 50% of A2000 companies will formalize the human oversight of AI-based decision automation to combat distrust of autogenerated recommendations and reputational risk.
  • By 2023, as 60% of A2000 companies embrace flexible data science and engineering talent sources, four-fifths of them will struggle with the visibility and governance of processes and the behavior of these external resources.

Vesset wrote in the IDC blog that the company conducted a study on the impact of COVID-19 on IT spending in November 2020: “Of more than 600 decision-makers globally, 2/3 of organizations expect their spending on analytics and AI technology to either increase or at a minimum to remain stable in 2021 as compared to their actual spending in 2020.”

He also wrote that “after the initial reaction to the crisis in early 2020, enterprises began to reassess their decision-making capabilities. In July 2020, 65% of organizations stated that the COVID-19 pandemic exposed gaps and shortcomings in their analytic and AI/ML models, prompting a reassessment of plans, new scenario evaluations, and new ‘war gaming’ exercises.”

Building an Intelligence Strategy

Many businesses, he wrote, “are looking beyond investments in core data warehousing, business, intelligence, and machine learning technology to capabilities for data and model ops and governance, collective intelligence, decision simulation, knowledge networks and perhaps most importantly, data literacy and data culture.”

He also found that “70% of managers and directors confirm that in the past 12 months their executives have explicitly called for their enterprises to become more data-driven. Similarly, 87% of CXOs say that becoming a more intelligent enterprise is their top priority for the next five years.”

“This change in the attitude and investment priorities of top executives is coupled with entry into the labor force of a new generation of data-native workers,” Vesset added. “As a cohort, they represent Generation D (Gen-D) that is not a chronological generation, but a vocational one, in which career and life activities are infused with data.”

Vesset wrote that “Raising enterprise intelligence depends on harnessing the power of collective intelligence, which can take on multiple forms: from teams of people acting together to influence a decision to people being augmented with intelligent machines to groups of machines or things ‘collaborating’ to achieve a goal.” He wrote that organizations are investing in, or are increasing their investments in:

  • Collaborative, augmented analytics solutions that shortcut existing workflows by automating multiple steps of the data ingestion to insights generation process while incorporating in-the-flow collaboration and knowledge management capabilities.
  • Solutions for managing distributed things or bots, such as drones or robots, require swarms to be enabled with independent ‘decision-making’ capabilities.

Vesset proposed that “it is time to redefine what enterprise intelligence means and set a new course for the future of intelligence – one that retains the best of business intelligence and analytics but extends them with other capabilities for the synthesis of information and extends into learning.”