Boost digital transformation with algorithmic business thinking



For over 15 years in telecommunications, senior lecturer at MIT Sloan saw a recurring problem: employees approach the same problem from different angles. People in research and development, engineering, and human resources all wanted the same results, but they weren’t able to connect and were not taking advantage of lessons learned in other areas.

“They missed each other,” McDonagh-Smith said. “Things got lost too often in translation. “

McDonagh-Smith thought of algorithms – a series of step-by-step instructions for accomplishing a task, normally associated with computing – as a way to solve this problem and unite people within an organization and unite humans with technology.

“If we really want to solve the problems, we have to seek a partnership of humans and machines working together,” he said.

This developed into a concept he called Algorithmic Business Thinking, a series of interconnected ideas, frameworks, and models to help people break down complex problems into their smallest building blocks, to be able to working on them in parallel, then recombining them so that they are opportunities for sustainable growth.

It’s useful for reframing issues and encouraging employee exploration, McDonagh-Smith said. Companies are using Algorithmic Business Thinking to explore approaches to complex business problems, such as Walmart optimizing human and machine investments to improve returns, and Boston Consulting Group identifying ways to keep the company’s accelerated digital transformation alive over the years. of the past 18 months due to COVID. -19 pandemic.

Algorithmic business thinking is a collection of ideas – “a toolbox, a mindset, and a digital language,” said McDonagh-Smith, who teaches the concept in an MIT Sloan Executive Education course.

The concept is not a panacea, he noted. It aims to complement existing methodologies and approaches, not to compete with them.

Four pillars of IT

Algorithmic business thinking is based on four cornerstones borrowed from computational thinking:

Decomposition, or the idea of ​​breaking up complex problems into smaller parts. For example, a problem can be broken down into four smaller problems, and each of them into four smaller problems, until you get to a point where you can start solving the smaller problems. It creates momentum and confidence, McDonagh-Smith said.

Pattern recognition, or recognize patterns of success and failure and be able to apply them in adjacent or different areas. For example, if the work has been carried out successfully in one area, this strategy could be transferred to other areas to increase efficiency.

Abstraction. While many believe abstraction has to do with being vague, abstraction in algorithmic business thinking does the opposite – it removes noise from the signal, McDonagh-Smith said. In the midst of so much data, being able to abstract and delete things that are not necessary for a certain task is especially valuable and allows people to focus on what is important.

Algorithmic partnership of man and machine. The first three cornerstones are fueling the evolution of the relationship between humans and machines. “Enterprise Algorithmic Thinking Algorithms are humans and machines working side by side, side by side, on problems.”

Human capabilities that make technology work

Research suggests that human characteristics and capabilities make technology effective and useful in organizations. Algorithmic business thinking highlights these human capabilities and how they are valuable in an organization’s push towards digital transformation.

This is illustrated by McDonagh-Smith’s take on the familiar double-helix DNA molecule, in which two strands are coiled together like a twisted ladder. McDonagh-Smith’s double helix model presents the digital world and the physical world linked by human traits, such as critical thinking, collaboration, and compassion. He highlighted three other key features:

Creativity, which helps people take full advantage of artificial intelligence technologies. “Technology allows us to do great things, but we have to understand what it means for the innovation of our business model, what it means for the real work in our organizations, and creativity is the key”, McDonagh-Smith said.

Curiousity, which helps companies find new directions and possibilities, and disrupt the status quo. It often means being comfortable embarking on new possibilities and directions. “The more curious you are or the more you can apply your curiosity, you create a larger landscape in which to operate,” McDonagh-Smith said. “It’s probably one of the best tools we have for countering prejudice as well. “

Consilience, which means unification. “I think we can unify physical and digital, human and machine capabilities,” he said. “I think we can unify the past with the future and the present.”

A common digital language to stimulate innovation

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The disconnect between employees that McDonagh-Smith observed can be resolved in part with a common digital language, he said. This is particularly important at a time of rapid development of technology and man / machine partnership. Humans must be able to communicate comfortably with each other about machines, and also communicate with the machines themselves. This idea was partially inspired by linguist and professor emeritus at MIT Noam Chomsky, who said that the primary function of language is not to communicate, but rather to connect interfaces.

A common digital language facilitates collaboration and communication between technologists and business-oriented people, Martha Anderson, senior director of digital transformation at Walmart, told McDonagh-Smith in a podcast he created for the course. management training.

“It may be more of an opportunity for companies that historically haven’t been seen as digital natives or tech companies,” she said.

To implement digital language as part of algorithmic business thinking, executives must seek to create a common motivation to engage in technology through incentives, compensation structures and organizational design, said McDonagh-Smith.

“You are creating this pool of digital language that people are immersed in,” he said. “But if you don’t create the motivation and you don’t create the environment, that will never happen.”

Watch the webinar: Accelerating Digital Transformation Through Algorithmic Business Thinking


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