“Artificial intelligence tools are only beginning to penetrate the workplace,” writes Jared Lindzon (@JLindzon), “but are causing leaders to rethink how their businesses run.”[1] In fact, many (if not most) analysts believe companies must transform themselves into digital enterprises if they are to survive and thrive in the coming decades and artificial intelligence (AI) platforms will play a major role in that transformation. Lindzon reports, “Artificial Intelligence may still be in its infancy, but it’s already forcing leadership teams around the world to reconsider some of their core structures.” Kessara Sakmaneevongsa, a partner at Deloitte Thailand, observes, “The dawn of the digital era represents opportunities that we have not seen before. … The only wrong approach for navigating digital disruption is to remain with the status quo.”[2]
Is Your Company Ready for Digital Transformation?
Howard Tiersky, CEO of FROM, agrees with Sakmaneevongsa. “In industry after industry,” he writes, “digitally centric players are growing rapidly while many legacy brands struggle. … The truth is that it’s challenging to transform an enterprise to compete in a new digital world. Many won’t make it. But it’s definitely possible.”[3] According to Tiersky, the hardest part of digital transformation may be having a vision of possibilities. “Although vision can evolve over time,” he writes, “companies that succeed in major transformations always start with a clear picture of where they want to go.” Companies are often reluctant to change because they fear leaving a path that has historically brought them success. Tiersky lists ten behaviors shared by companies who have successfully transformed into digital enterprises. They are:
1. Leadership Prioritization.
2. Digital Vision
3. Iterative Development Process
4. Flexible Platforms
5. APIs and Ecosystems
6. Customer Insight and Metrics
7. Culture of Innovation
8. Experimentation
9. Customer Data and Personalization
10. Readiness to Invent New Business Models around Digital
Some things will remain constant for business success; namely, seamlessly integrating people, processes, and technology. Tiersky’s list covers all three areas. The glue that will hold them all together in digital enterprises will be cognitive technologies. Cognitive technologies can integrate and analyze both structured and unstructured data providing actionable insights to decision makers. Cognitive computing platforms are also flexible and can be applied to challenges in every area of an enterprise. In some cases, cognitive platforms can make autonomous decisions and, because they leverage machine learning, they improve over time. They also support experimentation and innovation. I recommend a crawl, walk, run approach involving proof-of-concept projects that can be tweaked and proven before being scaled.
Digital Enterprises will Dominate the Future
Paul J.H. Schoemaker, a professor at the University of Pennsylvania’s Wharton School, and Philip E. Tetlock (@PTetlock), the Annenberg University Professor at the University of Pennsylvania, observe, “In coming years, the most intelligent organizations will need to blend technology-enabled insights with a sophisticated understanding of human judgment, reasoning, and choice. Those that do this successfully will have an advantage over their rivals.”[4] They continue:
“To succeed in the long run, businesses need to create and leverage some kind of sustainable competitive edge. This advantage can still derive from such traditional sources as scale-driven lower cost, proprietary intellectual property, highly motivated employees, or farsighted strategic leaders. But in the knowledge economy, strategic advantages will increasingly depend on a shared capacity to make superior judgments and choices. Intelligent enterprises today are being shaped by two distinct forces. The first is the growing power of computers and big data, which provide the foundation for operations research, forecasting models, and artificial intelligence (AI). The second is our growing understanding of human judgment, reasoning, and choice.”
It should be clear that digital enterprises rely on the collection and analysis of big data to create a competitive edge. The more data collected and analyzed the greater the need for cognitive technologies. Schoemaker’s and Tetlock’s research has led them to generate a list of five things business leaders can do to create successful digital enterprises. They are:
1. Find the strategic edge. “In assessing past organizational forecasts, home in on areas where improving subjective predictions can really move the needle.”
2. Run prediction tournaments. “Discover the best forecasting methods by encouraging competition, experimentation, and innovation among teams.”
3. Model the experts in your midst. “Identify the people internally who have demonstrated superior insights into key business areas, and leverage their wisdom using simple linear models.”
4. Experiment with artificial intelligence. “Go beyond simple linear models. Use deep neural nets in limited task domains to outperform human experts.”
5. Change the way the organization operates. “Promote an exploratory culture that continually looks for better ways to combine the capabilities of humans and machines.”
Cognitive computing platforms can help in each of these areas. Because they employ natural language processing, cognitive computing platforms can communicate using terms employees understand. This fosters better human/machine collaboration. It’s my belief that the best digital enterprises will leverage human/machine collaboration. Josh Bersin (@Josh_Bersin), principal and founder of Bersin by Deloitte, told Lindzon, “What we concluded is that what AI is definitely doing is not eliminating jobs, it is eliminating tasks of jobs, and creating new jobs, and the new jobs that are being created are more human jobs.” According to Lindzon, “Bersin defines ‘more human jobs’ as those that require traits robots haven’t yet mastered, like empathy, communication, and interdisciplinary problem solving. ‘Individuals that have very task-oriented jobs will have to be retrained, or they’re going to have to move into new roles,’ he adds.” Schoemaker and Tetlock conclude, “To create a more intelligent enterprise, executives need to leverage the strengths of both humans and computers in order to produce superior judgments. That will require a sophisticated understanding of both human decision making (the ‘soft side’) and evolving technology-enabled capabilities (the ‘hard side’).”
Summary
“The cognitive-science revolution holds both promise and challenge for business leaders,” assert Schoemaker and Tetlock. “For most companies, the devil will be in the details: which human versus machine approaches to apply to which topics and how to combine the various approaches. Sorting all this out will not be easy, because people and machines think in such different ways. But there is often a common analytical goal and point of comparison when dealing with tasks where foresight matters: assigning well-calibrated probability judgments to events of commercial or political significance.” It’s unfortunate they use the term “human versus machine approaches.” I agree with Kevin Kelly (@kevin2kelly), founding Executive Editor of Wired magazine, who wrote, “This is not a race against the machines. If we race against them, we lose. This is a race with the machines. You’ll be paid in the future based on how well you work with robots.”[5] Successful digital enterprises will be revolutionary and will ensure that human/machine collaboration fosters a brighter future.
Footnotes
[1] Jared Lindzon, “How AI Is Changing The Way Companies Are Organized,” Fast Company, 28 February 2017.
[2] Kessara Sakmaneevongsa, “How to get on the right side of digital disruption,” The Nation, 7 March 2017.
[3] Howard Tiersky, “Digital Transformation: Is Your Organization Ready?” CIO Review, 9 March 2017.
[4] Paul J.H. Schoemaker and Philip E. Tetlock, “Building a More Intelligent Enterprise,” MIT Sloan Management Review, 13 March 2017.
[5] Kevin Kelly, “The Seven Stages of Robot Replacement,” Backchannel, 27 December 2016.