Corporate Decision Making in the Digital Age

Stephen DeAngelis

October 24, 2019

The late Peter F. Drucker, an Austrian-born American management consultant, educator, and author, once stated, “Whenever you see a successful business, someone once made a courageous decision.” Bain analysts, Michael C. Mankins and Lori Sherer (), assert if you can improve a company’s decision making you can dramatically improve its bottom line. They explain, “The best way to understand any company’s operations is to view them as a series of decisions.”[1] They add, “We know from extensive research that decisions matter — a lot. Companies that make better decisions, make them faster and execute them more effectively than rivals nearly always turn in better financial performance. Not surprisingly, companies that employ advanced analytics to improve decision making and execution have the results to show for it.” Ashish Parmar, CEO of Prismetric, insists the Digital Age has placed new emphasis on the importance of decisions — specifically, data-driven decisions. He writes, “Digital transformation is fostering the data-driven culture to enable better-informed decision making. The significance of optimal decisions needs no explanation as they are paramount to determine the business success rate, respond to the present and future challenges, and gain a strategic advantage over the competitors. Such decisions can be taken only based on the data facts, not on the gut instincts.”[2]

 

Advanced analytics and decision-making

 

Parmar asserts, “The much-created hype around big data has died down with a new hype that’s focused on gaining insights from the torrent of data. This [is] why digital businesses [consider analytics an] all-important technology to embrace.” Magnolia Potter (@MuggleMagnolia) adds, “Data analytics have long been seen as a valuable way for businesses to refine their marketing and improve their communication. However, as we learn more about the ways that data can be applied to a business, we’re better understanding the many ways that it can improve business management.”[3] She adds, “Relying on data can help any operation to make better big decisions and improve overall management. From cognitive computing to applying data to streamline in-office processes, operations in both the public and private sectors can put data to use to improve management and inform business decisions.”

 

Former IBM executive Irving Wladawsky-Berger, writes, “Decisions typically involve two main tasks: predictions and judgment. As machine predictions become inexpensive and commonplace, the human judgment that leverages and complements prediction will become more valuable, especially given the increasing complexity of the decisions our institutions are called upon to make.”[3] Wladawsky-Berger’s observation about the technology making predictions cheap, is echoed by three professors from the University of Toronto’s Rotman School of Management, Ajay Agrawal, Joshua Gans (@joshgans), and Avi Goldfarb (@avicgoldfarb), who make the profound observation that technology’s primary value is making things cheaper. “Technological revolutions,” they write, “tend to involve some important activity becoming cheap.”[4] In the Information Age, cognitive technologies are making answers (which include predictions) cheap. Kevin Kelly (@kevin2kelly), founding Executive Editor of Wired magazine, notes, “While answers become cheap, our questions become valuable. This is the inverse of the situation for the past millennia, when it was easier to ask a question than to answer it.”[5]

 

Cognitive technologies augment rather than replace human decision making

 

Making good decisions remains difficult, even in the Digital Age. Wladawsky-Berger cites an article published by McKinsey & Co. entitled “Untangling Your Organization’s Decision Making,” which states, “It’s the best and worst of times for decision makers. Swelling stockpiles of data, advanced analytics, and intelligent algorithms are providing organizations with powerful new inputs and methods for making all manner of decisions. [On the other hand], Corporate leaders also are much more aware today than they were 20 years ago of the cognitive biases — anchoring, loss aversion, confirmation bias, and many more — that undermine decision making without our knowing it.” Wladawsky-Berger continues, “What accounts for this seeming paradox? Our emerging data and AI revolution holds the promise to augment our judgment and expertise and help us make smarter, more effective decisions. But our growing organizational complexity has clouded decision-making accountability.”

 

One of things the McKinsey article points out is that making decisions at the right level is a “practice 6.8 times more likely to be part of a winning company.” In order for the right people at the right level to become better decision makers, they need access to right data at the right time. To make that happen, organizations need to get rid of information silos and provide access to an integrated dataset. As noted above, cognitive computing platforms, like the Enterra Enterprise Cognitive System™ (AILA®) — a system that can Sense, Think, Act and Learn® — are playing increasingly important roles in corporate decision making. Cognitive technologies don’t offer pat answers; they provide insights that can be used to augment human decision making. Just as importantly, cognitive computing platforms can help speed up decision making. Wladawsky-Berger observes, “Such a combination of high quality and speed is much more common in winning organizations.”

 

Eric D. Brown (@EricDBrown), Managing Partner at Crossing Digital and CIO at Sundial Capital Research, underscores the fact that cognitive technologies and advanced analytics only improve and speed up decisions “if you invest in people and process.”[7] He writes, “Big data without the right people and the right skills is nothing more than a bunch of data stored in a system somewhere. The real key to success in the world of big data is finding a way to convert that data into useful information for people to internalize. Once it’s internalized, that data will convert to knowledge, which is where the real value is found within any type of data. … Big data success requires good systems and good strategy, along with human experience, expertise, and intuition to make proper use of data.”

 

Concluding thoughts

 

Sameer Dhanrajani (@DhanrajaniS), Chief Strategy Officer at Fractal Analytics, predicts, “Artificial Intelligence will deliver revolutionary impact on how enterprises make decisions today.” He concludes, “As we augment decision-making with algorithmic, AI-centered systems and platforms — the big expectation is that they will bring untold efficiencies in terms of cost, alongside improvement in the speed and quality with which decisions get made. It’s time to reimagine and deliver on enterprise decision-making that is increasingly shaped through artificial intelligence.” People who expect cognitive technologies to make decisions for them are likely to be disappointed. Those who understand the augmenting benefits of such technologies and who learn how to leverage them will ensure their organizations are Digital Age winners.

 

Footnotes
[1] Michael C. Mankins and Lori Sherer, “Creating value through advanced analytics,” Bain Brief, 11 February 2015.
[2] Ashish Parmar, “Big Data Analytics Paving The Path For Businesses With More Informed Decisions,” Datafloq, 1 March 2019.
[3] Magnolia Potter, “How Data Analytics Improve Business Decisions,” insideBIGDATA, 9 August 2019.
[4] Irving Wladawsky-Berger, “Decision Making in Our Increasingly Complex Organizations,” The Wall Street Journal, 12 July 2019.
[5] Ajay Agrawal, Joshua Gans, and Avi Goldfarb, “The Simple Economics of Machine Intelligence,” Harvard Business Review, 17 November 2016.
[6] Kevin Kelly, “With AI, Answers Are Cheap, But Questions Are The Future,” Longitudes, 9 March 2017.
[7] Eric D. Brown, “Why big data alone won’t speed up your decisions,” The Enterprisers Project, 10 September 2019.
[8] Sameer Dhanrajani, “Reimagining Enterprise Decision-Making With Artificial Intelligence,” Forbes, 15 October 2018.