By Stephen DeAngelis
Business circles are abuzz with terms like digital transformation and digital enterprise. The fascination with digitization in the digital age is completely understandable. The stress on digitization, however, sometimes understates the real goal of transformation — the ability to make better decisions. Bain analysts, Michael C. Mankins and Lori Sherer (@lorisherer), 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.” Digital transformation is all about making better decisions. Businesses successfully transforming become more than digital enterprises; they become cognitive businesses (aka intelligent enterprises).
Cognitive computing and early adapters
Cognitive computing — which I define as a combination of semantic intelligence (i.e., machine learning, natural language processing, and ontologies) and computational intelligence (i.e., advanced mathematics and analytics) — can do more than improve decision making; but, improving decision-making is one of its most important capabilities. Thomas H. Davenport (@tdav), a distinguished professor at Babson College, and Deloitte LLP managing directors Jeff Loucks and David Schatsky, observe, “‘Cognitive-aware’ executives expect artificial intelligence to have a major impact on business and the workforce, and many are already realizing benefits.”[2] They go to note a 2017 Deloitte survey found, “Many early adopters of cognitive technologies are upbeat about their potential, and many expect them to drive economic growth and transform both companies and entire industries.” In a separate article, they report a follow-on Deloitte survey concluded, “Companies are using AI to improve business processes, with survey respondents identifying increased emphasis on AI’s ability to support internal and external operations (42 and 31 percent, respectively). They are also using AI to enhance current products (44 percent) and improve decision-making (35 percent).”[3]
Becoming an intelligent enterprise
“The future has arrived,” writes business tech consultant Ryan Ayers (@TheBizTechGuru). “Today, computers can nearly mimic the human mind’s ability to learn, think, reason, analyze and make decisions. This technology is called cognitive computing.”[4] Ayers stresses the symbiotic relationship between cognitive computing and big data. Without data, cognitive platforms have nothing to learn from or anything to think and reason about, or anything to analyze or make decisions from. He notes, “Cognitive systems build on current advanced big data technologies by reducing much of the programming required to perform effective analyses. … Advanced technologies, such as cognitive intelligence, predictive analytics, and machine learning build on the foundation of big data systems. Now, with the introduction of cognitive intelligence technology, cutting-edge data analysis systems emulate the complexity of the human mind. Today, data scientists must teach cognitive intelligence technology how to learn. Tomorrow, the technology will teach itself.”
Jacob Wolinsky (@JacobWolinsky), founder of ValueWalk.com, notes, “Cognitive systems aren’t intended to replace human workers. Instead, they’re intended to help businesses process data, find biases and eliminate them, assist in decision-making, and automate some of the tedious tasks that take up the valuable time of employees. In business, AI can help encourage smart strategy and make companies more efficient.”[5] According to Jay Nair, Chief Operating Officer at Marlabs Inc., cognitive computing helps businesses go beyond being data-driven to being value driven. He explains, “Positive technological advancement is in the technology’s ability to augment human intelligence or performance; it’s what makes cognitive systems relevant — the ability to interpret, analyze, learn, and reason without constant human involvement. And that’s where things get interesting. With the inherent ability to now understand the context behind the content, cognitive computing is taking the Big Data world by a storm, transforming the ordinarily data-driven ecosystem into something value-driven.”[6] I appreciate the fact he talks about the ability to understand context. At Enterra Solutions®, we believe a big part of understanding context is leveraging common sense ontologies as part of smart business solutions. The Enterra Enterprise Cognitive System™ (AILA®) — a system that can Sense, Think, Act, and Learn® — utilizes Cycorp’s Cyc ontology database to ensure its insights are imbued with as much common sense and proper context as is currently possible.
One of the things distinguishing cognitive computing systems from older decision platforms is their ability to handle ambiguous situations. Analytics expert Kamalika Some (@KamalikaS) notes, “A cognitive computing system is used in complex situations for ambiguous and uncertain outcomes”[7] It would be nice if decisions were always black and white rather than myriad shades of gray; but, that’s not the world in which we live. Therefore, cognitive computing’s ability to deal with ambiguous data will become increasingly useful. Nair writes, “It’s necessary to transform data into information, but there’s more value in evolving data to represent knowledge and eventually — wisdom. We aren’t far from being able to do this, and all it’ll take is the right combination of technologies such as deep learning, natural language processing, augmented intelligence, and pattern recognition.” And I would add, ontologies.
Concluding thoughts
More and more analysts believe the adoption of cognitive technologies has become table stakes in the future business environment. Davenport, Loucks, and Schatsky conclude, “Companies cannot afford to bide their time while competitors potentially move forward with the technologies. … Now is the time for organizations to define AI-powered business use cases and outcomes that can deliver measurable ROI.” They note the Deloitte survey found, “Sixty-three percent of respondents are using AI to catch up, keep up, or edge slightly ahead of competitors, while 37 percent are using it to notably widen their lead.” Some adds, “Cognitive performance computing has taken the leaders in business, management consulting and government around the globe by storm. … Cognitive operations are increasingly being adapted in organizations where there is a constant set of unknowns.” Although we remain in the early implementation stage for cognitive systems, Ayers asserts, “Early adopters of cognitive technology expect that the innovative resource will have a major impact on commerce. Already, advanced analysis systems are heavily impacting and changing how enterprises conduct business.”
Footnotes
[1] Michael C. Mankins and Lori Sherer, “Creating value through advanced analytics,” Bain Brief, 11 February 2015.
[2] Thomas H. Davenport, Jeff Loucks, and David Schatsky, “Early Adopters Bullish on Business Value of Cognitive,” The Wall Street Journal, 11 January 2018.
[3] Jeff Loucks, Thomas H. Davenport, and David Schatsky, “The State of AI: Early Adopters Forge New Paths to Cognitive,” The Wall Street Journal, 28 November 2018.
[4] Ryan Ayers, “Big Data and Cognitive Business Disruption is all You Need to Know,” readwrite, 21 December 2018.
[5] Jacob Wolinsky, “How Cognitive Systems Are Changing Businesses,” ValueWalk, 18 December 2018.
[6] Jay Nair, “Cognitive Computing: Data-Driven to Value-Driven,” Data Science Central, 2 September 2018.
[7] Kamalika Some, “Leveraging Cognitive Computing for Business Gains,” Analytics Insight, 19 September 2018.
