Enterprise transformation is a continuing theme in business circles. Smart business professionals understand transformation is a continuing journey rather than a one-time trip from point A to point B. Most companies’ current efforts involve wrestling with how to transform into digital enterprises (i.e., organizations that can fully leverage big data). For some organizations that means adopting entirely new business models. Once organizations master the digital realm, they are likely to transform quickly into cognitive enterprises. The reason the latter transformation will more rapid than digital transformation is that cognitive computing platforms are likely to be part of digital transformation efforts. A cognitive enterprise is one which fully exploits the capabilities of cognitive computing across the organization. Monideepa Tarafdar (@mdeepa), a professor of information systems at Lancaster University Management School in the United Kingdom, and Cynthia M. Beath (@CynthiaBeath), a professor emerita at the University of Texas McCombs School of Business in Austin, explain this involves implementing enterprise cognitive computing (ECC). They write, “Enterprise cognitive computing — the use of AI to enhance business operations — involves embedding algorithms into applications that support organizational processes. ECC applications can automate repetitive, formulaic tasks and, in doing so, deliver orders-of-magnitude improvements in the speed of information analysis and in the reliability and accuracy of outputs.”[1]
Cognitive computing in the digital enterprise
The point that shouldn’t be missed in Tarafdar’s and Beath’s explanation is the importance of information analysis. We read a lot about the importance and value of big data; however, that value is derived from analysis. Jelani Harper explains data, by itself, can’t solve a problem until you turn it into information. She adds, “That’s just what cognitive computing is doing for the enterprise today — and what it’s been doing for the past couple of years. It plays a fundamental role in accelerating and automating the core tenets of data management (data modeling, data quality, transformation and integration) to fuel the applications and analytics that provide the merit for which data is renowned.”[2] Prakash Nanduri (@prakash_nanduri), co-founder and CEO of Paxata, told Harper, “To reach an information-driven world where we get the outcome we want, we have to start with data and use smart cognitive computing techniques to make data information.”
Kevin Kelly (@kevin2kelly), founding Executive Editor of Wired magazine, has tweeted, “In the very near future you will cognify everything in your life that is already electrified.” I’m not sure how quickly his prediction will come true, but, in the business world, leaders are cognifying their decision-making and processes at a rapid pace. Cognitive computing is gaining traction because it helps decision-makers in ways traditional computing techniques cannot. The staff at the Cognitive Computing Consortium (CCC) explains, “Cognitive computing makes a new class of problems computable. It addresses complex situations that are characterized by ambiguity and uncertainty; in other words it handles human kinds of problems.”[3] Businesses must deal with human kinds of problems on a daily basis. The CCC staff adds:
“Cognitive computing systems make context computable. They identify and extract context features such as hour, location, task, history or profile to present an information set that is appropriate for an individual or for a dependent application engaged in a specific process at a specific time and place. They provide machine-aided serendipity by wading through massive collections of diverse information to find patterns and then apply those patterns to respond to the needs of the moment. Cognitive computing systems redefine the nature of the relationship between people and their increasingly pervasive digital environment.”
The staff goes on to stress that cognitive computing platforms are adaptable, interactive, iterative and stateful (with both humans and other systems), and contextual. The Enterra Enterprise Cognitive System™ (AILA®) — a system that can Sense, Think, Act and Learn® — is all those things; however, it is especially adept at providing context. The ECS leverages the world’s largest commonsense ontology to ensure context is correct. The CCC staff notes, “[Cognitive computing systems] must understand, identify, and extract contextual elements such as meaning, syntax, time, location, appropriate domain, regulations, user’s profile, process, task and goal. They may draw on multiple sources of information, including both structured and unstructured digital information, as well as sensory inputs (visual, gestural, auditory, or sensor-provided). Cognitive systems differ from current computing applications in that they move beyond tabulating and calculating based on preconfigured rules and programs. Although they are capable of basic computing, they can also infer and even reason based on broad objectives.”
Cognitive computing and decision-making
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.”[4] 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.” Business leaders looking for pat answers from cognitive platforms are going to be disappointed. Author and consultant Ronald van Loon (@Ronald_vanLoon) explains, “Cognitive computing is not responsible for making decisions for humans, instead it is responsible for complementing or supplementing our own cognitive abilities of decision making.”[5] Rama Krishna Kuppa, Founder and CEO of ONGO Framework, insists organizations must transform into cognitive enterprises to thrive in the digital age. “Cognitive computing technology,” he writes, “revolves around making computers adept at mimicking the processes of the human brain, which is basically making them more intelligent. … The primary aspect of cognitive computing is its ability to learn and make decisions based on its experience. … Owing to the amazing performance of these systems, more and more industries and organizations are leveraging cognitive solutions to enhance their operations — like data accruement, insight generation, action planning and management — and boost productivity.”[6] He concludes, “Considering these factors, it is no wonder that the demand for cognitive computing technologies has seen an exponential rise. The global market is expected to cross $12.5 billion by the end of 2019 alone.”
Concluding thoughts
Tarafdar and Beath assert the implementation of enterprise cognitive computing “can generate handsome returns — dramatic improvements in performance, profitability, revenues, and customer satisfaction.” Accenture analysts call cognitive computing “the ultimate long-term solution” for many of businesses’ most nagging challenges.[7]
Footnotes
[1] Monideepa Tarafdar and Cynthia M. Beath, “Using AI to Enhance Business Operations,” MIT Sloan Management Review, 11 June 2019.
[2] Jelani Harper, “The future is now: cognitive computing throughout the enterprise today,” KM World, 29 April 2017.
[3] Staff, “Cognitive Computing Defined,” Cognitive Computing Consortium.
[4] Michael C. Mankins and Lori Sherer, “Creating value through advanced analytics,” Bain Brief, 11 February 2015.
[5] Ronald van Loon, “Cognitive computing: Moving from hype to deployment,” Big Data Made Simple, 15 March 2018.
[6] Rama Krishna Kuppa, “Why modern enterprises need to adopt cognitive computing for faster business growth in a digital economy,” Your Story, 14 March 2019.
[7] “From Digitally Disrupted to Digital Disrupter,” Accenture, 2014.
