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Big Data Analytics and Better Decision-making

November 8, 2016


We’ve all made bad decisions in our lives. In business, however, bad decisions can impact more than our individual lives. Business leaders are driven to make decisions, because making no decision can be as disastrous as makinga bad decision. I daresay most business leaders embrace Teddy Roosevelt’s philosophy, “In any moment of decision, the best thing you can do is the right thing, the next best thing is the wrong thing, and the worst thing you can do is nothing.” Today’s business leaders have new allies when it comes decision-making — big data and advanced analytics. In an intriguingly titled study called “The End of Bad Decisions,” McKinsey & Company analysts, Guido Frisiani, Pallav Jain, and Gloria Macias-Lizaso Miranda, observe, “[A] vast trove of big data has been building for years. But now we have the computing horsepower to make use of it. Calculations that would have once required a roomful of servers can now be accomplished on a laptop. Finally, new algorithms have come onto the market that enable users to take advantage of all that data and all that computing power.”


Decisions Define an Enterprise


Although I’m skeptical bad decisions are a thing of the past, I agree business leaders now have tools available capable of providing actionable insights from which better decisions can be made. Bain analysts, Michael C. Mankins and Lori Sherer (), note that decision making is one of the most important aspects of any business. “The best way to understand any company’s operations,” they write, “is to view them as a series of decisions.”[1] They explain:

“People in organizations make thousands of decisions every day. The decisions range from big, one-off strategic choices (such as where to locate the next multibillion-dollar plant) to everyday frontline decisions that add up to a lot of value over time (such as whether to suggest another purchase to a customer). In between those extremes are all the decisions that marketers, finance people, operations specialists and so on must make as they carry out their jobs week in and week out. 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.”

The tools to which the McKinsey analysts refer are found in artificial intelligence (AI) systems and, more specifically, in cognitive computing systems. I define cognitive computing as a combination of Semantic Intelligence (Artificial Intelligence + Natural Language Processing) combined with Computational Intelligence (Advanced Mathematics). Artificial intelligence systems can provide actionable insights when business leaders are faced with significant decisions and can autonomously make routine decisions freeing humans to concentrate on more important matters.


Embracing Cognitive Computing and Big Data Analytics


Most companies have plenty of data. They simply aren’t sure how to leverage it to make better decisions. David Weldon (@DWeldon646) reports, “Organizations for the most part agree on the great value of corporate data. Unfortunately, for the most part data professionals believe their organizations do a poor job of interpreting and using that data. A new study from Dimensional Research reveals this disconnect, and concludes that ‘data professionals have little confidence in the way business stakeholders within their organizations use corporate data when making important business decisions.’ The study finds a number of areas in which those that capture and manage data, and those that act on it, are out of sync.”[2] Disconnects often occur because data is contained in divisional silos. Since cognitive computer systems can gather and integrate both structured and unstructured data, they ensure decision-makers throughout an enterprise are using a single version of “the truth” when making decisions. Not only does this help with decision-making it helps promote corporate alignment.


Mohammad Farooq (@farooqSL) asserts, “Every decision made today has a significant impact on the future of that organization. The rate at which a company responds to challenges in the present and the future is what determines their rate of success. Data Science and Big Data analytics can help organizations in decision making and drive the company to a realistic future.”[3] As Farooq explains, the decision cycle for most businesses is getting faster while the amount of data needing analysis is simultaneously growing. “The time cycle for decision making is decreasing rapidly,” he writes. “Companies have to make decisions more quickly in this period than in the past. Accelerating decision-making time is crucial for the success of any organization. The use of Big Data doesn’t change the urgency of decision making. Big Data analytics mitigates.” That’s why embracing cognitive computing capabilities is and will continue to be essential for most businesses. And it’s why Accenture analysts conclude cognitive computing will provide the “ultimate long-term solution” for many business challenges.[4]


If you think analyzing data has been challenging in the past, just wait. The emergence of the Internet of Things (IoT) is going to exponentially increase the amount of data many companies must manage. As Devavrat Shah, a professor in MIT’s Department of Electrical Engineering and Computer Science, puts it, “There is a new stumbling block on the horizon. Sensors are now spreading across almost every industry, triggering a massive onslaught of new data that will clearly lead us into the next era of the information age.”[5] Shah suggests every company facing new information age challenges needs to do three things: capture the right data; ask the right questions; and build systems and skills for the future.




Brian Hopkins (@practicingEA). a Vice President and Principal Analyst for Forrester Research, asserts, “In this emerging world of too much data, what matters most is how you discover and implement digital insight in the fabric of your business. To do this, you don’t need more data; you need systems of insight driven from the top by a culture that values insights-to-execution. And you need technology and services that bring together data, analytics, implementation, and continuous learning and optimization.”[6] I couldn’t agree more. Although new technologies and services won’t bring an end to bad decisions, they certainly will reduce the number of bad decisions in the years ahead. Cliff Moyce (@cliffmoyce), global head of finance practice at DataArt, concludes, “The cognitive analytics revolution in business is underway. It is underpinned by artificial intelligence, cognitive computing and machine learning. Cognitive analytics will give business executives such as the CEO, CFO, CIO and CMO massively enhanced data-driven decision-making abilities, as well as the ability to track and learn from prior decisions. … Cognitive analytics is set to transform our ability to plan, develop and run businesses. It is genuinely transformational in a way that some other technologies have been (for example, Cloud) and some have not. It is not a panacea for all ills, but it does help enormously with the diagnoses of those ills. Early adopters will be well rewarded.”[7]


[1] Michael C. Mankins and Lori Sherer, “Creating value through advanced analytics,” Bain Brief, 11 February 2015.
[2] David Weldon, “Despite Best Intentions, Most Organizations Misinterpret, Misuse Data,” Information Management, 2 November 2016.
[3] Mohammad Farooq, “How Does Big Data Analytics Help in Decision Making,” Datafloq, 3 August 2015.
[4] “From Digitally Disrupted to Digital Disrupter,” Accenture, 2014.
[5] Devavrat Shah, “The Big Data Challenge: Getting from Data to Decisions in the Era of IoT,” DataInformed,
[6] Brian Hopkins, “Think You Want To Be ‘Data-Driven’?,” Information Management, 18 March 2016.
[7] Cliff Moyce, “OP/ED: Cognitive analytics gives business the edge,” FTSE Global Markets, 11 October 2016.

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