But, do you ever think about intuition being in your toolbox?
Intuition is a hot topic for blogs and columns these days – especially as it relates to Big Data. One side of the fence is cautious of people losing the skill of intuition while the other side is enthusiastic that individual intuition should be enhanced with data analytics.
Let’s start on the cautious side of the fence. In David Brooks’ column he states, “Data can’t account for everything in our experience, nor serve as the only guide for our thinking, planning and decision-making.” He goes on to list ways data analytics could create misinterpretations as well as limitations of data analytics.
In another column David Brooks states, “In sum, the data revolution is giving us wonderful ways to understand the present and the past. Will it transform our ability to predict and make decisions about the future? We’ll see. ”
Art Langer discusses using crutches in decision making. “… there are many great decisions that are made by people that go on intuition and “gut-feel.”
Irving Wladawsky-Berger talks about a few tough challenges: job and lifelong learning, rising standard of living in emerging economies, and an aging population. He predicts that as digital technologies are applied to problem solving we will have to upgrade our intuition to use the tools.
On the enthusiastic side of the fence is Jennifer Belissent. “What can you do with this data? Innovate. And, if you don’t, your competitors will. New competitors will rise up and disrupt the status quo in all industries.”
Thomas H. Davenport thinks we are prepping for analytics 3.0. “Tools that support particular decisions are being pushed to the point of decision-making in highly targeted and mobile “analytical apps.”
Regardless of your perspective on data analytics – cautious or enthusiastic – everyone agrees that intuition is critical to success. Paul Rafferty talks about how Big Data is used by Chief Marketing Officers (CMO). “But, it’s important to note: it’s wise to let CMOs keep their intuition in the toolbox.”
Intuition can be developed different ways. I think some people are just born better at it than others. Maybe their parents were intuitive and so they picked it up. Some people get it from an abundance of repeated and unique experiences. Others get it from having an outstanding mentor who teaches them how to be intuitive.
It is valuable to take a moment to understand intuition. At any point in time, we are all doing three things that enable us to leverage our intuition:
- Developing situation awareness,
- Accomplishing a goal, and
- Reacting to environmental cues.
Developing situation awareness: While we are developing situation awareness, we are gathering information from the environment with our senses. We see, hear, smell, touch, and taste. Once we get the raw data we try to make sense of what we are sensing by looking for patterns or the unexpected. Then, we predict what will happen next. I know this sounds a lot like Big Data – humans are the best data analytic systems there is.
Accomplishing a goal: As we develop our situation awareness we are working towards a goal. We could be planning, designing, monitoring, assessing, predicting, diagnosing, scheduling, explaining, or executing. The situation awareness aides us in choosing options and making decisions as we move toward our goal.
Reacting to environmental cues: Sometimes the situation awareness will pick up on a pattern that changes our priorities. We start a reaction – a change in our goal to address that new piece of information. Eventually, we will probably come back to the original goal.
The combination of the three activities – situation awareness, goal directed behavior, and reactions – are how we, at Discovery Machine, think of intuition. As we live life and collect experiences we get better and better at the three steps of intuition.
If we consider our own intellectual functions, there is a good place for Big Data to fit. There is an immense amount of data available that our senses have not been designed to process – such as website statistics, credit card transactions, and clinical trials. However, computers do a pretty good job at that. Even though Big Data complements our own cognitive processing, as humans, we can’t stop our own development and usage of intuition. We need to reflect upon our own cognition, learn how to do it better, and how to use tools to supplement our limitations. Refer to this blog series to learn how experts and practitioners can conduct the introspection and articulation of intuition.
Do the introspection and articulation of your thought processes. How can your analysis get better? How can you help other members of your team get better? How can other members of your team add value to the cognitive processes by adding in their own introspection and articulation? Now, how does a software tool like Big Data help you get even better at problem solving?
Considering the proposed definition of intuition and where Big Data fits, wouldn’t it be interesting if we could gather data on situation awareness, goal directed behavior, and reactions – the actual tasks and decisions people are making and why? That would give Big Data additional power since now all we are collecting is evidence of transaction.
I think the next phase of Big Data will be collecting data on cognitive decision making. If you had transactional data and decision making data, what would you do with that?
To see the rest of the series and find out more about Discovery Machines approach, see 6 Steps to Boomerang Expertise.
In my next blog, Strategic Knowledge is More Important than Big Data, I discuss why strategic knowledge is important and how it relates to Big Data.
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