Big data is changing the way we look at the world, from the way we operate our businesses to the way in which our governments respond to climate change. However, there still seems to be a disconnect between the information gathered by data science and the ways in which leadership responds to such discoveries.
Part of this is the enormity and scope of big data, but most of our inability to act is due to the human psychological framework. We trust our biases over empirical evidence, which leads to discoveries found too late and mistakes that are rarely admitted.
The Ostrich Paradox And Six Psychological Biases That Lead Us To Under-Prepare
Big data has given us the ability to see into the future like never before. Instead of relying on the minds of a few, we can unlock discoveries from hundreds or thousands of data points. From environmental changes to consumer choices, our ability to understand and predict the future has never been more attuned. And yet, we still make errors in judgment that actively contradict data. Why is that?
In their book The Ostrich Paradox: Why We Underprepare for Disasters, Robert Meyer and Howard Kunreuther discuss the six psychological factors that contribute to human error in the age of big data:
- Myopia
- Amnesia
- Optimism
- Inertia
- Simplification
- Herding
These six psychological traits benefit our individual lives but lead to grave errors in judgment at the macro-level. This is why data science is becoming the true leader in the fight against climate change to help us better prepare for a rapidly changing tomorrow.
The Antidote to Emotions-Based Decision Making
These psychological traps are inherently difficult to remove from the decision-making process, which is why data science is becoming the most critical element in the modern business world. Those who understand data better than the competition and can effectively use it for better decision-making are those who will ultimately succeed and lead markets in innovation.
You may be asking, “How is this different from the analytics used by businesses for decades prior?” This is an important distinction because there are several essential areas in which big data differs from previous analytical tools.
First and foremost, big data includes a scope that businesses couldn’t imagine even a few decades ago. Before, there was no worldwide network for data sharing or tools to track instantaneous data on actions or behaviors not specifically researched by analysts. However, now we have the technologies to track data on an incalculable scale and derive insights from knowledge points we never even thought to study.
The other common objection to data-driven decision-making is that it doesn’t capture the human element needed for more intelligent choices. However, Harvard University and the MIT Center for Digital Business decided to put the data-driven theory to test by interviewing over 330 North American businesses about their management practices and how they translated to business performance. They found that data-driven companies were 5% more productive and 6% more profitable than those who relied on traditional decision-making tactics.
Try Arkly Pro for freeHow To Become More Data-Driven
The evidence that data-driven decision-making can help improve performance and innovations is unequivocal. Moreover, using data to manage risks for your business or community can foster a healthier outlook for tomorrow. If you want to transform your leadership practices, we suggest these three steps:
Step 1: Look for trends
Big data doesn’t give you the answers, only the facts. The human element of creativity is still needed to detect patterns and glean insights from numbers. Don’t forget your role as a leader to read between the lines.
Step 2: Use data first for decision making
Falling into old habits (those six psychological decision-making mistakes) is easy, but it will cost you in the long run. Whenever you are faced with a difficult decision, consult the data first. The earlier you start researching instead of assuming, the easier it will be to make tough decisions led by data science.
Step 3: Get used to being uncomfortable
The reason we fall into those psychological habits is that accepting the truth is often uncomfortable. There will be things in the data you don’t want to receive, and some will be incredibly difficult to share with stakeholders. However, accepting the truth is much easier than trying to change it. As a leader, it is your job to make the tough calls and back them up through data science, knowing you’re making the right choice.
Want to know more about how data science is leading the fight against the climate crisis? Get in touch to learn more about how HighTide can help you make data-driven decisions to manage your flood risk.