The rise in computational power and machine learning has driven the growth of big data applications. As a result, the trend of adopting big data analytics among organizations to facilitate decisions is on the rise. The progress is so rapid that many organizations even rely on automated decision making using complex algorithms. However, a large majority of companies still rely on human intuition and experience for effective decision making. It is only human to be resistant to change, and thus managers still have doubts over the efficacy of big data analytics.
In hindsight, artificial intelligence is yet to achieve the decision-making potential of a human when it comes to emotions, thoughts, experiences, and heuristics. Nevertheless, the power of big data analytics cannot be ignored as it has consistently delivered better performance on all fronts. Combining the power of big data with human intuition can unlock limitless possibilities. Thus, it is imperative that businesses use big data analytics diligently to address business problems.
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Tips to Adopt a Scientific Approach to Decision Making using Big Data Analytics
Use Proper Data Visualization Tools
A ton of raw data, information, numbers, and figures could be overwhelming to a decision-maker and potentially lead to a case of information overload. A proper visualization tool can assist the decision-maker in playing out the scenario in their head and assist in devising effective solutions. Proper visualization tools can simplify the process of identifying the problem area and possibly suggest alternative solutions.
Test, Analyze, Adjust, and Repeat
The advent of the digital medium along with big data analytics has made it possible to customize marketing messages down to a single customer. It also paves the way to test out a decision on a small sample of the population, and monitor the result before implementing it on a large scale. Human intuition can guide in choosing the best decision alternative by continuous testing.
Differentiate Correlation from Causation
Big data analytics has the power to compute and predict almost anything thrown at it. Prediction models have become smart over time, but human intuition has a significant role to play here. Just because two data sets correlate it doesn’t mean one causes the other. For instance, an increase in temperature and crime rate doesn’t imply that one is causing the other. The underlying reason could be that because of heat, people are more likely to be on the street, which increases the chances of a crime being committed. It is important to analyze such a hypothesis before running it through predictive models thoroughly.
Contact our analytics experts to learn how you can implement these approaches in your organization to create a synergy between big data analytics and human intuition.
Use Appropriate Tools and Techniques
A majority of the analysts usually limit themselves to using basic correlation and familiar techniques like regression. Such action can lead to consequences being misguided by data as they fail to acknowledge all affecting variables. Analysts should resort to newer techniques such as neural networks and machine learning to leverage technology for efficient decision making.