The advancement of data analytics has opened many doors in today’s corporate world. One of the main areas affected is decision-making within a company. Previously, leadership and management relied solely on past experiences and a ‘gut feel.’
Today, data can transform how we make decisions based on facts and real-time evidence. That being said, are data-driven decisions always the best course of action?
In this article, we explore data vs intuition when making corporate decisions, their pros, and cons as well as a possible synergy between the two.
Data-Driven Decisions
In today’s corporate world, one wrong decision can make a big impact on a company. Big decisions can’t solely rely on a gut feeling because the risk is too large. Consequently, data has become an indispensable corporate tool in the modern day.
The capacity to comprehend and utilise data is a crucial competency for leaders in any industry since it enables them to predict the future with accuracy.
Companies are able to construct low-risk, customer-specific marketing plans with the use of data. Teams that are data-driven rely on a variety of data sources to make important future decisions.
Pros of data-driven decisions:
- Gives context and structure to the decision-making process.
- Facts from data analysis trump human biases.
- Provides clear, attainable goals.
- Allows executives to stay ahead of the curve so that the future is not left to chance.
Cons of data-driven decisions:
- Not applicable to all situations.
- Data must be current. Old data provide skewed results.
- Susceptible to anomalies such as COVID-19.
- Data can be manipulated to paint a scenario that doesn’t reflect reality.
Data-driven leadership must realise the weaknesses of relying solely on data to make big decisions. Data should essentially be the guiding light for executives in complex situations.
Intuitive Decisions
Intuition comes with experience and expertise. On multiple occasions, the data is unclear and a decision must be made intuitively. This empowers the leadership of the company to draw from previous experiences based on the characteristics of the situation.
Intuitive decision-making is significantly riskier than data-driven decision-making. The capacity of CEOs to read between the lines and make judgments based on criteria that cannot be measured by statistics is, nonetheless, crucial. They can fill data gaps with their own personal knowledge.
Pros of intuitive decisions:
- Intuition provides information where it’s missing in complex situations.
- Allows for action and sidesteps analysis-paralysis.
- Intuition breeds creativity and innovation in decision-making.
Cons of intuitive decisions:
- Lack of knowledge or experience results in poor intuitive choices.
- Open to human biases and consequently skewed data.
- High chance of making wrong decisions.
Intuitive decision-making is most effective in situations where the data is unclear and can’t be relied on. However, it’s not free from risk. Intuitive decisions should still be based on some form of information.
Synergy Between Data and Intuition
My experience has taught me that the optimal decision-making strategy incorporates both data and intuitive reasoning.
Intuition is guided by data so as not to stray too far from the facts. In complex situations where some information may be lacking, intuition supplements data.
Reed Hastings, the CEO of Netflix, explains that they begin with statistics, but their final decision is always based on intuition. They refer to it as “informed intuition”
Informed intuition is the point of synergy between the two decision-making styles. Together, they provide a solid foundation for leaders to make informed decisions about the future.
Leverage Experts is your partner through complex decision-making processes. Get in touch with our experts to learn more about utilising the power of data and intuition to take control of your company’s future.
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Nancy is a Senior Researcher and data analyst within the LE research team. Her research interest is focused on the interlink between disruptive technologies and the transformation of business models in various industries. This includes the digitisation of the healthcare sector, the evolving crypto eco-system, and the application of AI technologies. She contributes to the client’s success by identifying specific trends and opportunities for private equity investors, delivering diligent analysis on competitors and marketplaces, key stakeholders in evolving markets, and global investment trends in various industries.
Nancy builds on a comprehensive and diverse hands-on experience for change and transformation from managerial roles in the East African and GCC Healthcare systems. In addition, she has an MBA from Quantic School of Business and Technology, Washington D.C., and a qualification on AI in the Healthcare System from Stanford University.