July 18

How to avoid biases: Data-Driven-Decision-Making


Every day, whether you are aware of it or not, you make decisions.  You make a lot of decisions. Decision making is largely based on things we have learned and experiences from our past. Many of our decisions are based on our impulses. Sometimes they are based on an analysis of the pros and cons, the balance of each, looking at alternatives, calculating probabilities and making a decision that will maximize the benefits in the long run.

As we enter the new era of technological advancement, the era of digital, the era of data, our decision-making both small and big will change. In the era of data decision-making, we will move away from impulsive, intuitive decisions to decisions based on data and evidence with the help of intelligent machines.

Data undoubtedly is a key ingredient. Of course, it can’t just be any data; it must be the right data. The dataset must be relevant to the question at hand. It also must be timely, accurate, clean, unbiased; and perhaps most importantly, it must be trustworthy.

Data is the foundation and backbone of analytics. Without data you’re just another person with an opinion. Without insight into data, people make decisions based on instinct, speculation, or prevalent theory. Business and people are at risk of acting on biases or false assumptions. Data-driven-ness is about building tools, abilities, and, most crucially, a culture that acts on data.

Data-Driven Decision Making

DDDM or data-driven decision-making is defined as using facts, metrics, and data to guide strategic business decisions that align with their goals, objectives, and initiatives.

Data based decision making provides businesses with the capabilities to generate real time insights and predictions to optimize their performance. By this, they can test the success of different strategies and make informed business decisions for sustainable growth.

We, at Troy Valuations, Inc., use data to determine the value of your business.  Before we give our opinion and valuation, we are certain that data we are using is timely, accurate, clean, unbiased, and trustworthy to avoid risk. 


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