Data-driven decision making (or DDDM) is the method of making authoritative decisions based on actual data rather than instincts or monitoring alone. Consistency and continuing development is the importance of data in decision making. It helps businesses to develop new market opportunities, generate incremental revenues, forecast future developments, maximize existing operations, and create actionable insights.

There's always a risk factor in a company, but data-driven decisions make you less vulnerable to risky choices going wrong. Example- According to UTICA College, the name of Google is synonymous with data-driven decision making. The purpose of the organization is to ensure that data and analytics are focused on all decisions. The People Analytics Department was created by Google to help the organization make HR decisions using knowledge, including determining if managers are making a difference in the success of their teams. In order to address this question, the department used performance evaluations and employee surveys. It had a positive effect initially. But a closer look at the data found teams with better executives worked best, are happier, and worked longer at Google.

In order to motivate employees, Google created the "Great Managers Award" to nominate managers they think made a difference. Google also had managers interviewed about their operations. Google has built eight habits for successful managers using this data and the top three explanations for why managers may have a hard job. Google then used this knowledge to assess the actions of employees, to perform a twice-yearly feedback study, and to evaluate its management training program.

Therefore, the advantage of having a data-driven enterprise is that you have continuity over time. It lets people know how decisions are taken within the company. People can define, interpret, and handle the consequences of data collected and taken action.

It is possible to improve data-driven decision-making by looking at and prioritizing your goals, identifying and providing relevant data, drawing conclusions from that information, preparing your strategy, assessing progress, and repeating it.

Today, every industry strives to be data-driven. Most experts recognize that bias and false assumptions (among other problems) can cloud judgment without data and lead to poor decision-making. With technology underlying almost every part of your company, by testing various scenarios and their performance, you can use the data it produces to see exactly what is happening in your organization and use the knowledge to make your business more agile.

Data-driven decision making (DDDM) in 2020 and beyond is becoming a more prevalent method for business decisions. Instead of choices purely based on intuition or observation, it includes making decisions that are supported by data analytics and modeling.

Now, it is obvious why data is so important to a company. It is now crucial to have a clearer and quicker view of the things happening all over the world at the same time. The details should be the basis of each decision you make. But the real difficulty lies in the fact that you need to find the data that can produce the most important and real insights that can be used to make effective decisions that can move the organization to new heights.