What Is Data Driven Decision Making?
Data driven decision making (DDDM) is the process of using data to make informed and verified decisions. Modern analytics tools such as interactive dashboards, help people to overcome biases and make the best managerial rulings that are aligned with business strategies.
Fundamentally, data driven decision making means working towards key business goals by leveraging verified, analyzed data rather than merely shooting in the dark.
However, to extract genuine value from your data, it must be accurate as well as relevant to your aims. Collecting, extracting, formatting, and analyzing insights for enhanced data driven decision making in business was once an all-encompassing task, which naturally delayed the entire data decision making process.
But today, the development and democratization of business intelligence empower users without deep-rooted technical expertise to analyze as well as extract insights from their data. As a direct result, less IT support is required to produce reports, trends, visualizations, and insights that facilitate the data decision making process.
From these developments, data science was born (or at least, it evolved in a huge way) – a discipline where hacking skills and statistics meet niche expertise. This fairly new profession involves sifting large amounts of raw data to make intelligent data driven business decisions.
The ‘gold’ that data scientists ‘mine’ comes in two distinctive types: qualitative and quantitative, and both are critical to making a data driven decision.
Qualitative analysis focuses on data that isn’t defined by numbers or metrics such as interviews, videos, and anecdotes. Qualitative data analysis is based on observation rather than measurement. Here, it’s crucial to code the data to ensure that items are grouped together methodically as well as intelligently.
Quantitative data analysis focuses on numbers & statistics. The median, standard deviation, and other descriptive stats play a pivotal role here. This type of analysis is measured rather than observed. Both qualitative and quantitative data should be analyzed to make smarter data driven business decisions.
Now that we’ve explored the meaning of decision making in business, it’s time to consider the reason why data driven decision making (DDDM) is important.
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