A Sneak Peak to what is Data-Driven Decision-Making
What is Data-driven decision making?
Data-driven decision making (DDDM) is defined as using facts, metrics, and data to guide strategic business decisions that align with your goals, objectives, and initiatives.
Recently there have been an extensive investment in business infrastructure, which have improved the ability to collect data throughout the enterprise. Virtually every aspect of business is now open to data collection and often even instrumented for data collection: operations, manufacturing, supply-chain management, customer behavior, marketing campaign performance, workflow procedures, and so on. At the same time, information is now widely available on external events such as market trends, industry news, and competitors’ movements. This broad availability of data has led to increasing interest in methods for extracting useful information and knowledge from data — the realm of data analytics.
Data perspective
You can find data pretty much everywhere. Any time you observe and evaluate something in the world, you’re collecting and analyzing data. People at every level have conversations that start with data and they develop their data skills through practice and application. Your analysis helps you find easier ways of doing things, identify patterns to save you time, and discover surprising new perspectives that can completely change the way you experience things. We’ve always had and consumed vast amounts of data in our lives, and our brains have always looked for patterns to make sense of them.
A data perspective provides one with structure and principles, and this will give them a framework to systematically analyze business problems. As one gets better at data-analytic thinking they will develop intuition as to how and where to apply creativity and domain knowledge. There are also particular areas where intuition, creativity, common sense, and domain knowledge must be brought to bear.
Data and gut instinct
Detectives and data analysts have a lot in common. Both depend on facts and clues to make decisions. Both collect and look at the evidence at hand. Both talk to people who know part of the story. And both might even follow some footprints to see where they lead. Whether you’re a detective or a data analyst, your job is all about following steps to collect and understand facts.
Analysts use data-driven decision-making and follow a step-by-step process.
There are other factors that influence the decision-making process. You may have read mysteries where the detective used their gut instinct, and followed a hunch that helped them solve the case. Gut instinct is an intuitive understanding of something with little or no explanation. This isn’t always something conscious; we often pick up on the signals without even realizing. You just have a “feeling” it’s right.
Why gut instinct can be a problem. At the heart of data-driven decision making is data. Therefore, it’s essential that data analyst focus on the data to ensure they make informed decisions. If you ignore data by preferring to make decision based on your own experience, your decisions may be biased. But even worse, decisions based on gut instinct without any data to back them up can cause mistakes
The more you understand the data related to a project, the easier it will be to figure out what is required. These efforts will also help you identify errors and gaps in your data so you can communicate your findings more effectively. Sometimes past experience helps you make a connection that no one else would notice. For example, a detective might be able to crack open a case because they remember an old case just like the one, they’re solving today. It’s not just gut instinct.
Data + business knowledge = mystery solved
Many organizations have made data-driven decision making the norm — creating a culture that encourages critical thinking and curiosity. The amount of data and information collected has never been greater, but it’s also more complex. This is where business knowledge comes in.