Data-Driven Decision Making (DDDM)

Definition - What does Data-Driven Decision Making (DDDM) mean?

Data-driven decision making (DDDM) involves making decisions that are backed up by hard data rather than making decisions that are intuitive or based on observation alone. As business technology has advanced exponentially in recent years, data-driven decision making has become a much more fundamental part of all sorts of industries, including important fields like medicine, transportation and equipment manufacturing.

Data-driven decision making is also known as data-driven decision management or data-directed decision making.

Techopedia explains Data-Driven Decision Making (DDDM)

The idea of data-driven decision making is that decisions should be extrapolated from key data sets that show their projected efficacy and how they might work out. Businesses generally use a wide range of enterprise tools to get this data, and to present it in ways that back up decisions. This is in stark contrast to the way that decision-making had been done throughout the history of commercial enterprise, where before the presence of new complex technologies, individuals often made decisions on the basis of observation or informed guesswork.

These days, if one wants to know how a given product might perform in a market, what a customer might think of a slogan, or where to deploy business resources, decision support software can help. That has led to a much bigger demand for data-driven decision making solutions. TechTarget cites a study from the MIT Center for Digital Business that shows businesses using data-based decision-making were found to have 4 percent higher productivity and 6 percent more profit on average.

In order to serve this booming demand, companies have come out with self-service data analytics products – the idea is that self-service products lead to more egalitarian data collection and transfer. In other words, without self-serve tools, only a skilled data scientist can crunch the numbers and come up with the data supporting decisions, where with decision support tools that are self-serve, executives and others who are further from the IT department can do their own analysis and present their own decisions backed up with the data in question.

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