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In the world of big data, some things are easy to objectively measure, such as how much money a person spends, or how much time it takes to accomplish something. Other things are notoriously difficult to quantify, such as moods, subjective opinions, and beliefs.
As our technology enables us to make and store more measurements, and as demand for big data analysis continues to grow, we’re going to have the option to quantify these “unquantifiable” metrics. There are some major advantages to this approach, but are they worth the potential costs?
The Plus Side of Quantification
These are some of the biggest advantages this kind of data quantification can offer:
Tools for decision making. When you’re making a major decision on behalf of a company, staking thousands to millions of dollars on your conclusions, you can’t cite your instincts or beliefs as hard evidence in favor of your chosen position. It’s better to have something evidence-backed and provable on your side. For example, you can calculate a priority score for projects in your portfolio management (PPM) strategies, or even rely on average user ratings to gauge satisfaction.
Avoiding blind speculation. Numerical values also hold us to some degree of objectivity; without a figure to point …
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