There is no shortage of evidence to show that, in nearly every decision point in life, analytical decision-making is more accurate and produces better decision outcomes. Conversely hunches, intuition, guesstimates, and conjecture based decision making provide for below average performance, and remove the possibility of improved decision making.
Performing analytics on a large data set starts with understanding and formulating a hypothesis. We then move on to gathering and analyzing relevant data. This then leads us to interpreting and communicating these analytical results. Developing quantitative thinking adds to a data scientists ability to deliver precise results. In full spectrum summarizing data, finding the meaning in it and extracting the value is a complete solution to an analytic data project deliverable.
Analytic decision solutions can be found everywhere:
- Marketing (pricing, locations, promotions, advertising placement, website customization)
- Supply chain (inventory levels, distribution center placement, routing)
- Finance (identification of financial performance drivers)
- H.R. (prospective employees, workforce compensation, benefits selection)
- R&D (which product features are most desired by customers)