Editor - When we work with foodservice brands here at RSMI Restaurant Social Media Index and DigitalCoCo, we query the data pools with an eye on predictive analytics - we can successfully tell restaurant operators if they are likely to experience sales ups or downs. This article describes six best practices that medium/large businesses implement - we can bring this ability to any size restaurant operator.
Predictive analytics is fast becoming a mainstream technology tied to business outcomes, so the playing field is expanding from data science labs into the business and even corner offices.
According to TDWI 's Predictive Analytics for Business Advantages 2014 survey, business analysts will soon overtake statisticians and data scientists as the top users of predictive analytics tools. To prepare for this transformation, where data teams and business managers work closely together, here are six tips to help companies take advantage of predictive analytics:
1. Pinpoint the need
Too often, teams try to aggregate interesting data sources and see where it takes them. Data scientists and business managers need to define their problem as well as what they 're testing for and their desired outcomes. Only then should the data team start building a model. Read More..