The more data we share, collect and analyse, the easier it is to see into the future with predictive analytics. But what’s it all about and how can it benefit your business?
‘Predictive Analytics’ is described as “In business, predictive models exploit patterns found in historical and transactional data to identify risks and opportunities. Models capture relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions, guiding decision making for candidate transactions.” – from Wikipedia
PA can be applied in an infinite number of scenarios to help businesses improve their service, save money or even, in the case of Visa and Chevron, prevent fraud. The great thing about this is that CIPHR contains both historical and transactional data, enabling our customers to predict future patterns and events based on data already within their system.
Some examples where CIPHR data can be used to predict potential future events include:
- Problematic absence – do you have employees that are absent at certain times in the year, say, during certain sporting events?
- Will you be under resourced at certain times of year based on previous years holiday patterns?
- Are there particular months in the year where your recruitment efforts in certain areas will be more successful?
- Are there employees that may be at risk of resigning based on previous appraisals?