“what gets measured, gets managed” Peter Drucker
This quote by the father of management thinking, is inspiringly relevant to todays’ business data. Vital to measurement is capturing data to ensure your business has ALL the information to hand. The key here is in capturing and migrating data from ALL sources and pooling them into one large unified data set.
Managing these measurements arises from applied analytics to particular data sets to answer particular questions your business strategy requires. Being able to see real-time results of actual data to prove success or failure of certain elements of business processes is vital for assessment as well as developing future strategic goals.
Predictive analytics bring an enhanced set of data management opportunities with them, which provide invaluable insights for decision making as these algorithms can demonstrate a future outcome. This ‘prediction’ enables proposed business strategies to be optimised for best business results.
An example is in the prediction of fraud outcomes and the opportunity to minimise business risk; as recently discussed at the #ClaimsTech conference in London. Capturing current and historical fraud data provides business with:
1. insights into client behaviours
2. insurance products offered
3. financial risk management
4. legal action
5. overall company performance
Applying predictive modelling will demonstrate future cases of potential fraud cases, thereby giving the business an ideal opportunity to test future outcomes enabling their business to become more competitive as they can adapt their strategy and businesses as follows:
1. create a new client vetting strategy
2. update underwriting requirements
3. enhance insurance product offerings
4. minimise risk of financial loss
5. reduce legal expenses
6. improve their bottom line
For insurance / finance businesses and using this example, there are many more elements to predictive modelling such as being able to run statistical analysis for several year sets, generating segmented fraud reports; based on client type, geolocation, or per product set. Alternatively, your business can ‘slice and dice’ your business data and apply key analytics as you require.
This is just the tip of the iceberg. There are so many other opportunities applying predictive analytics and machine learning to data sets can offer. All with the possibility of gaining competitive advantage, purely by turning core, raw data into intelligent insights; historical, real-time and future predictions.
Find out how and learn how unifying data and applying sets of algorithms can benefit your business by contacting us or call 01923 773282 with any questions or comments.