There has been an argument over the past few years about real-time vs right-time data amongst vendors and analysts, who approach the question from the feasibility of technology, talking about ‘federated databases’ real-time ETL. real-time purchase history. For techies these are valid questions and interesting arguments. But, if the data doesn’t reach the point of decision making in a form for someone – whether a customer service representative, a salesperson, a manager – to make a decision RIGHT NOW then the value of the information in the data has been lost.
If instead we approach the question from the point of view of the business process then we get a different result. By building rules into systems which build on models and historical data, this data can be turned into real-time insight. By telling people on the front line what decision to make as part of their interaction with a customer, rather than providing them with information that may be interpreted differently businesses can ensure that corporate strategies and tactics are implemented on the front line. These best practices are then shared as service across the business whenever a particular task is needed to ensure consistency.
Examples of organizations who could use this form of real-time insight include corporate banks who use models based on Basel II rules to inform the risk profile of loans offered, telecoms companies who can offer appropriate upgrades to profitable and non-profitable customers, and media firms who can make their ad pricing more efficient by sharing the services which provide pricing guidance across the business.
Providing real-time insight requires good data quality and in particular the use of master data management services across operational and analytic systems. Predictive models can mine the historical data and identify the appropriate models and segments based on incoming customer information which a rules-based system can direct to the right prompt on the salesperson’s screen.
How much need is there for ‘real-time data’ in this model? To make the most of real-time insight, businesses actually need to know as much as they can about a customer BEFORE the transaction actually happens – based on purchase history, website history, information provided online. After the fact is too late to actually impact the decision – meaning that traditional ‘real-time’ data approaches cannot be acted upon to change the direction of the transaction in your favour.
Really useful real-time data means that the data is being used to make a difference to the business. This means real-time insight, over real-time transaction history. Real-time insight gives businesses the opportunity to align their operational decisions with strategic and tactical objectives, meaning that operational effectiveness is increased.
