Would you like to be able to predict the future and steer your business on the right course?
We help companies to predict future events in a way that gives the business enough time react. We do this by implementing Complex Event Processing (CEP) as a business tool to processes business events in real-time, analyse events and take action to create a favourable business outcome.
Traditional approaches to trend analysis, such as business intelligence (BI), only provide a rear view perspective on your data. This drastically limits the results can be achieved as actions are often triggered to late for the business to react. This is due to the database driven nature of most BI tools, which focus on historical data and not real-time events.
Predicting business activity helps companies to relieve the pain of missed opportunities, unforeseen problems and unanticipated expenses.
Below are some example use cases where Complex Event Processing can be leveraged to predict and react to business events.
How does it work?
Complex Event Processing leverages historical data, real-time business events and configurable business rules to detect business patterns and react accordingly.
Example use cases for Complex Event Processing
In the telecommunications business, operators have found that if a customer calls with the same complaint 3 times in short succession, it is likely that the customer will soon switch providers. These companies operator to provide a better experience on the second or third call.
Retailers have learned consumers alter their buying behaviour during a heat wave and tend to sell out of stock too quickly. In short retailers want to forecast the demand for their products, which, in turn, enables suppliers to more efficiently plan production and delivery schedules.
Depending on industry sector, supply chain logistics can amount to between 5 and 50 percent of a product’s delivered cost. These companies want to know who are their most loyal customers, which deliveries are most profitable, where to locate distribution centres, optimal points to replace delivery teams, and how to better locate and track delivery items.
Manufacturing companies need to know what goods are in transit, what is about to enter the warehouse, what is being shipped from suppliers, in order to dynamically route goods in-transit.
Healthcare providers will be able to combine their patient history data with real-time events, using telehealthcare, to act on early warning signs and provide treatment or intervention before conditions worsen.
o
Defining your predictive event
Predicting business events that create favourable business outcomes does not have to be complex. In order for Complex Event Processing to work you must:
- Be committed to customer satisfaction and a willingness to seize opportunities
- Have a compelling business problem, such as a need to reduce customer churn
- Identify a predictable pattern. Events do not occur in isolation and thus it is essential to correlate real-time events and historical data to provide a complete view
- Implement business rules to detect a pattern in real-time
- Implement an alternative process
Should we talk?
- Are you committed to customer service excellence?
- Are you willing to seize opportunities?
- Do you have a compelling and predictable business problem?
If the answer is “yes” to the above then we would like to talk. Why not book a free consultation to discuss your business problem in more detail to see if we can help.
