Capping IT Off

Capping IT Off

Opinions expressed on this blog reflect the writer’s views and not the position of the Capgemini Group

Information driven Process Management

One defining shift that marks our society today is the rate of change and its democratization. Information flows in real time through ordinary people using simple channels like social media or mobile. The Jasmine Revolution in the Middle East showed how information democratization led the change to actual democracy.

The same concept applies to organizations. Today we are facing tumultuous changes in the way we work or communicate or even buy & sell products and services. The shift of “information power” to consumers as well as the rate and scale at which this information moves have made businesses re-think old marketing paradigms. Businesses are struggling to present a personalized interaction every time they interact with these “Hyper-Aware “customers. They are facing falling revenue per customer and margins pressures. Increasing IT or contact centres have failed to bridge this gap.

While this represents a state of flux and confusion, it may actually represent a once-in-a-generation opportunity for organizations to emerge as new leaders in this fast changing digital world. In order to be nimble and meet these challenges heads-on, organizations must focus on two fundamental capabilities – ability to transform business processes in-line with the changing business & competitive realities and aligning information directly with the processes. We call this Information driven Process Management.

The concepts involved in this change have been in vogue for some time now but new paradigms have emerged in recent years such as cloud, big data, analytics, MDM and process-contextual decision modelling capabilities. The key piece in this puzzle is the process-context aware intelligent decisioning which until now was primarily driven manually. Today leading BPM platforms come with in-built decisioning engines that follow adaptive/predictive models, to either learn from scratch or utilize existing enterprise data to “offer personalized suggestions”. This allows end users to drive intelligent business actions within and outside of the BPM platforms.

If we could combine a customer’s usage patterns from the analytical systems with the power of the customer & household information from MDM and mash it within the decisioning engine of the process hub platform, it would allow businesses to determine the type of interaction/personalized offer they need to make to their customers. It would allow businesses to use these decisions to drive business processes or interaction cases across channels to deliver seamless yet personalized experience to customers wherever and whenever they need it.

For example, consider the following scenarios - a bank wanting to define personalized credit card limits and interest rates based on the customer lifetime value and risk for default; or a mobile communications conglomerate looking to define personalized plans every month for its customers based on their usage patterns and holiday cycles or a utility planning to personalize energy plans depending upon a customer’s consumption patterns.

In all these cases, master data and analytics systems would combine vast amounts of information about the customer, his/her demographics, usage patterns as well as patterns from similar profiles in the same region or socio-economic strata to come up with personalized information regarding potential opportunities or offerings. This information fed to the decisioning engine would allow businesses to combine and modify existing services into customer specific individualized offers. The sales & fulfilment of these offers can then happen by using the process hub’s case management capability by connecting the front & back office operations to deliver these services across multiple platforms including social media, mobile or contact centres.

About the author

Tanmay Dey
Tanmay Dey
I help define BPM strategy and solutions for customers especially around how BPM interacts with various technologies including MDM, Analytics, Social media and cloud

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