bpmNEXT 2015 Day 2 Demos: Kofax, IBM, Process Analytica

Our first afternoon demo session included two mobile presentations and one on analytics, hitting a couple of the hot buttons of today’s BPM.

Kofax: Integrating Mobile Capture and Mobile Signature for Better Multichannel Customer Engagement Processes

John Reynolds highlighted the difficulty in automating processes that involve customers if you can’t link the real world — in the form of paper documents and signatures — with your digital processes. Kofax started in document scanning, and they’ve expanded their repertoire to include all manner of capture that can make processes more automated and faster to complete. Smartphones become intelligent scanners and signature capture devices, reducing latency in capture information from customers. John demonstrated the Kofax Mobile Capture app, both natively and embedded within a custom application, using physical documents and his iPhone; it captures images of a financial statement, a utility bill and a driver’s license, then pre-processes them on the device to remove irregularities that might impact automated character recognition and threshold them to binary images to reduce the data transmission size. These can then be directly injected into a customer onboarding process, with both the scanned image and the extracted data included, for automated or manual validation of the documents to continue the process. He showed the back-end tool used to train the recognition engine by manually identifying the data fields on sample images, which can accept a variety of formats for the same type of document, e.g., driver’s licenses from different states. This is done by a business person who understands the documents, not developers. Similarly, you can also use their Kapow Design Studio to train their system on how to extract information from a website (John was having the demo from hell, and his Kapow license had expired) by marking the information on the screen and walking through the required steps to extract the required data fields. They take on a small part of the process automation, mostly around the capture of information for front-end processes such as customer onboarding, but are seeing many implementations moving toward an “app” model of several smaller applications and processes being used for an end-to-end process, rather than a single monolithic process application.

IBM: Mobile Case Management and Capture in Insurance

Mike Marin and Jonathan Lee continued on the mobile theme, stressing that mobile is no longer an option for customer-facing and remote worker functionality. They demonstrated IBM Case Manager for an insurance example, showing how mobile functionality could be used to enhance the claims process by mobile capture, content management and case handling. Unlike the Kofax scenario where the customer uses the mobile app, this is a mobile app for a knowledge worker, the claims adjuster, who may need a richer informational context and more functionality such as document type classification than a customer would use. They captured the (printed and filled) claims form and a photo of the vehicle involved in the claim using a smartphone, then the more complete case view on a tablet that showed more case data and related tasks. The supervisor view shows related cases plus a case visualizer that shows a timeline view of the case. They finished with a look at the new IBM mobile UI design concepts, which presented a more modern mobile interface style including a high-level card view and a smoother transition between information and functions.

Process Analytica: Process Discovery and Analytics in Healthcare Systems

Robert Shapiro shifted the topic to process mining/discovery and analytics, specifically in healthcare applications. He started with a view of process mining, simulation and other analytical techniques, and how to integrate with different types of healthcare systems via their history logs. Looking at their existing processes based on the history data, missed KPIs and root causes can be identified, and potential solutions derived and compared in a systematic and analytic manner. Using their Optima process analytics workbench, he demonstrated importing and analyzing an event log to create a BPMN model based on the history of events: this is a complete model that includes interrupting and non-interrupting boundary events, and split and merge gateways based on the patterns of events, with probabilistic weights and/or decision logic calculated for the splitting gateways. Keeping in mind that the log events come from systems that have no explicit process model, the automatic derivation of the boundary events and gateways and their characteristics provides a significant step in process improvement efforts, and can be further analyzed using their simulation capabilities. Most of the advanced analysis and model derivation (e.g., for gateway and boundary conditions) is dependent on capturing data value changes in the event logs, not just activity transitions; this is an important distinction since many event logs don’t capture that information.

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