When all you have is a hammer, everything looks like a nail. Optimizing processes by cutting out yet another inefficiency, leveraging yet another lean opportunity, only brings you so far. As the need for radical business agility continues to accelerate, there is limit to the classical process way of responding to complex events in real time. Driven by AI, fixed and inflexible processes can be replaced by powerful reasoning systems. These systems fluidly adjust to whatever situation occurs, anticipating next-best actions and resources needed on the fly. And as they continuously learn from what works and what doesn’t, they increasingly become hands – and care – free. Stop! Hammer Time: the self-driving enterprise is coming.
- Business Rules Management System (BRMS) solutions externalize decision logic from applications, allowing both IT and business experts to define and manage decision logic. This logic is then executed by Business Rule Engine (BRE) systems.
- Structured methodology adapts to the new ERP (Enterprise Resource Planning) roll out, creating bespoke levers to help organizations maximize the business case from platform investment.
- Dynamic case management systems capture and process business events across process silos, providing end-to-end intelligence and optimized outcomes on a case-by-case basis.
- An AI-powered cash collection agent who understands the pain of waiting in line for a simple query to be answered, combining the power of intelligent automation with best practice process understanding.
- Amalgamating ESOARmethodology (Capgemini’s approach to automation), DGEM process knowledge (Capgemini’s approach to achieving operational efficiencies), HANA (a SAP in-memory database) expertise and competency model supports a greenfield client to setup their enterprise.
- A large consumer goods company used the power of DGEM, ESOAR and HANA environments to set up their finance back office support services around the world.
- In Australia, a large utilities company leveraged HANA as a powerful tool, using DGEM for HANA as a design shop to engineer their process landscape quickly and effectively.
- Utilizing the AI-powered cash collection assistant, a large retail company improved their customer satisfaction ratings by reducing the dependency on their helpdesk agents to resolve vendor queries quickly.
- PayPal managed to reduce its fraud rate to just 0.32% of revenue using a sophisticated deep learning system that analyzes transactions in real time.
- A transport company used AI-based case management to streamline and automate the management of customer correspondence, leading to an 85% reduction in manual case preparation and handling effort.
- Collaborative working across business units delivers detailed process mapping on the new HANA environment, ensuring the Target Operating Model fits the new HANA design roll out.
- Identifying platform optimization opportunities as part of transformation advances the benefits case from the tools landscape.
- Reducing the turnaround time for the collections process improves customer satisfaction.
- Impact process efficiencies and opportunities to setup, design and grow the client environment.
- Split-second responses to high-volume data streams and events in real time, particularly regarding the IoT (Internet of Things) and digital customer channels.
- Case management: Appian case management, Pega case management, IBM Case Manager, Celaton InStream
- Technology: HANA
- Business rules anddecision management: io, Drools open source, Oracle Policy Automation, Pega Customer Decision Hub
- Complex event processing: Amazon Kinesis, SAP Complex Event Processing, TibcoBusinessEvents, Apache Flink, EsperTech Esper
- Methodology: ESOAR, DGEM