Previous blogs describe the Operations Control Center (OCC) as an integral part of SAP’s best practice operational model for IT organizations. As the operations part of “DevOps” (the Innovation Control Center or ICC covering the development part), it is responsible for services such as IT Monitoring, Alerting, Reporting/Analytics, Dashboards/Transparency as well as Root Cause Analysis of the hybrid system and solution landscape, covering information systems on premise and in cloud. Its main processes are Event Management and Continuous Improvement, embedded into the value chain Detect-to-Correct. Modern OCCs incorporate intelligent collaboration and procedure automation. Examples of attended (supported) and unattended (automated) event and alert reactions can be found in part 1 of this article series.
Conversational Artificial Intelligence and Human Computer Interaction
Conversational Artificial Intelligence (CAI) supported user experience (esp. user interfaces) play a more and more prominent role in today’s Operations Control Center. Traditionally, special-purpose applications like hierarchical monitors, central inboxes (for alert/event processing), interactive reports (for analytical/continuous improvement), unified dashboards as well as specific root cause analysis tools are implemented in various managing systems and utilized by OCC Operators. These staff members in turn interact with further processes and applications, for Incident Management, Problem Management, Change Management etc.
While there are arguments and reasons in favor of certain special-purpose applications, the benefits of providing a more general-purpose user experience for OCC Operators are obvious:
- Collaborative event processing,
- Interactive root-cause analysis,
- Intuitive activity flow,
- Multi-channel user experience,
- Unified user interface (including accessibility).
Complementing the traditional approach, the intelligent OCC is applying Intelligent Conversational Artificial Intelligence (CAI) for interaction with users and objects, adding non-human operators (aka bots or operobots) to its virtual staff.
Attended (supported) Activity Processing and Operator Collaboration
Two examples shall illustrate the benefits of conversational artificial intelligence supported multi-channel user-experience for the Operations Control Center. Again, the examples are kept simple to explain building blocks and solution space rather than to serve as technical specification and immediate recommendation.
Event Management with Conversational AI
Example: Conversational AI Use Case ‘Checking status and alerts for system and solution landscape’
Pain Point: Different applications and “inboxes” for monitoring and alerting different aspects of your system and solution landscape. This is sometimes true even in one and the same managing system (i.e. the “central” monitoring software system) but the more so if no central monitoring software system is available, but several of them for different aspects and scope.
Objective: Unified access to data and information, i.e. avoiding time-consuming navigation between different screens to consume monitoring and alerting. Moreover, access to the most recent data and information.
Bot Skill: CAI4OCC is a chatbot that can provide the Operations Control Center Operator with (a) metric values (Monitoring use case) and (b) top alerts (Alerting use case).
Ad a) If the user chooses “metrics”, certain input parameters can be provided, like metric type/key figure and system ID (or equivalent). Thereafter, the current (i.e. most recent) values/measures are retrieved and presented to the user.
Ad b) If the user chooses “alerts”, top x alert types are collected and presented, e.g. from SAP Solution Manager Alert Inbox.
Benefit Case: Save time and effort by avoiding navigation through different screens. Get live data and thus speed up the process of solving issues (scenario Detect-to-Correct, process Event Management).
Incident Management with Conversational AI
Example: Conversational AI Use Case ‘Creating and checking incidents in case the issue underlying the event cannot be resolved immediately’
Pain Point: Different applications and screens for creation a new incident and checking status of an existing incident. The Operator has to go through several at times irrelevant fields when creating an incident from an event/alert. Additionally, the Operator needs to navigate to a different system and application to present the details of an existing incident.
Objective: Unified access to data and information, i.e. avoiding time-consuming navigation between different screens to create and consume incident information.
Bot Skill: CAI4OCC is a chatbot that can provide the Operations Control Center Operator with the capability to (a) check and (b) create incidents (follow-on document-type) for events/alerts.
Ad b) If the user chooses “create incident”, a new incident (aka ticket) is created based on data entered by the user (i.e. taken from the event/alert).
Benefit Case: Save time and effort when creating and consuming tickets. Users do not lose focus on the actual work and can remain in one user experience (scenario Detect-to-Correct, process Incident Management).
In combination with managed systems and managing systems as sources of data collectors, respectively the managing system as creators of events/alerts, Robotic Process Automation and Conversational Artificial Intelligence runtimes offer a unified user interface for seamless execution of Run Operations tasks and activities. This user experience also offers an interaction with other operators and operobots to get the job done. This is not limited to Event Management and Incident Management, of course. Problem Management, Change Management, Request Management, as well as use cases for Analytics of IT Operations can be integrated as well. The author will provide examples in the next article of this series.