• Resource management/FinOps to enhance automation solutions
• Emerging data platforms consolidate app platforms to improve digitization opportunity, CX, and worker efficiency
Intelligent automation innovations continue to demonstrate to enterprises the benefits of the cloud’s value-chain. This is most recently being addressed via improved insights and management of cloud resources, increased worker efficiency by shifting to digital documentation and driving workflow automation and enhancing the CX through more meaningful and real-time data access.
As of late, the business automation realm is largely focused on improving the productivity of companies’ back-office workers. GlobalData has compiled the most relevant automation updates of late. (For more in-depth research, please see Intelligent Automation Updates Help Tame Resource Management, September 29, 2022).
Application resource management is a fast-emerging solution set, which will fit nicely into intelligent automation portfolios for its ability to support application performance, compliance, and cost reduction–all necessary elements for DevOps teams looking to improve cloud efficiencies and justify cloud costs. A growing movement among enterprises to manage unruly cloud costs is quickly prioritizing the notion of FinOps. This emerging technology coupled with AIOps tools, observability, and remediation capabilities make it a relevant technology to watch within the automation segment. Solutions will appear in the form of application resource management or resource utilization, most likely integrated into future evolutions of observability and monitoring offerings. FinOps’ greatest value is to heighten software engineers’ awareness of how to factor in cost optimization when mapping out new application architectures early in the design phase.
A surge of awareness is building around application resource management solutions. For example, IBM’s recent acquisition of Turbonomic will bring IBM Cloud and OpenShift cost-cutting methods by helping optimize the deployment of IT resources across the dev/test/production process. Some other players in this space include Microsoft Azure platform management tools, ServiceNow, Apptio, and Platform9. At the same time, observability solutions are proving to be a complementary technology for providing proactive incident resolution, remediation, and avoidance. Vendors moving into this space include Dynatrace, VMware vRealize, AppDynamics, and Amazon CloudWatch among others.
The industry is witnessing the beginning of consolidation between application platforms and data platforms/CDP. These next-generation software architectures will improve the speed and access to data which will enhance the customer experience. Companies such as Salesforce owned MuleSoft are leveraging their industry-leading integration technology for creating pre-built connectors for common data platforms (CDP).
New consolidated data management and automation capabilities broaden immediate access to customer data across a variety of customer channels and scenarios, providing multiple views of a customer’s consumer/purchasing activities. This in turn helps marketers trigger new business opportunities via more meaningful and relevant interactions. Low-code platforms will further enhance the platforms, allowing for a broader set of participants, namely business users, into the app modernization process.
Companies are keen to improve productivity of document-centric workers, particularly those related to manual tasks, replacing claims adjustors, and improving real-time insight based on new data entering the company. This is key to helping usher in digital transformations and modernize traditional business processes into workflow automations.
Advancements occur by shifting pixels from the page to digital documentation and attaching new forms of automation for immediate value including natural language processing (NLP) and robotic process automation (RPA). Vendors are expanding portfolios with these capabilities for modernizing business processes. Additional enabling technologies include process mining, and observability. Process mining helps discover inefficiencies within an organization, which in turn helps assign appropriate RPA candidates. RPA orchestrates sequences of tasks by a particular worker. Observability helps increase visibility through analytics and improved data integration.
The DevOps model will be the driving force behind these latest automation updates, looking to improve efficiencies for the back-office worker and further workflow automations and implementations of robotics/NLP. Also falling within this domain will be increased directives to rein-in resource costs and management with a focus on economic digitization.