Elsa Petterson
Partner success manager @ Put It Forward
Table of Contents
- Enterprise Process Automation and Orchestration
- The current situation - Where Automation Tech Falls Short
- Key Capabilities of Next-Generation Business Automation Platforms
- Types of automation technologies
- Impact of disparate automation solutions
- What is end-to-end automation of processes and value streams?
- Tracking success - KPI's and Operational Metrics
- How does an end-to-end automation solution work?
- Key takeaways: How to approach intelligent automation orchestration
Keeping up with Industrial Revolution 4.0 is not easy—technologies constantly evolve, and so must businesses. One crucial solution is automation. Many organizations implement it to enhance productivity, align teams, and cut down on costs. Yet, not everyone does it on an equal level. So, how do you identify what level your company is on? You will learn that in this article, where we explain automation maturity and how you can evaluate it.
The current situation - Where Automation Tech Falls Short
In today's fast-paced and ever-changing business world, enterprises are constantly looking for ways to optimize their operations and stay ahead of the competition. One of the most promising methods for achieving this is through automation. Businesses can streamline their processes and improve efficiency by combining different technologies, such as RPA, document automation, document automation, APIs, and workflow automation.
However, managing and integrating different automation platforms can be challenging. That's why it's essential to adopt a comprehensive approach that includes a variety of custom, packaged, and platform-embedded AI models to assist with automation. With AI, the potential for automation dramatically expands, and processes become more dynamic and efficient.
As the potential for automation expands with AI, processes become more dynamic. The traditional enterprise application fixed user interface (UI) interacting with data models will be supplemented and overridden by algorithms and AI recommendations to suggest, trigger, and situationally route work. However, automation technologies are primarily hybrid, deployed in both cloud and edge locations, making it challenging to manage the lifecycle of business processes and ecosystem-based value streams.
To stay competitive in today's fast-paced and constantly evolving business world, enterprises need to optimize their operations and stay ahead of the competition. One of the most promising methods for achieving this is through automation. By adopting a comprehensive approach that includes a variety of technologies, businesses can streamline their processes, improve efficiency and productivity, and maintain a competitive edge in the market.
Modern automation solutions have revealed the hard limits of current offerings:
- RPA can't orchestrate effectively across departmental processes
- Integration technologies are constrained to API-based approaches
- AI capabilities are localized at best and don't incorporate enterprise data to drive meaningful outcomes
- Performance KPIs are not relevant and not aligned with business drivers
- Event-based insights to trigger cross-platform outcomes aren't possible
In short, automation is vital to staying ahead in today's business landscape. By adopting a comprehensive approach that includes a variety of technologies, businesses can optimize their operations, increase efficiency, and stay ahead of the competition.
Key Capabilities of Next-Generation Business Automation Platforms
Companies must adopt a more comprehensive and disciplined planning approach beyond standalone automation to achieve effective automation. This comprehensive approach has pushed automation vendors to support a range of automation and AI technologies to create solutions. Whether acquired, built in-house or supported through partnerships, the next generation of automation requires developing skills and adopting technologies in five key areas.
- End-to-end process automation
- Seamless orchestration across automation technologies
- AI-powered insight-driven automation
- Democratization of automation
- Value-driven automation planning and business observability
Types of automation technologies
There are many automation technologies that, to the untrained eye, can seem remarkably similar. They look similar because outcomes describe the approach to the problem space. The following chart starts to organize how these different approaches can be categorized by the type of problem they solve rather than the outcome.
For this paper, we'll use four categories as the main groups of automation technology.
- System integration - technologies that connect and orchestrate using integration technologies
- Labor automation - technologies that replace and augment manual tasks and coordinate work
- Decision-centric automation - business rules management and predictive analytics
- Business-value automation - capabilities that enable views into what is happening
Impact of disparate automation solutions
The impact of various types of automation technology on enterprises is multifaceted and transformative, affecting nearly every aspect of business operations. Key impacts are increased efficiency and productivity, cost containment, and being able to scale competitively in a shorter period.
While there is no argument against any of these benefits, there is now a core issue with how they work together. Said another way that today's automation technologies have benefitted siloed portions of the business organization, not the whole organization.
Now, the needs of the enterprise have to shift to where the nature of how people work has shifted, where automation technologies are core to the entire organization.
Overall, the strategic implementation of automation technologies can fundamentally change how enterprises operate, delivering significant benefits while posing challenges related to workforce adaptation and the ongoing maintenance and integration of new technologies.
What is end-to-end automation of processes and value streams?
Leadership and the enterprise seek technologies that can genuinely orchestrate at the horizontal level. Bridging the gap between localized RPA solutions, middleware, events, and AI-based solutions.
These processes must enable human-in-the-loop scenarios, co-pilot and auto-pilot scenarios, and traditional workflows to work harmoniously together.
End to End Automation and Process Flow
Tracking success - KPI's and Operational Metrics
Key Performance Indicators (KPIs) and operational metrics are crucial for business leaders leveraging intelligent automation technology, as they provide a measurable framework to evaluate the success and efficiency of automated systems. These metrics enable leaders to assess how well automation aligns with strategic business objectives, ensuring that technology investments deliver tangible benefits. For instance, in automated customer service operations, KPIs like first contact resolution and average handling time can directly measure the impact of chatbots and AI interfaces on customer satisfaction. Establishing precise KPIs linked to specific business outcomes allows leaders to quantify the effectiveness of automation, enabling continuous adjustment and optimization. This focus on measurable results helps maintain alignment between technological capabilities and business goals, fostering accountability and clarity across the organization.
Developing effective KPIs for automation begins with clearly understanding business objectives and identifying which aspects of operational performance are critical to achieving these goals. Utilizing these KPIs involves consultation with stakeholders across various levels of the organization to gain insights into the unique challenges and opportunities within different areas. After identifying these key areas, specific, measurable, achievable, relevant, and time-bound (SMART) criteria should be applied to each KPI to ensure they are practical and focused. For instance, a KPI for reducing operational costs through automation should specify the percentage reduction expected within a set timeframe. The development process should also consider the data availability and the capability of automation technologies to accurately capture and report on these metrics, ensuring that the KPIs are reliable and actionable.
Implementing effective KPIs requires integrating them into the daily operations and decision-making processes. These KPIs involve setting up dashboard displays that provide real-time data visualizations based on the operational metrics from automated systems. Regular reviews and updates of these KPIs are essential to reflect changing business needs and technological advancements. Training and engaging employees to understand and use these KPIs promotes a data-driven culture supporting objective decision-making. Furthermore, leaders should establish a feedback loop where insights gained from monitoring KPIs refine automation strategies and operations continuously. This approach maximizes the return on investment in automation technologies and ensures that the organization remains agile and responsive to internal efficiencies and external market dynamics.
How does an end-to-end automation solution work?
Leveraging orchestration to integrate complex use cases significantly enhances the value derived from a unified platform. However, development teams must incorporate third-party applications and platforms strategically to harness the power of automation and remain fully competitive. This necessity arises from several key factors:
- Technology Gaps: At times, the primary platform may not offer the specific technology required to meet unique business needs, making the integration of third-party applications indispensable.
- Standardization and Preference: Businesses often have a preferred automation technology based on standardization across the enterprise, necessitating third-party solutions to be used.
- Superior Capabilities: When seeking best-of-breed performance, the capabilities of new technologies may need to improve, prompting the need for third-party solutions that offer advanced functionalities.
- Event-Driven Design: For event-driven workflows requiring straight-through processing, third-party platforms can provide the necessary support through APIs or plug-ins, enhancing the orchestration capabilities of the primary platform.
Utilizing third-party technologies is not just about filling gaps; it's about strategically augmenting your automation ecosystem to drive superior performance, innovation, and competitive advantage. As automation complexity increases—spanning various workers, applications, platforms, and business processes—the orchestration of work across these diverse elements becomes more challenging. Direct integration through APIs or plug-ins addresses this challenge, ensuring reliable workflow execution even when it extends beyond the primary platform.
In today's fast-paced business environment, ensuring the seamless and reliable execution of automated processes, especially those integrating diverse technologies and applications, is paramount. Embracing a strategic approach to incorporating third-party technologies solves immediate challenges and positions your enterprise for future growth and success.
Key takeaways: How to approach intelligent automation orchestration
Enterprises should adopt a comprehensive approach to automation, considering the impact of inefficiencies on all related business processes and value streams rather than just focusing on individual tasks or activities. This approach will result in a more significant business impact by improving key performance metrics across interconnected processes.
It is essential to prioritize platforms that can orchestrate multiple automation and AI technologies into complete solutions, ensuring seamless integration and orchestration of RPA, workflow automation, APIs, AI, and other technologies for this to be achieved.
Another crucial aspect is leveraging AI, particularly generative AI, to make automation more intelligent, adaptive, and impactful over time. Platforms with robust AI capabilities will be better equipped for the future. As this is an emerging area, paying attention to AI roadmaps and the vendor's track record in executing against a roadmap is vital.
Enterprises should also empower their business teams to build their automation using low-code platforms and monitor innovations in automating through conversations with an assistant powered by GenAI. This process requires supporting programs that upskill business teams and provide business incentives.
Finally, it is crucial to take an ecosystem view and realize that no single vendor can offer the best of breed for every capability. Therefore, enterprises should seek platforms with an open architecture to partner successfully with competing and complementary automation providers and integrate external technologies when necessary.
This video shows you how to take different localized automation technologies and seamlessly orchestrate and integrate them simultaneously via triggers and events.
Note: automation technologies in this scenario are UiPath, Azure DevOps, Adobe Workfront, Atlassian Jira, Atlassian ServiceDesk, and PowerBi