Process discovery and hyperautomation: the hype is real but not all discovery approaches are equal
Shree Krupa K | Senior Content Writer
- Hyperautomation is a continuous improvement journey that starts with process discovery.
- Traditional process discovery approaches including log mining and screenshot analysis tools are limited in the scope and depth of their insight.
- To truly understand how processes are performed you need insight across entire teams and any application they use to get their work done.
- This comprehensive discovery approach provides insight into all ways you can improve a process – standardization, consolidation, and automation – and ensures you make smart automation investments with the greatest potential impact.
Is your automation program powered by process discovery?
If you answered yes, you’re riding what some call the next wave of the industry – hyperautomation.
If you’re still trying to wrap your head around all the “hype”, don’t worry. We’re here to help.
Hyperautomation leverages the combination of the right tools and technologies to achieve greater automation success. It’s a continuous improvement journey tracing the sophisticated steps of the automation program. It’s a journey that starts with process discovery.
What is hyperautomation?
According to Gartner, hyperautomation deals with the application of advanced technologies, including artificial intelligence (AI) and machine learning (ML), to increasingly automate processes and augment humans. Hyperautomation extends across a range of tools that can be automated, but also refers to the sophistication of the automation (i.e., discover, analyze, design, automate, measure, monitor, reassess.)
Process discovery provides the visibility needed to scale automation programs
In today’s enterprise, business processes are more “spaghetti-like” than people like to think. Their complexity is driven by a web of interdependent workflows that span different teams and a variety of IT systems.
These complex processes have been further complicated by multiple process variations that have crept into the organization over time. For instance, your team members could execute a process in their own ways, either for more efficiency or because the process requires a special exception. Lack of proper documentation makes it difficult to identify these hidden discrepancies and capture them when considering a process for automation.
Limited visibility into how processes are actually performed has been a major roadblock for automation programs. In fact, in a global survey of automation leaders, a lack of processes was listed as the #1 factor preventing them from scaling their programs faster. This results in a narrowed focus on low-hanging opportunities, or worse, the bad taste of automating broken processes that fail to deliver benefits.
Image source: The state of enterprise automation
This is a key reason why process discovery is a crucial step in your hyperautomation journey. It removes the guesswork of “what should I automate?” by using empirical data to guide your decision making.
Not all process discovery approaches are created equal
The conventional approach to process discovery involves hiring a consultant to shadow employees and document processes. As part of their engagement, consultants review process documents and manuals, analyze hundreds of application screens, and interview process experts. This manual approach is time-consuming, inefficient, and error-prone. Also, because most processes are poorly documented and adhered to, this approach fails when trying to extrapolate small scale observations across large and diverse teams.
More recently, organizations have looked to augment manual approaches with technology-driven process discovery. However, most tools in the marketplace also come with their own limitations:
- Log mining: these tools rely on application logs to generate a high-level view of how processes are performed in enterprise systems. This can be useful when 80%+ of activity in a pre-determined process is within one supported application (e.g., ERP). However, most large enterprises have 100s-1000s of applications, many of which are home-grown or legacy and do not produce usable logs. This presents major gaps in insight for processes that span multiple applications.
- Screenshot analysis: these tools rely on screenshots captured during user activity (e.g., clicks) to identify tasks and processes. Thousands of screenshots are taken each day and techniques such as computer vision/OCR are used to extract information. Analytics then try to make sense of patterns and sequences. This approach is highly resource intensive and often requires significant manual effort to validate analyses on large image sets. Scaling beyond simple tasks performed by a small team becomes cost prohibitive and ineffective.
Depending on your goals these two popular approaches can present major gaps in insight when trying to understand how processes are performed by your teams and the applications they use to get work done.
Accelerate your journey to hyperautomation with a comprehensive discovery platform
At Soroco, we power a connected hyperautomation journey that starts with our comprehensive discovery platform: Scout.
Scout goes beyond log mining and screenshot analysis tools to provide a complete view of how processes are performed in your environment. Its unique insight is being used by F500 leaders across industries to identify process transformation opportunities, prioritize actions, and measure the impact of any implemented change.
Let’s take a closer look at what makes Scout unique:
- Scout supports all workplace applications: Do your processes span legacy, proprietary, and web apps? No problem. Unlike alternative solutions, Scout goes beyond enterprise applications and predetermined processes so you can understand how work really navigates your IT environment.
- Scout can be deployed at scale: Do your processes span large, diverse teams? Scout can be deployed across 100s-1000s of users in various teams, roles, and geographies. This ensures you have a complete view of how your teams get work done.
- Scout is about holistic process improvement: Scout is not only about automation. It provides insight into all ways you can improve a process – standardization, consolidation, and automation – and ensures you make smart automation investments with the greatest potential impact.
- Scout is a universal discovery platform: Scout’s rich data and insights power multiple change programs in the enterprise, not just process improvement.
Whether you are focused on reducing operational costs, improving the customer experience, creating new revenue streams, or optimizing old ones, Scout provides comprehensive intelligence to guide your transformation.
The impact: Bayer’s success story
Bayer, one of the world’s largest multinational pharmaceutical and life sciences companies, used Scout to accelerate its process transformation.
Bayer deployed Scout across its Supply Chain and Logistics teams to identify opportunities for process improvement. Scout’s comprehensive analysis identified five processes that could be consolidated into one optimized process. Bayer then used Soroco to automate a single, high impact process vs. wasting time and energy automating multiple broken processes.
Interested in how Scout can guide your hyperautomation journey? Watch our latest webinar with Bayer to hear more about how Scout enabled them to scale beyond task-level automation and achieve high value process transformation. Or contact us.