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Process Intelligence: The Next Leap Forward in the Intelligent Business

Scott Opitz

November 14, 2019

Process Intelligence: The Next Leap Forward in the Intelligent Business | ABBYY Blog Post

Everything accomplished in an organization requires a series of business activities, which together comprise a process. Whether the organization is a hospital, bank, manufacturer, or any other type of business, its level of success is directly tied to how well it performs and manages its many business processes.

However, today’s business intelligence (BI) and data discovery tools provide organizations with only the most basic insight into its processes – even critical business processes directly related to improving customer interactions and loyalty, building better quality products, mitigating risk, ensuring compliance and more. The key problem is BI tools generally do not provide analytics in the context of an overall business process. While BI and data discovery tools can provide point-in-time measures or key performance indicators for a given task, they cannot provide answers to such critical questions as:

  • What overall business process(es) is this task part of?
  • How does the performance of this task impact the other tasks within this process?
  • Are the performance quality and timeliness acceptable? If not, is the root cause due to problems with this task or other tasks earlier in the process?
  • Is this task being performed each time the process is executed? If not, why not?

Business transformation and operational excellence cannot take place without answers to these questions. Those answers can only be found through a new, process intelligence platform that goes beyond BI tools to provide a deeper, holistic understanding of the entire process and how the performance of each task affects other tasks.

While process intelligence is not intended to be a replacement for BI, it is the next evolutionary step in analytics that provides new, advanced capabilities essential to monitor, analyze, and improve an organization’s critical operational processes. No separate BPM or process modeling tools are required. It provides the ability to access and analyze data about individual instances of a process to monitor both effectiveness and compliance – even when the individual tasks are performed on multiple backend systems of record.

For example, a patient entering an emergency room is one discrete element in a process spanning multiple departments and systems of record. After arriving, triage is performed, after which the patient is assigned a room and then a doctor; evaluation and treatment occur; the patient can then be either admitted or discharged. Some sections of the process can be dynamically adjusted, such as when the triage process shows a patient is low urgency and sent back to the waiting room or high-priority resulting in the patient being placed ahead of those already receiving treatment. Other steps in the process may need to be strictly followed to ensure patient safety and some may represent a dependency on outside entities (e.g. specialists, lab services, radiology, etc.).

Clearly, an organization’s ability to understand and manage each type of process and each individual process instance is directly related to its ability to understand exactly how processes are executed at various points in time, under different operating conditions. Unlike traditional BI solutions, a process intelligence platform will provide this deeper level of understanding, which in turn enables the discovery of new opportunities to optimize operational performance across virtually every industry, from healthcare providers to financial services companies and manufacturers.

Beyond process intelligence’s ability to understand what your data means in relation to the performance of multiple steps of any business process, there are three key benefits that a process intelligence platform delivers that today’s BI tools cannot match:

Understanding processes that span multiple operational systems. The complexity and diversity of real-world IT systems are one of the key reasons why BI, BPM and process analysis technologies fall short when it comes to understanding and monitoring business processes. Process intelligence must be able to discover operational processes where individual process steps are executed on multiple back-end systems of record, and where no system of record or BPM, workflow or other process automation technology provides central orchestration of the process – even when the process definition is either unknown to operations personnel or incorrectly documented. These challenges require the combination of a powerful data integration platform and a sophisticated process state engine. The combination of these technologies allows for the discovery and harvesting of data artifacts left behind in the multiple systems of record when any process is executed and manages the correlation of this data based on the process context.

Improve the effectiveness of a process.

Using process intelligence an organization can identify exactly where waste, inefficiencies, and loss (in time, effort and resources) are occurring throughout a process and take timely action to mitigate these obstacles and bottlenecks. For example, a hospital can find answers to how long a patient is in each step of an emergency room visit, a financial institution can know how many mortgage applications are currently waiting at each step and how that relates to how the previous process steps were performed, or an organization can know what percentage of invoices followed the prescribed process path and for those that deviated understand why. Some of the questions are best addressed by using an overview of the entire process. In other cases, understanding how subsets of process instances behave will provide better insight into how well the processes are being executed and where opportunities for improvement exist.

Determining how often the recommended process flow is followed (process compliance).

Process intelligence identifies when and where exceptions to the expected or prescribed process occur, for example when activities are skipped completely, done out of order or repeated. This analysis needs to be highly interactive and allow the user to drill down into the process data to gain a deeper understanding of the operation. By understanding how many exceptions occur at each step, analysts can better understand the areas in which to focus and make fact-based personnel or process changes.

By combining BI with process intelligence organizations can gain greater operational insights into process performance and compliance, based on actual operational data gathered from each instance of a process and not blind assumptions arising from the limited perspective of BI tools. This new analytic depth, down to the process level, is an absolute must-have to achieve new levels of efficiency, effectiveness, and compliance – breakthroughs that may well remain undiscovered using other BI tools.

Enterprise Process Mining
Scott Opitz ABBYY

Scott Opitz

Chief Technology Officer at ABBYY

Scott Opitz is Chief Technology Officer and responsible for the global product strategy and execution. Prior to this, he held the position of Chief Marketing Officer, driving global marketing strategies. He joined ABBYY with the acquisition of TimelinePI, for which he was co-founder, President, and CEO from its inception. In this role, he oversaw the integration of TimelinePI’s process intelligence products (now ABBYY Timeline) into ABBYY’s worldwide sales and distribution channels.

A 30-year veteran of the computer industry, Scott has founded and built companies in the application integration, business process management, and business intelligence spaces. Scott founded and served as President and Chief Executive Officer of Altosoft Corporation, a business intelligence software company that was ultimately acquired by Kofax. Following the acquisition of Altosoft, Scott served as Senior Vice President & General Manager for Analytics.

In previous positions, Scott served as Senior Vice President, Worldwide Marketing & Business Development for webMethods (now Software AG), where he was responsible for webMethods’ marketing, business development, and strategic product planning. He joined webMethods as a result of its acquisition of IntelliFrame Corporation, a provider of data integration products and the InVista integrated workflow and BPM platform that he co-founded. Scott has also held numerous executive-level positions in technology, marketing and business development roles for public and private companies.

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