Digital Transformation Starts with Process
By: Ryan M. Raiker
Tags: Data Science, Technology, Artificial Intelligence, Automation, Future

Digital Transformation is a top priority for many companies, however, 70% fail to meet expectations. Perhaps the most compelling reason is the lack of visibility to how business processes actually execute.

While 80% of the companies surveyed by McKinsey consider digital transformation a top corporate priority, nearly 70% fail to meet expectations.

There are several factors that contribute to such an outcome. Perhaps the most compelling reason is the lack of visibility to how business processes actually execute. Without a complete understanding of all the components of the business process, organizations lose the ability to identify where the weaknesses lie and plan for improvements. As Peter Drucker, the founder of modern management theory, said: “you can’t manage what you can’t measure.”

It’s really time to own your processes…

You can do more with end-to-end process analytics and begin to transform your entire organization; because transformation starts with understanding. You can’t improve what you don’t measure.

Answering deeper questions…

Are you tired of the lackluster information your analytics team is delivering? Wish you could understand more about who is responsible, what is causing, and why problems are occurring?? We all are…

Successful automation initiatives can transform every facet of an organization, from the boardroom to the shop floor. In order to effectively deploy a Robotic Process Automation (RPA) project and realize the potential that automation can yield, businesses need to have an in-depth understanding of their organization’s processes. The most common and expensive mistake businesses make when implementing automation initiatives is failing to properly understand how their processes are actually performing and then choosing the wrong processes to automate. Leveraging actual business process data is critical to the long-term financial and technical success of any automation project. Rarely does the enthusiasm to just jump in and figure it out on the fly ever prove to be a recipe for success.

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The data is available, but can you access it?

The challenge for many organizations is understanding how their processes operate in real-time, across diverse functional teams, and within siloed back-end systems. Traditionally, enterprises have tried to generate process insights by utilizing a combination of manual efforts and first-generation platforms, including process mining and business intelligence, which prove to be time-consuming, costly, and error-prone. Comprehensive process data that reflects end-to-end workflows is key to automation success. And it already exists in just about every enterprise software application.

Whether utilizing an ERP, CRM, or another application, the data is waiting to be put to use. Solutions such as Process Intelligence enable organizations to discover, assess, visualize, analyze, and monitor process flows. Powered by artificial intelligence and machine learning technologies, Process Intelligence delivers accurate, in-depth, and real-time process discovery, analysis, and monitoring, which help automation leaders to accelerate digital transformation initiatives.

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Stopping processes from failing

Many automation projects initially fail. While a number of factors play a role in the ultimate results that a transformation project delivers, understanding, and automating the right processes is a key component of successful digital change. Automating the wrong processes can lead to wasted resources and less return on investments. However, choosing the right processes for automation can be challenging without having a clear idea of how processes actually run. Many organizations think they understand how their processes work when, in reality, there are often tens or even hundreds of variations for a single process.

Traditional methods of discovering and analyzing processes involve internal personnel or outside consultants observing, timing, and documenting processes by hand, and then manually sorting and compiling the data. This time-consuming method usually takes several months to complete and is also highly subjective. The data reflects how the process performed during the specific instance in which it was being observed.

Other methods include business intelligence, which is a great asset in providing summary data and point-in-time metrics but lacks an understanding of the key to a process: time. Traditional process mining tools, many of which originated from the graduate program at Eidenhoven University, have made the assumption that corporate processes fit onto a simple process map, but neglect to recognize that processes function much more like a timeline.

A Future Beyond Business Intelligence and Process Mining

Process Intelligence is designed to help organizations discover and measure how current processes work, identify process bottlenecks, and surface areas for process optimization based on four foundational pillars:

Creation of a “digital twin” of the event data from disparate systems of record associated with business process execution;

Analyzing the performance of any process type, particularly highly variable case management processes;

Real-time Operational Monitoring of process behaviors that empower business users to remediate process bottlenecks; and

Artificial Intelligence/Machine Learning-based predictive analytics allows users to proactively identify the outcome or performance of any process instance in the early stages of the process execution.

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Analyzing the performance of any process type, particularly highly variable case management processes

Often the most challenging, yet most impactful, areas for process discovery and analysis are case-based processes, for example, customer-facing processes such as call center operations, health care administration, and claims processing.

Process Monitoring Should Reflect Real Life

Keeping in mind the complexity and diversity of most business workflows, what would a process flowchart look like if it were to reflect the process of treating a patient in an emergency room? If you factor in all possible forks and loops in the workflow, representing doctors’ decisions, test results, and changes in the patient’s conditions, the process representation will look less like a flowchart and more like an incomprehensible web. We generally refer to this as the plate of spaghetti effect, as the process map looks much like a plate of spaghetti. Even in simpler cases, customer support or sales management, for example, the number of steps, repetitions, and variations could vary greatly.

Process Intelligence can help your organizations easily identify, quantify, and target the highest-impact process instances for digital transformation or automation initiatives.

Real-time Operational Monitoring of process behaviors that empower business users to remediate process bottlenecks

Having the insight to and being able to visualize how your processes behave empowers your organization to remediate inefficiencies and make informed decisions as to what aspects of your processes should be standardized through a combination of automation and more effective deployment of human capital through:

Protocol analysis that must be followed and identifying processes that fail to meet those conditions

Alerting the right staff or automating remediation to ensure processes are functioning properly, and eliminating bad processes before they happen with ongoing monitoring

Automatic comparison pre and post initiative process instances side by side to identify if your process improvements are performing as planned

Artificial Intelligence/Machine Learning-based predictive analytics that allows users to proactively identify the outcome or performance of any process instance in the early stages of the process execution

One of Peter Drucker’s often-quoted advice is “the best way to predict the future is to create it.” Process Intelligence enables organizations to have continuous visibility of how processes behave. Based on such insight, then re-imagine how process optimization can create sustainable competitive advantages by focusing on those business processes that are proven to generate reduced transaction costs and improved customer service levels. What if you could not only see what will happen next but also prescribe a solution to avoid a problem or costly mistake before it happens? That is what the ultimate objective of digital transformation is all about: predicting the future process state. By combining process mining with machine learning and artificial intelligence, your organizations can achieve highly integrated and fully automated insights to forecast processes in their future state and take action to ensure positive outcomes.

Process knowledge is important for successful digital transformation initiatives; however, having an understanding of all the critical information locked within semi-structured and unstructured content is also critical. It is dependent on having real-time access to all your business-critical data no matter which business process platform it lies within. This includes the vast amount of data that exists in various business documents, including claims, invoices, proof of delivery, loan agreements, contracts, orders, identity documents, tax forms, pay stubs, utility bills, and more. This understanding of both content and processes is referred to as having digital intelligence.

With Digital Intelligence, organizations gain the valuable, yet often hard to attain, insight into their operations that enables true business transformation. With access to real-time data about exactly how processes are currently working and the content that fuels them, Digital Intelligence empowers enterprises to make a tremendous impact where it matters most: customer experience, competitive advantage, visibility, and compliance.

The latest Everest Group Process Mining Products PEAK Matrix® Assessment 2020 illustrates that traditional process mining has deep roots among data professionals and automation leaders, but the Process Intelligence approach is gaining momentum — especially with the impact of stay at home orders, social distancing, and economic uncertainty. Business leaders need to have a valuable understanding of their business workflows, identify the best use cases for RPA projects quickly, fix process bottlenecks as soon as they occur, and continually optimize automation performance. Process Intelligence answers this call throughout the entire business, even across diverse workflows, departments, technology systems, and locations.

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