Resilience through
Clarity

Let’s first define “Resilience” in the context of an organization – “It is the capacity of the organization as a whole to adapt quickly and bounce back in the face of adversity”. In fact, we go one step further to say that this ability can become a source of competitive advantage in the current business situation, not just to bounce back but to bounce forward – ahead of the competition. It is now increasingly clear that the recovery from the current situation will be Digital; – and hence accelerating and scaling the Digital journey becomes the critical path towards building resilience. It is no surprise that several organizations are accelerating their digital transformation plans, with time frames shortened exponentially due to the ongoing pandemic. Alongside the need for rapid transformation, crucial to business resilience in the second phase of the new normal, enterprises also need to think about scale. Hasty and short-term thinking may be tempting given the circumstances but will prove costly in the longer term. A measured and effective transformation, will need strategic planning and nuanced decision-making, both of which necessitate an intricate understanding of enterprise processes.

However, before enterprises can begin their journey of change, they need to establish a clear roadmap and transformation strategy. Globally and across verticals, enterprises find it challenging to address issues like resource underutilization, process leakages, and failed automation deployments. This inability stems from a lack of granular and nuanced understanding of enterprise processes. Any enterprise function is a collection of processes, and consequently any fundamental shift must be underpinned by a consistent, logical, and thorough exercise in process optimization.

It is important to note here that quality and consistency at scale are critical to the success of any technology-driven transformation initiative and the need to evolve, while a welcome opportunity for companies, comes with its fair share of challenges. All too often, we have found that biased process selection hampers the effectiveness of enterprise transformation plans. By relying on subjective data and documentation that is often both inaccurate and out of date, enterprise automation initiatives are set up for failure from the outset, often more misguided in planning than flawed in execution. At the planning stage, enterprises must ask a wide range of questions before executing their transformation strategy. These include:

• Are processes being executed in line with the documented steps?
• How many processes do not follow the optimal execution pathway? What is the impact of these deviations on efficiency and the bottom line?
• What are the main reasons for process deviations?
• Where do leakages occur, and how can they be mitigated?
• What parts of the process can be automated for maximum efficiency and impact?

Rushing to implement automation plans without answering these questions can have disastrous consequences, and subjective human accounts, hunches, or historical data are inadequate means of tackling the problem. It is here that a powerful combination of Process Mining and Process Discovery meets the challenges head-on. As an intelligent and fully automated technique, Process Discovery gathers primary data from user keystrokes to identify automation candidates. Now, combined with Process Mining, Process Discovery is exponentially more effective in guiding automation efforts, ensuring substantially higher chances of success.

Using a combination of Process Discovery and Process Mining to drive results

Before we take a look under the hood, it may be essential to delineate the two concepts. Consider the typical enterprise process. In most cases, enterprise processes can have five levels (Level 1 – Level 5), with each level, in ascending order of granularity, offering specific insights. Process Mining is a technique that focuses on L1-L3 analyzing event commits and application logs to discover, monitor, and improve real processes based on current organizational information. It can generate enterprise-wide process maps offering a thorough understanding of all process structures. While all but eliminating manual effort in this exercise, Process Mining throws up one concern – the absence of nuance derived from analyzing human-system interactions. This gap is where Process Discovery comes into its own.

As a machine learning-based technique that identifies process automation candidates, Process Discovery also designs automation workflows, injecting speed, efficiency, and attention-to-detail into the automation strategy process. As a non-intrusive tool, Process Discovery analyzes primary data from user keystrokes using built-for-purpose neural network algorithms to generate accurate and detailed business process maps, creating a robust foundation for automation execution. Therefore, a combination of Process Mining and Discovery can offer enterprises a faster and more assured pathway to automation success. Let’s understand how these technologies work together.

Consider the Purchase Order (PO) process in procurement. While Process Mining can offer insights into how an enterprise is creating POs – from purchase requisition to PO creation to PO approval – Process Discovery generates a granular process map based on user keystrokes gathered non-intrusively from screen navigation, application access, and any other activities. Continuing with the example of the PO process, let’s say Process Mining points enterprises to the fact that the most significant bottlenecks occur at the PO creation stage. Organizations now need to understand precisely how creation is executed, deploying Process Discovery to analyze user-system interactions at this stage. Once this task-level analysis from data recorded from user machines is fed into an AI engine, enterprises may gather insights about:

• The number of ways POs are processed
• The most common way users process POs
• Average time to process a transaction and the number of process steps involved
• Business variations in PO processing steps across areas such as subcontracting or stock transfers
• Exception variations such as ‘PO on Hold’

Enterprises can then harness these insights to amplify the efficiency of process re-engineering, process automation, process compliance, process training, and process efficiency.

Understanding the benefits of Process Mining and Process Discovery

Broadly speaking, the combination of Process Mining and Process Discovery offers impact in four specific areas:

Evolving with Process Discovery and Process Mining

Rapid evolution is not just a function of technology adoption. The choice of technology, scale, implementation partner, and change management process are all equally important. Process Mining and Process Discovery can help enterprises understand themselves and their systems better by generating accurate and highly insightful process maps based on actual execution data. Armed with these insights, enterprises can make well-informed decisions about their tech stack and rollout, avoiding the inconvenience seen with prematurely decommissioned systems or hasty adoption.

The new normal has changed how we live, work, and operate. The situation is no different for enterprise growth and scale. The focus on agility, resilience, and efficiency will disrupt conventional enterprise models and accelerate enterprise transformation speed. On the other hand, it will also complicate the shift and place an intense focus on smart and agile thinking at a scale that drives measurable impact. A combination of Process Discovery and Process Mining will help organizations function with the clarity required to catalyze sustained growth and innovation. A well-charted growth path supported by robust insights will be the defining element of the enterprises that don’t just navigate the new normal but determine the future.

EdgeVerve has partnered with Minitⁱ, a leading provider of Process Mining, to enhance its Process Discovery offering. This partnership will accelerate process excellence for EdgeVerve’s clients by offering them comprehensive, actionable process intelligence.

References:

1. https://www.edgeverve.com/assistedge/assistedge-discover/