“Efficiency” is a word constantly used by organizations, regardless of their sector or purpose. It’s both a goal and an expectation, and there can seemingly never be too much mention of it –for good reason. Making the most of available resources is imperative for businesses to operate sustainably and meet their full potential, especially amidst economic downturns.
Achieving efficiency often involves change, which can pose a significant organizational challenge. Evaluating current operations and workflows can be difficult, and even if opportunities for improvement are found, rocking the boat by upending core processes isn’t always well received by employees. Data shows that 70% of organizations’ attempts to digitally transform processes fail, leading only to more losses in time, money, and employee buy-in.
Despite the inherent difficulty, disrupting the status quo is often still necessary to rectify delays and other inefficiencies that plague businesses. Luckily, decision-makers now have tools at their disposal to ensure they’re taking the right steps towards automating their processes, informed by highly relevant data and insights. This is known as process intelligence.
What is Process Intelligence?
Process intelligence is a sophisticated technology that evaluates organizational workflows with the goal of identifying bottlenecks, automation opportunities, and other inefficiencies to be improved upon.
By having this deeper understanding and enhanced perspective of operations, businesses can dramatically improve their efficiency – but only if they take the right approach.
It must be driven by insights generated through both task and process mining, using timestamps at various points throughout a timeline to generate a model that allows for easy identification of discrepancies.
How to Approach Process Intelligence
Incorporating Task Mining
Task mining and process mining are two distinct concepts that work in tandem to form the larger practice of process intelligence. The difference between the two can be described most simply as “front end” vs. “back end.” Task mining focuses on employees’ micro-interactions like keystrokes and mouse clicks that occur while completing tasks, while process mining examines event logs and behind-the-scenes movements throughout the larger process.
To make the most of these insights, businesses should augment process mining with task mining together. Task mining allows for steps to be standardized at the individual level, yielding more predictability and requiring less guesswork when determining how long employee tasks will take. Process mining can then provide more effective and reliable solutions as there is less variance at individual points in a timeline.
We know that process mining can scrutinize past and present processes, but what about the future?
Process simulation is an advanced application of process mining with predictive power, allowing decision-makers to experiment with various workflows while accounting for the wide range of variables they encounter in the scope of their operations.
Many organizations build processes around a supposed “happy path,” or a universally ideal and efficient scenario as it relates to a user experience. Unfortunately, it is rare to encounter any such one-size-fits-all solution in the complex landscapes that most businesses operate in. Thus, using process simulation to design a “primary path” contingent on various complexities allows for flexibility and the ability to adapt to specific situations.
Imagine a flight simulator. A prospective pilot can gain the experience needed to handle any situation or variable that might be encountered – barometric pressure, inclement weather, equipment failure, refueling – without the risk of experiencing it firsthand.
Process simulation is similar in its depth and complexity, allowing users to design an optimal workflow informed by as much data as possible before implementing. Instead of a pilot adjusting hypothetical wind speeds, however, an insurance provider can see how hiring additional agents might affect a claims process or what would happen if a certain step was completed at twice its current speed. This forecasting ability enables organizations to be proactive in optimizing their workflows with highly specific variables in mind.
Harnessing Employee Buy-In
Digital transformation has profoundly affected the labor market, both eliminating and diminishing some jobs while also creating new and lucrative opportunities. With more and more tasks being automated every day, “automation” can be a dirty word for employees who are concerned about their role’s permanence. Thus, telling employees that your business is going to implement a system that identifies inefficiencies and opportunities for automation might not elicit enthusiasm.
However, process intelligence isn’t about trading your human employees for robots – it aims to use human capabilities more effectively. By identifying the correct steps in a process to automate, businesses can lighten the load of repetitive and monotonous tasks that employees are assigned and instead delegate them more creative, cognitive, and rewarding projects.
This symbiosis between intelligent automation and human ingenuity improves experiences for both the business and its customers. Illustrating this mutually beneficial relationship is crucial for getting employees on board for process intelligence.
Process intelligence isn’t an instant solution, and introducing change always brings inherent obstacles. So, what outcome does process intelligence yield that makes it worth the headache?
When surveyed, 45% of US organizations said implementing process, and task mining tools increased their efficiency, while 41% reported increased revenue. When considering ROI, 72% of surveyed US companies said process automation yielded at least twice the value of their initial investment, while only 4% reported a negative ROI.
When businesses approach process intelligence the right way, the potential benefits in efficiency, revenue, and overall experience for employees and customers alike are hard to ignore. As the world continues to adopt artificial intelligence and automation in such a wide array of use cases, staying informed and literate in these practices is imperative to keep up. Heading into 2023 and beyond, organizations’ decision-makers will not want to hold back progress by being resistant to change.
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