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Best Practices

The Biggest Issues Facing Business Automation Today and How Process Mining Helps

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When one business problem gets quashed, another emerges with buoyancy like a bad game of Whack-a-Mole. Fierce competition, changing market demands, environmental factors, and a fluctuating talent pool keep businesses on the edge of their seats. All this, combined with increasing pressure to squeeze out more profits with less, means companies must learn how to harness the power of automation.

Process mining is one such tool which alleviates pressure towards making impactful, data-driven decisions and works in congruence with business automation. Process mining can quickly asses automation risks and identify opportunities for further automation expansion. Here are some of the most significant issues facing businesses automation today and how process mining helps.

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How to prioritize automation

Problem: many business processes are eligible for automation and managers struggle to separate those which need automation, could benefit from automation, and which are best left as is.

Solution: use process mining to map business processes and identify stages or entire processes which are best positioned for improvement through automation.

Business process automation is not a question of if, but when. However, the green light shouldn’t be switched on across the board all in one go. Automation must be rolled out strategically and prioritized in places where it can have the greatest impact. Automation has taken over a range of business functions including customer service (chatbots), logistics (outbound delivery), e-commerce (abandoned cart emails) and accounting (invoicing), to name a few.

The number of business processes and functions eligible for automation can be overwhelming. Deciding how, when and why to automate a business process needs to be supported by more than just a whim. The data is there, and process mining helps interpret vast quantities at speed.

Decision-makers can overcome this burden by using the power of process mining to nominate business processes which can benefit the most from automation. Start by applying process mining to the top ten business processes. The top ten processes might be defined by the frequency of use, perceived impact, or the number of employees involved. Process mining will highlight which processes are overextended, sluggish or touch too many human hands for completion. Managers can then analyze the outputs from process mining and effectively prioritize the order of automation and effective process redesign.

How to make humans less like robots (and robots more like humans)

Problem: knowledge worker’s time is wasted on clerical tasks, which are time-consuming yet necessary for business.

Solution: use process mining to root out clerical steps of processes better suited for RPA (robotic process automation)

Knowledge workers, simply put, use their brains to bring value to an organization. Rather than earning a living by the sweat on one's brow, the knowledge worker’s greatest asset is their mind. Creative, ever-changing and autonomous, the knowledge worker is tasked with skills beyond heavy lifting and manual labor, yet they are still burdened by clerical tasks.

Machines have already taken over plenty of human jobs. Considering our (recent) past lives as farmers, humans have surrendered about 90% of their jobs to robots in the past 100 years. The future predicts even more jobs surrendered to machines, with McKinsey Global Institute predicting that up to 800 million global workers will lose their jobs to new technology by 2030.

While predictions may seem categorically daunting, there’s a bright future ahead for knowledge workers who cast aside the yoke of clerical tasks and dictate the flow upon which robots “takeover”. Process mining can be used to find processes that aren’t worth knowledge worker’s time and are better suited for automation. Tedious process steps that require repetition across multiple systems (or even within the same system) will be highlighted by process discovery maps which can then be transferred to RPA in the process redesign phase.

Process blind spots in automation

Problem: unknown causations occur when too much automation takes places (i.e., machines create process steps or generate data unbeknownst to humans)

Solution: process mining uses event logs stored across IT systems (as opposed to the human interpretation of process steps) to capture a 100% true ‘as is’ process view.

In addition to strategic rollout, business process automation needs quality control. As more and more processes become automated and machines take on more significant roles in the process delivery, humans may overlook the output of such a takeover. Process mining helps to reveal hidden steps or unknown impacts made by automated systems. Remember, the additional data or process steps generated by automation need not be malicious in nature to be damaging.

Let’s say, for example, empty cart emails are automatically generated from an email platform, which then triggers an automated workflow series, which then triggers a new user persona classification. Individually, each process step may function as intended, but combined, it may feel like overbearing communication to the end customer. Process mining will find and connect these automated touch points and support decision-makers in process redesign which will meet their intended goals.

Process mining in partnership with automation

The inevitable has already arrived; automation is an indispensable part of how businesses function. From building cars to resolving service issues, machines have taken over human tasks. Heavy lifting aside, machines now cut into knowledge worker’s space. But when businesses face the topic of automation with care and knowledge, process automation becomes an asset, opportunity and potentially even a USP. To learn more about how process mining can help your organization tackle the landscape of business automation, get in touch with our team here at Minit.

Michal Rosik

12. 02. 2019