Process Mining as an Essential Step in Optimizing Shared Services

This article addresses the benefits of Process Mining, how to avoid pitfalls, where to start, what to expect, and why Process Mining is essential for optimizing Shared Services.

Why is Process Mining Important for Shared Services?

While the Shared Services model has become popular across many organizations intent on optimizing business support services, its benefits range far beyond the obvious quality and cost improvements. From a high-level perspective, Shared Services acts as an information operation, receiving inputs at one end and delivering outputs at the other, effectively churning data all day long. A few years ago, practitioners suddenly woke up to the fact that there were additional and obvious benefits to be gained from tapping into and analyzing all this data for the business insights it provided.

Apart from the value for business insights and improved decision making, however, the data also helps evaluate process efficiency, and many organizations are now adopting Process Mining to understand what's actually happening across a given process by monitoring this data that would otherwise remain hidden.

It’s providing highly valuable operational insights.

"The beauty of Process Mining is that it identifies weaknesses, inefficiencies, and gaps that are not generally visible to the human eye, because they are difficult to analyze with the tools currently at our disposal," explains Sadettin Sezer, responsible for Process Management in Accounting & Controlling, and RPA, at Daimler Group Services Berlin.

“Process Mining offers a brand-new opportunity to analyze data and identify areas for improvement.”

A similar sentiment was echoed by the leader* of a F500 GBS, who addressed a conference on intelligent automation recently, highlighting how Process Mining optimizes automation.

Shared Services’ performance depends on combining the right technologies with the right process and the right people, he explained. Process standardization plays a big role here, as does automation – and Process Mining represents the first step to successful automation by taking the information that is in your systems and putting a process point of view on top of it. What happens is that the common paths as well as variations immediately pop out.

Ultimately, this information and the insights they drive make processes smarter and faster.

"The beauty of Process Mining is that it identifies weaknesses, inefficiencies, and gaps that are not generally visible to the human eye, because they are difficult to analyze with the tools currently at our disposal."

This is particularly important when different entities or countries don't have consistent processes. A number of different tools might be deployed globally to do the same thing, or there may be multiple purchases of the same tool. In addition, business process modeling is often applied inconsistently. Today, many companies’ objective is to shift from a legacy human workforce to a smart digital workforce model. Optimizing automation via Process Mining is a key strategy in achieving this objective.

More specifically, activating Process Mining supports moving from reports to exceptions-based reporting, along with suggestions on how to improve the process. To do so, however, requires taking a process view, as opposed to a task view.

What is ultimately at stake is ‘agile’ automation. Process redesign based on subject matter expertise alone is just not sustainable, therefore it makes sense to drive improvement from a process lens. To do that, however, we need to understand the process. That is where Process Mining comes in.

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One of the key benefits to leveraging Process Mining is the ability to standardize automations. By taking the top variants that emerge through visual Process Mining, and building automations around them, companies are able to standardize to the automation, not separate from it.

Where and How to Start?

The choice of where to start depends on each enterprise’s process landscape. At Daimler, the team decided to focus on the priorities for the organization, Sadettin explains. “Certain processes were always easy to manage, and others need more effort. The latter is where we focused our Process Mining efforts.”

Wolfgang Weckenmann, Director in the consolidation and accounting center at Carl Zeiss AG, manages transactional accounting across several legal entities in different countries, and chose Process Mining because he was looking for a tool to use in collaboration with internal audit, to highlight opportunities for improvement. "We were looking for a solution to help improve processes, especially across accounts payable and accounts receivable, and selected Process Mining to identify gaps, especially in how we handle invoices from receipt until payment,” he explains. He agrees that the choice of where to start should be determined by the operational goals. Within accounts payable, among the many KPIs that were listed, there were four in particular, including on-time payment, and POs associated with invoices, that were key for performance improvement. “That helped us determine our initial focus area,” Wolfgang explained.

What can Process Mining Achieve and What Are its Limitations?

The big wins in Process Mining emerge where additional information comes to light that allows a process to be adjusted. By way of example, Daimler’s Sadettin points out that although process definitions are generally held in the systems, loopholes emerge that result in certain steps being bypassed. Process Mining highlights these areas, he explains, identifying loopholes and ‘process weaknesses.’

Process Mining is not a panacea, however. Whatever solution you choose, and however impressive it is, exceptions will always remain, points out Aleksandra Kowalczyk, Continuous Improvement and Project Manager at Carl Zeiss Shared Services. These exceptions require specialists to step in.

In addition, while Process Mining covers the end-to-end process, it does not extend to downstream or upstream, and so it's important that management gains transparency over the bigger picture to drive additional improvements.

“Process Mining is highly effective as a tool, but it is not a transformation driver, nor is it actually about automating," Aleksandra explains. “It works by identifying the data buried in our processing and offering valuable analysis on how well the process is tracking to its original definition, or objective. It's about analyzing data and gaining more information – that is what drives performance improvement. In our case, the solution drew visual lines between our ERP system and the processes, and helped us recognize the gaps across different entities, which we were not aware of.”

“The real value, however, lies in driving action from the results. What you do with the information is down to you," she adds.

Tips on Implementing Process Mining

Just as with any tool, there are best practices that support achieving the best results, for example starting small and then scaling up.

"It makes sense to collect early experiences and figure out how the tool works and what exactly it can deliver, before tackling a big complex process," Sadettin suggests. "The other part of this is that you need to manage expectations. If you start by setting high expectations you run the risk of disappointing. Start small and figure out how it works first. Then you can build."

At ZEISS, Wolfgang Weckenmann suggests leveraging an experienced consulting partner, as he did, to ensure a best practice approach. "We were looking for improvements in Shared Services but first had to understand the actual processes in place and how process mining tools work," he explains. “Having an external partner helped us deploy Process Mining most effectively.”

One of the really key challenges in Process Mining is that it's difficult to drive a convincing business case upfront – in contrast, for example, to RPA. It’s simply not as intuitive to determine the business case for a tool that provides ‘insight and analysis’ on underlying data. Obviously, it depends on what you do with that information, which comes down to strategic decisions by management. So, the focus should not be on the business case but on the strategic investment.

To start with, for a successful implementation it is key to define an appropriate ‘scope’. These Process Mining solutions offer such a breadth of opportunity, that it's tempting to ‘go big’, Sadettin explains. "There's a tendency to scope extension and you quickly find your team overwhelmed. So, we regrouped during our second implementation and focused on what we considered were ‘optimal’ processes.”

‘Optimal’ processes are generally smaller projects where teams traditionally find themselves challenged and struggle to derive valuable analytics. Often, these processes are not stable enough for humans to adhere to the correct guidelines. That makes them optimal for evaluation.

*The speaker’s company does not allow specific quotes to be attributed publicly.