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Process Risk in '24: Case Studies & How to Mitigate it in 7 Steps

Process Risk in '24: Case Studies & How to Mitigate it in 7 StepsProcess Risk in '24: Case Studies & How to Mitigate it in 7 Steps

Processes may underperform, go over budget , or increase the lead-time because of  process risks, such as malfunctioning equipment or human errors. Such process risks incur cost on the company  and lower customer satisfaction, harming a business’ reputation and finances in the process. 

To overcome these risks and their consequences, leaders should know how to identify and mitigate them. 

In this article, we’ll cover the different types of process risk, give examples of them , and offer 7 process risk management best practices. 

What is business process risk? 

Process risk, a sub-component of operational risk, refers to inefficient and ineffective business processes that lead to higher costs and lower customer satisfaction. These “ineffective business processes” can stem from: 

  • Actual failed processes
  • Inadequate policies systems
  • And disrupting events, such as employee errors, fraudulent activities, or other physical events

For example, an error in the order fulfillment process reflects poorly on the quality control process  and lowers customer experience. 

Therefore, process risk can also be explained to be  a result of a lack of proper process management.  

What are some real-life business process risk examples?

Commonly, there are h two forms of process risks:

Process risks in banking

These risks mostly result from documentation issues. 

For example, during the KYC process or loan processing stage, a bank filling the wrong information on the documents will slow down processes, such as loan/credit card approvals, and financial statement generation and can suffer from high audit and compliance fees.

Explore how to benefit from process mining in banking and reduce such risks.

Process risks in supply chain

In the supply chain, process risks in the order fulfillment stage are common and cause inefficiency.. For instance, mistakes in establishing the correct amount of inventory  can slow down delivery time or even fail to  finalize the fulfillment of the orders.  

Explore how to use process mining in logistics/supply chain firms to mitigate these risks.

What are process risk types?

Process risk types are harmful scenarios that stem from different departments/entities and can  cause inefficient, ineffective, and non-compliant processes. 

These risk types can be an external problem, an internal error, or both. These types include:

  • IT risk: They include  hardware and software failures, spams, viruses, malwares, and cyber attacks that infect a company’s digital infrastructure. 
  • Human error risk: Errors that are resulted from manual work. For instance, an accountant might enter the wrong number accidentally, which is a minor yet common mistake, and due to miscalculations’ ripple effect, can cause significant loss for the company.  
  • Workplace safety risk: It refers to any accidents or injuries that may threaten human health and safety. 
  • Process quality risk: This risk occurs when processes are not well designed and planned. For instance, a car  manufacturer plans its manufacturing in sequences depending on the time-to-completion and complexity of the task at hand, such as seat and seat cushion installation (with the former taking priority). However, if the manufacturer cannot accurately calculate the processing time for each step (i.e. seat cushions not being sourced on time due to supply chain issues and the installation phase being pushed back) the delivery timelines promised to customers and dealerships will be jeopardized, costing time and money.  
  • Infrastructure and equipment failure risk: These are breakdowns in primary building blocks of a process, such as communication breakdowns, network shutdowns, transportation fragmentations or the breakdown of the machinery or tools that are used to complete processes, which result in  process failures.  Such failures can delay the production, assembly, and delivery of products and harm order fulfillment as a result.

What are the 7 best practices to mitigate process risks?

We may not eliminate all the risks but we can minimize them by improving the operations, activities, and task management. 

Here are 7 recommendations to manage your process risks:

1. Develop a data-driven process risk assessment

The  first important step is to identify the risks in your processes. 

To achieve this, you should leverage your event logs data where information about the process executions is stored. By analyzing such data, you can evaluate your risk exposure in a data-driven manner.   

To extract and analyze process data, you can benefit from process mining, which is a tool that can automatically extract and analyze your event logs data. 

2. Map your processes 

Process maps and visuals can paint a picture of  the complexity of a process. 

Therefore, you should map your processes including each task, activities, sub-processes, and employees. Mapping your processes can streamline the identification of risky areas so that you can specifically implement changes where they are needed to hedge against the risks. 

To do so, you can use process mining since it automatically maps the discovered process model. You can zoom into each step or activity to check its impact on process performance. 

3. Increase automation level

Once the process is mapped and  the event log data is analyzed, you can assess your automation level to  discover new automation opportunities. 

Automation increases efficiency because it can reduce the risk that comes with manual errors. But choosing the right area to implement automation and to choose the right tool is not easy. Learn how to choose the correct automation tool.

You can also deploy process mining to assess your automation level and detect areas that require automation. Some process mining vendors offer a digital twin of an organization‘s capability which can help you to calculate ROI for each automation initiative and decide accordingly.

Process mining can also be helpful to manage the automation project. Learn how process mining helps you discover and manage automation projects.

4. Monitor and measure process performance

To ensure that your processes follow time, cost, quality, and compliance objectives, you should set performance metrics and monitor your all transactions, such as onboarding, sales, service or product delivery.

Monitoring and measuring your processes will allow you to pinpoint risks and intervene in time. Also, you can enhance your predictions by constantly monitoring your processes, ensuring early anticipations and improving process controls. 

Several process mining tools include KPIs for business analysts to track their performance easily. Some vendors also allow users to personalize their KPIs. These solutions also come packed with predictive analytics capabilities on their platforms so that you can predict whether the selected process will result in the desired outcome or not. 

For instance, process mining users can estimate if the loan application will be approved on the promised date or not. Estimating the date and taking precautions, such as setting reminders, can prevent high-cost risks. 

5. Comply with best practices and regulations

Following the best practices and complying with regulations can help reduce workplace safety or IT security risks. Also, you can standardize your processes by ensuring that each process follows best practices. 

Suppose a bank monitors its loan processes and identifies idiosyncrasies in  employees’ execution behavior. Lack of standardization, and each employee beating on their own drum,  can affect the bank’s reputation negatively while increasing lead time and cost. 

This can result in the bank being slapped with  high fees due to non-compliance. The bank should standardize its processes around best practices and regulations.  

Process mining’s core feature conformance check allows you to assess your compliance level by comparing your processes against best practices, ideal models, and regulations. 

For instance, Piraeus Bank analyzed its loan processes and detected variations in the application processes with the help of process mining. As a result, they shortened their application processes from 35 minutes to 5 minutes on average. 

6. Improve communication channel

Different parties that co-function and collaborate on mazy processes should be in constant communication with each other to be on the same page and avoid an infrastructure failure. 

For example, when a test manager notices that hiring inexperienced developers might lower the software quality. Therefore, the manager is expected to increase the number of re-tests. Yet, such a solution prolongs the time to launch the product in time. 

In such a situation, the manager should either communicate with the HR team to ensure that the right developers are in the team or improve the onboarding of young developers to prevent such problems. 

Process mining maps can determine relevant parties. Thus, these visuals can streamline the communication among these different teams. 

7. Consider process inter-dependency 

In many cases, processes are complex and interdependent like procure to pay (P2P) so various processes or sub-processes might affect each other. It is important to consider such inter-process relations while looking for inefficiencies or measuring the impact of a change in your operations. 

Imagine an improvement for requisition activities can increase efficiency for this process while creating bottlenecks at the invoice level. 

Multi-level process mining (MLPM) can help you understand inter-dependency and complexity by defining different entities in a given process and tracking interactions among them. By offering a more comprehensive model, the MLPM can ensure you can find out the risks and tackle them in-time. 

Further reading

Explore how process mining can enable process improvement and management:

If you believe your business can benefit from process mining, do not hesitate reviewing our data-driven comprehensive process mining vendor list.

And, if you are left with more questions, we are happy to help:

Find the Right Vendors
Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Hazal Şimşek
Hazal is an industry analyst in AIMultiple. She is experienced in market research, quantitative research and data analytics. She received her master’s degree in Social Sciences from the University of Carlos III of Madrid and her bachelor’s degree in International Relations from Bilkent University.

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