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Pair Methodology with Technology for Process Improvement in '24

Pair Methodology with Technology for Process Improvement in '24Pair Methodology with Technology for Process Improvement in '24

Process improvement analyzes business processes to detect errors and bottlenecks and implement changes to improve them. There are different approaches to enhance processes, either technology or methodology-based. The downside of having too many approaches is that it might confuse business leaders when deciding to implement a process improvement framework. 

In this research, we provide a framework of both technology and methodology-based process improvement tools and 3 best practices to facilitate implementing process improvement for businesses.

Best practices recommendations

1. Adopt process intelligence tools

Process intelligence is valuable because it enables analysts to grasp their operations and workflows to identify areas for improvement, in a data-driven and fast manner. Therefore, process improvement teams are highly recommended to embrace process intelligence solutions.

These solutions include tools such as process mining, task mining and the digital twin of an organization (DTO). While deciding on the tools, business analysts and process experts can evaluate the tools based on the way they apply machine learning to extract and model processes, the end-goals they provide and benefits they offer.

Learn more on how to implement process improvement by checking out our 6-steps guide.

2. Pair methodology with technology

Methodology-based solutions; such as Agile, lean or six sigma, were designed in an age where process intelligence was gathered via interviews and manual data analysis. Though their data collection methods are outdated, their approach to process optimization is not. Business analysts and leaders can leverage the best of both worlds by hiring personnel that are trained in process optimization and familiar with process intelligence tools to improve processes.

The methodologies enable the employees develop process improvement perspective and assist them with optimization related tasks such as collecting feedbacks on processes, identify customer values and/or reduce variations. Meanwhile, the employees can benefit from process intelligent tools to implement all these improvement tasks automatically while extracting and collecting real-life data.

3. Automate for improvement

Once processes are clear, automation is the next step. Some companies first start with automation and then end up with complex and hard to maintain processes. Since automation does not prevent the need for process maintenance (e.g. new regulations and technologies will require process changes), process simplicity and optimization are important steps to take before process automation. While you analyze a process for improvement, you can keep an eye on tasks and operations that require automation.

Technology-based solutions

Technology-based solutions help businesses enhance automation or help identify process bottlenecks, by leveraging and benefiting from real-time data extracted from the company systems. With these solutions, businesses aim to gain more accurate insights about their process performance, to identify their strengths/weaknesses by extracting data from various sources, and to increase automation levels to improve process efficiency. Feel free to read on the 4 technologies that accelerate process improvement, to discover more about the topic.

Below we explain some of the technology-based solutions which include:

  • Process intelligence tools
    • Process mining
    • Task mining
    • Digital twin of an organization (DTO)
    • Process modeling
    • Process mapping
  • Automation tools
    • Robotic process automation (RPA)
    • Data Extraction
    • Business process automation (BPA)
  • Business Process Management (BPM)

Process Intelligence tools 

Process intelligence tools help collect and analyze business process data and map the operational workflow to identify errors, deviations, and problems to improve efficiency. Some of the process intelligence tools include:  

1. Process mining 

Process mining extracts process data from IT systems to visualize and analyze it. Process mining enables business analysts, IT teams and leaders from different business functions and sectors to detect bottlenecks, assess performance and drive insights to improve their tasks and operations.

To discover the inner workings of process mining in more detail, do not hesitate to check process mining.

2. Task mining 

Task mining collects user interaction data, such as recordings and screenshots, to better understand the task execution. Analysts and leaders can use task mining to identify the most time-consuming, and costly tasks, to modify them. 

3. Digital Twin of an organization (DTO)

digital twin of an organization (DTO) is a virtual replica of a business, firm or department. DTOs are useful for monitoring operations and implementing modifications in process flows by simulating changes and measuring the ROI of such changes. 

Several process mining vendors offer task mining and DTO capabilities to increase performance assessment accuracy and enable data-driven decision-making for process improvement. 

4. Process modeling

Process modeling is another technology that allows businesses to visualize their workflows by providing an end-to-end overview of their operations. Process modeling is often compared with process mining and mapping. Although process mining offers more functionalities and use cases than process modeling, there is room to leverage both for process improvement.

For example, process improvement teams can generate ideal models by using process modeling and then upload the model they design to the process mining software as a reference model to compare it against the actual processes discovered by process mining. Read more on process modeling vs process mining.

5. Process mapping

Process mapping allows illustrating the process flow including interactions within the organization and each steps taken in the given process. The maps use symbols that are easy to follow by everyone. Therefore, process maps are helpful to understand how processes work and facilitate communication across the business.

Process improvement teams can leverage process mapping software to visualize the process they want to enhance and identify the weaknesses and strengthens before making any change.

Automation tools

Automation tools enable business analysts to modify their processes by automating tasks and functions in order to standardize these processes, increase workflow efficiency and reduce costs and errors in the execution of the operations. Automation tools can include business process automation solutions to transform entire process flow or RPA which focuses on automating given tasks. Discover more on automation benefits by reading our RPA benefits and examples.

1. RPA

Robotic Process Automation (RPA) is a solution under BPA technology. It generates bots to perform tasks and operations by monitoring users’ interactions when they execute processes. These bots can be rule-based bots that follow “if-then” rules by using screen scraping, or AI-enabled bots that leverage AI algorithms, such as NLP and OCR, to discover and replicate the process execution. 

2. Data extraction

Data extraction can help capture process data registered in documents automatically by using deep learning, facilitating internal audit and compliance with standardized reference models and procedures. For example, sales teams can extract data from customer reviews and examine process relevant comments to improve their customer service operations.

3. BPA

BPA software improves processes by automating repetitive tasks and manual tasks to reduce errors and costs while increasing efficiency. BPA software traditionally relied less on the user interface on automation however the line between BPA and RPA solutions are blurring and we are considering merging these categories but for now you can find a list of tools for Business Process Automation (BPA) among our vendor lists.

BPM software

Business process management is the overall discipline of process management from process modeling to execution and optimization. Business Process Management (BPM) software is a broad software category that involves technology based solutions for different steps (e.g. process intelligence or process automation) lifecycle. You can think of BPM as not a unique category but a category where solutions in process intelligence or process automation may list themselves.

You can view all relevant solutions in our data-driven vendor lists for business process management.

Methodology-based solutions

Some companies introduce new philosophies to their processes to increase overall performance. These solutions mostly don’t require a solution provider; businesses can implement them by themselves, or with the help of consulting firms. The main goal of these solutions is to bring in a new attitude to employees to improve processes. Here are the typical methodology-based process improvement solutions that we have encountered:

  • Lean: This methodology helps identify customer values to modify processes based on it.
  • Six Sigma: This technique is used for reducing variance and detecting the root causes of errors.
  • Agile: The software enables cooperation across departments to improve processes with incremental steps.

You can learn more about these techniques in our top 6 process improvement methodology articles.

Further Reading 

You can learn more on process improvement and case studies and best practices by reading our in-depth articles:

If you believe you can leverage technology-based process improvement tools, you can start reviewing our data-driven RPA and Process Mining vendor lists.

If you need help with process improvement solutions, let us help you to find the right vendor:

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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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