Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 55% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE and NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and resources that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
We follow ethical norms & our process for objectivity. Brands with links to their websites fund our research.
The biggest problem with processes is that although businesses have full knowledge about their desired processes, they have no idea about what their actual processes look like. This situation causes companies to make suboptimal decisions in process improvement and automation.
To prevent this issue, process discovery is a vital technique to see the full picture regarding processes, including their variations. With that, businesses can have accurate insights on how they actually perform and take optimal actions for improvement. Today, there are different technology solutions to support companies for process discovery.
Process discovery is the set of different tools and techniques to discover how any process in companies is actually executed. With process discovery, businesses can have a full understanding of their processes, uncover the process steps that they are not aware of and realize process deviations. These insights can help them to identify problems and decide the best areas for process improvement.
Businesses need to benefit from raw event logs and extract relevant data to discover their actual processes. With cause-and-effect analysis, they can connect different events to create process models, including their deviations. Process discovery follows the steps below:
Above is an example of process maps. Processes don’t work as desired in real-life. After conducting a process discovery analysis, businesses can understand how their “as-is” processes work. In the image, the thicker the lines are, the more frequent the process variation is. As you can see in the process map, actual processes are too complex and deviating.
Process discovery is a sub-branch of process mining and most process mining software includes process discovery capabilities.
As businesses get larger and companies strive to differentiate themselves from the competition, processes get more complex. The complexity can also cause new events to occur, and businesses might not be aware of them. Thus, process discovery techniques are vital today to understand the “as-is” pictures and become aware of process deviations.
Process discovery is not a new term though. It has been popular since the early 2000s and now process discovery capabilities are commonly provided by process mining solutions
By discovering actual processes, companies can reduce variations and prevent errors that incur unnecessary costs for them. Process discovery can also help businesses identify the best processes for automation, which also reduces costs in the end.
For example, a process mining vendor claims that Vaisala, a Finnish company, has used a process mining tool to discover the deviations in its operational processes, including sales, technical support, and repairs. As they could have a better understanding of their operations, it is claimed that they improved their repairs processes by ~59% depending on the product and reported a significant reduction in operational costs.
A 2020 survey by Deloitte states that 53% of their respondents started implementing some form of Robotic Process Automation (RPA), and this percentage will become 72% by 2022. Considering the growing potential of RPA, businesses should also be aware that almost half of RPA projects fail.
To choose the best processes for automation, companies need to understand their processes and discover their variations. By having the full picture of their processes, businesses can implement their RPA solution in the desired timeline and unlock their initiative’s full potential.
To read about common RPA pitfalls, feel free to read our guide.
While auditing is a time-taking process, process discovery can shorten these processes by providing all process variations. Besides, companies can discover non-compliant deviations and take action against such issues faster.
While process discovery has critical benefits for businesses, there are several points that companies should watch out during this process:
The primary purpose of process discovery is to understand the actual processes. For this, companies rely on historical data in process discovery. Therefore, process discovery does not normally inform companies about events that could potentially take place.
As a solution, companies can simulate different scenarios and get prepared against possible problems that might occur in the future.
During process discovery, companies should be careful about
For process discovery, three main pieces of data are required: event name, unique identifier, and timestamp. When one of these data is missing, businesses cannot map the event with the others. This might prevent them from discovering process variations.
Process mining is a developing solution that provides actual business processes by a layer of software integrated into the company’s IT systems. This technology uses event logs and data-driven performance metrics to connect process steps in a cause-and-effect relationship.
This solution is a broader approach that is not limited to process discovery. Companies use process mining to find ways to optimize their processes. Thus, it shares factual insights about each event in the processes and helps companies to identify bottlenecks and eliminate unnecessary steps in their processes.
You can read more about process mining in our in-depth guide.
Business Process Management Software (BPMS) is also a generalized tool that allows companies to define, optimize, and report on their processes. It focuses on helping companies to optimize their processes for achieving their objectives. While BPMS mostly focuses on monitoring processes rather than discovering new ones, it can still be used to understand process deviations and detect nonconforming process steps. With the insights it generates, a company can fully understand its processes by integrating BPMS into its system.
Process mining traditionally relied on log files. However, companies are also working on collecting data from
This requires using a software agent to record employee transactions. The main limitation of these tools is that they have no view of what happens inside the system, they are viewing the process from an end-user perspective. These tools help discover processes to enhance process automation and identify repetitive user actions.
Discover latest solutions to discover your processes and workflows through our objective and comprehensive list of vendors:
If you still have questions about process discovery, we would like to help:
Sources:
