Our SaaS solution delivers state-of-the-art data-driven process analytics based on process mining for more transparency, targeted process optimization and more efficient use of resources

Our modular solution consists of several components that can be customized and are aimed at different user groups. The Dashboard provides quick transparency on the most important key figures and is suitable as a process-related addition to reporting. The Analyzer enables multidimensional process analysis by means of several views and visualization options. The Workbench gives data experts and data scientists the possibility to perform individual analyses using Jupyter Notebook. There is direct access to the underlying data lake of the process data.


How do I get a quick overview of the process?

The Dashboard provides a compact, real-time overview of the business processes by displaying key figures such as lead times, automation rate, compliance violations, bundling behavior, process path variants, etc. By means of filter options, users can narrow down their analysis to specific time periods, certain process activities, selected variants, specific customers and much more. In addition, the dashboard can be customized by placing individual widgets on the canvas as desired. The objective is to create transparency and supplement existing reporting tool with the process-oriented perspective that traditional BI solutions do not provide. More about exemplary key figures can be found here.

Targeted users: Process manager and higher management


How can I optimize processes by uncovering bottlenecks, problems, complexity, etc.?

The Analyzer is the centerpiece of our solution. It offers a wide variety of analysis views with which processes can be analyzed down to the smallest detail. Here, too, filters allow the analysis to be narrowed down in detail in order to get to the bottom of process problems. A dimension switch allows processes to be tracked using different business objects – creating a 360° perspective! Display options allow important aspects to be highlighted or additional information to be displayed.

Targeted users: Process analyst and process owner 


How can I use ‘advanced analytics’ to uncover problem origins?

The Workbench allows data experts to create their own analytics scripts using Python. There are no limits to the imagination and the complexity of the desired outcomes. Via a direct data connection to the underlying causal process graphs, sophisticated analytics use cases can be implemented with artificial intelligence, machine learning or conventional statistical analyses. The scripts created can be saved and shared with other users. The associated interface is based on the widely used industry standard Jupyter Notebook.

Targeted users: Process analyst and data scientist 

“A company’s ability to flexibly change its organizational processes indicates its readiness to undergo other radical reconfigurations.”

– Kim, Shin, Kim, and Lee (2011: 488)

Process Performance Indicators (PPIs)

Which key figures can I use to continuously measure my process? 

Our tool allows calculating all kinds of PPIs that are built to support higher management or a process owner in order to monitor the process execution over time. PPIs give implication on whether a certain process optimization initiative has led to positive business outcomes. Below we highlighted a selection of important PPIs from the Order-to-Cash process*.

Avg. Throughput Time

Calculation of the average time it takes for a certain process from its first to its last activity. By using filter functions, it is possible to limit the calculation to just a customer, an order type, a single process instance, a region, etc.

Rework Rate

Uncover how many rework actions take place along a business process. This allows not only uncovering the additional costs necessary for manual work but also the intensity a customer or supplier changes its requests. Of course, there is the possibility to filter by customer, order type, resource, region, etc.

Activity Batching Factor

The batching factor calculates how intensive certain process activities bundle multiple business objects along the process. For instance, a delivery activity can encapsulate multiple orders for the same customer. From a cost perspective, it can be helpful to combine the delivery of multiple orders for the same customer in order to save money for transportation.

Number of Process Variants

The number of process variants is an indication of process complexity. We count one process variant as one individual process path taken. In reality, we often experience hundreds or thousands of individual process paths. Usually, the goal is to reduce the number of process variants in order to get closer to the standard process paths.

Number of Process Violations

A process violation occurs if one process activity is executed in a way that contradicts its initial definition. For instance, an process activity was executed in the wrong order, a four-eye-check was skipped or certain thresholds were exceeded.

Days Sales Outstanding (DSO)

Days sales outstanding indicates the average amount of time it takes between the invoice date and the actual payment of a customer. The number is highly important for assessing the liquidity and cash flow based on outstanding account receivables. The number helps optimize cash discount rates in order to nudge the customer towards an earlier payment. By using Noreja, it is possible to filter by certain business objects like customers, orders, order types, etc.

Cash Discount Received

The cash discount received is a measure of how intensive a customer uses a cash discount in exchange for early payments. A high number indicates that the cash discount is attractive for the customer and that the customer has good payment morale. A low cash discount received leaves room for maneuver during upcoming payment terms negotiations.

Hidden Credit Time

The hidden credit time is the average number of days between delivery and invoicing. It indicates how much time a seller grants credit for its customers, hence, is not paid for its services or products. By reducing the hidden credit line, the cash flow is optimized.

* Depending on the source database and the availability of relevant data