Processand Expertise for Streamlining Business Processes. With over 450 process implementations, we know exactly how to improve your processes and what the crucial parts of a successful Process Mining initiative are
What is Process Mining?
Process mining is a technique designed to discover, monitor, and improve processes by extracting available knowledge from the event logs in IT systems.
Why Process Mining?
- Process Mining provides you with data-driven insights
- It works on top of your existing systems
- Accurate, fast, and cheap in comparison to its alternatives
What are common business processes?
The most common business processes include O2C (Order to Cash) and P2P (Purchase to Pay). Every enterprise most likely has these processes as their core, there are many more, such as Accounts Receivable, Accounts Payable, Procurement, Order Management, and Inventory Management processes. What is common among all these processes? Processand’s experts will help you optimize all of these processes to help you achieve excellence.
Why Processand?
Processand is a global consulting and software implementation company that drives the successful transformation and digital realignment of IT-supported business processes. We support SMEs and large international corporations in converting their IT and ERP data into actionable insights.
As one of the leading partners of Celonis SE, our focus is on the implementation of the innovative and market-leading process mining technology, the data analysis based on it and the strategic support of our customers. With the help of process mining technology and our extensive process management know-how, we create concrete added value for our customers in the age of increasing IT complexity.
In this way we enable you to become more agile, take advantage of new growth opportunities, optimize your company processes and make the best possible decisions.
Begin your Process Mining journey with a partner you can trust
Every journey begins with the first step. Let our team of highly experienced Process Mining veterans guide you through the rough parts of the road ahead and help you realize maximum ROI.
How it works
Scope and implement
Every interaction inside the transactional systems of your business (like SAP, Oracle, Salesforce, ServiceNow, etc.) leaves "digital footprints" - raw data that can be transformed into a history of actions.
The first stage of Process Mining involves data engineers establishing a continuous data link to key data sources (through pre-build connectors and APIs), extracting and transforming raw data into an event log.
Event logs have three parts
Process Mining technology aggregates these event logs and reconstructs process flows across your whole organization as they happened - every time they happened.
Validate and analyze
Analysing event logs at scale renders your whole process environment in a level of detail that whiteboards, interviews, and process mapping software could never provide— every step of every process, every time it’s ever been executed.
In the second stage of Process Mining, data analysts methodically quantify the sum total of your process environment: every case, pathway, variation and error, as well as their business impacts.
All of this happens across a few different steps:
Process discovery
Build a complete picture of every process by exploring an interactive visualization of key metrics, like:
- Volume of cases/items in the process
- Total value of cases/items in the process
- Number of steps in the process
- Number of different paths (“variants”) that cases/items take through the process
- Number of cases/items that flow through each variant
- Visualization of steps and variants
Process analytics
Use powerful AI to understand the root cause (and enhancement opportunity) of every process variation, determine its operational significance and prioritize your response according to its impact on meaningful KPIs tied to key business outcomes, like:
- On-time delivery
- Working capital
- Customer satisfaction
- Risk reduction
- Operating costs
- Automation rates
IMPROVe
The variations and root causes identified during the Discover phase form the basis of enhancement opportunities—practical actions that remove friction and automate flow for your human and digital work forces.
In the third stage of Process Mining business users leverage AI and machine learning models to execute these enhancement actions across all relevant transactional systems within the same Process Mining interface.
These actions could be in service of:
- Correcting errors
- Removing erroneous steps (or adding new ones)
- Reducing manual effort
- Improving orchestration, standardization and governance
- Increasing rates of automation
Monitor
Continual improvement is central to Process Mining—discovery, analysis and enhancement are on-going activities that keep your processes in tight lockstep with your evolving business needs.
In the fourth stage of Process Mining, executives and managers measure and monitor process performance toward KPIs and business outcomes.
Hold teams accountable to progress against targets
Course-correct in real time
Grow engagement across different teams
Build demand for further Process Mining initiatives across the business
Communicate success upward and outward
What our clients say:
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We had a very good collaboration with both Celonis and the implementation partner Processand. They immediately understood what we were aiming for and were able to support us quickly with their expertise.
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We had ambitious goals that we wanted to realise in the shortest possible time. So it made sense to bring a reliable partner like Processand on board. Not only does their experience bring a different perspective to the project, but we also benefit from their expertise from other industries.
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The application of process mining technologies enabled deep insights into the complex workflows of the Accounts Payable process, individual steps were visualized and the correlations and effects were also shown. This detailed analysis enabled us to identify previously hidden bottlenecks, redundancies and inefficient process steps. In addition, the data preparation by Processand was directly usable for management presentations.
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Processand accompanies us since 2017 around the Process Mining technology. In the meantime, a close partnership has developed from this, which is now also growing in the area of Processand's own products, such as their Duplicate Invoice Checker. Processand has convinced us through innovation and first-class service until today.
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With our implementation partner Processand, we’ve found the right experts whose experience enabled them to implement our wishes quickly and competently.
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We began our Process Mining journey together with Processand and ever since then we have realized substantial value. This was made possible through Processand’s expertise and we are glad that we chose them as our implementation partners.
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The beauty of Process Mining is that the end-to-end process knows no functional or structural boundaries. As a result, we bring strategic and operational purchasing, accounting, and subsidiary procurement functions to the same table and can find data and fact-based solutions.
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Processand was our first choice for the implementation of Celonis in the IBC and since then has been supporting us in all aspects of Process Mining.
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We were immediately convinced by Processand's comprehensive expertise in data modeling and project management during our Process Mining implementation. The data design that we develop with Processand enables new fields of application to take our process efficiency and digital operations to a new level.
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With Processand we have a long-standing, trusting and innovative cooperation. With the implementation of audit-specific requirements we have jointly developed advanced procedures, which have been implemented in sophisticated Process Mining analyses.
Learn More About Process Mining.
Get in touch
Begin Your Process Mining Implementation
With over 450 process implementations, we know exactly what the crucial parts of a successful Process Mining initiative are
Alexandra Tyrkich
Head of Data Science
