In today's day and age where your order management process runs across a lot of different systems, keeping track of order frequency is no easy task. This is where Process Mining comes in
0%
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on time delivery
0%
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in delivery block
Drive Sustainability in Order Management
With complete transparency over your processes, keeping track suddenly becomes very simple, yet efficient. With Process Mining technology, visualize and quantify your processes, optimize lead times, reduce waste, and most importantly, make sure your customers are satisfied. Processand grants you the ability to connect the dots between the moving parts of your supply chain.
How we help
Reveal wasteful inefficiencies and deliver tangible results with Processand
Process Mining Use Cases
Order to Cash
On-Time Delivery
inefficiency / challenge
- Late deliveries can imply penalty payments and have a negative impact on customer satisfaction.
- Lack of transparency about the delivery process as well as key process KPIs.
- Difficulties to measure and enforce partner performance and SLAs.
- Lack of information on product delivery times.
solution and targeted outcome
- Implement an analysis that visualizes early, late and on-time deliveries as well as the distribution of the deviation from on-time dates.
- Dive deeper to identify areas with late deliveries.
- Expand with root cause analysis.
- Alerting to act on problematic cases and to inform customer.
business objectives
- Customer Satisfaction
core KPIs
- % On-Time Deliveries
- Delivery-in-Full Ratio
- # PO items
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Lead Times
inefficiency / challenge
- Large companies often lack an overview about the end-to-end O2C process.
- Difficult to connect different systems across locations and processes.
solution and targeted outcome
- Connect processes with various company codes etc. in one analysis.
- Conduct lead time analysis across various dimensions and detect bottlenecks.
- Optimize lead times and process related KPIs.
business objectives
- Customer Satisfaction
- Working Capital
core KPIs
- Cycle Times
- On Time Ratio
- # Sales Order Items
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Margin Analysis
inefficiency / challenge
- Keeping track of margins between purchasing and selling price is challenging with increasing turnover and a variety of different products with frequent price changes.
- A detailed overview, however, is essential for the profitability of a corporation.
solution and targeted outcome
- Margin analyses offer a detailed real-time overview of margins.
- Track margins between purchasing and selling price for pass-through articles.
- Track margins of stock items comparing sales price and moving average purchase price at the time of dispatch.
business objectives
- Revenue Increase
- Working Capital
core KPIs
- # SO with Match
- # SO with Deviations
- Margin
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Order Rejections
inefficiency / challenge
- Orders are created but later rejected, either causing internal rework or having a negative impact on customer satisfaction.
- Lack of transparency on order rejections and reasons.
solution and targeted outcome
- Visualize and quantify the amount of order rejections.
- Analyze various dimensions to investigate if repetitive patterns exist.
- Classify rejection cases, explore their root causes and execute actions to decrease order rejection rate.
business objectives
- Customer Satisfaction
- Labor Productivity
core KPIs
- Order Value of Rejections
- Order Rejection Rate
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Order Frequency
inefficiency / challenge
- Keeping track of order frequency is important to efficiently manage warehouse and logistics capacity.
- Companies often lack this information and thus fail to forecast the demanded supplies efficiently.
solution and targeted outcome
- Track order frequency by different time periods (month, week and day).
- Apply root cause analysis with drill downs by customer, material and country to identify specific patterns.
- Observe, analyze and plan according to order frequency patterns in the data.
business objectives
- Revenue Reliability
- Labor Productivity
core KPIs
- SO Items per Week
- SO Items per Month
- Sales Order Items per Day
read more
Learn More About Process Mining.
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Begin Your Process Mining Implementation
With over 450 process implementations, we know exactly what the crucial parts of a successful Process Mining initiative are
Christine Häcker
Data Scientist
