Orchestrate 170 debt collection workflows combined into 6 sequences into fully automatic process

‍Problem description

• During daily work, analysts spend 1,5h daily checking whether all debt coll processes have started on the right day, time and sequence.
• Currently have 6 sequences of different processes that start on the day and time we specify.
  
  1. SEQUENCE 1 – start at 5:30 a.m. Monday to Friday (70 processes)
  2. SEQUENCE 2 – start at 9:00 a.m. Monday to Friday (20 processes), must end by 11:00 a.m.
  3. SEQUENCE 3 – start at 5:30 a.m. Saturday (38 processes)
  4. SEQUENCE 4 – start at 7:30 a.m. from Monday to Friday after recalculation of process no. 5 from sequence 1
  5. SEQUENCE 5 – start at 8:00 a.m. Monday to Friday (processes 1 to 5 collect data that is sent to an external score conversion tool, after the work is completed, a signal is sent that starts process 6)
  6. SEQUENCE 6 - start at 10:00 on the first working day of the month

Solution

• SLS Platform orchestrated all that processes and sequences
• Check the stage of conversion and whether any errors have interrupted calculations.
• Notification is necessary in case a process fails to start as expected.
• Confirmation that recalculation of a given sequence is complete, with the end times recalculated. If the assumed time for the recalculation is exceeded (e.g. any sequence), an alert appears.
• Determine the computation time of each process in all sequences.

Key Results

• Monitoring of the process shortened from 1,5h daily into few minutes.
• Changes in workflow of the processes and sequences takes minutes instead of days or weeks.

Why Choose SLS?

The SLS platform enables businesses to:  

• Leverage AI-powered demand forecasting models for precise inventory planning.  
• Integrate predictive insights into supply chain operations to reduce waste and improve efficiency.  
• Adapt quickly to market changes with real-time data and flexible model updates.  
  

With SLS, retailers and e-commerce businesses can enhance operational efficiency, reduce costs, and improve customer satisfaction.

Questions Answered:

How can we forecast demand more accurately across thousands of sales points?  

• Answer: By using SLS’s predictive machine learning models that incorporate historical data and market variables for precise forecasting.  

How can we optimize inventory management to reduce waste and improve availability?  

• Answer: SLS integrates demand predictions with inventory and logistics systems, ensuring optimal stock levels and efficient supply chain operations.