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Becoming a Process Minding Organization - a Solution Overview

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While process mining is perceived by many as a very cool technology, yet companies are not willing to embrace it as warmly and quickly as expected. Managers still expect more convincing and significant added value. Another issue might be with offering process mining technology as somewhat detached solution and not taking into account BI solutions, which might already exist in a company.
The attached presentation proposes a solution which is based on an integration of ERP, BI and process mining technologies.
The technologies used enable a quick, easy and low cost “jumpstart” in order to increase ‘process minding’ in a company. Hope you find it useful!

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Becoming a Process Minding Organization - a Solution Overview

  1. 1. Mind Your Processes Author: Dafna Levy A Solution Proposal
  2. 2. The Common Performance Measurement  Companies usually measure their performance with financial data only.
  3. 3. But Business Success Depends on Process Performance
  4. 4. Acquiring Process Minding Process Performance Business Performance  Looking at financial metrics without linking them to processes limits the ability to improve business performance  Real-time process monitoring based on operational KPIs (e.g., time, cost, quality, risk) and discovering root causes of deviations, enable managers to gain operational insights.
  5. 5. The Solution Overview
  6. 6. Business Discovery with QlikView (BI)  The Business Discovery dashboard displays info based on sales data from Priority ERP  The sales manager is not satisfied with the displayed financial results  Analysis of the business data to discover the root causes is not enough  The manager is willing to analyze operational data too.
  7. 7. Measuring Operational Performance  Operational KPIs are based on historical data of sales orders from Priority ERP.  The gauges bounds are defined by managers  Note: The dashboard is based on a gradual implementation. First, data for selected metrics are retrieved in order to reveal performance issues with the process in question. Later on, the gauges bound values are determined by the manager.
  8. 8. The Process Model (in Priority ERP)  Built-In mechanism in Priority ERP to define and control process steps  The model includes statuses and paths between them - i.e., the workflow  Currently, there is no way to discover inefficiency or bottlenecks with reports generated by the ERP system.
  9. 9. How Events are Created  Display of the sales orders screen in Priority ERP  When updating a status or an employee in a sales order, an event record is created in a sub-level form  The event log data, together with business data can be easily retrieved and exported from Priority ERP for process analysis.
  10. 10. Process Discovery with QlikView  The Process Discovery sheet displays events & business data of closed sales orders from Priority ERP  Analysis of process performance with various dimensions is enabled  Gauges display operational info about duration, efficiency, costs and more  The current sheet is linked to the Business Discovery sheet.
  11. 11. Analysis of Slow Orders (> 40 days)  Bar chart displays sales orders durations on the X-axis, and number of orders on the Y-axis  Pie chart displays costs and durations per statuses or employees  Gauges are updated according to user selections
  12. 12. Business Data of the Slow Orders  The Business Discovery sheet is automatically updated with the previous selections  Only the slow orders-related data are displayed  Analysis of specific customers, part families or profit centers assists in discovering root causes of issues in the process.
  13. 13. Preparing Data for Automatic Process Discovery  Further analysis of the slow process can be performed with a process mining tool (e.g., Disco)  Data of the slow process can be selected & exported with a click of a button.
  14. 14. Overview of Slow Process Data in Disco  Extended data enable rich and more significant process discovery
  15. 15. Animation of the Slow Process
  16. 16. Analyzing the Fast Orders for Benchmarking  The chart displays now data of sales orders with a duration of up to 15 days.  Comparing slow & fast processing of the sales orders can reveal opportunities for improvements (e.g., discover the efficient employees and adapt best practices)  The data is exported for further analysis with process mining technology.
  17. 17. Benchmarking with Disco Fast Process Slow Process
  18. 18. Business Rules in Priority ERP  A tool to define and manage goals of a business process  Enables to define time-based rules & alerts  Analysis of all deviations from rules is not enabled in the ERP system.
  19. 19. Analysis of Business Rules with QlikView  The table displays statistics results of automatic analysis of process rules with QlikView  The expected duration can be compared to the actual  The results can be used to define base values for metrics and alerts.
  20. 20. Real-Time Process Control  The Process Control dashboard displays both business & operational data of open sales orders  A deviation of case durations can trigger an alert (online or Email)
  21. 21. Real-Time Rules Monitoring  The Rules Monitoring dashboard enables constant control of the executed process  The gauges display average deviation from the desired duration, and the percent of the orders which deviated for a selected rule.  Alerts can be added for rules deviations as well. 
  22. 22. Summary  The solution can be applied to any system which manages processes  The solution can be developed with any BI tool  Some benefits of integrating process mining technology:  Holistic approach vs. detached (i.e., a stand-alone solution/service)  Event data are extracted directly from the BI database  Event data are enriched with business data ► Analysis and benchmarking results enable fine-tuning of KPIs ► Operational & business managers can share results and insights More info & examples can be found here.
  23. 23. Thank You! Dafna Levy Email: dafnal@nool.co.il Phone: +972 (0)54-6881739 Weblog: http://bpmintro.wordpress.com

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