Kanban for Automation - Case Study
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This document discusses using Kanban for automation projects. It outlines the vision to automate business processes across various domains using robotic process automation (RPA). The challenges included replacing existing bots, integrating disparate systems, limited documentation, and prioritization issues. The solution involved developing a process/product flow, technical practices like reusable components and an automation framework, and continuous improvement through defined processes and metrics. Metrics to measure success included man-to-machine ratio, time to market, throughput, and return on investment. Key learnings focused on eliminating waste, automating to improve processes, continuous learning, and reducing technical debt.
Kanban for Automation - Case Study
- 1. Kanban for Automation Projects By, Ramkumar Arumugam - A Case Study
- 2. AGENDA • Vision • Challenges • Solution and Process • Technical Practices • Continuous Improvement • Kanban Metrics • Key Learnings • Q & A
- 3. Vision • Automate business process in Indirect Procurement, HR, Distribution & Finance domains • Migrate existing business processes (in house bots) to industry leading RPA tool for scalability and maintainability
- 4. Goals and Objectives Reduce Cycle time Automate routine work Reduce Average Handling Time Seamless Integration with BPM, SAP, Oracle Increase Efficiency Scalable Platform Multiple Domains Reusability
- 5. Challenges Replacing existing 50+bots using RPA tool Disparate systems including Oracle, SAP, BPM & legacy Limited documentation for business processes Delays in BOT sign- off Data setup issues in 3rd party systems Prioritization issues Newer technology (Nascent RPA) No defined IT processes for BOT development
- 6. Process/Product Flow Requirements Videos Process Flows Workshops Framework Reusable components BOT Review Utility KEDB Automated Data Setup Bot Execution QA/UAT Auto Alerts Checker BOTs Rollout WIP WIP
- 7. Tools and Technical Practices 20+ Reusable Components Automation Framework to reduce development effort BOT code review utility Automatic BOT Alerts on Failures COE Best Practices for RPA development Improvise Development based on feedback Incremental delivery to avoid resistance
- 8. Continuous Improvement Defined IT Process Quality over Velocity Design Improvements Actionable Retro & Feedback loops Metrics Driven Delivery Automate the Automation BOT Command CenterBootstrapped/Lean Team
- 9. Automation Assessment Framework Kick-Off Ideation Assessm ent Develop/Conf iguration Release Support Benefit Realization • Scope for Automation • Risks related to technology, security, tools, etc • Plan – resource / asset / project • Reuse approach • Assess pain points • Use Case identification for BOTS development • Understand short-term & long-term goals • Perform automation ideation • Finalize Use Cases / Automation Processes to meet contractual commitments / stakeholder needs • Use Case detailing • Analysis of use cases from dependencies / DB perspective • Finalize solution / architecture • Configure product and develop code for BOTS • Establish Test Plan / Test Cases • Leverage best practices • Validate automation recommendat ions • Finalize release readiness • Ensure knowledge transfer • Monitor Audit Logs / BOTS / Failure Report • Monitor impact on Transaction Volumes / Change • Gather customer satisfaction feedback • ROI trends Digital FTEs • Reduction in Processing / Reporting time • Improvement in Productivity / TAT • Performance Dashboard PHASESACTIVITIES Kick-Off Minutes Initial set of Use Cases Test Logs / Self Assessment Report BOTS Certified BOTS Release Readiness Report BOT Performance Report Customer Feedback Report Performance Dashboard Finalized Use Cases OUTCOMES
- 10. Metrics driven delivery Metric Operational Definition Business Outcomes Man to Machine Ratio Number of BOTS Vs Number of FTE in the Team Time to Market, TCO % of reusable component used (Number of Components reused / Total Number of Components ) * 100 Time to Market Cost of RPA implementation 1.Licence cost (# of licenses , cost of license, reduction if any for increased volume) 2.Configuation cost (tools cost for design/architecture/ development + cost for solution development including testing) 3.Maintanance cost (Cost for Software updates , changes in Application , changes in Process) 4. Infrastructure cost (IT cost including in house / Cloud ; desktop costs) TCO % Reduction in FTE due to BOTS (Number of FTE released due to BOTS / Number of FTE before the BOTS release )*100 Time to Market Throughput (Process time before automation - Process time after automation )/ Process time before automation* 100 Time to Market
- 11. Metrics driven delivery Metric Operational Definition Business Outcomes ROI Total Cost Savings / Overall Cost of Implementation TCO % Reduction in MTTR (MTTR before Automation – MTTR after automation) / MTTR before automation) *100 Time to Market % of BOTS tickets re-opened (# of tickets resolved by BOTS that got re-opened / total # of tickets resolved by BOTS) * 100 CSAT First Bot resolution 1) Number of tickets resolved by BOTS / Overall Number of tickets 2) Number of tickets resolved by BOTS at L1/ Total Number of tickets resolved at L1 (Left shift from L1 to BOT) Time to Market % Test Automation Total Number of TCs Automated / Total Number of Test Cases) *100 Time to Market
- 12. Key Learnings Eliminate waste to improve efficiencies Automate to run better Hackathons for product or process improvements Continuous Learnings Leadership Advocacy Improved Development Efficiency KEDB Reduce Technical Debt through utilities Improve AHT
- 13. Thank You