Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Process Mining For Customer Support


Published on

Introduction to Process Mining and its applicability to enterprise technology customer support. Please visit my blog at for further discussion.

Published in: Technology
  • Be the first to comment

  • Be the first to like this

Process Mining For Customer Support

  1. 1. Process  Mining   for   Customer  Support   Haim  Toeg    
  2. 2. Process mining is a discipline positioned at the crossroads of computational intelligence, data mining, and process modeling and analysis. The idea of process mining is to discover, monitor and improve real processes by extracting knowledge from the event logs produced as part of on-going business activity. Adapted from Process Mining Manifesto What Is Process Mining?
  3. 3. Process  Aware  System  Lifecycle  
  4. 4. Some  reasons  support  may  adapt  well  to  Process  Mining:   *  Highly  disciplined   *  Heavily  instrumented  and  regimented   *  Fairly  well  documented  processes   *  Culture  of  metrics  and  improvement   Why  Support?  
  5. 5. *  Business:  Do  More  With  Less   *  Efficiency  and  Effectiveness   *  Reduce  cost  /  case  or  /  customer  -­‐>  Operational  metrics   *  Case  life,  backlog,  time  since  last  touched   *  Cases  /  installation   *  Improve  effectiveness  -­‐>  Result  metrics   *  NPS,  CSAT   *  Correlate  and  analyze  data   *  Prioritized  action  list     Process  Improvement  Goals  
  6. 6. *  Greater  granularity  <-­‐>  abstraction   *  Drill  down  to  individual  process  elements   *  Segregate  data  by  operational  element  (geo,  product)   *  Combine  process  elements  to  study  overall  activity   Improving  Process  Improvement  
  7. 7. Yes,  we  do!   But,  We  Don’t  Have  The  Data  
  8. 8. Traditional Operation
  9. 9. Weaknesses?   *  Reliance  on  generalized  metrics   *  Anecdotal  review  of  one  or  small  number  of  process   instances   *  Limited  ability  to  drill  down  and  investigate   *  Not  much  abstraction  ability  either   *  Event  logs  used  only  sporadically  and  reactively   Familiar?  
  10. 10. With  Process  Mining  –  Discovery  
  11. 11. *  Model  the  executed,  real-­‐world,  processes   *  Identify  and  review  process  variants   *  Discover  informal  collaboration  and  knowledge   *  Investigate  and  measure  every  action  and  transition   *  Support  for  Lean  perspectives   *  Workload  /  People  perspectives     Discovery  Benefits  
  12. 12. Discovery  Results   Case  flow  via  activities:   Process  flow:   •  Activity  Frequency     Bottlenecks:   •  Critical  activities  and   paths   •  Investigate  operational   metrics  
  13. 13. Lean  Resource  Perspective   Activity  flow  through  cases:   •  Most  demanding  cases   •  Case  idle  times  
  14. 14. Bottleneck  Identification   Critical  Resources:   •  People   •  Machines    
  15. 15. Collaboration   Flow  of  work  through  specific   people  or  resources:   •  Knowledge  centers   •  Critical  resources  
  16. 16. Conformance  
  17. 17. Combine  your  existing  and  discovered  process  models:   *  Find  degree  of  conformance  between  the  two   *  Understand  repeat  offences  and  take  corrective  action   *  Systems   *  Processes   *  Metrics     *  People   *  Estimate  cost  and  benefit  of  alignment  vs.  no  action   Conformance  Benefits  
  18. 18. Conformance  Report  
  19. 19. *  Leverage  existing  data  using  recently  developed  leading   edge  techniques   *  Review  executed  processes  in  detail  to  get:   *  Excessively  repeated  activities   *  Process  bottlenecks   *  Critical  resources   *  Knowledge  hoarding   *  Drive  systematic,  prioritized  process  and  organizational   improvement   Process  Mining  for  Support  
  20. 20. Eliminate  The  Disconnect  
  21. 21. Thank  You   Haim  Toeg   +1.832.419.5645