Basic Queue Theory and Gantt Charts

2. Basic Queue Theory and Gantt Charts Steve Harrison Wednesday 20th January 2014 Seminar Room 2 MEC

3. Topics • Variation – A recap • Basic Queue theory • Gantt Charts – Process Building Blocks • Other Variation Concepts

4. “If I had to reduce my message for management to just a few words, I’d say it all had to do with reducing variation.”W. Edwards Deming

5. Variation – what to do?

6. Application – Responding to Variation Identify the Cause: If Positive: Maximise, optimise, replicate, standardise. If Negative: Minimise, eliminate. Special Cause Variation Reduce variation: Increase precision - make the process even more reliable. Not satisfied with median performance (result): Redesign process to get a better result Common Cause Variation 6

7. Variation and Queues

8. Variation & Queues 100% 80% 50% Procedure Time (Minutes) Consecutive Patients 80% rule is the most efficient balancing waiting and waste

11. How to calculate • =(((Max – Min)/100)*80 )+ Min • 23 – 7 = 16 • 16/100 = 0.16 • 0.16*80 = 12.8 • 12.8 + 7 = 19.8 • 19.8 approx 20mins

12. Plan Cycle Time = 20m

13. Cycle time at 80% - PDSA 1 More Reliable More Variable

14. PDSA - Plan

15. PDSA - Plan

16. PDSA – Do & Study

17. Demand is increasing.... More slots needed...

18. 80% = 21mins 3hrs = 8 Patients

19. 80% = 18mins 80% = 21mins 3hrs = 8 Patients 3hrs = 10 Patients

20. 80% = 21mins 80% = 18mins 80% = 14mins 3hrs = 8 Patients 3hrs = 10 Patients 3hrs = 12 Patients

21. How do you reduce common cause variation?

22. GSM

23. More Queuing....

24. Capacity required = 27

25. Capacity required = 27

27. Capacity required = 49 (5 beds less than separate units ~£400,000)

28. Lung Cancer Clinic 13 + 11 = 24

29. Lung Cancer - pooled

30. And Finally - More Queuing....

31. Which is best? S C Q S C Q C Q C Q S C Q S S C Q S

32. S And Finally - Which is best? C Q Long C Q Short C Q Long S S C Q Long S C Q Short S

33. Discussion

34. Thanks!