The red brick cancer ACE! Conf 2013-04-16

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We will explore the differences between systems with high resource efficiency and systems focused on flow efficiency. You will learn how to understand and improve the end to end flow in your system.

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  • The RED brick cancerACE! ConferenceOn Lean and Agile best practices2013 15-16 April, Krakow, Poland
  • Let me tell you two short stories of two Swedish women in their thirties.We will follow them both through their interaction with the Swedish healthcare system.We will start with Maria.
  • It is Monday morning and as Maria gets dressed she discovers a lump in her left breast.She is concerned, and with just cause.Breast cancer is the most common cancer among women in Sweden.
  • She contacts here local healthcare center and gets an appointment the next day with her family doctor.
  • She meets with the family doctor.He makes the examination but can’t rule out that the lump is cancer.He refers her for a consultation to the breast clinic at the local hospital.
  • Maria is told she will receive the time for the consultation in the mail.
  • Maria is worried and what to get the examination over with. She checks her mail every day for the appointment.
  • After ten days she has still not received her appointment letter. She calls to try to find out status.After some searching the nurse on the phone finds her referral and promise it will be processed later today.
  • Four days later she receives the appointment letter.The appointment is scheduled for the next week.
  • Today it’s time for the mammography and ultra sound.Maria arrives a little bit early. She sits down in the waiting room.15 minutes after the scheduled time her name is calledThe mammogram and ultra sound just takes few minutes.
  • She is once again sent home as the referral to the breast surgeon is sent.
  • Ten(10) days later she is due back at the breast surgeon at the local hospital.
  • The breast surgeon has analyzed the images but unfortunately he can’t rule out cancer. He need to refer her to a cytologist so they can take a tissue sample.
  • Maria is sent home and she is now out of herself of worry and can’t remember a thing the surgeon told her.Would she be sent a new appointment or should she schedule one her self? The next day she calls back to the hospital,but can’t get by the automatic machine. She leaves a message.
  • Later that same day she is called back by a nurse. She explains that a referral has been sent to the cytologist.
  • She is told that she has an appointment in two weeks.
  • Two weeks of constant worries Maria meets the cytologist. He takes a tissue sample.He explains that the sample now needs to be analyzed and the result will be sent to the breast surgeon she meet earlier. The doctor don’t know exactly how long the analysis will take as the lab is usually very busy.
  • She will receive an appointment in the mail.
  • After six long weeksMaria is back at the breast surgeon for the diagnose.
  • Nowletusmeet Anna.
  • It is a gray Tuesday morning and when in the morning showerAnna discovered a lump in her breast.At lunch she shares her worry about the lump with her best friend. She tells Anna about the “One stop breast clinic” at the local hospital. Anna decides to check it out as soon as the lunch is over.
  • Back at her computer Anna finds the information on the “One stop breast clinic”.Next time it is open is in two days. She decides to go.
  • It is now Thursday afternoon and she walks into the clinic.She immediately gets examined by a nurse. The lump defiantly needs to be examined.
  • Anna is sent to the waiting room and will be called as soon as the doctor is available
  • Only 15 minutes later a breast surgeon calls her name. He examines her breast. He can’t rule anything out.He want to take a ultrasound and a mammogram.
  • Anna is one again sent back to the waiting room. You will be called as soon the nurse is available, she is told. She prepares herself for a long wait.
  • But just after a few minutes her name is called and a specially trained nurse take the mammogram and thena doctor performs the ultrasound. They confirm the lump in the breast. But a tissue sample is needed.
  • The nurse follows Anna to a cytologist who takes a tissue sample.He apologues as he asks Anna to take seat in the waiting room again as the sample is sends off for analysis.
  • Anna is one again back in the waiting room. She buys a soft drink in the vending machine and starts reading a magazine.
  • A few minuteslater, to her surprise,she is back to the breast surgeon and he gives her the diagnose.
  • Both Maria and Anna went through the same diagnose process steps but with two totally different experiences. For Maria it took over 1000 hours to get her diagnose but it took less than 60 hours for Anna. How come they had such different experiences? Maria’s process time line is full of red LEGO bricks. Anna's not so much. Why?
  • The two different process has been optimized based on two different business strategies.
  • Maria’s process is optimized from the different healthcare units perspectives. It has been optimized for resource efficiency. This means that the process is optimized to keep the doctors, nurses and machines as busy as possible. This is supposed to drive down the cost per activity. The result is most often a process full of red bricks.
  • On the other hand, Anna’s process is optimized for flow efficiency. The process is also optimized on her as the customer. This means that the process is optimized to have Anna go through the process as fast as possible with as little wait time as possible, not so many red bricks. How busy the doctors, nurses and machines are is a secondary concern.
  • You may think that the process Anna went through is much more expensive than the process Maria went through. But in fact the “One stop shop” concept that focus on flow efficiency costs the same or less. This is often due to the fact that most yellow bricks, failure demand, can be removed from the process.
  • If you would build a LEGO time line of your processes, would they be mostly red and yellow? Or would they be mostly green?
  • Queuing theory.Little’s Law states that the more things in process, the longer the cycle time.If we have an average completion rate of 1 feature a week and we have 3 features in process we get a cycle time of 3 weeks per feature. If we instead are working on 1 feature at a time, we get a cycle time of 1 week per feature.
  • The red brick cancer ACE! Conf 2013-04-16

    1. 1. Håkan Forss hakan.forss@avegagroup.se @hakanforss http://hakanforss.wordpress.com/Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    2. 2. Håkan Forss Lean/Agile Coach @hakanforssCreated by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    3. 3. Scrum and XPCreated by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    4. 4. KanbanCreated by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    5. 5. Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    6. 6. Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    7. 7. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    8. 8. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    9. 9. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    10. 10. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    11. 11. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    12. 12. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    13. 13. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    14. 14. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    15. 15. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    16. 16. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    17. 17. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    18. 18. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    19. 19. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    20. 20. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    21. 21. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    22. 22. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    23. 23. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    24. 24. Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    25. 25. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    26. 26. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    27. 27. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    28. 28. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    29. 29. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    30. 30. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    31. 31. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    32. 32. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    33. 33. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    34. 34. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    35. 35. > 1000 hours < 60 hours Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    36. 36. Two differentbusiness strategiesCreated by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    37. 37. Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    38. 38. Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    39. 39. Optimized for Resource efficiency Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    40. 40. Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    41. 41. Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    42. 42. Optimized for Flow efficiency Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    43. 43. Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    44. 44. Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    45. 45. What process is most expensive? Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    46. 46. Non value adding: Wait timeNon value adding: Required wasteValue adding: Actual demand Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    47. 47. Common bricksWaiting in a queueWaiting for a decisionWaiting of someone to finishtheir workCreated by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    48. 48. Common bricks Rework due to Defects Handovers Lack of understanding the requirements Over processing, backlog maintenance Reporting and status meetings Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    49. 49. Flow efficiency in numbers Usually 1-5% value added of total lead time 20% value added is a high number Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    50. 50. How many and bricks do you have?Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    51. 51. The three ”laws”Little’s LawLaw of bottlenecksLaw of variation Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    52. 52. Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    53. 53. Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    54. 54. Little’s Law Work-in-ProcessLead Time = Throughput Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    55. 55. Little’s Law 12 1 min = 12 / minCreated by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    56. 56. Little’s Law 60.5 min = 12 / minCreated by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    57. 57. Little’s Law 24 2 min = 12 / minCreated by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    58. 58. ABC ABC ABCAAA BBB CCC Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    59. 59. The three ”laws”Little’s LawLaw of bottlenecksLaw of variation Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    60. 60. BottlenecksEvery process has at least one Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    61. 61. You can’t go faster than your bottleneck Capacity = 6 Capacity = 4 Capacity = 6 Throughput = 4 Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    62. 62. You can’t go faster than your bottleneck Capacity => 4 Capacity = 4 Capacity > 4 Throughput = 4 As long as capacity in front of the bottleneck is equal to or grater than the bottleneck you will go as fast as your bottleneck Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    63. 63. You can’t go faster than your bottleneck Capacity = 6 Capacity = 4 Capacity > 4 Throughput = 4 Full use of a higher capacity in front of the bottleneck will make lead time go up Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    64. 64. You can’t go faster than your bottleneck Capacity => 4 Capacity = 4 Capacity >= 4 Throughput = 4 As long as capacity is equal to or greater after the bottleneck you will go as fast as your bottleneck Higher capacity after the bottleneck than at the bottleneck will not improve throughput over time Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    65. 65. The three ”laws”Little’s LawLaw of bottlenecksLaw of variation Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    66. 66. Low variationCreated by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    67. 67. High variationCreated by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    68. 68. Common sources of variation Arrival rate Work size and complexity Ad-hoc processes, swarming Available capacity Available and needed competence Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    69. 69. Common ways to improve Flow efficiency Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    70. 70. Reducing batch sizeSmaller features MMF, MVPDeliver continuouslyCreated by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    71. 71. Reduce work-in-process Use a kanban system to limit work-in-process Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    72. 72. Improve qualityContinuous IntegrationPair programming and TDDStop the line and root causeanalysis of defectsCreated by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    73. 73. Reduce process variation Reduce batch size Reduce length or remove iterations Use a mixed feature portfolio Avoid swarming and ad-hoc processes Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    74. 74. Time to choose sideCreated by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    75. 75. Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com
    76. 76. Håkan ForssMail: hakan.forss@avegagroup.seTwitter: @hakanforssBlog: http://hakanforss.wordpress.com Created by Håkan Forss @hakanforss http://hakanforss.wordpress.com

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