Training Project completed in June of 2001; completion of this project qualified me for certification as a Black Belt.
- 1. Training ProjectSheraton North Charleston Jon Haid, Black
Belt
2. Project Definition
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- Laundry Operation Improvement
- Problem or Opportunity Statement
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- The laundry is responsible for cleaning and distribution of
linen for 296 guest rooms.Food and beverage linen is currently
being rented from National Linen.
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- Current laundry process experiences down time.Current expense
are approximately $80,000 per year at $1.17 per occupied room. Lack
of clean laundry available on the guest floors results in time
wasted by the housekeepers to secure clean linen.
3. Define Impact vs. Effort
- Financial Impact:Reduction of Laundry Cost per Occupied Room by
10%, to $1.06 POR by the end of July, 2001.
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- Laundry Associates will participate in data collection.
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- Will not require major operating changes.
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- No increase in management or personnel .
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- Sponsor will be fully engaged in process.
4. Define Impact vs. Effort
- Based on Impact / Effort Definition Apply Score (High = 5,
Medium = 3, Low = 1)
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- Rev. Growth Low-Personnel Requirements Medium
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- Cost ReductionLow -Length of Project Low
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- GSI ImprovementLow -Capital Cost Low
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- ASI ImprovementLow -Risk of Project Medium
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- Jon Haid, Black BeltCarol Ferrell, Team Member
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- Zainab Rahman, Team MemberLee Harley, Sponsor
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- Victoria Carey, Team MemberSally Sexton, Team Member
5. Define - SIPOC 6. Stakeholder Analysis 7. Define Customer
Requirements 8. Constraints & Assumptions 9. Define Process
Mapping 10. Current Laundry Process 11. Metro Delivery Process 12.
Measure Key Measures 13. Measure Performance Measures 14. Measure -
Rolled Throughput Yield 15. Population Sampling Worksheet 16.
Measurement Planning Worksheet 17. Measurement Assessment Worksheet
18. Measurement Selection Matrix 19. Data Collection Sheet This
sheet was used to record the amount of clean linen delivered to
each floor on a daily basis. Jon Haid: 2 - 8 refers to Floor Number
20. Travel Time Tracking Sheet This sheet was used by the Room
Attendants to record each time they had to leave a guestroom or
come downstairs to obtain linen Jon Haid: Each linen type
represents a potential defect. 21. Linen Inventory Levels This
sheet represents the amount of linen required to be fully up to par
in each room.Its broken down by floor and room types. 22. Actual
Linen Inventory This sheet is a record of the physical inventory
taken. Jon Haid: This inventory indicates a shortage of Full Size
sheets, which if not available on each floor, would be a defect.
23. Shift in Project Scope 24. RACI Chart 25. Minitab - Descriptive
Statistics This chart shows the amount of hours worked in the
Laundry.The average is 16 hours per day, but there were days with
either 1 or as many as 3 attendants. 26. Data Collection Sheet Jon
Haid: This sheet was used to record Laundry Attendant hours worked,
as well as Rooms Occupied, Departures, & Arrivals. 27. Analyze
VA / NVA Analysis 28. Analyze Data Analysis Tools This Pareto Chart
shows the most frequent item missing in the Guestroom is Wash
Cloths, followed by Double Sheets & Pillow Cases. 29. Analyze
Data Analysis Tools 30. Analyze Data Analysis Tools Mean 31.
Analyze Data Analysis Tools Travel Times 32. Analyze Root Cause
Analysis Jon Haid: Project focus is on metro delivery process. 33.
Analyze Root Cause Analysis 34. Analyze Root Cause Analysis 35.
Analyze Correlation and Regression This Scatter Plot shows there is
No Correlation between minutes of travel time and occupied rooms.
36. Analyze Correlation Coefficient Jon Haid: Since r, the Pearson
correlation, is .303 there is no meaningful correlation between the
minutes of travel time and occupied rooms. 37. Analyze Correlation
and Regression Jon Haid: The prediction equation is produced by
Minitab. 38. Analyze Correlation and Regression This Scatter Plot
shows consistently lower travel times when linen was delivered
before the shift.The minutes shown as negative values represent
delivery after the shift started which showed a substantial
increase in travel times. 39. Analyze Positive Correlation Jon
Haid: When comparing Travel Time during the Housekeepers shift to
the number of minutes prior to the shift the metro was delivered,
we get a meaningful correlation, because the Pearson correlation is
below -.65. 40. Regression Analysis 41. Improve - Idea
Generation
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- Provide less linen to guests.
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- Dont wash sheets so often.
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- Use dark linen so stains dont show.
42. Improve - Idea Generation
- How to reduce travel time How to reduce pizza delivery
time
- Similar but different situations:
- Elevator traffic Traffic on the street
- Missing pieces of linen Not having the right ingredients
43. As Is Mapping Travel time is shown as rework, or loops in
this process. 44. Should Be Mapping Jon Haid: Our solution will
eliminate or reduce the travel time, or rework. 45. Improve
Solution Statements
- To reduce travel time by Housekeepers to secure clean linen, we
will change the distribution, or delivery process, of clean linen
to the guest room floors.Laundry Attendants will deliver metros
loaded with clean linen to the guest floors prior to the arrival of
the Housekeepers.Metros must contain adequate linen by type to
accommodate all room types.
- To reduce travel time by Housekeepers to secure clean linen, we
will purchase more linen so that we can always have adequate
supplies on the floors.
46. Improve Criteria Matrix Jon Haid: This was the chosen
solution for the pilot plan 47. Improve - Implementation Plan 48.
Improve Pilot Plan Jon Haid: Pilot plan was to deliver metros to
floors before Housekeepers came in each day. 49. Improve - FMEA Jon
Haid: Loading of metros has an RPN (risk-priority number) of 360,
which means this will be a high priority to focus on. 50. Improve -
Implementation Summary 51. Control Control Charts Data point
1appears outside of the control limits, on this particular day,
there was no laundry attendant available to deliver the metros,
delivery was completed later in the morning by the Supervisor.This
is known as"Special Cause" variation.Because of this "Special
Cause", this chart is "Out of Control". 52. Control Control Charts
The top chart of Individual Travel Times shows the trend over time.
The bottom chart or Moving Ranges shows the difference in
consecutive values over time. Data point 1is causing both charts to
be "Out of Control". 53. Control Control Charts This P-Chart shows
the proportion defective; in this case the number of rooms
requiring travel time as aproportion of the total rooms occupied
for that day. 54. Control Documentation Plan 55. Process Management
Chart 56. Process Management Chart 57. Control - Voice of the
Customer Comments from Housekeepers & Laundry Associates after
implementation. 58. Control - RACI Chart 59. Dashboards
Housekeepers will continue to document any travel time on this
sheet & will turn these sheets in to the Supervisor each day.
Times will be posted on Control Charts and posted in Department and
reviewed at morning line-up meetings . 60. Dashboards Jon
Haid:Projected savings are replaced with Actuals each month. 61.
Control - Dashboards 62. Dashboard - November 2001 Jon Haid: This
Control Chart shows that the process has been in control for over
50 days. 63. Dashboard - Sigma Calculation Jon Haid: Sigma Value
went from 2.8 to 3.6. 64. Control - Lessons Learned 65. Quick Hit
Generated At the start of this project, we made a change in how we
handled all of our Food & Beverage linen.By sending all Food
and Beverage items to an outside vendor, we were able to eliminate
one FTE in the laundry. We estimate potential savings over the
first 18 months to be approximately $27,000, in payroll and
benefits expense. 66. Quick Hit - Potential Savings
