a presentation on service time variation in cafe coffee day
DESCRIPTION
A work on service quality managementTRANSCRIPT
A project on service time variation in Café coffee day
SUSHANT
Structure Service time
Project methodology
Analysis
Observation and recommendation
What do we sell?
Experience
◦Physical product
◦Ambience
◦Service
Quality of service depends on following aspects:
1. Quality of customer and staff interaction
2. Quality of complaint handling
3. Optimum service time
Optimum service timeWhat is it?For this project, we have taken it as the time
interval between taking the order to the service of order at the table.
Is it important?◦ Type of customer ◦ Time of the day◦ Format of the outlet ◦ Time period between the order is taken
and the order is served◦ competition
Research methodologyData collection
Sources of data
Sampling
Sources of data and collectionPrimary The primary data was collected by putting
timing of order received and service timing on the KOTs of the respective order.
Data collection was done for 22 days in the S P Road outlet, Hyderabad.
Secondary For secondary data, I referred to the
websites of Café coffee day, Google, Wikipedia.
Books Statistics for management (Levin & Rubin),Principles of retailing(J Fernie).
Papers : Café coffee day and Barista, a comparative study, ASBM, Bhuvneswar.
Sampling Sampling was done randomly and 50
samples (KOTs) were taken daily.
Extraneous effects were removed by removing or not choosing very large orders and very small order.
All the orders were also noted with the time of delay due to factors other than considered.
Analysis Statistical process control
◦X bar chart ◦R bar chart
Total quality management◦Fishbone diagram ◦Pareto chart
X- bar chart X bar charts are the control charts for
process means. The control limits in X bar charts place bounds on the amount of variability we are willing to tolerate in our sample means. In X bar charts we have
A center line X bar-bar or X grand mean
An upper control limit (UCL) line, with value = grand mean + 3σ
A lower control limit (LCL) line, with value = grand mean - 3σ
R- chartIn R charts, we plot the values of the
sample ranges for each of the samples. The center line for R charts is placed at R bar.
UCL (upper control limit) = R bar (D4) where D4 = 1+3 d3/d2
LCL (lower control limit) = R bar (D3) where D3 = 1 – d3/d2
D4, D3, d2, d3 are constants.
Analysis
X – BAR CHART
1 2 3 4 5 6 7 8 9 101112131415161718192021220
2
4
6
8
10
12
14
6.5
5.28
6.01
11
6.3
12
7.8
10.8
5.34
10.8
(UCL)
(LCL)
Grand mean 7.52
ANALYSISAs we plot the CL, UCL and LCL and the daily
values of the X bar, a quick glance at the chart shows us that on the dates 15/05/10, 18/05/10, 22/05/10 and 30/05/10 the average serving time jumps above the UCL(upper control limit).
To check whether the cause for this variation is assignable or random, close investigation shows that there is some relation between sales on that particular day and the delay in service.
Now we can see clearly that whenever the sale is more than Rs.20,000, it is affecting the service time and the order is served late. Now we will try this same by excluding the outliers or the values above the UCL.
X – BAR CHART (excluding outliers)
1 3 5 7 11 15 17 190123456789
Series 1
Series 1
X- BAR CHART (without outliers)From the above chart, we can
see that once we remove the outliers the service time is well within control limits.
R – BAR CHART
1 2 3 4 5 6 7 8 9 101112131415161718192021220
2
4
6
8
10
12
14Series 1
UCL 12.535
LCL 3.758
R BAR CHART The values of the daily ranges
are in the control limits. This shows that there are not great differences between one day range to another day range, but these range values have to be compared with another competitor to get the advantage of this chart.
FISHBONE DIAGRAM(Total quality management)
The TQM approach to any business starts with the realization that all errors, defects, and problems have causes and there is only finite numbers of these. The fishbone diagram takes an unstructured list of factors that contribute to delayed service and organizes that list in two major ways. First, it gathers the factors into logical groups. And then, within the groups, it indicates how the various factors feed into one another in cause and effect relationship.
FISHBONE DIAGRAMCUSTOMERS inside counter
operationsequipment
low awareness less skilled team members
no time constraints for order prep.
No audit or checking for service time
Less number of team members
Sudden breakdown
Low efficiency
Service area operations team members
Less skilled TM
Less no of TM
Wrong order
no serving time check provision
skills
Recruitment process training
BonusCompensation
Delayed Service
commitment
PARETO CHARTFrom the above fishbone diagram we see
that there are several factors that affect the service time.
In TQM, we distinguish between vital few and trivial many. So that, we can solve the vital problem first, and then the next vital one, it is a continuous process of improvement.
To identify the vital problems, we use Pareto chart. A Pareto chart is a bar graph showing groups of error causes arranged by their frequencies of occurrences.
PARETO CHART
COUNTER
OPERA
TIONS
SERVICE A
REA OPE
RATIONS
EQUIPM
ENTS
CUSTO
MERS
TEAM MEM
BERS
0
10
20
30
40
50
60
70
80
FREQUENCY OF FACTORS
FREQUENCY
PARETO CHARTAs from the Pareto chart, the data
shows that 60% of delay can be attributed to inside the counter preparation, 20% to service area ops and rest are not significant now. Thus in the TQM parlance, as we say slay the dragon first, we can concentrate on the inside counter part of the operation first.
Conclusion & recommendationThrough continuous observation,
it is observed that there are no control measures for service time.
The variation in the serving time is out of control
The variation is assignable and not random.
Conclusion & recommendationIntroduction of service time sheets for
customers: these sheets will be given to every customer at the moment the order is taken. These sheets will show the time that a standard order should take and based on the statistical calculations on an average the standard deviation that may happen; it will also show minimum time and max time an order should take. We can make this format interesting by inserting concepts like before time, well in time, average etc.
Conclusion & recommendationIntroduction of service time record in the
billing system itself: here in coffee day when an order comes to the counter it gets fed into the system, now if we can introduce a automated barking system in the three sections (cold, hot, food) by the means of LED boards to display the orders it will make the recording of service time possible. Once the order is prepared and placed at the counter the button on the board is to be pressed to receive the new order from the system.
Conclusion & recommendationIntroduction of better equipment
those can be helpful at the peak time of business. For example, big ice blenders which can continuously blend ice for some while without melting it, it will decrease the time for making ice blended drinks.
Conclusion & recommendation Reports for evaluation : Having a digital recording
system for service time will provide us with data that can be easily converted into useful reports. These reports when compared with sales report and other reports over a period of time will provide useful insights.
Thank you