1. PROJECT REPORT ON
“Successful implementation and roll out of barcoding technology. “
Submitted by,
Mr. Ravikumar Pawar.
Roll No. 15RM926
Birla Institute of Management Technology, Greater Noida.
Under The Guidance of,
Prof. Mr. Arindam Deb (Faculty Mentor).
Mr. Manish Shrivastav (Corporate Mentor).
(Corporate Strategy head, Safexpress Pvt. Ltd.)
2. 2
INDEX
INDEX ...................................................................................................... 1
CERTIFICATE.............................................................................................. 2
ACKNOWLEDGEM ENT .................................................................................. 3
LETTER OF TRANSMITTAL ........................................................................... 4
EXECUTIVE SUMMARY ................................................................................ 5
…………………………………………..............................................................
1. INTRODUCTION TO THE COMPANY ................................................. 8
2. LITERATURE REVIEW........................................................................ 9
3. PROBLEM DEFINITION ...................................................................... 10
4. APPROACH TO THE PROBLEM......................................................... 13
5. METHODOLOGY USED ...................................................................... 15
5.1 DATA COLLECTION FROM PRIMARY SOURCE …….…………………...15
5.2 SCALING TECHNIQUES .................................................................. 16
5.3 HYPOTHESIS................................................................................... 18
6. DATA ANALYSIS................................................................................. 21
7. RESULTS AND CONCLUSION............................................................ 26
8. LIMITATIONS AND CAVEATS............................................................. 29
9. RECOMMENDATIONS........................................................................ 31
10. REFERENCE..................................................................................... 33
11. APPENDIX......................................................................................... 34
12. GLOSSARYOF ABBREVIATIONS..................................................... 41
3. 3
Summer Project Certificate
This is to certify that Mr. Ravikumar Bhagwan Pawar. Roll No.
15RM926 a student of PGDM-RM has worked on a summer project
titled “Successful implementation and rollout of barcoding technology “
at ‘Safexpress Pvt. Ltd.’ afterTrimester-III in partial fulfilment of the
requirement for the Post Graduate Diplomain Management programme.
This is his original work to the best of my knowledge.
Date: ____________ Signature_________
(Prof. Arindam Deb)
BIMTECH SEAL Name of Faculty Mentor
4. 4
Acknowledgement
“It is not possible to prepare a project report without the assistance & encouragement of
other people. This one is certainly no exception.”
On the very outset of this report, I would like to extend my sincere & heartfelt obligation
towards all the personages who have helped me in this endeavor. Without their active guidance,
help, cooperation & encouragement, I would not have made headway in the project.
I am ineffably indebted to Mr. Manish Shrivastav for conscientious guidance and
encouragement to accomplish this assignment. I am extremely thankful and pay my gratitude
to my faculty Prof. Arindam Deb for his valuable guidance and support on completion of this
project in its presently. I extend my gratitude to Birla Institute of Management Technology
for giving me this opportunity. I also acknowledge with a deep sense of reverence, my gratitude
towards my parents and member of my family, who has always supported me morally as well
as economically.
At last but not least gratitude goes to all of my friends who directly or indirectly helped me to
complete this project report.
Any omission in this brief acknowledgement does not mean lack of gratitude.
Thanking You,
Ravikumar Pawar.
Roll No. 15RM926.
5. 5
Letter of Transmittal
25/06/2016
To
Mr. Arindam Deb
Faculty - Centre for Retail & Marketing
Birla Institute of Management Technology,
Greater Noida 201306.
Subject: Submission of internship report on “Successful implementation and Roll out of
Barcoding technology”.
Dear Sir,
It is an immense pleasure for me to submit you internship report titled “Successful
implementation and Roll out of Barcoding technology”. I was assigned to work at Pune,
Nashik, Aurangabad Hub of Safexpress. I tried my level best to complete this report properly
and to produce a meaningful report within all the constraints. I concentrated on areas that I
believed would be the most relevant to make the report coherent as well as practical as possible.
It was a great pleasure for working on this report to learn some real life lessons and first-hand
knowledge on Logistic and supply chain. I would be glad to furnish you with any clarifications,
if required. I therefore submit it, hoping that you would excuse the minor flaws.
Thank You.
Sincerely Yours,
_____________
Ravikumar Pawar
Roll No. 15RM926
Executive Member of Alumni Conduit,
Birla Institute of Management Technology,
Greater Noida 201306.
6. 6
Executive Summary
Have you ever thought of how does needful things for day to day life become
available in your city/town? All the products, raw material or semi-finished goods
become available from the anywhere to everywhere. But how is the question? Obvious
answer is transportation makes it possible to make the things available at right place
and right time. Providing products to the right customer at right place and right time is
the definition of retail. Various logistic companies perform these operations for
manufacturers. Safexpress is one of the supply chain and logistics companies
providing the logistics services for large number of well-known brands. Now a day’s
supply chain and logistics industry is booming very fast. Though many companies are
growing they lack the technology to improve the quality of services they offer.
Safexpress was facing very common problem of logistics that was ‘Short and excess
material while loading and unloading’. Various clients like Mahindra & Mahindra, John
Dear, Mercedes, SKF, Bajaj automobiles, UCB, etc. provides material for transhipment
to all over India to Safexpress. Safexpress appoint booking associate to pick up and
deliver material from these clients to the nearest hub of Safexpress. When material is
handed over to the B.A. (Booking Associates) they makes entry of the material into
ERP software of Safexpress named PROPEL. At the time of entry, they have to enter
data like no of packets, Actual weight, volumetric weight, source and destination
location. After loading the truck and making entry at client side they bring the truck to
the nearest Hub where material gets unloaded and segregated as per the destination
location. While unloading OA (Operation Assistant) need to generate unloading tally.
Unloading tally contains all the details of material entered by BA at client side. OA
need to count the unloaded material and insure that material count in unloading tally
and actual received material is equivalent. To check the count OA, mark a line for
every box/packet unloaded by labour on the unloading tally. During this process one
labour reads loudly the number i.e. unique id given by Safexpress to that packet and
according to that labours sound OA makes mark on unloading tally. In this process
many times OA found that actual count of packets is not matching with the tally. Hence
sometimes material gets short, but by mistake OA mark it received and after that
Safexpress need to pay claim to the clients for that material. Last year amount of claim
was 22 crores approximately. To reduce the claim and solve the problem of short and
7. 7
excess material Safexpress decided to take help of technology. And to implement and
roll out technology Safexpress hired team of 10 interns to work all over the India. We
used barcoded stickers to each packet and used scanners for check the count as
packet received or load into vehicle. Challenge was to train the employees and set
new standard process of working and replacing the existing processes without error
and without increasing the time period of work. All the labours are illiterate and they
were not ready to accept the change and they didn’t want to accept the technology. In
addition, OAs need to maintain relation with labours so as to get the work done
efficiently and fast. Most of the OAs too were not ready to change their habit and
opposing the technology. We have to train the OAs and insure that OAs will use
scanner to load and unload vehicle even after the internship gets over. To satisfy and
check the productivity before training and after training we maintained unloading and
loading time of all the vehicles before and after the use of technology. There after we
used paired T-test to check the productivity before and after training with use of
scanners and without scanners. As a result, we get to know that the productivity of the
employees and workers including OAs improved after the training and use of
scanners. During my internship I have tested the scanners in three different hubs
Pune, Nashik and Aurangabad in Maharashtra state. And find out other hindrances in
the way of implementation and solved the issues by redefining the processes.
Technology benefited company to track the shipments and check the proper
count. Safexpress used data recorded by scanners for performance evaluation as well.
Technology will solve the problem of claim and create a base for future technology
usage. By applying various algorithms and statistical methods on data captured by
scanners Safexpress will be able to maintain optimum load in hubs. These data will
give real time picture of load at any particular time. This data will help company for
network optimization also. In future, barcoding technology will be used as platform for
new technology and will ease the implementation of future technology.
8. 8
1.0) Introduction to The Company
Safexpress Pvt. Ltd., a leader in Supply Chain Management industry started its
operations in India in 1997 with 9 offices, 12 vehicles and 9 hubs all across the country.
In its constant pursuit to serve the Indian economy effectively, Safexpress has today
given a new face to the Indian Logistics industry. The unparalleled leader in Indian
Supply Chain Management, today, Safexpress delivers to every nook & corner of India
through its Largest Network and Fastest Transit Times. The company provides its
services to a vast range of customers ranging from the Automotive, Engineering,
Electronics, Telecom, IT to Retail, FMCG, Healthcare and Publishing industry.
A known industry veteran and Logistics Guru of India, Mr. Pawan Jain, Chairman
and MD, Safexpress, commands immense respect in the corporate fraternity today.
Armed with an experience of almost three decades, Mr. Jain is known to have
contributed immensely in the growth of logistics industry in India. With a sharp intellect
and deep insight, Mr. Jain realized that two core values of Reliability and Speedy
Delivery were imperative to ensure customer satisfaction in the logistics industry.
Thus, he coined the name Safexpress, which stood for an amalgamation of Safe and
Express Service. Under his able guidance, Safexpress has achieved the Leadership
position in the Logistics Industry. The Logistics Industry is highly fragmented with
many unorganized players having regional presence. Less than 1% is organized.
Apart from the few companies that are listed, not much information is available relating
to the other players. However, it won’t be wrong to say that the large organized players
account for more than half of the industry turnover. Our company’s market share is
27%.
Growing at a phenomenal rate of 35% year on year, Safexpress, today, is a Rs5bn
company. At present, Safexpress have 42 hubs and super-hubs, a fleet of around
3300 weatherproof ISO 9002 certified containerized vehicles serving over 550
destinations and covering 5,00,000 km daily. Safexpress’s warehousing space
exceeds three million square feet. Safexpress cover all the 610 districts of India.
We are coming up with Logistics Parks at 32 locations in India. In Chennai company
have already invested Rs350mn to set up a three lakh-sq-ft. Logistics Park. Company
plan to add a total of seven million square feet of warehouse space within the next
three years.
9. 9
2.0) Literature Review
We have seen barcodes printed on nearly every item in grocery store. They are either
UPC or EAN linear barcodes. There are about 300 other different types of barcodes,
out of which code 39 are the most popular. Also there are 2D barcodes that store a
large amount of information in a smaller space than linear barcodes. There are two
basic advantages of barcode scanning over manual entry, their speed and accuracy.
For the entry of 12 characters of data, keyboard takes 12 secs, while scanning of 12-
character data takes only 3 sec. The error rate for typing is one substitution error for
every 300 characters’ types. Error rate for barcode range from 1 substitution for every
15000 to 36 trillion characters scanned [1]. Collected information about scanners and
types of scanners. Also compared scanners with each other for the ease of use and
efficiency. From the research published in International Journal of computer
Applications by K. N. Subramanya warehouses play a vital role because they function
as nodes that direct the flow of materials within a distribution network. The effects of
organizing warehousing activities can directly be seen in customer service levels, lead
times, and the cost structure of a company. With WMS implementation the cycle time
of the process also decreases. The cycle time reduces and the cost benefit analysis
for WMS implementation in warehouse shows an increased savings per month. The
study proves WMS to be an enabling factor for performance and productivity
improvement. The productivity of a WMS warehouse is way higher than when the
operations are manually performed [2]. In the research paper published in IOSR
Journal of Business and Management by Rajiv Bhandari, Technology” is vehicle to
enhance supply chain competitiveness and performance by enhancing the overall
effectiveness and efficiency of logistics system. Hence choosing the right technology
for various logistics activities or sub-processes is very crucial to any business to gain
competitive advantage in today’s competitive market [3].
Implementation of barcode technology not only helped to reduce the cost but also it
improved the efficiency and productivity of hubs. Barcoding technology in Safexpress
will create base for all future technologies and provides competitive edge over all other
competitors. Barcoding technology will result into the time saving at operations in the
hub. Barcoding will create a way and provides necessary resources to implement
‘WMS’ at warehouses which will take the level of Safexpress to the height of success.
10. 10
3.0) PROBLEM DEFINITION
Journey of Safexpress began over fourteen years ago from a small warehouse on the
outskirts of Delhi. The winds of change driving the Indian economy helped Safexpress
sail steadily, across districts, across cities and across states and today, Safexpress
serve every square inch of our country. Belief of company ‘Custodians first, Carriers
later’ helped build and carry lasting relationships. Company’s investments in creating
a world class warehousing infrastructure, enabling operations using information
technology, and setting up a continuous learning environment has catalysed growth;
and Safexpress believe that these along with innovation, agility and adaptability, will
help scale greater heights in the coming years. Yes, it was a challenge carving out a
niche in the nascent Indian Logistics & Supply Chain sector, and Safexpress were
happy to bring in processes that are an industry benchmark.
During this journey Safexpress found that due to some flaws in processes company
were facing the problem of excess and short material received by consignee. And in
case of short material delivered Safexpress need to give claim against the short
material. This short and excess happens at the time of loading and unloading vehicles
during booking, transhipment and delivery operations. Various big brand companies
are working with Safexpress as client and trust on safexpress for speedy delivery of
material and safety of material. Bringing new clients and pickup of material is done by
Booking Associates(BA) and Green Truck Associates(GTA). Below figure explains the
booking process in detail. As GTA or BA receives the consignment they check for
transit-worthiness of consignment and assign waybill number to each consignment.
Then calculate the chargeable weight and they segregate the material according to
the destination locations (Gateway Destinations) and create waybill. Last step is to
handover consigner copy to customer and dispatch material to hub before dispatching
material Booking Associate need to enter waybill data into online ERP system called
as propel. When vehicle reaches at hub first process is to create vehicle arrival report.
After vehicle reporting unloading tally of that vehicle is generated by selecting the
vehicle number from the list of arrived vehicles. Unloading tally contains the detail
information of all the waybills and number of packets in each waybill. Unloading tally
then handed over to the any of the Operating Assistant(OA) who gets free at that
moment. OA keeps record of the actual material unloaded and number of packets
mentioned in the unloading tally.
11. 11
Fig. (1). Booking process
OA marks a line for each packet unloaded by the workers/labours. Workers are divided
into group of 5 to 6 labours in each group, these groups are called as toil and each toil
has a one toil master. When unloading starts, toil master stands beside the OA and
remaining 4 workers bring the packets out of the vehicle. Each packet has sticker
pasted on it when worker brings box out of the vehicle toil master read and shout
waybill number with lot size i.e. number of packets in that waybill. For example, for
waybill number 4723461 with 10 packets in that waybill, toil master will shout “chautis
iksath das ka lot Nagpure...”. then OA listens the sound and finds the waybill in the
unloading tally and mark a line in front of that waybill. This way all the truck gets
unloaded but, due to the many sounds generated in material handling works as noise
in listening the exact waybill number. Other problem is that at a same time there are
several vehicles gets unloaded and many toil masers shouts their waybill number
hence it become difficult for OA to listen the exact number and mark accordingly. Due
to these hindrances in clearly listening OA does not trust on his judgement and even
if he found that there are some packets missing in vehicle than the mentioned in
unloading tally, he will mark all the packets received. And in case of excess material
12. 12
received at hub, it becomes a choice of the hub staff whether to show that material on
the record or not. There is no current system by which one can surely say that there
is excess packet/s received by the hub. The same problem occurred during loading
the vehicle. One more problem is that many of times labour only reads the last 4 digits
and lot size and hence cause miss routing of packets whose waybills last 4 digits are
same. Due to miss routing and short-excess problem Safexpress won’t be able to
deliver the material to the customer in the desired time and quantity. Hence customers
ask for the claim against the material not received or received after the required time.
This problem of paying claim amount become a largest problem for the company as
last year’s claim amount reached near about 22 crores.
Fig. (2) Unloading Tally
13. 13
4.0) Approach to The Problem
To solve these problem and handling the issue of the short and excess, company
decided to take help of technological advancements. Then strategy department of
company decided to implement the barcoding technology to reduce or avoid short
excess of material. As company is planning to implement technology which will be cost
effective and can be used as base for future technology implementations. Strategy
team designed a new set of standard processes to be followed while loading and
unloading with barcoding scanners. Safexpress come up with barcoding stickers and
barcode scanners to scan and unload the vehicle. Use of scanners definitely will not
allow any kind of confusion in counting that for sure. Scanner also used to update the
unloaded and loaded data to the ERP system Propel at that same time from the
scanners itself. Safexpress used Chainway scanners with android operating system
and 4.5-inch screen size plus laser based barcode scanner integrated into device.
Safexpress developed an android application which will load and update tally to and
from propel by using internet connection. Company planned to start barcode scanning
in 30 hubs initially with the help of 10 interns. Each intern was allocated 3 different
hubs. During the internship Objectives was to
1) Find out the flaws in the new processes
2) Find out the technological barriers
3) Find out psychological barriers.
4) Train the employees including staff members and OAs with labors to follow new set
of standards.
5)Train OAs to use scanners effectively and at ease for loading and unloading
purposes.
Initially whole project is divided into 4 major areas which are
1- Booking Vehicles and Route Vehicles Unloading through scanners
2- Loading of transshipment/route vehicles
3- Delivery unloading
4- Delivery loading.
14. 14
I have worked into first phase and successfully implemented barcode scanning
into 3 hubs assigned to me PUNE, NASHIK, and AURANGABAD hub. In these hubs
80% booking vehicles get unloaded using scanners and same material is loaded into
route vehicles by using scanners only. To know the performance difference before and
after use of scanners and training we used paired sample T test. During the roll-out
technology we collected the data like number of waybills in the tally, number of
boxes/packets in the truck, and time taken to load and unload the vehicle. Hence using
this method, we proved that performance after training is improved.
15. 15
5.0) Methodology Used
5.1) Research Design
To test the productivity and check out the difference between performance
before training and after training we used Paired Sample T test. Paired sample t-test
is a statistical technique that is used to compare two population means in the case of
two samples that are correlated. Paired sample t-test is used in ‘before-after’ studies,
or when the samples are the matched pairs, or when it is a case-control study. For
example, if we give training to a company employee and we want to know whether or
not the training had any impact on the efficiency of the employee, we could use the
paired sample test. We collect data from the employee on a seven scale rating, before
the training and after the training. By using the paired sample t-test, we can statistically
conclude whether or not training has improved the efficiency of the employee.
Steps Followed:
1. Set up hypothesis:
We set up two hypotheses. The first is the null hypothesis, which assumes that the
mean of two paired samples are equal. The second hypothesis will be an alternative
hypothesis, which assumes that the means of two paired samples are not equal. That
means null hypothesis will be there is no difference in performance before and after
training.
2. Select the level of significance:
After making the hypothesis, we choose the level of significance. In most of the cases,
significance level is 5%.
3. Calculate the parameter:
To calculate the parameter, we will use the following formula:
16. 16
Where d bar is the mean difference between two samples, s² is the sample variance,
n is the sample size and t is a paired sample t-test with n-1 degrees of freedom.
An alternate formula for paired sample t-test is:
4. Testing of hypothesis or decision making:
After calculating the parameter, we will compare the calculated value with the table
value. If the calculated value is greater than the table value, then we will reject the
null hypothesis for the paired sample t-test. If the calculated value is less than the
table value, then we will accept the null hypothesis and say that there is no significant
mean difference between the two paired samples.
5. Assumptions:
1. Only the matched pairs can be used to perform the test.
2. Normal distributions are assumed.
3. The variance of two samples is equal.
4. Cases must be independent of each other.
5.2) Data Collection from Primary Source
Collected data from the 3 different hubs of time taken to unload the vehicles with
scanners and without scanners. In the very first week of internship we observed the
actual processes being followed at the respective hubs and noted down the flaws as
well as we keep record of time taken to unload the vehicle without scanners. While
recording the time we also kept record of Number of waybills in the tally, tally number,
total number of packets in the vehicle and who unloaded that vehicle.
For my performance evaluation method, I used these three parameters and based on
this parameter I have given weightage to each vehicle observed and then applied
17. 17
paired t test to find out the results. Below table shows the recorded data at the time of
unloading.
Example of Unloading Details recorded for Pune Hub: - (Without Scanners)
Table 5.2.1- Data collection example for unloading without scanner
Example of Unloading details recorded for Pune Hub: - (With Scanners)
HUB
BOOKING
BRANCH
UNLOADING
TALLY NO.
ARRIVAL
DATE
ARRIVAL
TIME
SCAN
TIME
NO. OF
WAYBILLS
NO. OF
BOXES
Pune Pune 26 7980932 04 May 2016 7:06 30 9 65
Pune Pune 26 7980436 04 May 2016 1:31 85 34 264
Pune Pune 26 7982239 04 May 2016 15:47 35 4 22
Pune Pune 26 7981412 04 May 2016 11:17 95 42 277
Pune Pune 26 7985222 04 May 2016 22:28 140 54 370
Pune Pune 26 7985201 04 May 2016 22:25 90 33 200
Pune Pune 26 7983793 04 May 2016 19:31 150 118 403
Pune Pune 26 7987405 05 May 2016 14:17 20 7 12
Pune Pune 26 7986775 05 May 2016 10:27 25 6 45
Pune Pune 26 7986764 05 May 2016 10:23 10 8 18
Pune Pune 26 7987029 05 May 2016 12:02 180 80 572
Table 5.2.2 Data collection example for unloading with scanner.
5.3) Scaling Techniques
HUB
BOOKING
BRANCH
UNLOADING TALLY NO.
ARRIVAL
DATE
UNLOADING
TIME
WITHOUT
SCANNING
NO. OF
WAYBILLS
NO. OF
BOXES
Pune chakan 22 7917069 20 April 2016 40 24 82
Pune Pune 26 7914590 20 April 2016 120 101 314
Pune Pune 26 7914834 20 April 2016 51 1 326
Pune Pune 26 7913782 20 April 2016 35 7 25
Pune Pune 26 7915763 20 April 2016 35 8 87
Pune Pune 26 7915443 20 April 2016 140 54 328
18. 18
Collected data mainly indicating three parameters first Unloading Time in minutes,
Second Number of waybills in the Unloading tally and third is Total number of
packets/boxes in the vehicle. To evaluate the performance data is converted into
valuable scores for each vehicle record. In the scoring process we assigned the
weightage to the three parameters which affect the performance of OA while unloading
the vehicle.
Weightage to ‘Unloading Time’:
Unloading time is different for each vehicle and depends on various factors but
assuming all other factors constant we can give the importance to the unloading time
to evaluate performance. Weightage assigned explains the importance of that
particular parameter into the performance.
Weightage to ‘Number of Waybills’:
As you can see in the fig. (2) inside “problem definition” section, print of unloading tally
consist all the waybills listed. Toli master shouts the waybill and then OA mark the
unloaded packet as received into physical tally, but before marking he need to find out
that particular waybill from the list of waybills. This processes of finding the waybill and
ticking the material as received becomes tedious when tally contains maximum
waybills. Generally, more than one page contains approximately 25 waybills. More
than 25 waybills cover 2 pages in the tally so, for OA it becomes difficult to change the
page and search for the waybill number he listened. Due to this process OAs
performance gets affected. To calculate exact weightage, we assigned weightage as
per following chart.
Number
of
Waybills
1 to
10
11 to
20
21 to
30
31 to
40
41 to
50
51 to
60
61
to
70
71 to
80
81 to
90
90<
Weightage
Assigned
1 2 3 4 5 6 7 8 9 10
Table.5.3.1) Weightage scale for “Number of Waybills”.
Weightage to ‘Total Number of Packets’:
19. 19
As the size and actual weight of each packet is different and cause delay into the
unloading process. Hence considering the number of times OA need to mark the line
depends on the total number of packets available in the tally. Hence we multiplied the
number of packets with weightage assigned for waybills and the time taken for unload
the vehicle, to count score for performance evaluation.
For example, consider 1st vehicle from table 5.2.1.
Tentative Score = Number of packets * Weightage assigned * Unloading time
= 82 * 2 * 42
= 6888
After calculating tentative score, we converted this score into 2-digit final score value
by dividing tentative score by 100.
So, Final Score = 6888/100
Final Score=68.88
By following the same logic, we calculated the score for all the collected sample data
and applied the paired t test to check the hypothesis.
5.4) Hypothesis
20. 20
The hypotheses can be expressed in two different ways that express the same idea
and are mathematically equivalent:
H0: µ1 = µ2 ("the paired population means are equal")
H1: µ1 ≠ µ2 ("the paired population means are not equal")
OR
H0: µ1 - µ2 = 0 ("the difference between the paired population means is equal to 0")
H1: µ1 - µ2 ≠ 0 ("the difference between the paired population means is not 0")
Where,
µ1 is the population mean of variable 1, and
µ2 is the population mean of variable 2.
According to above logic our hypothesis becomes:
H0: µ1 = µ2 ("Performance before and after training is equal")
H1: µ1 ≠ µ2 ("Performance before and after training is not equal")
OR
H0: µ1 - µ2 = 0 ("the difference in the performance before and after training is 0")
H1: µ1 - µ2 ≠ 0 ("the difference in the performance before and after training is not 0")
And if null hypothesis gets rejected then it will explain that performance is either
decreased or increased. For testing the hypothesis using paired t test we used SPSS
tools to get exact result with reliable graphs and tables that that can be analyzed later
to conclude the results.
6.0) Data Analysis
21. 21
First of all, we selected sample of 34 vehicles from the population of 160 vehicle
records. Vehicles having same number of boxes are compared with scanner and
without scanner unloading. Initially we recorded 50 vehicles without barcoding and
scanner training. After second week we have recorded data for 160 vehicles with
scanner training. Then for the paired sample T-test, vehicles unloaded with scanner
and having same number of packets are compared with vehicles unloaded without
scanner.
Following table shows the Sample data on which paired t test is applied.
Sl. HUB BOOKING
BRANCH
UNLOADING
TALLY NO.
ARRIVAL
DATE
SCAN
TIME
NO. OF
WAYBILLS
NO. OF
BOXES
Weightage Score
1 Pune chakan 22 7917069 20 April 2016 40 24 82 3 6.15
2 Pune Pune 26 7914590 20 April 2016 120 101 314 10 26.16667
3 Pune Pune 26 7914834 20 April 2016 51 1 326 1 6.392157
4 Pune Pune 26 7913782 20 April 2016 35 7 25 1 0.714286
5 Pune Pune 26 7915763 20 April 2016 35 8 87 1 2.485714
6 Pune Pune 26 7915443 20 April 2016 140 54 328 6 14.05714
7 Pune Pune 26 7913855 20 April 2016 100 32 386 4 15.44
8 Pune chakan 12 7914069 20 April 2016 45 6 322 1 7.155556
9 Pune chakan 13 7917176 20 April 2016 140 18 341 2 4.871429
10 Pune chakan 22 7912289 20 April 2016 25 5 24 1 0.96
11 Pune chakan 22 7916436 20 April 2016 16 3 10 1 0.625
12 Pune Pune 26 7921825 21 April 2016 40 39 150 4 15
13 Pune Pune 26 7921061 21 April 2016 95 74 217 8 18.27368
14 Pune Pune 26 7919172 21 April 2016 90 8 184 1 2.044444
15 Pune chakan 13 7922358 21 April 2016 60 7 416 1 6.933333
16 Pune chakan 16 7917344 21 April 2016 32 9 246 1 7.6875
17 Pune chakan 22 7920712 21 April 2016 5 2 12 1 2.4
18 Pune chakan 22 7922417 21 April 2016 30 9 22 1 0.733333
19 Pune Pune 26 7924104 22 April 2016 30 8 60 1 2
20 Pune Pune 26 7924288 22 April 2016 100 19 144 2 2.88
21 Pune Pune 26 7924823 22 April 2016 25 3 4 1 0.16
22 Pune Pune 26 7924840 22 April 2016 25 4 8 1 0.32
23 Pune Pune 26 7927028 22 April 2016 40 13 29 2 1.45
24 Pune Pune 26 7924709 22 April 2016 160 43 485 5 15.15625
25 Pune Pune 26 7926134 22 April 2016 20 10 22 1 1.1
26 Pune chakan 13 7927482 22 April 2016 110 9 349 1 3.172727
27 Pune chakan 22 7926566 22 April 2016 40 5 29 1 0.725
28 Pune chakan 13 7932427 23 April 2016 160 38 380 4 9.5
29 Pune chakan 22 7927794 23 April 2016 50 11 125 2 5
30 Pune chakan 22 7932510 23 April 2016 51 14 116 2 4.54902
22. 22
Data After Barcode Implementation:
31 Pune chakan 12 7929693 23 April 2016 50 4 224 1 4.48
32 Pune chakan 22 7927549 22 April 2016 120 28 349 3 8.725
33 Pune chakan 22 7922603 22 April 2016 55 31 232 4 16.87273
34 Pune chakan 13 7927456 22 April 2016 100 38 572 4 22.88
Sl. HUB
BOOKING
BRANCH
UNLOADING
TALLY NO.
ARRIVAL
DATE
SCAN
TIME
NO. OF
WAYBILLS
NO. OF
BOXES
Weightage Score
1 Pune Pune 26 8002984 08 May 2016 110 26 81 3 26.73
2 Pune Pune 26 8012783 10 May 2016 90 94 317 10 285.3
3 Pune Pune 26 7995815 08 May 2016 100 35 331 4 132.4
4 ARD ARD-101 8199888 16 June 2016 5 3 25 1 0.125
5 Pune Pune 26 8030068 13 May 2016 45 2 93 1 4.185
6 Pune Pune 26 7986963 05 May 2016 85 29 321 3 81.855
7 Pune Pune 26 8028644 13 May 2016 125 54 387 6 290.25
8 Pune Pune 26 7986961 05 May 2016 50 1 268 1 13.4
9 Pune Pune 26 8005524 09 May 2016 75 22 302 3 67.95
10 ARD ARD-13 8200824 16 June 2016 120 14 761 2 182.64
11 Pune Pune 26 8022730 12 May 2016 100 26 351 3 105.3
12 Pune Pune 26 8001068 07 May 2016 40 9 127 2 10.16
13 ARD ARD-18 8206465 17 June 2016 5 1 25 1 0.125
14 Pune Pune 26 8011669 10 May 2016 10 4 10 1 0.1
15 Pune Pune 26 8035356 14 May 2016 45 39 151 4 27.18
16 Pune Pune 26 8030909 13 May 2016 75 63 221 7 116.025
17 Pune Pune 26 8009917 10 May 2016 60 2 181 1 10.86
18 Pune Pune 26 7952411 28 April 2016 55 19 243 2 26.73
19 ARD ARD-13 8195629 15 June 2016 60 10 405 1 24.3
20 ARD ARD-15 8196835 15 June 2016 20 13 241 2 9.64
21 Pune Pune 26 7987405 05 May 2016 20 7 12 1 0.24
22 Pune Pune 26 7982239 04 May 2016 35 4 22 1 0.77
23 Pune Pune 26 8019862 11 May 2016 30 19 60 2 3.6
24 Pune Pune 26 8010661 10 May 2016 45 6 120 1 5.4
25 Pune Pune 26 8036296 14 May 2016 60 47 144 5 43.2
26 ARD ARD-14 8206472 17 June 2016 2 1 4 1 0.008
27 Pune Pune 26 8015458 11 May 2016 30 4 8 1 0.24
28 Pune Pune 26 8037541 15 May 2016 20 4 29 1 0.58
29 Pune Pune 26 7999893 07 May 2016 80 84 526 9 378.72
30 Pune Pune 26 8030644 13 May 2016 15 4 20 1 0.3
31 Pune Pune 26 7985222 04 May 2016 140 54 370 6 310.8
32 Pune Pune 26 7986775 05 May 2016 25 6 45 1 1.125
33 Pune Pune 26 7978372 03 May 2016 20 14 31 2 1.24
34 ARD ARD-101 8206469 17 June 2016 12 1 120 1 1.44
35 Pune Pune 26 8029949 13 May 2016 55 44 130 5 35.75
36 Pune Pune 26 8028644 13 May 2016 125 54 387 6 290.25
23. 23
In the above table calculated the score for each vehicle using the formula mentioned
in the section (5.3). After calculating the Scores before and after the training these
score values are given to the SPSS16.0 as an input and performed paired T-test to
check the hypothesis.
Output of SPSS:
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 Before Training 6.9724 34 6.96825 1.19504
After Training 11.6937 34 11.99082 2.05641
Table 6.1) Paired sample statics
From the above table we can say that there is difference between the mean value of
two samples. Standard deviation of sample collected before training is 6.96825 and
the standard deviation of sample collected after training is 11.99082.
Paired Samples Correlations
N Correlation Sig.
Pair 1 Before Training & After
Training
34 .733 .000
Table 6.2) Paired sample correlation
Table 6.3) Paired Sample T-Test
37 ARD ARD-12 8207128 17 June 2016 60 23 218 3 39.24
38 Pune Pune 26 8034276 14 May 2016 120 45 362 5 217.2
39 Pune Pune 26 7989793 05 May 2016 85 57 238 6 121.38
40 Pune Pune 26 7987029 05 May 2016 180 80 572 9 926.64
Paired Samples Test
Paired Differences
t df
Sig. (2-
tailed)Mean
Std.
Deviatio
n
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
Before Training -
After Training
-
4.72129
8.35407 1.43271 -7.63616 -1.80642 -3.295 33
.002
24. 24
Paired Samples Test Box
This is the above box you will look at. It contains info about the paired samples t-test
that is conducted. We are most interested in the value that is in the final column of this
table. Take a look at the Sig. (2-tailed) value.
Sig (2-Tailed) value
This value will tell if the two condition Means are statistically different. Often times, this
value will be referred to as the p value. In this example, the Sig (2-Tailed) value is
0.002
If the Sig (2-Tailed) value is greater than 0.05
We can conclude that there is no statistically significant difference between two
conditions. We can conclude that the differences between condition Means are likely
due to chance and not likely due to the manipulation.
If the Sig (2-Tailed) value is less than or equal to 0.05 We can conclude that there is
a statistically significant difference between two conditions. We can conclude that the
differences between condition Means are not likely due to change and are probably
due to the manipulation.
Our Example
The Sig. (2-Tailed) value in our example is 0.002. This value is less than .05. Because
of this, we can conclude that there is a statistically significant difference between the
mean score of vehicles unloaded after scanner and before scanner. Hence we reject
the null hypothesis and accepts alternative hypothesis.
Since our Paired Samples Statistics box revealed that the Mean number of scores for
after training is greater than the Mean for the before training condition, we can
conclude that there is slightly increase in the productivity and efficiency of the OAs
25. 25
due to use of the technology. And this increase is not due to the chance. Company
started to use barcode stickers as shown in the below fig.
7.0) Results and Conclusion
From the statistical tools applied we get to know that technology helping
company to improve the efficiency and increase the productivity. Also technology will
help company to reduce the short and excess problem as once material scanned OA
will be sure that material is received or loaded into vehicles for sure. Technology of
barcoding created a base for the Safexpress to start new technology projects and
take company to the height of success.
26. 26
Fig. Barcode Sticker
This barcode contains the waybill no of 8 digits and last four digits are box number
from that particular lot. For example, in above figure you can see that waybill number
is 47258767 and the box number is 17 from the lot of 21 hence barcode id will become
“472587670017”. This barcode is then scanned using the Chainway scanners which
has propel application integrated within it. As we tested the hypothesis to check out
whether there is difference occurred due to scanners or not and we found that
performance in the three hubs increased due to the technology implementation.
As you can see into below graph, it clearly shows that in manual process when number
of boxes are less time required to unload the vehicle is near about same as of scanner.
When number of packets increases the time required for the manual process becomes
maximum and by scanner it become possible to scan the vehicle in a less time as it
did not need to stop labor to read the waybill number every time. This way by using
the scanner and barcoding stickers safexpress has built its own technological launch
pad and is ready to take off.
27. 27
Fig.7.1) Comparative chart of time required for unloading.
Below figure explains about the score comparison of unloading vehicles before and
after use of scanners. Fig 7.2) shows the score of unloading vehicles before scanner
implementation and fig 7.3) shows Score values of vehicles after Scanning.
Fig. 7.3) Scoring data Before Barcode implementation.
0
20
40
60
80
100
120
140
160
180
200
0 100 200 300 400 500 600 700 800
Chart Title
With Scanner
0 200 400 600 800 1000
1
4
7
10
13
16
19
22
25
28
31
34
37
40
28. 28
Fig.7.3) Score data After Barcode implementation.
For assigning scores we considered box size and weight equal and compared vehicles
having nearly same number of boxes. Emphasis of scoring was on the number of
waybills and time taken to unload the vehicle. After analyzing all the figures and tables
we clearly state that barcoding improved the efficiency and performance for loading
and unloading the vehicles.
0 100 200 300 400 500 600 700 800
1
4
7
10
13
16
19
22
25
28
31
34
37
40
29. 29
8.0) Limitations and Caveats
Lack of skilled Man power:
Near about 80% booking associates are illiterate or less educated, hence they are not
able to make data entry and print the stickers as per the company guidelines. BAs
creating additional problems and due to which work load increases in case of using
barcode scanners. As scanners can be used only when Booking Associate followed
each and every step as per company guidelines. For example, creating multiple
manifests unnecessarily for a single vehicle. They are not able to handle Barcode
printers so as to print stickers effectively. Booking associates creating mistakes during
printing like if there is a lot of 130 stickers and he printed stickers up to 100 and due
to some issue printer stops (issues like paper-out situation) then they will print stickers
from 1 to 30 again which will create 30 duplicate packets. All the booking associates
have been told and explained how to use printer for sticker printing and about standard
processes to be followed. Booking associates appointed labors such as drivers who
are illiterate and taking time to learn process.
Psychological barriers:
When project was started all the labors and OAs start to spread the word like this
technology will not work a long and it is going to fail. In some hubs labor opposed to
work if OA using scanner. As toil masters job is taken by the scanner toil master is not
needed anymore for company hence those toil masters used to spread negative word
of mouth in the labors. Toli masters spread the word that due to scanner it will take
hours to unload a vehicle. Some Experienced OAs were not ready to accept this
change they feel like using scanner is difficult and they were not confident about the
accuracy and use of scanner. Fear of technology like ‘what if something went wrong?’
kept OAs away from the learning to use the scanner. Hough some OAs taken interest
and learnt firsthand to use scanner.
Process Barriers:
In some situations, scanner does increases the work just because of following
standard processes and the same job can be done in minutes if done manually.
Suppose if a vehicle comes from booking location and contains the material for three
different hub locations or material which is departing through three route vehicles. In
30. 30
this case previously OA ask to park booking vehicle near to all three route vehicles
and as material comes out of the booking vehicle he counts for the unloading and ask
labor to put into respective route vehicle in this process he counts the material only
once and come to know that how many boxes sent to all route vehicle.
Same situation with scanner becomes tedious and requires more man power as you
will need three OAs to load three route vehicle and one OA to unload the booking
vehicle. Apart from that if any OA decided to handle the all scanners by him only it’s
not possible to keep changing the scanners so rapidly and cause delay.
Technological Barriers:
Scanners are connected to the Wi-Fi internet present in the hub but in some hubs
there is no internet connectivity such as broadband. They are using data cards
provided by Safexpress and for such hubs scanners with GSM SIM card used to
connect with propel. This connectivity speed depends upon the network coverage and
becomes hindrance in uploading the data while loading unloading.
31. 31
9.0) Recommendations
Company is doing very well and project also implemented successfully and hit the
expectations. Though there are some flaws in the current processes and need to
remove many of the flaws are technical flaws and need to correct immediately.
1. Scanner Must show the missing packets number.
It becomes very difficult if any sticker gets damaged or removed of the
box which is from a lot of 100,200 or any large figure. Then only option is to
show box as short and excess the material later.
2. Printing of any damaged sticker in hub should require authentication.
As currently if any box come with damaged sticker OA prints
duplicate sticker and paste it on box and scan the box but it can be miss used
as if only scanning the sticker without physical material present in the hub.
3. Need to solve the Palate issues:
In the below figure we can see that it is not possible to scan the
boxes which are kept at middle. In this case Safexpress need to communicate
with client company and find out the solution to the palate issue.
4. Company should provide fast internet connectivity to the Booking
associates.
5. Company should stop providing manual stickers as early as possible.
As on one side Safexpress is implementing barcode scanner
technology and on other hand Safexpres provides manual stickers till now
which will result into mixed stickers into vehicle and hence vehicle cannot
unload through scanner.
6. To implement barcode technology HUBs must know that record of how
many vehicles unloaded through scanner is maintained at corporate
office.
32. 32
7. Technical support should be active to solve the technical issues.
Many employees are not technology savvy and therefore they fear to
use the technology and if anything went wrong they don’t try to solve the
problem instead they will the IT team in that case if IT does not respond or treat
on urgent basis that employee will not use the technology for future usage and
will find out the alternate solution to do the same work. So, IT team should be
active enough to handle all the queries.
33. 33
10.0) Reference
1. “Impact of Warehouse Management System in a Supply Chain” by Ramaa.A R
V C E Dept. of Industrial Engg and Management, RVCE, B’lore.,
K.N.Subramanya R V C E Dept. of Industrial Engg and Management, RVCE,
B’lore, T.M.Rangaswamy R V C E Dept. of Industrial Engg and Management,
RVCE, B’lore. Published in International Journal of Computer Applications
(0975 – 8887) Volume 54– No.1, September 2012
.
2. “Impact of Technology on Logistics and Supply Chain Management” by Rajiv
Bhandari published in IOSR Journal of Business and Management(IOSR-JBM)
e-ISSN: 2278-487X, p-ISSN: 2319-7668 PP 19-24.
1. “Improving Business Logistics using Barcode Scanners” by Niharika Garg,
Department of Computer Science, ITM University, Gurgaon, Haryana122001,
India published in International Journal of Computer Applications(0975 – 8887)
Volume 50 – No.15, July 2012.
34. 34
11.0) Appendix
Data collected at Pune HUB 1st Week:
HUB
BOOKING
BRANCH
UNLOADIN
G TALLY
NO.
ARRIVAL
DATE
ARRIV
AL
TIME
UNLOADIN
G TIME
WITHOUT
SCANNING
NO. OF
WAYBILL
S
NO.
OF
BOXE
S
Pune chakan 22 7917069 20 April 2016 23:15 40 min 24 82
Pune Pune 26 7914590 20 April 2016 17:43 2 hr 101 314
Pune Pune 26 7914834 20 April 2016 18:15 51 min 1 326
Pune Pune 26 7913782 20 April 2016 14:59 35 min 7 25
Pune Pune 26 7915763 20 April 2016 19:57 35 min 8 87
Pune Pune 26 7915443 20 April 2016 19:18 2 hr 20 min 54 328
Pune Pune 26 7913855 20 April 2016 15:18 1 hr 40 min 32 386
Pune Pune 26 7914826 20 April 2016 18:15 1 hr 5 min 44 270
Pune chakan 12 7916744 20 April 2016 22:16 2 hr 55 min 45 2234
Pune chakan 12 7914069 20 April 2016 16:08 45 min 6 322
Pune chakan 13 7916706 20 April 2016 22:09 2 hr 55 min 59 706
Pune chakan 13 7917176 20 April 2016 23:43 2 hr 20 min 18 341
Pune chakan 16 7912402 20 April 2016 3:14 30 min 59 128
Pune chakan 22 7912289 20 April 2016 2:08 25 min 5 24
Pune chakan 22 7916436 20 April 2016 21:20 16 min 3 10
Pune Pune 26 7921825 21 April 2016 21:40 40 min 39 150
Pune Pune 26 7921061 21 April 2016 19:57 1 hr 35 min 74 217
Pune Pune 26 7919172 21 April 2016 15:00 1 hr 26 min 8 184
Pune chakan 12 7919471 21 April 2016 16:22 40 min 4 643
Pune chakan 13 7922290 21 April 2016 22:57 1 hr 4 min 44 246
Pune chakan 13 7922358 21 April 2016 23:04 1 hr 7 416
Pune chakan 16 7917344 21 April 2016 0:18 32 min 9 246
Pune chakan 22 7920712 21 April 2016 19:16 5 min 2 12
Pune chakan 22 7922417 21 April 2016 23:18 27 min 9 22
Pune Pune 26 7924104 22 April 2016 13:26 30 min 8 60
Pune Pune 26 7924705 22 April 2016 16:27 50 min 40 120
Pune Pune 26 7924288 22 April 2016 14:45 1 hr 35 min 19 144
Pune Pune 26 7924823 22 April 2016 16:55 25 min 3 4
Pune Pune 26 7924840 22 April 2016 16:58 25 min 4 8
Pune Pune 26 7927028 22 April 2016 21:53 37 min 13 29
Pune Pune 26 7924709 22 April 2016 16:27 2 hr 40 min 43 485
Pune Pune 26 7926134 22 April 2016 19:38 20 min 10 22
Pune chakan 12 7926769 22 April 2016 21:05 1 hr 40 min 37 725
Pune chakan 12 7924403 22 April 2016 15:23 45 min 4 570
Pune chakan 13 7927456 22 April 2016 23:23 1 hr 39 min 38 572
Pune chakan 13 7927482 22 April 2016 23:28 1 hr 48 min 9 349
Pune chakan 16 7927352 22 April 2016 23:01 5 min 4 44
35. 35
Pune chakan 22 7926566 22 April 2016 20:30 37 min 5 29
Pune chakan 22 7927549 22 April 2016 23:41 2 hr 28 349
Pune chakan 22 7922603 22 April 2016 0:14 55 min 30 232
Pune chakan 12 7929693 23 April 2016 16:01 50 min 4 224
Pune chakan 12 7932381 23 April 2016 22:42 1 hr 7 min 65 1106
Pune chakan 13 7932635 23 April 2016 23:32 2 hr 50 min 7 803
Pune chakan 13 7932427 23 April 2016 22:54 2 hr 40 min 38 380
Pune chakan 22 7927794 23 April 2016 0:56 50 min 11 125
Pune chakan 22 7932510 23 April 2016 23:11 51 min 14 116
Data collected at Pune HUB 2nd Week:
HUB
BOOKING
BRANCH
UNLOADING
TALLY NO.
ARRIVAL
DATE
ARRIVAL
TIME
UNLOADING
TIME
WITHOUT
SCANNING
SCAN
TIME
NO. OF
WAYBILLS
NO. OF
BOXES
Pune Pune 26 7949793 27 April 2016 20:52 1 hr - 23 220
Pune Pune 26 7950742 27 April 2016 23:17 1 hr 42 min - 90 282
Pune Pune 26 7947026 27 April 2016 12:50 15 min - 5 11
Pune Pune 26 7947421 27 April 2016 15:17 22 min - 13 20
Pune Pune 26 7955379 28 April 2016 21:04 20 min - 6 9
Pune Pune 26 7954339 28 April 2016 19:05 33 min - 2 122
Pune Pune 26 7954342 28 April 2016 19:05 2 hr - 104 429
Pune Pune 26 7952607 28 April 2016 14:02 20 min - 6 10
Pune Pune 26 7952411 28 April 2016 12:41 - 55 min 19 243
Pune Pune 26 7952408 28 April 2016 12:40 20 min - 9 40
Pune Pune 26 7961438 29 April 2016 22:54 1 hr 30 min - 28 267
Pune Pune 26 7956379 29 April 2016 23:51 30 min - 13 54
Pune Pune 26 7957692 29 April 2016 12:00 25 min - 17 50
Pune Pune 26 7958299 29 April 2016 15:21 45 min - 29 209
Pune Pune 26 7960272 29 April 2016 20:00 45 min - 6 100
Pune Pune 26 7957693 29 April 2016 12:01 1 hr 10 min - 28 350
Pune Pune 26 7958578 29 April 2016 16:28 1 hr 30 min - 2 378
Pune Pune 26 7958441 29 April 2016 15:57 1 hr 40 min - 9 282
Pune Pune 26 7965979 30 April 2016 20:35 52 min - 1 87
Pune Pune 26 7965588 30 April 2016 19:47 1 hr 5 min - 39 130
Pune Pune 26 7965156 30 April 2016 19:02 1 hr 43 min - 21 282
Pune Pune 26 7965231 30 April 2016 19:09 50 min - 22 116
Pune Pune 26 7966915 30 April 2016 23:09 28 min - 10 15
Pune Pune 26 7963597 30 April 2016 14:43 40 min - 7 15
Pune Pune 26 7963166 30 April 2016 12:06 - 1 hr 39 259
Pune Pune 26 7972291 02 May 2016 18:38 1 hr 40 min - 41 356
Pune Pune 26 7971510 02 May 2016 16:40 1 hr 20 min - 73 493
Pune Pune 26 7972274 02 May 2016 18:37 1 hr 30 min - 47 309
Pune Pune 26 7971951 02 May 2016 17:52 -
3 hr 5
min
36 500
36. 36
Pune Pune 26 7973474 02 May 2016 20:45 1 hr - 36 91
Pune Pune 26 7976328 03 May 2016 13:59 - 30 min 5 239
Pune Pune 26 7976325 03 May 2016 13:58 -
1 hr 15
min
38 236
Pune Pune 26 7977149 03 May 2016 17:20 -
1 hr 3
min
16 284
Pune Pune 26 7978372 03 May 2016 19:45 - 20 min 14 31
Pune Pune 26 7979227 03 May 2016 - - 35 min 5 15
Pune Pune 26 7978578 03 May 2016 - -
3 hr 5
min
104 591
Pune Pune 26 7979723 03 May 2016 22:27 - 30 min 29 62
Data collected at Pune HUB 3rd Week:
HU
B
BOOKIN
G
BRANCH
UNLOADIN
G TALLY
NO.
ARRIVAL
DATE
ARRIVA
L TIME
SCAN
TIME
NO. OF
WAYBILL
S
NO.
OF
BOXE
S
Pune Pune 26 7980932 04 May 2016 7:06 30 min 9 65
Pune Pune 26 7980436 04 May 2016 1:31 1 hr 25 min 34 264
Pune Pune 26 7982239 04 May 2016 15:47 35 min 4 22
Pune Pune 26 7981412 04 May 2016 11:17 1 hr 35 min 42 277
Pune Pune 26 7985222 04 May 2016 22:28 2 hr 25 min 54 370
Pune Pune 26 7985201 04 May 2016 22:25 1 hr 37 min 33 200
Pune Pune 26 7983793 04 May 2016 19:31 2 hr 50 min 118 403
Pune Pune 26 7987405 05 May 2016 14:17 20 min 7 12
Pune Pune 26 7986775 05 May 2016 10:27 29 min 6 45
Pune Pune 26 7986764 05 May 2016 10:23 12 min 8 18
Pune Pune 26 7987029 05 May 2016 12:02 3 hr 80 572
Pune Pune 26 7987281 05 May 2016 13:29 5 min 2 8
Pune Pune 26 7989310 05 May 2016 19:37 21 min 16 100
Pune Pune 26 7985583 05 May 2016 23:30 1 hr 20 min 30 155
Pune Pune 26 7985613 05 May 2016 23:37 1 hr 10 min 88 267
Pune Pune 26 7986963 05 May 2016 11:41 1 hr 25 min 29 321
Pune Pune 26 7988315 05 May 2016 17:32 20 min 4 10
Pune Pune 26 7986961 05 May 2016 11:41 54 min 1 268
Pune Pune 26 7989364 05 May 2016 19:43 20 min 8 10
Pune Pune 26 7989793 05 May 2016 20:30 1 hr 25 min 57 238
Pune Pune 26 7990539 05 May 2016 20:37 3 hr 115 582
Pune Pune 26 7987281 05 May 2016 13:29 10 min 2 8
37. 37
Pune Pune 26 7986961 05 May 2016 11:41 50 min 1 268
Pune Pune 26 7993699 06 May 2016 17:07 10 min 3 50
Pune Pune 26 7993339 06 May 2016 14:15 1 hr 20 213
Pune Pune 26 7995404 06 May 2016 19:53 10 min 8 14
Pune Pune 26 7992999 06 May 2016 14:14 20 min 21 34
Pune Pune 26 7998367 06 May 2016 13:37 25 min 11 15
Pune Pune 26 7997481 06 May 2016 7:13 37 min 15 64
Pune Pune 26 7995732 06 May 2016 21:12 1 hr 58 min 21 104
Pune Pune 26 7995690 06 May 2016 19:53 45 min 12 162
Pune Pune 26 7999515 07 May 2016 17:38 23 min 3 49
Pune Pune 26 7999550 07 May 2016 17:46 45 min 21 154
Pune Pune 26 8000748 07 May 2016 19:39 1 hr 40 min 30 95
Pune Pune 26 7999893 07 May 2016 18:31 1 hr 20 min 84 526
Pune Pune 26 8001068 07 May 2016 20:45 40 min 9 127
Pune Pune 26 8004102 08 May 2016 19:10 - 28 155
Pune Pune 26 8002984 08 May 2016 9:43 38 min 26 81
Pune Pune 26 8003972 08 May 2016 17:58 1 hr 50 min 94 399
Pune Pune 26 8003670 08 May 2016 15:31 40 min 7 153
Pune Pune 26 8004367 08 May 2016 20:34 30 min 43 104
Pune Pune 26 8004148 08 May 2016 19:38 1 hr 30 min 47 187
Pune Pune 26 7995815 08 May 2016 17:08 1 hr 46 min 35 331
Pune Pune 26 8008807 09 May 2016 21:36 15 min 8 16
Pune Pune 26 8008809 09 May 2016 20:16 1 hr 35 min 6 383
Pune Pune 26 8008639 09 May 2016 21:18 15 min 8 9
Pune Pune 26 8006436 09 May 2016 16:58 1 hr 23 264
Pune Pune 26 8005524 09 May 2016 12:43 1 hr 15 min 22 302
Pune Pune 26 8012028 10 May 2016 17:17 10 min 3 6
Pune Pune 26 8011690 10 May 2016 16:13 25 min 28 43
Pune Pune 26 8009917 10 May 2016 2:24 1 hr 2 181
Pune Pune 26 8010987 10 May 2016 12:39 20 min 3 12
Pune Pune 26 8009913 10 May 2016 2:24 1 hr 20 min 4 348
Pune Pune 26 8010625 10 May 2016 8:38 35 min 49 76
Pune Pune 26 8010661 10 May 2016 7:09 49 min 6 120
Pune Pune 26 8011358 10 May 2016 14:31 10 min 5 5
Pune Pune 26 8011672 10 May 2016 16:09 10 min 5 6
Pune Pune 26 8011669 10 May 2016 16:07 10 min 4 10
38. 38
Pune Pune 26 8012716 10 May 2016 18:41 10 min 5 6
Pune Pune 26 8012783 10 May 2016 18:49 1 hr 30 min 94 317
Data Collected at 4th Week Pune Hub:
HUB
BOOKIN
G
BRANCH
UNLOADIN
G TALLY
NO.
ARRIVAL
DATE
ARRIVAL
TIME
SCAN TIME
NO. OF
WAYBILL
S
NO. OF
BOXES
Pune Pune 26 8019070 11 May 2016 19:53 1 hr 23 97
Pune Pune 26 8022373 11 May 2016 11:15 20 min 6 7
Pune Pune 26 8018012 11 May 2016 18:09 1 hr 10 min 42 191
Pune Pune 26 8019862 11 May 2016 21:34 30 min 19 60
Pune Pune 26 8019062 11 May 2016 19:54 35 min 37 70
Pune Pune 26 8016631 11 May 2016 12:52 20 min 5 6
Pune Pune 26 8016179 11 May 2016 10:26 50 min 17 48
Pune Pune 26 8015458 11 May 2016 2:29 30 min 4 8
Pune Pune 26 8015459 11 May 2016 2:29 50 min 5 5
Pune Pune 26 8017942 11 May 2016 17:45 13 min 7 11
Pune Pune 26 8017460 11 May 2016 16:47 15 min 4 50
Pune Pune 26 8021110 12 May 2016 3:49 30 min 6 12
Pune Pune 26 8022730 12 May 2016 6:48 1 hr 40 min 26 351
Pune Pune 26 8028687 13 May 2016 17:13 10 min 5 5
Pune Pune 26 8028908 13 May 2016 17:41 1 hr 15 min 56 163
Pune Pune 26 8027615 13 May 2016 12:07 10 min 6 9
Pune Pune 26 8026567 13 May 2016 2:29 10 min 5 14
Pune Pune 26 8030644 13 May 2016 20:46 15 min 4 20
Pune Pune 26 8028644 13 May 2016 17:01 2 hr 5 min 54 387
Pune Pune 26 8030068 13 May 2016 19:52 45 min 2 93
Pune Pune 26 8030909 13 May 2016 17:12 1 hr 15 min 63 221
Pune Pune 26 8028028 13 May 2016 14:26 15 min 8 18
Pune Pune 26 8029949 13 May 2016 19:25 55 min 44 130
Pune Pune 26 8030058 13 May 2016 19:51 1 hr 10 min 45 171
Pune Pune 26 8031983 14 May 2016 0:46 22 min 9 10
Pune Pune 26 8033700 14 May 2016 18:18 5 min 3 12
Pune Pune 26 8034099 14 May 2016 16:48 37 min 10 79
Pune Pune 26 8033704 14 May 2016 6:01 50 min 14 194
Pune Pune 26 8034274 14 May 2016 17:14 10 min 12 14
Pune Pune 26 8033114 14 May 2016 11:57 20 min 24 36
Pune Pune 26 8033119 14 May 2016 11:58 25 min 37 56
Pune Pune 26 8033446 14 May 2016 13:45 7 min 5 6
Pune Pune 26 8036032 14 May 2016 20:45 30 min 12 18
Pune Pune 26 8034276 14 May 2016 17:15 2 hr 45 362
Pune Pune 26 8035356 14 May 2016 19:29 45 min 39 151
Pune Pune 26 8036683 14 May 2016 22:42 10 min 6 16
Pune Pune 26 8036452 14 May 2016 21:21 50 min 24 57
39. 39
Pune Pune 26 8036296 14 May 2016 21:22 1 hr 47 144
Pune Pune 26 8034607 14 May 2016 17:04 46 min 21 77
Pune Pune 26 8038845 15 May 2016 17:34 55 min 20 173
Pune Pune 26 8038438 15 May 2016 14:50 15 min 5 6
Pune Pune 26 8038393 15 May 2016 14:22 1 hr 20 min 12 186
Pune Pune 26 8038177 15 May 2016 12:34 15 min 24 53
Pune Pune 26 8038073 15 May 2016 11:33 40 min 31 82
Pune Pune 26 8037521 15 May 2016 5:05 15 min 19 41
Pune Pune 26 8037541 15 May 2016 5:35 20 min 4 29
Pune Pune 26 8040623 16 May 2016 13:06 13 min 3 42
Pune Pune 27 8046307 17 May 2016 16:17 15 min 7 8
Pune Pune 28 8045635 17 May 2016 12:22 15 min 8 18
Pune Pune 29 8046593 17 May 2016 17:09 10 min 5 16
Pune Pune 30 8047621 17 May 2016 19:14 20 min 4 7
Pune Pune 31 8047819 17 May 2016 19:35 30 min 24 69
Pune Pune 32 8047814 17 May 2016 19:34 20 min 15 34
Pune Pune 33 8045135 17 May 2016 9:54 20 min 28 45
Pune Pune 34 8048323 17 May 2016 20:27 10 min 8 19
Pune Pune 35 8046613 17 May 2016 16:37 50 min 16 77
Pune Pune 36 8045480 17 May 2016 11:23 25 min 29 77
Data Collected at Aurangabad:
BOOKING
BRANCH
UNLOADING
TALLY NO.
ARRIVAL
DATE
ARRIVAL
TIME
SCAN
TIME
NO. OF
WAYBILLS
NO. OF
BOXES
ARD-15 8189311 14 June 2016 17:30 28 1 10
ARD-102 8189452 14 June 2016 18:10 5 1 15
ARD-15 8189598 14 June 2016 19:20 25 1 8
ARD-101 8189721 14 June 2016 20:00 75 1 200
ARD-12 8190461 14 June 2016 20:15 85 23 297
ARD-15 8196835 15 June 2016 20:55 20 13 241
ARD-19 8195536 15 June 2016 18:30 15 7 69
ARD-14 8195548 15 June 2016 18:31 1 1 1
ARD-13 8195629 15 June 2016 18:32 60 10 405
ARD-14 8195551 15 June 2016 18:32 5 4 7
ARD-14 8195545 15 June 2016 18:31 20 8 32
ARD-102 8196127 15 June 2016 19:02 5 3 13
ARD-101 8196118 15 June 2016 19:33 20 3 52
ARD-12 8197397 15 June 2016 22:22 60 25 273
ARD-13 8199811 16 June 2016 14:45 5 7 68
ARD-101 8199888 16 June 2016 15:05 5 3 25
ARD-101 8200802 16 June 2016 17:42 5 3 14
ARD-11 8200884 16 June 2016 17:53 5 6 19
ARD-13 8202205 16 June 2016 20:12 20 9 179
ARD-19 8202557 16 June 2016 20:54 15 5 71
ARD-12 8201078 16 June 2016 18:18 30 21 248
40. 40
ARD-13 8200824 16 June 2016 17:45 120 14 761
ARD-19 8207106 17 June 2016 18:45 2 1 6
ARD-17 8206489 17 June 2016 17:27 30 3 402
ARD-18 8206465 17 June 2016 17:24 5 1 25
ARD-14 8206472 17 June 2016 17:25 2 1 4
ARD-101 8206469 17 June 2016 17:23 12 1 120
ARD-19 8207112 17 June 2016 18:46 20 5 68
DHULE-11 L 6861406 17 June 2016 30 19 205
HYDERABAD-
11
8207645 17 June 2016 19:39 50 17 103
ARD-12 8207128 17 June 2016 18:47 60 23 218
DHULE-11 L 6862228 17 June 2016 20:35 20 2 79
DHULE-11 L 6862315 17 June 2016 21:09 10 3 30
Statistical Test Outputs:
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 Before Training 6.9724 34 6.96825 1.19504
After Training 11.6937 34 11.99082 2.05641
Paired Samples Correlations
N Correlation Sig.
Pair 1 Before Training & After
Training
34 .733 .000
Paired Samples Test
Paired Differences
t df
Sig. (2-
tailed)Mean
Std.
Deviatio
n
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
Before Training -
After Training
-
4.72129
8.35407 1.43271 -7.63616 -1.80642 -3.295 33 .002
41. 41
12.0) Glossary of Abbreviations
OA – Operation Assistant: is person who observe and responsible for loading
and unloading the vehicle.
BA – Booking Associate is a person who books material from client company
to transfer via safexpress.
GTA – Green Truck Associate is a person having company owned vehicle for
picking the retail material for business.
Scanner – is a device used to read the barcode and interpret the information
recorded into graphical format.
Barcode – Barcode is a 2D or 1D graphical representation of data may it be
numerical or characters.