MAGMA yaitu Suatu benda cair, padat dan liat mempunyai temperatur sangat tinggi, berada jauh di bawah permukaan bumi, bisa bersifat asam, basa maupun ultra basa, dan mengandung gas magmatis. Di permukaan disebut LAVA
MAGMA yaitu Suatu benda cair, padat dan liat mempunyai temperatur sangat tinggi, berada jauh di bawah permukaan bumi, bisa bersifat asam, basa maupun ultra basa, dan mengandung gas magmatis. Di permukaan disebut LAVA
During the summer 2015 MHCA conference in San Diego, California Valley Behavioral Health CEO Gary Larcenaire and Healthcare Social Media Strategist Bobbie Rathjens discussed how they raised thousands of dollars for non-verbal children affected by autism so they could each have iPad technology to communicate.
Prometeia distinguishes its approach by consistently
pursuing state of the art methodologies, with a fully
dedicated team of econometricians and financial
specialists with broad experience in developed and
emerging markets.
Our internally developed methodologies are constantly
updated with the best practices and entirely integrated
into the ERMAS Suite, enabling banks to take a
proactive approach towards risk management and
increasing profitability.
The Mechanics of Testing Large Data Pipelines (QCon London 2016)Mathieu Bastian
Talk about testing large Data Pipelines, mostly inspired from my experience at LinkedIn working on relevancy and recommender system pipelines.
Abstract: Applied machine learning data pipelines are being developed at a very fast pace and often exceed traditional web/business applications codebase in terms of scale and complexity. The algorithms and processes these data workflows implement fulfill business-critical applications which require robust and scalable architectures. But how to make these data pipelines robust? When the number of developers and data jobs grow while at the same time the underlying data change how do we test that everything works as expected?
In software development we divide things in clean, independent modules and use unit and integration testing to prevent bugs and regression. So why is it more complicated with big data workflows? Partly because these workflows usually pull data from dozens of sources out of our control and have a large number of interdependent data processing jobs. Also, partly because we don't know yet how to do or lack the proper tools.
Data Products: 5 Deadly Sins and How To Prevent ThemMathieu Bastian
Data Stage keynote at WebSummit Dublin 2015. This presentation dives into the five most critical sins Data Product teams might encounter and calls to action to prevent them.
Why Online Reputation Management is Critical to Your Success & How to Get it ...Bobbie Rathjens
From the Afia, Inc. webinar held on January 21, 2015. Contained in this presentation for the healthcare or medical professional is the following information:
- Why online provider and practice reputations are directly tied to the success of medical practices.
- Real life examples of online physician reviews that lead to litigation and how to avoid this from happening to you.
- Advice on what to do if you receive a bad review.
- How to manage online reputations the right way.
For more information, go to: http://www.afiahealth.com/social
The above slides present a few Case Studies in Distribution. Case studies of Dabawallas, Newspaper and Fresh Flower are analyzed in detail. The objectives of these three case studies are highlighted. The presentation is compiled by Welingkar’s Distance Learning Division.
For more such innovative content on management studies, join WeSchool PGDM-DLP Program: http://bit.ly/DistMang
Join us on Facebook: http://www.facebook.com/welearnindia
Follow us on Twitter: https://twitter.com/WeLearnIndia
Read our latest blog at: http://welearnindia.wordpress.com
Subscribe to our Slideshare Channel: http://www.slideshare.net/welingkarDLP
Three cases are discussed. They include the much-talked about Dabbawallas example who operate at a six sigma performance of 99.9999. Then there is a newspaper case study that highlights speed as a distribution objective and fresh flower case study that represents cargo quality as a principle objective of distribution.
During the summer 2015 MHCA conference in San Diego, California Valley Behavioral Health CEO Gary Larcenaire and Healthcare Social Media Strategist Bobbie Rathjens discussed how they raised thousands of dollars for non-verbal children affected by autism so they could each have iPad technology to communicate.
Prometeia distinguishes its approach by consistently
pursuing state of the art methodologies, with a fully
dedicated team of econometricians and financial
specialists with broad experience in developed and
emerging markets.
Our internally developed methodologies are constantly
updated with the best practices and entirely integrated
into the ERMAS Suite, enabling banks to take a
proactive approach towards risk management and
increasing profitability.
The Mechanics of Testing Large Data Pipelines (QCon London 2016)Mathieu Bastian
Talk about testing large Data Pipelines, mostly inspired from my experience at LinkedIn working on relevancy and recommender system pipelines.
Abstract: Applied machine learning data pipelines are being developed at a very fast pace and often exceed traditional web/business applications codebase in terms of scale and complexity. The algorithms and processes these data workflows implement fulfill business-critical applications which require robust and scalable architectures. But how to make these data pipelines robust? When the number of developers and data jobs grow while at the same time the underlying data change how do we test that everything works as expected?
In software development we divide things in clean, independent modules and use unit and integration testing to prevent bugs and regression. So why is it more complicated with big data workflows? Partly because these workflows usually pull data from dozens of sources out of our control and have a large number of interdependent data processing jobs. Also, partly because we don't know yet how to do or lack the proper tools.
Data Products: 5 Deadly Sins and How To Prevent ThemMathieu Bastian
Data Stage keynote at WebSummit Dublin 2015. This presentation dives into the five most critical sins Data Product teams might encounter and calls to action to prevent them.
Why Online Reputation Management is Critical to Your Success & How to Get it ...Bobbie Rathjens
From the Afia, Inc. webinar held on January 21, 2015. Contained in this presentation for the healthcare or medical professional is the following information:
- Why online provider and practice reputations are directly tied to the success of medical practices.
- Real life examples of online physician reviews that lead to litigation and how to avoid this from happening to you.
- Advice on what to do if you receive a bad review.
- How to manage online reputations the right way.
For more information, go to: http://www.afiahealth.com/social
The above slides present a few Case Studies in Distribution. Case studies of Dabawallas, Newspaper and Fresh Flower are analyzed in detail. The objectives of these three case studies are highlighted. The presentation is compiled by Welingkar’s Distance Learning Division.
For more such innovative content on management studies, join WeSchool PGDM-DLP Program: http://bit.ly/DistMang
Join us on Facebook: http://www.facebook.com/welearnindia
Follow us on Twitter: https://twitter.com/WeLearnIndia
Read our latest blog at: http://welearnindia.wordpress.com
Subscribe to our Slideshare Channel: http://www.slideshare.net/welingkarDLP
Three cases are discussed. They include the much-talked about Dabbawallas example who operate at a six sigma performance of 99.9999. Then there is a newspaper case study that highlights speed as a distribution objective and fresh flower case study that represents cargo quality as a principle objective of distribution.
This presentation explains how the dabbawala system works in Mumbai. It also contains certain statistical data and the achievements of the said system.
1. Cell No.: 91-9869152163
Andheri Office - 26821897
Grant Rd. Office – 23860742
Off: 3, Raghunath Patnak Chawl,
Sambhaji Nagar,
Sahar Road, Near Fly-Over Bridge,
Andheri (E), Mumbai – 69
Email id: rdmedgedabbawala@yahoo.co.in
The Wonder Of Dabbawallas
Unfolded
2. What is NMTBSA?
Nutan
Mumbai
Tiffin
Box
Suppliers
Association
3. ABOUT NMTBSA
• History : Started in 1890
• Charitable trust : Registered in 1956
• Avg. Literacy Rate : 8th Grade Schooling
• Total area coverage : 60 Kms to 70 Kms
• Employee Strength : 5000
• Number of Tiffin's : 2,00,000 Tiffin Boxes
i.e 4,00,000 transactions every day.
• Time taken : 3 hrs
5. Working of NMTBSA
• Error Rate : 1 in 16 million transactions
• Six Sigma performance (99.999999)
• Technological Backup : Nil.
• Cost of service - Rs. 300/month ($
6.00/month)
• Standard price for all (Weight, Distance,
Space)
• Rs. 36 Cr. Turnover approx.
[6000*12*5000=360000000 i.e Rs. 36 crore
p.a.]
• “No strike” record as each one a share holder
• Earnings -5000 to 6000 p.m.
• Diwali bonus: one month’s from customers.
6. Zero % fuel Zero % investment
Zero % modern technology Zero % Disputes
99.9999% performance 100 % Customer Satisfaction
7. APPROACH
DISCIPLINES :
• No Alcohol Drinking during business hours
• Wearing White Cap during business hours
• Carry Identity Cards
WOMEN:
• Mrs. Bhikhubai of Kandivali
• Mrs. Anandibai of Borivali
• Mrs. Parvatabai of Karale (Ghatkopar)
• Mrs. Laxmibai Bagade of Santa Cruz
LATEST MARKETING STRATEGY:
Marketing pamphlets in the “Dabba”
8. Case Study: NMTBSA
Tiffin Box Suppliers Association
How do they do it …?
Executive Committee
(5 members)
• Organizational
Structure Teams of 20-25 headed by
a group leader
• Operations
• The Code Individual dabbawallahs workload:
Collect from home – 35 tiffins
• War against Time Delivery at office – 35 tiffins
(9:00 am – 12:30 pm) Return empty tiffins to home – 35 tiffins
9. ORGANISATIONAL STRUCTURE
PRESIDENT
VICE PRESIDENT
GENERAL SECRETARY 13 MEMBERS
TREASURER
DIRECTORS ( 9 )
MUKADAM
MEMBERS ( 5000 )
10. Coding System
VLP : Vile Parle (suburb in
Mumbai)
9EX12 : Code for Dabbawalas
at Destination
EX : Express Towers
(building name)
12 : Floor no.
E : Code for Dabbawala
at residential station
3 : Code for destination
Station eg. Churchgate D’souza
Station (Nariman Point)
11. • Let us now look at an example of these
codes on the tiffins to better understand
the system and what it all denotes:
12. The Flow Logic
Zones for destination
Grant Road 1
(12) 2
Point of 3
Aggregation
Churchgate 4
And Sorting
(1-10)
5
A E
6
Lower Parel
B D
C (14) 7
Distribution
By Carriers
Collection from home at lunchtime
To offices
13. • 10:34-11:20 am
(Andheri Stn.)
• This time period is
actually the journey
time. The
dabbawalas load the
wooden crates filled
with tiffins onto the
luggage or goods
compartment in the
train. Generally, they
choose to occupy
the last
compartment of the
train.
12 coach train
4,000 commuters
8,000 disputes
But no excuses,
Duty first
14. • 11:20 – 12:30 pm
(Church Gate Station)
• At this stage, the
unloading takes place
at the destination
station
• Re-arrangement of
tiffins takes place as
per the destination area
and destination building
15. • In particular areas
with high density
of customers
(Nariman Pt.,Fort ,
CST), a special
crate is dedicated
to the area. This
crate carries 150
tiffins and is driven
by 3-4
dabbawalas!
16. RETURN JOURNEY:
• 1:15 – 2:00 pm ( At All Destination Stations)
Here on begins the collection process where the
dabbawalas have to pick up the tiffins from the
offices where they had delivered almost an hour
ago.
17. • 2:00 – 2:30 pm (At Destination Station)
• The dabbawalla’s meet for the segregation as per
the destination suburb.
18. • 2:48 – 3:30 pm
• The return journey by
train where the group
finally meets up after the
day’s routine of
dispatching and
collecting from various
destination offices
• Usually, since it is more
of a pleasant journey
compared to the earlier
part of the day, the
dabbawalas lighten up
the moment with merry
making, joking around
and singing.
19. • 3:30 – 4:00 pm
( The Origin Station)
• This is the stage
where the final sorting
and dispatch takes
place. The group
meets up at origin
station and they
finally sort out the
tiffins as per the origin
area
20. Awards and Felicitation
• Shri.Varkari Prabhodhan Mahasmati Dindi (palkhi)
sohala – 4th march – 2001.
• Documentaries made by BBC ,UTV, MTV, ZEE TV,
AAJ TAK, TV TODAY, SAHARA SAMAY, STAR
TV, CNBC TV 18, CNN, SONY TV, TV TOKYO,
NDTV.
•CASE STUDY –
•ICFAI Press Hyderabad
•Richard Ivey School of Business - Ontarion
22. Awards and Felicitation (contd.)
• Invitation from CII for conference held in Bangalore,
IIML, IIMA, CII Cochin, CII Delhi, Dr. Reddy’s Lab
Foundation Hyderabad, SCMHRD Pune, SCMHRD
Nasik, Sadahana – Poone.
• Included in a subject in Graduate School of
Journalism University of California, Berkeley.
• Radio –
• German Radio Network
• Radio Mirchi
• Radio Mid-day
• FM – Gold
• BBC Radio
23. Invitation to Italy
• Was invited for the Terra Madre World
meeting of food communities between
October 20-23, 2004.
• We were part of the “Community of
Cooked Food distributors from
Mumbai”.
• Invited to marriage of Hon. Price
Charles of England on 9 , April 2005.
25. Some Achievements
• World record in best time management.
• Name in “GUINESS BOOK of World
Records”.
• Registered with Ripley's “ believe it or not”.
26. Ph.D. on Mumbai Dabbawala
By
Principal Pawan G. Agrawal
M.Com., B.Ed., LL.B., A.C.S.
Director
AGRAWAL INSTITUTE OF MANAGEMENT
Mumbai
Topic : Study of Logistic & Supply Chain
Management of Dabbawala in Mumbai.
University : Yashwantrao Chavan Mukta
Vidyapeeth, Nashik.
Research Work : Doing since last One and Half Year.
Guide : Dr. Kulkarni, Nashik.