USP Mega-city Logistics public - MIT...

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10/25/11 1 Megacity Logis2cs in Emerging Markets USP, October 25, 2011 São Paulo, Brasil Edgar E Blanco [email protected] Research Director Executive Director MIT SCALE Latin America E. Blanco © 2011 MIT CTL . Do not quote without author authoriza2on 1 2 Why are Emerging Markets important? Source: Wikipedia, World Bank 2006 Database China 1,314M - $2k India 1,113M - $0.8k USA 300M - $45k Mexico 104M - $8k Brazil 187M - $4.7k Nigeria 149M - $0.6k Egypt 75M - $1.3k Germany 82M - $36k Russia 142M - $5.8k Vietnam 84M - $0.6k Japan 128M – $38k Philippines 87M – $1.4k Indonesia 222M - $1.4k Pakistan 155M - $0.7k Bangladesh 144M - $0.4k Country Population – GNI per Capita EU 459M - $34k World 6,440M - $7.5k E. Blanco © 2011 MIT CTL . Do not quote without author authoriza2on

Transcript of USP Mega-city Logistics public - MIT...

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Megacity  Logis2cs  in  Emerging  Markets  

USP,  October  25,    2011  São  Paulo,  Brasil  

Edgar E Blanco [email protected] Research Director Executive Director MIT SCALE Latin America

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     1  

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Why  are  Emerging  Markets  important?  

Source: Wikipedia, World Bank 2006 Database

China 1,314M - $2k

India 1,113M - $0.8k

USA 300M - $45k

Mexico 104M - $8k

Brazil 187M - $4.7k

Nigeria 149M - $0.6k

Egypt 75M - $1.3k

Germany 82M - $36k

Russia 142M - $5.8k

Vietnam 84M - $0.6k

Japan 128M – $38k

Philippines 87M – $1.4k

Indonesia 222M - $1.4k

Pakistan 155M - $0.7k

Bangladesh 144M - $0.4k

Country Population – GNI per Capita

EU 459M - $34k

World 6,440M - $7.5k

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on    

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 …  why  is  megacity  logis-cs  strategic  today?  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     3  

Urbaniza2on  today  

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E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     5  

Urbaniza2on  tomorrow  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     6  

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Megaci2es  with  popula2on  >  5M  

1950s   2000s  1900s  (5)  

Tokyo  ~  13M  New  York  ~  12M  Osaka  ~  9M  London  ~  8M  

Paris,  Shanghai  ~  5M  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     7  

(1)  London  ~  6.5M  

Osaka(?),  New  York  ~  4M  Paris,  Berlin  ~  3M  

Tokyo  ~  1.5  

(78)  Tokyo  ~  35M  

Mumbai,  Mexico  City  ~  20M  São  Paulo,  New  York  ~  19M  

Shanghai  ~  17M  Kolkata,  Delhi  ~  16M  Beijing,  London  ~  15M  LA,  Buenos  Aires  ~  12M  Rio,  Paris,  Manila~  11M  Moscow,  Istanbul  ~  10M  

....  45  more  Source  MGI,  Forbes,  University  of  Cologne    

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     8  

Megaci2es  with  popula2on  >  5M  

Source:    University  of  Cologne    

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Megacity  Dynamic  1:    Accelera2ng  growth  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     9  

Megaci2es  keep  growing  

•  100  mega-­‐ci2es  represent  38%  of  global  GDP  •  Projected  to  double  by  2025  •  Complex  environment  …  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     10  

Source:  MGI  (2011)  

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Megacity  Dynamic  2:    Urban  density  to  “new”  levels  

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Pu[ng  density  in  Perspec-ve  

12  E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on    

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Megacity  Dynamic  3:    Drama2c  socio-­‐economic  contrasts  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     13  

Diverse  city  profiles  

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Fuente: MEIKO 2009+ DANE 2009

121  hhabs  per  store  Per  capita  COL$469K  

151  habs  per  store  Per  capita  COL$237K  

155  habs  per  store  Per  capita  COL$186K  

148  habs  per  store  Per  capita  COL$267K  

242  habs  per  store  Per  capita  COL$2.185K  279  habs  per  store  

Per  capita  COL$2.0195K  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on    

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Megacity  Dynamic  4:    People  mobility  is  the  priority  

…  and  boxes  do  not  vote  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     15  

Grinding  halt…  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     16  

4  –  5  Km/h  

10  –  15  Km/h  

Source:  BRT  Across  LaItudes;  Gakenheimer  &  Zegras  (MIT)  

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Shrinking  freight-­‐friendly  infrastructure  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     17  

Source:  BRT  Across  LaItudes  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     18  

Source:  Espiritoutdoor.com  

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E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     19  

Source:  TURBLOG  

Megacity  Dynamic  5:    Small  stores  mager  

(and  they  only  take  cash)  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     20  

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E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     21  

Source  Nielsen  

Channel Complexity

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   MOM  &  POP  STORE  • 200  –  1500  sq.l.  • Owner  opera2on  &  individual  decision-­‐making  • Counter  • Knowledge  &  proximity  to  community  •  Informality  (p.e.  taxes,  invoicing,  financing)  • Smaller  size  products  • Slow  volume,  high  frequency,  few  items  (500  –  5,000  SKUs)    • Examples:  Tiendas  de  barrio,  ferreterías,  panaderías,  kioskos,  mayoristas,  droguerías,  autoservicio  independiente,  etc.  

       

MODERN  RETAIL  • 5000  sq.l  or  more  • “Corporate”  decision-­‐making  process  • Self-­‐service  • Mul2ple  outlets,  shared  brand  • Organiza2onal  structure,  physical  infrastructure,  IT  technology  • Regular  size  products  • High  volume,  high  frequency,  many  items(30,000  –  150,000  SKUs)  • Examples:  Supermercados,  hipermercados,  2endas  de  conveniencia,  cadenas  de  autoservicios  etc.  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on    

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E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     25  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     26  

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Megacity  Dynamic  6:    More  fragmented  logis-cs  opera2ons  

More  store  loca2ons  Smaller  shipment  sizes  More  empty  miles  More  conges2on  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     27  

Megacity  logis2cs  dynamics  

1.   Accelera2ng  growth    2.   Urban  density  to  “new”  levels  3.   Drama2c  socio-­‐economic  contrasts    4.   People  mobility  is  the  priority  5.   Small  stores  mager  6.   More  fragmented  logis-cs  opera2ons  

 E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  

without  author  authoriza2on     28  

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The  megacity  dilemma…  

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•  Increasing  wealth,  eroding  accessibility  •  Disconnected  actors  

– Regional  urban  planning  – Land  use  – Passenger  transport  planning  – Companies  

•  Not  a  good  understanding  of  the  logis2c  system  and  its  dynamics  – Physical,  informa2on,  monetary  flows  

Tradi2onal  city  logis2cs  policy  focus  on  the  symptoms…  

•  Truck  routes  •  Urban  freight  informa2on  and  maps  •  Vehicle  weight  and  size  regula2ons  •  Truck  lanes  &  loading  zones  •  Road  charging  systems  •  Urban  consolida2on  centers  •  Megacity  freight  movements  grow  faster  than  policies  …  

 E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  

without  author  authoriza2on     30  

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Proac2ve  &  innova-ve  megacity  logis2cs  strategies  

needed…  Beyond  compliance  Scalability  &  speed  

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Ex:  City  of  New  York  Night  Deliveries  Pilot  (Holguin-­‐Veras,  2010)  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     32  

Source:  Holguin-­‐Veras  (RPI)  

•  Is made jointly between receivers and carriers –  40% receivers, 38% receivers+carriers, 22% carriers

•  Let’s take a look at the payoff matrix –  The first sign represents the impact on carrier and the second the

impact on receiver

Strategy Regular hours Off-hoursRegular hours (-,+) (I) (-,-) (II)

Off-hours (-,-) (III) (+,-) (IV)

Receiver

Carrier

(These are non-feasible solutions)

(This is the solution preferred by most carriers)

(This is the solution preferred by most receivers)

The fact that more than 90% of deliveries are made in the day hours clearly show who has the power…

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Average space mean speeds

33 More than twice as fast E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  

without  author  authoriza2on    

Average service times

34 More than three times as fast E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  

without  author  authoriza2on    

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Ex:  France  Urban  Freight  Ini2a2ves  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     35  

 Average  distance  of  terminals  to  center  of  gravity  increased  from  6  to  16  km    

Average  distance  of  jobs  to  center  of  gravity  has  increased  by  2  km  

Source:    LaeIIa  Dablanc  TURBLOG,  2010)  

Porsolio  of  ini2a2ves…  

•  Chronopost  –  small  electric  vehicles,  network  re-­‐design  aligned  with  urban  topology  

•  La  pe2te  Reine  cargocycles  –  elelectric  assisted  vehicles  for  small  parcel  deliveiries  

•  Monoprix  experiment  –  Urban  consolida2on  intermodal  center  

•  Consolidated  freight  land-­‐use  plan  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     36  Source:    LaeIIa  Dablanc  TURBLOG,  2010)  

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Ex:  Tailored  OR  for  megaci2es  

•  No  megaci2es  when  logis2cs  op2miza2on  field  was  created  – Facility  loca2on  problem  (Weber,  1909)  – Vehicle  rou2ng  problem  (Dantzig  and  Ramser,  1960)  

•  Implicit  assump2ons  of  homogeneous  urban  density  and  transporta2on  environments  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     37  

Subject to

Fixed  cost  per  truck  type  

Variable  cost  per  truck  type  

-­‐ 150 -­‐ 100 -­‐ 50

-­‐ 100

-­‐ 50

50

100

150

200

Simple  problem  structures,  very  different  solu2ons  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     38  

Source:    Velazquez,  Blanco,  Fransoo  (2011)  

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Ex:  Tokyo  high-­‐rise  3PL  

•  Inefficient  distribu2on  to  high-­‐rise  buildings  in  Tokyo  Shinjuku  area  – 130,000  workers  in  20  high-­‐rise  buildings  –  Individual  deliveries  to  office  areas  

•  Crea2on  of  Shinjuku  Matenro  Staff  3PL  to  deliver  goods  – Collabora2on  of  carriers  – Micro-­‐urban  distribu2on  center  

•  For-­‐profit  venture  E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  

without  author  authoriza2on     39  

Source, Junichi Yashiro (TURBLOG, 2011)  

Shinjuku,  Tokyo  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     40  

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Shinjuku  X-­‐Docking  Process  

E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on     41  

The  Wonder  Of  Dabbawallas  Unfolded  NUTAN  MUMBAI  TIFFIN  BOX  SUPPLIERS  ASSOCIATION  

Web  Site  :  mumbaidabbawala.org  

Sant  Dnyaneshwar   Lord  Ganesha  

Late  Shri  Mahadu  H.  Bachhe  Founder     Late  Shri  Dhondiba  Medge  

Sr.  Member    

42  E.  Blanco  ©  2011  MIT  CTL  .  Do  not  quote  without  author  authoriza2on    

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ABOUT NMTBSA History                                            :  Started  in  1890  Charitable  trust                  :  Registered  in  1956  Employee  Strength      :  5000  Avg.  Literacy  Rate      :  8th  Grade  Schooling  Total  area  coverage  :  60  Kms  to  70  Kms  Number  of  Tiffins          :  2,00,000  Tiffin  Boxes            400,000  transac2ons  every  day  (including  return)            i.e.  400,000*25  days*12  months=  120,000,000              (120  million  or  12  crore  transac2ons  per  year)    Time  taken                            :  8  to  9  Hours                Morning  3  Hours  War2me  

(9  A.M.  to  12  P.M.  for  the  Collec-on  and  Delivery)  

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II. City Profile – Mumbai, INDIA

Shared  transport/freight  Infrastructure  

Suburban Rail Network •  2  Zones  –  Western  (80  km)  &  

Central  (120  km,  Harbor-­‐100  km)    •  Extensive  reach:      300  km  /  95  

stns.  transpor2ng  6.9  Mill.  Daily  •  Avg.  4,500  pass.  packed  in  9  car  

rakes  (Cap:  1,700)  •  3  rakes  in  each  train  dedicated  to  

freight  

Source, Deepak Baindur (TURBLOG, 2011)  

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Ex:  Virtual  Retailing  in  San2ago  

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Final  thoughts…  

•  Recognize  uniqueness  of  megacity  dynamics  and  their  impact  in  logis2cs  – Dynamics  +  Topology  

•  Collabora2on  between  government  &  industry  sorely  needed  in  freight  planning  –  Beyond  “constrained-­‐based”  policy  

•  Aim  for  innova-on,  not  reac-on  –  Localized  research  &  collabora2on  needed  –  Embrace  complexity  – Opportuni2es  for  disrup2ve  technology  investments  

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Thanks!    

Q&A  

Edgar  E  Blanco  [email protected]  

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