Mapp i n g   t h e   fl ow   o f   i n f o rma1on  a nd   k n ow l e d g e   b e tween  s t a k e ho l d e r   g r o up s :  we a kn e s s e s  a n d   s t r e n g t h s   i n   k n ow l e d g e  mana g emen t   a n d   c ommun i c a1on      John  Norton,  DWF        Final  conference:    knowledge  management  for  improving  DRR  &  CCA    26  –  27  May  2015  Université  de  Savoie-­‐Mont  Blanc,  Chambéry                              EC    FP7  Project  N°  603807  

   

Mapping  informa1on  flow  in  the  KNOW4DRR  programme  

Mapping  knowledge  and  informa1on  flow  between  different  stakeholders  concerned  with  disaster  risk  reduc1on  and  climate  change  adapta1on  has  been  an  important  part  of  the  project  process  

   

In  Year  1  of  the  project,  we  mapped  the  results  of  case  studies  to  show  informa1on  and  knowledge  flows  between  different  social  stakeholder  groups,  intended  to  support  disaster  risk  reduc1on  and  climate  change  adapta1on:  did  it  get  there?  Does  it  work?      

   

The  aim:      Get  a  snapshot  of  where  informa1on  transfer  and  the  knowledge  it  should  contribute  to  decision  making  either  does  or  does  not  work:    •  what  can  we  do  be_er?    •  what  can  we  learn?    

11  cases  covered  different  disasters  •  ADELPHI  (&  POLIMI)/  Severe  floods  along  the  ELBE  river,  

Germany,  August  2002    •  CIESAS/  Reloca1on  of  landslide  survivors  in  Chiapas  State,  

Mexico,  2005  and  later  •  CSIC  Group  /  Case  study  of  the  Lorca  earthquake,    

Spain,  11th  May  2011  •  DWF/  typhoon  events,  2006  &  2009,  Vietnam  •  HUA/  Ilia  forest  fires,  August  2007,  Greece  •  HUA/  Kalamata  earthquake,  Greece,  1986  •  HUA/  sea  level  rise  &  Climate  Change  AdaptaAon,  Greece  •  U  SALZBERG  –  PLUS  /  flood  event  in  Salzach  catchment,  

Austria,  June  2013  •  POLIMI/Umbria  flood  event,  Italy,  November  2012  •  UNISAVOIE/  La  Faute-­‐sur-­‐Mer  storm  disaster,  Atlan1c  

Coast,  France,  February  2010        •  UNU-­‐EHS/  People-­‐centred  tsunami  early  warning,    

Padang,  West  Sumatra  

A  data/informa1on/knowledge/wisdom  pyramid  An  early  stage  the  KNOW4DRR  project  modelled  the  stages  of  exchange  of  knowledge  for  DRR  using  a  Data  –  Informa1on  –  Knowledge  -­‐Wisdom  (DIKW)  pyramid,  lots  of  data  at  its  base,  li_le  wisdom  at  the    top.  We  sued  this  a  basis  for  the  mapping  process:  

This  reflected  an  issue:    much  data,  but  far  less  knowledge  and  even  less  wisdom  generated  for  decision  making  on  DRR/CCA.  

The  mapping  process  considered    informa1on  transfer  over  «  1me  »  -­‐  using  the  disaster  management  cycle;    informa1on  flow  between  four  principle  stakeholder  groups       Disaster  management  cycle  phases  

Stakeholders   Before  last  event   Early  warning   During  the  event/Response  

Recovery  &  reconstruc1on  

Period  aper  recovery  

Public  Sector                      ScienAsts                  Private  Sector                            Civil  society                      

Which  Stakeholders  ?  

Public  Sector  

ScienAsts  

Private  Sector        

Civil  society  

Hazard specialists

Risk experts

Scientists

Other

Insurers

Business

Media

Other

Lifelines managing co.

Citizens associations

NGO

Households/individuals

Other

A  focus  on  informa1on  &  knowledge  flow  &  their  impact  

What?     What   informa1on  was  sent  by  each  stakeholder   (who)  about   the   iden1fied  risk  or  hazard   (or  event)  in  your  case  study?  

How?     How  was   this   informa1on   sent?  How  open?  Was   the   informa1on   fragmented   in   this   process  and  did  this  hinder  its  use?  How?  

To  whom?     Who  was  it  sent  to  (to  which  ini1al  target  stakeholders)?  Was  there  an  indica1on  that  message/informa1on  was  received?  

Onward  transfer?     Did  informa1on  get  passed  on  by  a  receiving  stakeholder  to  addi1onal  stakeholders  (e.g.  from  local  authority  to  households)?  Was  informa1on  shared/networked?  

What  acAon?  By  whom?    

How  was  the  informa1on  used?  Did  it  influence  or  not  any  decision  making?  How  and  who  by?    

Why  not?     If  informa1on  was  not  or  only  par1ally  used  by  this  stakeholder  to  influence  decision  making  or  ac1on,  why?  e.g.  were  there  other  priori1es  or  constraints:  finance,  etc.  ?  

Feedback?     Was   there   feedback   from   this   stakeholder   (recipient)   to   the   sender   of   informa1on?   Did  feedback/evalua1on  influence  subsequent  policy/ac1ons?  

Uncertainty?     Did  the  informa1on  help  reduce  risk  or  uncertainty?  How  and  why?  

Wisdom?     Did  informa1on  become  knowledge/wisdom?  

To  explore  what  happens  to  informaAon  “sent”  -­‐  how  it  was  used  or  not  used  by  the  different  stakeholders  with  different  priori1es  and  capaci1es  -­‐  DWF  asked  partners  9  ques1ons:

Mapping  the  cases  The  cases  were  analysed  &  the  results  mapped  graphically.    •  On  the  ver1cal  axis,  the  stakeholders  groups,    •  On  the  horizontal  axis,  the  Disaster  Management  Cycle  stages.  

   

The  inten1on:  to  see  quickly  where  blockage  occurs  or  ac1on  is  taken  on  the  basis  of  informa1on  transmi_ed,  using  symbols.    

 

Typhoons  in  Vietnam,  2006  &  2009  

«  La  Faute  sur  Mer  »  storm  surge  disaster,  France    

«  They  [the  local  authoriAes]  all  knew  our  lives  

were  at  risk  from  drowning»  

 17  September  2014  

1st  day  of  the  trial  of  local  authority  representaAves,  charged  with  the  

 involuntary  manslaughter    of  29  people.  

 Analysis    The  mapping  tables  have  been  reviewed  to  answer  the  ques1on:    “Did  communica1on  &  informa1on  help  decision  making  and  a  be_er  DRR  outcome  or  not?”    A  mixed  result!    

8  8  

5  

A  first  view  

•  Since  almost  all  cases  reported  disaster  generated  examples  where  things  went  wrong,  there  is  an  impression  of  poor  communica1on  &  knowledge  sharing  

•  Secondly,  aper  the  events,  there  has  been  more  learning  &  progress.    

The  nega1ve  or  low  impact  issues   •  Too  many  organiza1ons  and  agencies  dealing  with  aspects  of  the  

disaster  management  cycle  creates  confusion.  •  Top  down  strategy  too  theore1cal  and  difficult  to  implement.  •  Informa1on  too  li_le  or  late,  some1mes  incorrect  or  not  

understood  by  target  stakeholder.  •  Lack  of  stakeholder  capacity  building  and  awareness  raising.  •  One  way  informaAon  flow  /  insufficient  feedback.  •  Absence  and  loss  of  knowledge:  the  value  of  local  or  indigenous  

knowledge  about  risks  and  responses  is  under-­‐valued.    •  Media  can  do  be^er  as  an  important  but  uncertain  communica1on  

interface.  •  Other  prioriAes  influence  decisions  -­‐  and  prime  sufferers  lose  out.  

The  posi1ve  impact  issues    

•  RaAonal  disaster  risk  management  structures  and  prac1ce  •  Promote  interdisciplinary  work  •  More  stakeholder  involvement  •  Educa1on  and  capacity  building,  including  for  media  and  civil  

society  •  Improving  informaAon  quality  

Uneven  spread  of  informa1on    There  are  gaps,  failures  and  some  abuse  in  the  transfer  of  knowledge.      Most  of  all,  there  is    an  uneven  spread  of  informa1on  and  knowledge  exchange  for  decision  making  on  DRR  and  CCA  across  stakeholder  groups.      

 

Maintaining  knowledge,  awareness;  

Climate  change  issues  highlights  the  challenge  of  maintaining  interest  &  knowledge  for  DRR  and  Climate  change  over  1me.      

Ac1on  needs  to  happen  before  the  event.  For  many  people  warning  comes  too  late.  Achieving  sustained  civil  society  &  private  sector  miAgaAon  acAon  is  hard.    

Turnbull  et  al  2013  

think  in  advance  to  be  prepared  

The  other  stakeholder  pyramid    There  is  a  second  knowledge  flow  pyramid  for  “stakeholder    communica1on”.    It  is  upside  down!    Much  data  at  the  top:    public  sector  and  scien1sts.    Lower  down  -­‐  Private  Sector  and  Civil  Society:  the  delivery  of  what  higher  level  stakeholders  consider  useful  informa1on  to  these  more  vulnerable  stakeholders  gets  less  and  less.    

Civil  society  the  loser,  and  an  opportunity  Informa1on  flow  and  knowledge  development  has  the  least  impact  on  those  who  need  it  most:  the  most  vulnerable  and  cri1cal  sectors  that  needing    preven1ve  ac1on,  (life-­‐line  services,  industry,  for  example).        There  is  insufficient  communica1on  to,  and  insufficient  considera1on  of  the  household  and  the  community,  their  individual  engagement.        This  translates  into  an  undervalued  apprecia1on  that  community  and  households  have  capacity,  poten1al,  local  knowledge,  social  structures,  and  responsibili1es.    Insufficient  listening  to  civil  society  and  learning  about  local  prac1ce.      Civil  society  is  the  loser  in  the  informaAon  exchange  process.  Exchange  and  capacity  building  should  be  more  holisAc.  

More  inter-­‐disciplinary  and  holisi1c  effort  •  The  exchange  of  knowledge  cannot  be  considered  in  isola1on,  

just  as  DRR  and  CCA  must  not  be  compartmentalised.    •  The  idea  of  dis1nct  specialist  disciplines  is  outmoded.      •  There  are  signs  of  more  inter-­‐disciplinary  work  about  DRR  and  

CCA,  and  this  is  a  necessity.  

•  To  be  opera1ve,  knowledge  must  be  linked  to  an  enabling  environment,  that  combines  informa1on,  ins1tu1onal  capacity,  financial  systems  and  capacity  building  including  technical  knowledge.  To  consider  knowledge  transfer  for  disaster  risk  reduc1on  without  doing  this  is  a  route  to  failure.  

More  knowledge  or  more  uncertainty?  •  Changes  in  context,  such  as  urbanisa1on,  and  change  in  

weather  and  climate  reduce  faith  in  old  &  local  knowledge  •  Lack  of  knowledge  on  what  to  do  about  DRR  and  CCA  ac1ons  

generates  uncertainty.    •  Uncertainty  leads  to  lack  of  ac1on  before  and  at  cri1cal  1mes  

in  the  disaster  management  cycle.  

 The  mapping  process  has  highlighted    the  need  to    improve  the  transforma1on  of  informa1on  into  contemporary  and  applicable  knowledge  that  leads  to  ac1on  

 Thank  you