k4 d ws_p_longstaff_bolzano_2013

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Managing uncertainty in resilient organizations P. H. Longstaff Syracuse University KNOW4DRR Bolzano 2013 P.H. Longstaff

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Page 1: K4 d ws_p_longstaff_bolzano_2013

Managing  uncertainty  in  resilient  organizations  P.  H.  Longstaff  Syracuse  University  

KNOW4D

RR      Bo

lzano

 2013                              

P.H.    Lon

gstaff    

Page 2: K4 d ws_p_longstaff_bolzano_2013

Planning  Options  •  Resistance  (The  Citadel)    •  In  baLle,  surprise  or  superior  force  reduces  

ability  to  resist    •  Tendency  to  fail  catastrophically    •  Trust  high  unPl  failure  •  Resilience  (Surviving  to  operate  another  

day)  •  StaPc:  Bouncing  back  –  return  to  “normal”  •  AdapPve:  Bouncing  forward    •  Trust  built  and  reinforced  oYen  

KNOW4D

RR      Bo

lzano

 2013                              

P.H.    Lon

gstaff    

Page 3: K4 d ws_p_longstaff_bolzano_2013

•  For  predictable  systems:    •  Development  of  facts,  reproducibility,  risk  eliminaPon  (resistance)    

•  For  known  unknowns:  •  Cyclical  systems  and  unpredictable  emergence  (power  laws)  •  Development  of  “odds”  and  risk  miPgaPon  (sta8c  resilience)    

•   For  unpredictable  systems:  •  Black  Swans,  new  surprises  •  Development  of  acceptable  parameters;  nudging  and  learning    (adap8ve  resilience)    

 

Goals  for  managing  uncertainty    

Page 4: K4 d ws_p_longstaff_bolzano_2013

“Normal”  distribution  

Normal

Freq

uenc

y

75604530150-15-30

60

50

40

30

20

10

0

A Typical Normal Distribution

Mean~20 ; Std Dev ~20

Normal

Page 5: K4 d ws_p_longstaff_bolzano_2013

Gamma  (Power  Law)  distribution  

Gamma

Freq

uenc

y

1251007550250-25

100

80

60

40

20

0

A Typical Gamma Distribution

Mean~20 ; Std Dev ~20

Page 6: K4 d ws_p_longstaff_bolzano_2013

Power  Laws  and  Hollywood:  Typical  Revenue  pattern    

REVENUE

400.0360.0

320.0280.0

240.0200.0

160.0120.0

80.040.0

0.0

50

40

30

20

10

0

Std. Dev = 70.38 Mean = 57.0

N = 189.00

Page 7: K4 d ws_p_longstaff_bolzano_2013

Resilience  usually  increases  with      • Diversity  –  many  opPons  for  resources  •  Interoperability,  cross-­‐training  • Access  to  other  networks  (bridgers)    

•  IntervenPon  at  the  right  scale  • Right  balance  of  Tight/Loose  Coupling  • Adap8ve  capacity  –  mechanisms  for  • Ability  to  change  • Knowledge  management  (knowing  and  remembering)    

KNOW4D

RR      Bo

lzano

 2013                              

P.H.    Lon

gstaff    

Page 8: K4 d ws_p_longstaff_bolzano_2013

Resilience  requires  trustworthy  information  • Accurate  sensing  of  environment  

•  Watch  out  for  Local  adaptaPon  and  PracPcal  DriY  (ScoL  Snook,  USAF,  ret.)    

•  CounPng  the  right  stuff  (not  what’s  handy,  what  proves  it’s  working)  

•  What  is  NOT  working  (hide  it  or  suffer?)  •  InsPtuPonal  memory  • ConnecPon  to  other  info  and  ideas  • Unexpected  events  “audit”  our  ability  to  adapt  –  how  do  we  learn  from  that?  

KNOW4D

RR      Bo

lzano

 2013                              

P.H.    Lon

gstaff    

Page 9: K4 d ws_p_longstaff_bolzano_2013

Learning  and  Adaptation  are  Lowered  by  •  Hindsight  bias    •  ConfirmaPon  Bias/MoPvated  ScepPcism  •  Overconfidence  in  knowledge  –  “planning  fallacy”  •  No  ba6le  plan  ever  survives  first  contact  with  the  enemy    

 Helmuth  von  Moltke,  A  19th-­‐century  head  of  the  Prussian  army  

•  Plans  can  decrease  mindful  an=cipa=on  of  the  unexpected        Weick  and  Sutcliffe,  Managing  the  Unexpected  

•   Clinging  to  Cogworld  (Microscope  v.  Kaleidoscope  -­‐  NSF)    •  Demands  a  “fix”  –  constrain  system,  new  complexity,  more  uncertainty  

•  The  Blame  Game  •  The  Buck  doesn’t  stop  anywhere  

KNOW4D

RR      Bo

lzano

 2013                              

P.H.    Lon

gstaff    

Page 10: K4 d ws_p_longstaff_bolzano_2013

Changing  the  Game:  building  adaptability  in  environments  with  high  uncertainty  •  Acknowledge  unpredictability  and  create  new  ways  to  learn  and  plan  

•  Create  a  sub-­‐system  for  Pmes  of  crisis  and  plan  how  you  will  learn  in  that  sub-­‐system  

•  Decide  when  improvisaPon  is  going  to  be  OK  and  how  you  can  learn  from  it  

•  Set  up  sensors  that  indicate  when    •  adapPve  mechanisms  are  failing  (e.g.  challenges  

cascade)    •  Ppping  points  are  near  •  buffers/reserves  are  near  exhausPon  

KNOW4D

RR      Bo

lzano

 2013                              

P.H.    Lon

gstaff    

Page 11: K4 d ws_p_longstaff_bolzano_2013

Heroes  of  Uncertainty    •  Combine  an  awareness  of  common  paLerns  with  an  acute  aLenPon  to  the  specific  circumstances  of  a  unique  situaPon.  

•  David  Brooks  NYT  28  May  2013  

•  Understand  that  they  don’t  know  it  all  –  humility.  •  Know  that  they  may  fail  and  accept  it  as  a  temporary  set-­‐back.  

KNOW4D

RR      Bo

lzano

 2013                              

P.H.    Lon

gstaff