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Tighten up the Ship or Build an Airplane? - How to decide?
 

Tighten up the Ship or Build an Airplane? - How to decide?

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Dr. Bush and I describe our experience applying the principles of decision analysis to small business, which typically do not have access to as many informed resources as larger organizations where ...

Dr. Bush and I describe our experience applying the principles of decision analysis to small business, which typically do not have access to as many informed resources as larger organizations where decision analysis is more routinely applied.Published in "Decision Analysis Today," newsletter of the INFORMS Decision Analysis Society, Volume 29, No. 1, April 2010, pg. 16.

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    Tighten up the Ship or Build an Airplane? - How to decide? Tighten up the Ship or Build an Airplane? - How to decide? Document Transcript

    • Tighten  up  the  Ship  or  build  an  Airplane?  -­‐  How  to  decide?     Robert  D.  Brown,  III  and  Gerald  A.  Bush    Tightening  up  the  ship,  rowing  faster,  getting  more  draft  per  stroke,  putting  stronger  rowers  on  the   oars   -­‐   whether   you   are   in   a   short   race   or   taking   a   long   voyage   across   the   sea,   selection   and  use  of  the  most  efficient  resources  and  processes  is  essential.  Sometimes  your  ship  needs  new  oars,  sometimes  better  communication  by  the  coxswain  calling  the  beat,  and  almost  always  a  clearer  map  to  navigate  the  trip  you  are  taking.  These  ideas  are  the  foundation  of  many  modern  business  improvement  initiatives  and  the  type  of  decision  that  leaders  make.    Businesses  seem  to  spend  a  lot  of  time  pursuing  operational  excellence.  A  variety  of  industrial  engineering  methods  exist  today  to  solve  problems  and  redesign  key  processes  and  systems  to  accomplish  this  goal.  Such  process  tools  and  data  analysis  methods  contribute  to  the  rethinking  about   how   products   or   services   are   delivered   internally   to   a   business   or   externally   to   its  customers.   It   has   become   competitively   necessary   to   seek   operational   excellence,   no   matter  what  business  model  or  strategy  you  pursue.     “…operational  excellence  does  not  However,   operational   excellence   does   not   ensure  a  competitive  advantage  assure   a   competitive   advantage   over   others   in   over  others  in  the  game.”  the   game.   Big   sailing   ships   enabled   small  European  countries  to  become  global  empires  in  the  17th  century  by  overpowering  those  who  did  not  have  such  ships  and  guns.  Later  on,  early  20th  century  warship  captains  were  surprised  when   they   looked   up   and   saw   airplanes   about   to   drop   bombs   on   their   ships.   Such   disruptive  competitive   advantages   cannot   be   fully   countered   just   by   redesigning   ships   for   incremental  improvements  in  efficiency,  pursuing  operational  excellence  or  using  advanced  data  analytics.  While  everyone  aims  for  operational  excellence  by  rowing  faster  and  more  efficiently,  someone  else  invents  sails  and  guns.  Then,  all  too  soon,  being  a  player  requires  airplanes  and  bombs.    Operational  excellence  contributes  to  more  efficient  use  of  resources  and  incrementally  better  results  from  existing  business  models,  while  strategic  innovations  explore  valuable  frontiers  or  new   combinations   of   business   models.   In   the   business   world,   an   example   of   “sails   and   guns”  might  be  the  use  of  supply  chain  technology  to  create  an  advantaged  cost  structure  and  high  velocity  in  the  retailing  industry,  e.g.  WalMart.  An  example  of  “airplanes  and  bombs”  might  be  Amazon’s   use   of   the   intelligent   recommendations   to   produce   a   richer   sales   basket   and  distributed   warehousing   with   overnight   shipping   to   obviate   the   need   for   stores.   These  competitive   advantages   allow   such   leaders   to   dominate   their   game,   while   operational  excellence  initiatives  assure  the  scale  and  sustainability  of  their  businesses.      “Big   data,”   “data   visualization,”   and   “analytics”   are   the   hot,   new   trends   offering   insights   into  previously   untapped   value   for   improving   operations.   The   real   time   capability   to   make   tactical  decisions  is  phenomenal.  A  lot  of  expensive  technology  and  systems  will  be  sold  and  attention  paid  to  analytics  in  the  next  few  years  as  this  next  level  of  operational  excellence  is  pursued.  
    • With  all  the  technology  available  today,  analytics  will  quickly  become  another  necessary  ticket  for   operational   excellence   and   profitability   for   your  business  –  as  long  as  the  game  doesn’t  change.     “…the  data  of  a  business  is  a   treasure  trove  for  driving  Is  it  a  problem  when  the  game  changes?   operational  excellence  –  as  long  Business   trends   tend   to   develop   a   life   of   their   own,  demanding   organizational   focus   and   commitment   as  the  game  doesn’t  change.”    to  implementation  of  new  systems  to  improve  the  business.  This  can  prevent  decision  makers  from  recognizing  important  strategic  inflections  or  clearly  understanding  when  change  to  the  underlying  business  model  is  needed.  For  example,  a  recent   Wall   Street   Journal   article   described   how   a   struggling   food   distribution   company  invested   in   a   big   data   analytics   system   to   lift   it   out   of   its   malaise.   The   system   successfully  improved   sales   by   3-­‐4%   over   a   period   of   one   year,   with   incremental   value   per   delivery.   Despite  declaring   success,   it   was   not   clear   if   the   sales   improvement   was   sustainable,   as   it   did   not  expand   the   company’s   addressable   market.   Furthermore,   over   the   same   period   of   time  inflation  increased  by  about  3.5%,  matching  the  improvement  in  sales  for  the  year.    At  the  same  time,  other  food  retailers  were  changing  the  game  with  organic  and  locally  sourced  produce  displayed  in  appealing  fashion  inside  their  big  box  stores.  Trying  to  compete  with  these  players   who   were   achieving   major   gains   in   market   share,   the   management   team   of   the  struggling  food  company  may  have  fallen  prey  to  any  of  three  common  errors:   1. Succumbing  to  the  siren  song  of  trendy  technology  promises  in  a  time  of  desperation,   2. Allowing   operational   tunnel   vision   to   keep   them   from   acknowledging   the   true   nature   of   the  problem,   3. Not  evaluating  strategic  alternatives  that  could  deliver  a  better  return  on  capital.  So,  how  to  get  the  right  perspective  for  decisions?  Data   analytics   and   engineering   methods   look   inside   available   data   and   processes   to   achieve  better  performance  from  an  existing  business  model.  This  is  important,  but  too  much  of  a  focus  on  today  can  make  you  unprepared  for  what  is  coming  next.  Strategic  thinking  is  about  asking,  “What   are   the   real   problems   or   opportunities   we   face?   Have   we   considered   other   ideas   to  create  a  real  competitive  advantage?”  A  robust  business  considers  these  three  scenarios:    Scenario  1  In   a   stable   situation,   visualizing   available   data   is   sufficient   to   make   decisions.   Running   a  manufacturing  plant,  optimizing  a  network,  or  planning  product  allocation  can  rely  on  historic  data  trends  for  making  good  operating  decisions.  In  fact,  losing  time  overanalyzing  things  may  be  counterproductive  in  a  high  velocity  business.  Imagine  a  trading  house  having  the  patience  for  anything  beyond  a  few  fractions  of  a  second  to  capture  an  arbitrage  gap  in  the  market.  Scenario  2  When   there   are   problems   or   opportunities   to   change,   visualizing   data   can   help   to   illustrate   the  gaps.   A   quick   decision   analysis   for   comparing   alternative   solutions   prevents   the   tendency   to  jump   on   the   first   good   idea   that   comes   up.   The   process   may   validate   your   intuitive   hunch   or,   it  may   lead   to   some   ideas   that   better   address   issues   of   alignment,   risk   or   uncertainty   in   the  
    • system.   The   result   will   be   more   informed   decisions,   along   with   the   knowledge   of   what   it   will  take   to   implement   the   change   successfully.   Instead   of   improving   just   a   few   percent,   it   may  provide   a   major   shift   in   growth   potential   or   operating   efficiency.   Also,   by   quantifying   the  business  value  of  initiatives,  decision  analysis  leads  to  more  objective  prioritization  and  focus  of  scarce  resources,  rather  than  overloading  the  organization  with  too  many  things  at  once.  Scenario  3  When   a   business   has   lost   its   competitive  advantage  or  an  idea  comes  up  that  may  be  a  real   “…it  is  usually  the  uncertainties  innovation,   then   a   strategic   decision   analysis   or  risks  that  lead  to  competitive  process   will   be   very   helpful.   It   is   usually   the   advantages.”  uncertainties   or   risks   that   provide   the    opportunity   to   create   a   competitive   advantage.   If   you   can   develop   options   to   navigate   through  the  risks  and  complexities  of  a  situation,  you  can  create  a  dominant,  game-­‐changing  business.  Many   businesses   spend   the   majority   of   their   time   trying   to   win   on   operational   efficiency   alone,  so  they  miss  the  next  big  opportunity.  Xerox  may  be  the  poster  child  for  this,  failing  to  use  the  innovations   from   their   Palo   Alto   Research   Center   (PARC),   while   many   Silicon   Valley   startups  built   new   businesses   around   them,   including   Apple.   Even   for   the   innovators,   however,   their  new   ideas   have   a   time   horizon   when   they   will   be   obsolete.   Once   others   begin   to   figure   out   the  same   information   inefficiencies   and   risks,   the   game   collapses   again   to   one   of   incremental  competition  for  declining  margins.  The  innovation  cycle  needs  to  start  anew.  Let  Decision  Science  be  your  guide  Data  analytics  is  necessary  to  run  a  business,  but  it  is  insufficient  without  decision  analysis  to  quantify   the   value   of   the   ideas   that   emerge   so   you   can   make   good   choices.   An   honest  assessment   about   your   business   situation   and   the   nature   of   the   information   you   have   (facts,  uncertainties,  risks)  avoids  the  biases  and  traps  that  quick  intuitive  decisions  can  lead  you  into.    Having   the   understanding   and   capabilities   to  guide   business   teams   and   decision   makers   “Decision  analysis  can  dramatically  through   a   quality   process   to   create   and   compare   reduce  the  risk  of  being  surprised  alternatives   utilizes   the   full   creativity,   value   of   by  a  wrong  decision  and  being  too  information,   and   value   of   control   available   late  to  do  anything  about  it.”  within  the  risks  and  uncertainties.      Where   it   has   become   a   part   of   the   culture,   executives   consider   decision   analysis   a   significant  competitive  advantage  over  others  who  rely  on  data  analysis  or  assumptions  in  their  business  case   approach   to   making   tough   decisions.   John   W.   Tukey   explained   the   distinction   between  exploratory   data   analysis   and   confirmatory   data   analysis   with   the   quote,   “I   would   rather   be  approximately   right   than   be   precisely   wrong.”   Decision   analysis   can   provide   the   guidance   to  know  when  to  continue  pursuing  operational  excellence  and  how  to  do  so,  or  when  to  switch  to  new  frontiers  of  value  creation.  It  dramatically  reduces  the  risk  of  being  surprised  by  a  wrong  decision  and  being  too  late  to  do  anything  about  it.    
    • Gerald  A.  Bush,  Ph.D.  works  with  companies  on  innovative  business  strategies,   dealing  with  complex  business  decisions  and  building  an  adaptive  approach  in   dynamic  markets.  Typical  clients  have  included  Abbott,  GSK,  J&J,  Kimberly  Clark,   Merck,  Novartis,  Roche,  Delta  Air  Lines,  JetBlue,  Chevron,  Dow,  ExxonMobil,  Shell,   Motorola  and  HP.  Typical  engagements  include  creation  of  novel  product  concepts,   development  of  cost-­‐advantaged  operations,  decisions  on  global  marketing,   organizational  redesign  and  integration  of  acquisitions,  decisions  on  major  facilities   investments,  resolution  of  labor-­‐management  issues  and  adoption  of  information   technology  strategies.  Gary  is  a  graduate  from  Georgia  Institute  of  Technology.    He   is  an  invited  speaker  at  the  New  York  University  Stern  School  for  Business  and  the   Institute  for  Operations  Research  and  Management  Sciences. Robert  D.  Brown,  III  is  an  experienced  decision  strategist  with  over  17  years  of   professional  experience  and  a  world  class  architect  of  complex,  quantitative  models   using  Analytica  software.  He  provides  advanced  decision  guidance,  risk   management,  and  business  analytics  to  help  executive  decision  makers  gain  deep   insights  into  complex  and  risky  capital  investment  opportunities,  system  behavior,   and  planning  exercises.  Some  of  his  clients  have  included  Bechtel-­‐SAIC,  Canon,   Chevron,  Cisco  Systems,  ExxonMobil,  Milliken,  and  Novartis.  Robert  is  a  graduate   from  the  school  of  Mechanical  Engineering  at  Georgia  Institute  of  Technology.