White Papers The Evolution of Smart Commodity Management | Page 5

Smart  Commodity  Management                                                                                                                                                                                                                                  A  ComTech  Advisory  Whitepaper   Of  course,  while  all  of  this  evolution  and  change  was  going  on  in  the  commodities  markets,  significant  change  was   also   occurring   in   information   processing   and   technologies.   Vendors   were   able   to   leverage   these   newer   technologies,   increasing   processing   speeds,   improving   “The  use  of  big  data  will  become  a  key  basis  of   the   user   experience,   and   introducing   greater   competition  and  growth  for  individual  firms.  From  the   modularization   of   the   applications   -­‐   allowing   buyers   standpoint  of  competitiveness  and  the  potential  capture   to  pick  and  choose  just  what  they  needed  within  the   of  value,  all  companies  need  to  take  big  data  seriously.  In   common  CM  footprint.  The  use  of  flexible  tools  meant   most  industries,  established  competitors  and  new   that   the   software   could   be   more   configurable   and   entrants  alike  will  leverage  data-­‐driven  strategies  to   personalizable,   reducing   implementation   timescales   innovate,  compete,  and  capture  value  from  deep  and  up-­‐ and   improving   the   users’   interaction   experience   with   to-­‐real-­‐time  information.”  McKinsey  &  Co.,  Big  data:  The   next  frontier  for  innovation,  competition,  and  productivity.   the   software.   These   new   technologies   have   also   allowed   improved   data   visualization,   increasing   productivity   and   enhanci ng   risk   management   capabilities.   Finally,   newer   architectures   also   improved   the   connectivity  of  the  CM  solutions  making  it  easier  to  interface  or  integrate  with  third-­‐party  software.     Underlying  all  of  this  however  is  data.  Back  in  the  early  days  of  natural  gas  marketing  systems,  all  that  was  really   needed  was  daily  volume  and  price  data.  As  the  industry  evolved,  more  and  more  data  was  generated,  stored  and   processed.   Simple   data   sets   grew   to   incorporate   massive   time   series   data   sets   (and   multiple   versions   of   the   same   data)  for  forward  curves  and  expanded  details  for  deals  needed  to  be  captured  such  as  contract  terms,  complex   price  structures,  timelines,  quality  requirements,  weights,  and  so  on.  Document  images  and  other  types  of  non-­‐ standard   data   were   increasingly   required   to   be   stored,   especially   associated   with   scheduling   and   supply   chains.   On   the   trading   side,   storage   of   phone   recordings,   IM   logs   and   other   evidence   of   negotiations   became   more   important  as  regulations  and  regulatory  oversight  increased.    These  regulations,  such  as  Dodd  Frank  in  the  US  and   EMIR  and  REMIT  in  Europe,  have  placed  increased  demands  on  the  technologies  of  trading,  requiring  high  levels   of   transparency   and   reporting,   including   trade   reporting   to   central   repositories.   Essentially,   as   the   CM   software   category  expanded,  evolved  and  matured,  so  did  the  data  management  requirements  -­‐  Big  Data,  both  structured   and  unstructured,  needed  to  be  better  stored,  manipulated  and  displayed.   Smart  Commodity  Management     A   key   requirement   of   Commodity   Management   is   that   it   needs   to   assist   users   in   making   informed   decisions   by   transforming   large   amounts   of   data   into   insights   by   providing   predictive   and   user   controllable   analytics.   Smart   commodity  management  solutions  must  provide  real-­‐time,  meaningful  and  actionable  information  to  traders,  risk   managers  and  executives  in  order  to  enable  them  to  view,  analyze  and  simulate  positions,  market  movements  and   risk   metrics.  Users  need   to   be   able   to  monitor  metrics  like  position,  exposure,   inventory,  in-­‐transit  movements,   scheduled  movements,  counterparty  risk  limits,  P&L,  and  so  on  by  both  commodity  and  instrument  type,  across   both  physicals  and  derivatives,  enterprise-­‐wide  or  via  drill-­‐down  to  trading  unit  and  individual  trader  levels.  Smart   Commodity   Management   must   provide   a   wide   range   of   tools   to   mine,   analyze   and   generate   insights   from   transactional  data,  for  use  not  only  in  strategic  decision-­‐making  by  C-­‐level  executives,  but  also  by  risk  managers   and  traders  for  tactical  purposes.   Unfortunately,   most   of   today’s   CM   software   systems   have   a   legacy   of   being   built   as   client/server   solutions,   focused   primarily   on   capturing   and   storing   transaction   data.   While   they   do   provide   some   tools   to   analyze   and   report   that   transactional   data,   these   capabilities   are   by   and   large   standard   risk   calculations   (such   as   VAR)   and   ©  Commodity  Technology  Advisory  LLC,  2014           5