The paradox of service industrialization

The  paradox  of  Service  Industrializa7on  

Jesus  Alcoba  González,  Ph.D.  16.02.2011  

Service  Systems  

People  

Technology  

Shared  InformaFon  

IFM & IBM.: Succeeding through Service Innovation: A Service Perspective for Education, Research, Business and Government. University of Cambridge Institute for Manufacturing, Cambridge (2008)

three  pilars  of  SSME  

Service  Systems  

People  

Technology  

Shared  InformaFon  

IFM & IBM.: Succeeding through Service Innovation: A Service Perspective for Education, Research, Business and Government. University of Cambridge Institute for Manufacturing, Cambridge (2008)

one  is  less  considered  than  the  rest  

we  do  not  perceive  things  as  they  are  

Rubin,  Wetzler  &  Nebes  (1986)  

we  do  not  remember  things  as  they  are  

98%  

   =              =    

brain  ac7vity  is  internally  focused    

mental  models  

mental  models  create  meaning  

mental  models  create  meaning  

You  have  to  be  very  smart  if  you  can  read  this.  

mental  models  create  meaning  

mental  models  are  difficult  to  change  

mental  models  are  difficult  to  change  

mental  models  are  difficult  to  change  

different  people  =  different  meaning  

(Pine  &  Gilmore,  1998)  

economy  has  changed  

margin  

industrializaFon  

price  

CUSTOMIZATION  

CLIENTS  

PRICE  

INDUSTRIALIZATION  

CLIENTS  

PRICE  

cost  

industraliza7on  and  value  

different  people  =  different  experiences  

different  people  =  same  experience  

High  level  of  industrializa7on.  Top  quality  controls.  Health  protec7on.  Traceability.   …  but  

NO  EXPERIENCE  AT  ALL!  

industraliza7on  and  perceived  value  

experience  design  

(Pine  &  Gilmore,  1998)  

immersion  and  par7cipa7on  

(Treacy  &  Wiersema,  1993)  

personaliza7on  

Immersion  

Personaliza7on  Par7cipa7on  

3  keys  to  build  customer  experience  

Informa7on  Systems   First  contact  with  client  

How  to  increase  the  amount  of  available  informaFon  and  how  it  is  interconnected  in  customers’  databases  so  that  every  department  knows  the  whole  informaFon  about  every  client.  

How  to  increase  interpersonal  adapFve  behaviour  and  service  offering  adaptaFon  to  the  staff  in  contact  with  the  customers,  by  devising  specific  ways  to  deal  with  the  client  depending  on  his/her  profile.    

How  to  present  those  large  amounts  of  informaFon  in  a  way  that  can  be  rapidly  understood  by  computers  and  humans.    

How  to  benefit  from  the  analysis  of  the  first  moment  in  which  a  customer  comes  into  contact  with  the  service  either  virtually  or  personally.    

How  to  interpret  the  behaviour  of  a  client  in  a  specific  moment  according  to  the  past  history  of  that  customer  with  the  service,  and  also  how  to  predict  the  future  behaviour  of  the  customer  based  on  that  history.  

How  to  classify  customers  who  come  into  contact  with  a  service  from  the  first  moment  (classifying  beZer  to  provide  a  more  adapted  service).  

How  to  extract  informaFon  from  client  databases  so  that  the  systems  can  assess  specific  acFons  for  them,  in  order  to  customize  and  enrich  the  service  experience.  

How  to  gather  informaFon  about  client  expectaFons.  

How  to  capture  and  store  subjecFvity  in  databases.     How  to  classify  clients  depending  on  their  need  for  customizaFon.    

Service-­‐client  interac7on   Measuring  

How  to  improve  research  on  customers’  percepFon  of  the  experience  by  introducing  qualitaFve  research  techniques.    

How  to  measure  the  impact  of  outsourcing,  offshoring  and  lean  manufacturing  in  customizaFon.  

How  to  store  customers’  percepFon  of  the  experience  (mainly  if  it  is  negaFve)  and  how  to  use  that  informaFon.    

How  to  measure  the  influence  of  using  automated  systems  in  customers’  percepFon  of  service  value.  

How  to  increase  clients  self  disclosure  of  informaFon.   How  to  measure  the  impact  of  customizaFon  in  service  producFon  cost.  

How  to  benefit  from  service  improvement  ideas  spontaneously  given  by  clients.    

How  to  measure  the  number  of  contacts  or  informaFon  which  a  service  needs  in  order  to  gather  enough  informaFon  from  clients  to  provide  the  required  level  of  customizaFon.  

How  to  interpret  a  client’s  emoFonal  state  by  analyzing  natural  language  automaFcally  (wriZen  or  spoken).    

How  to  measure  client  saFsfacFon  with  the  customizaFon  level.    

20  issues  to  research