SlideShare a Scribd company logo
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Learn	
  How	
  To	
  Find	
  The	
  
Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter	
  
	
  
	
  
	
  
December	
  2015	
  
#NewMR	
  2015	
  	
  
Corporate	
  Sponsors	
  
#NewMR	
  2015	
  	
  
Supporters	
  
Schlesinger	
  Associates	
  
Keen	
  as	
  Mustard	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Why	
  are	
  we	
  interested	
  in	
  storytelling?	
  
Memorable	
  
ABenCon	
  
Grabbing	
  
Easier	
  to	
  
understand	
  
Gives	
  
coherent	
  
message	
  
Shows	
  we	
  
understand	
  it	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
The	
  data	
  doesn’t	
  
speak	
  for	
  itself	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Storytelling	
  –	
  NarraHve	
  Theme	
  	
  
Wake	
  
Breakfast	
  
Travel	
  
Work	
  
Lunch	
  
Work	
  
Drinking	
  
Travel	
  
Sleep	
  
Get	
  changed	
  
Warm	
  up	
  
Run	
  
Warm	
  down	
  
Shower	
  
Get	
  changed	
  
•  Smallpox	
  emerged	
  
about	
  10,000	
  years	
  ago	
  
•  300-­‐500	
  million	
  deaths	
  during	
  
20th	
  Century	
  
•  One	
  of	
  the	
  first	
  to	
  be	
  tackled	
  
by	
  vaccinaCon	
  
•  Declared	
  exCnct	
  in	
  1979	
  
•  One	
  of	
  only	
  2	
  so	
  far	
  
(Rinderpest)	
  
•  Let’s	
  tackle	
  others,	
  e.g.	
  Polio	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Frameworks	
  
Most	
  of	
  the	
  teams	
  that	
  reliably	
  produce	
  good	
  analysis	
  
and	
  useful	
  stories	
  use	
  frameworks	
  
–  Individuals	
  are	
  less	
  dependent	
  on	
  frameworks	
  
Elements	
  of	
  frameworks	
  
–  How	
  to	
  frame	
  the	
  problem	
  
–  Linking	
  the	
  project	
  to	
  a	
  wider	
  context	
  
–  A	
  standard	
  method	
  of	
  organising	
  the	
  data	
  (qual	
  and	
  quant)	
  
–  SystemaCc	
  methods	
  of	
  analysing	
  data	
  
–  A	
  preferred	
  method	
  for	
  extracCng	
  the	
  story	
  and	
  linking	
  it	
  
the	
  wider	
  context	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Further	
  Reading	
  
Published	
  by	
  Wiley,	
  2004	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
From	
  Data	
  to	
  Stories	
  
1.  Define	
  the	
  problem	
  
2.  Establish	
  what	
  is	
  currently	
  known/believed	
  
3.  Check	
  and	
  organise	
  the	
  data	
  
4.  Find	
  the	
  message	
  in	
  the	
  data	
  
5.  Cra`	
  and	
  tell	
  the	
  story	
  
Starts	
  when	
  the	
  request	
  for	
  a	
  study	
  emerges.	
  It	
  
does	
  NOT	
  start	
  when	
  the	
  fieldwork	
  finishes.	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Define	
  the	
  Problem	
  
“A	
  problem	
  defined	
  is	
  a	
  problem	
  half-­‐solved”	
  
Sources	
  of	
  informaCon:	
  
–  The	
  request	
  for	
  a	
  study	
  
–  The	
  proposal	
  
–  Discussions	
  between	
  sponsor,	
  insight	
  team	
  and	
  supplier	
  
•  What	
  is	
  the	
  background	
  to	
  the	
  project?	
  
•  What	
  would	
  success	
  look	
  like?	
  
•  What	
  acCons	
  should	
  follow	
  from	
  the	
  research?	
  
•  What	
  do	
  people	
  think	
  the	
  results	
  are	
  going	
  to	
  be?	
  
(Or,	
  what	
  are	
  the	
  prevalent	
  hypotheses?)	
  
Smith	
  &	
  Fletcher,	
  2004	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Establish	
  What	
  is	
  Already	
  Known?	
  
•  The	
  frameworks	
  approach	
  avoids	
  focusing	
  on	
  
just	
  the	
  current	
  research	
  project	
  
•  The	
  analysis,	
  the	
  validity,	
  and	
  the	
  story	
  need	
  to	
  
blend	
  research	
  with	
  the	
  wider	
  context	
  
•  The	
  context	
  is	
  a	
  web	
  of	
  exisCng	
  knowledge:	
  
–  Within	
  your	
  organisaCon	
  
–  Within	
  the	
  agency/supplier	
  
–  In	
  the	
  public	
  realm	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Who	
  is	
  the	
  project	
  for?	
  	
  _________________	
  
	
  
What	
  is	
  the	
  business	
  issue/problem	
  that	
  is	
  being	
  addressed?	
  
__________________________________________________	
  
	
  
What	
  does	
  the	
  business	
  want	
  to	
  do,	
  once	
  it	
  has	
  addressed	
  this	
  issue?	
  
______________________________________________________	
  
	
  
What	
  do	
  we	
  already	
  know?	
  
	
  Item 	
  Held	
  by: 	
  DescripHon	
  
1  	
   	
  ______ 	
  ______ 	
  ______________	
  
2  	
   	
  ______ 	
  ______ 	
  ______________	
  
3  	
   	
  ______ 	
  ______ 	
  ______________	
  
	
  
AssumpHons	
  and	
  predicHons	
  
	
  Who 	
  What	
  
1.  	
   	
  ______ 	
  ______	
  
2.  	
   	
  ______ 	
  ______	
  
Simplified	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Assembling	
  the	
  Evidence	
  
•  QuanCtaCve	
  
– Standardize?	
  Missing	
  Data?	
  Indexing?	
  Re-­‐basing?	
  
•  QualitaCve	
  
– TranslaCons?	
  Transcripts?	
  Notes?	
  
•  The	
  nature	
  of	
  the	
  sources	
  
– Credibility?	
  Bias?	
  InteracCons?	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Normalising	
  by	
  ‘Share	
  of’	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
‘Share	
  of’	
  is	
  a	
  relaHve	
  measure	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Normalizing	
  by	
  Coding	
  
•  SenCment	
  analysis,	
  open-­‐ended	
  comments	
  
converted	
  to	
  PosiCve,	
  NegaCve	
  and	
  Neutral	
  
•  DigiCzing	
  from	
  analogue	
  to	
  binary	
  
•  AllocaCng	
  to	
  segments	
  
•  Scoring	
  different	
  elements	
  
–  (think	
  American	
  Football	
  or	
  Rugby,	
  different	
  points	
  for	
  
different	
  events,	
  leading	
  to	
  points	
  in	
  a	
  league)	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Normalizing	
  by	
  
Growth	
  PaXerns	
  
Forbes:	
  hBp://bit.ly/NewMR_208	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Is	
  My	
  Data	
  Right?	
  
We	
  see	
  paBerns,	
  even	
  
when	
  they	
  are	
  not	
  there.	
  
	
  
Image	
  from	
  Viking	
  I,	
  1976	
  
Mars	
  –	
  led	
  to	
  theories	
  of	
  
intelligent	
  life.	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Spurious	
  CorrelaHons	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
HRT	
  and	
  CHD	
  
•  Several	
  studies	
  showed	
  that	
  women	
  taking	
  HRT	
  
were	
  less	
  likely	
  to	
  suffer	
  from	
  coronary	
  heart	
  disease	
  
•  Some	
  leading	
  doctors	
  propose	
  that	
  HRT	
  was	
  protecCng	
  
women	
  against	
  CHD	
  
•  Randomised	
  Controlled	
  tests	
  showed	
  that	
  HRT	
  created	
  
a	
  slight	
  increase	
  in	
  risk	
  of	
  CHD	
  
•  Huh!	
  
–  Women	
  taking	
  HRT	
  were	
  typically	
  from	
  higher	
  income,	
  
healthier	
  groups	
  in	
  society	
  –	
  who	
  have	
  lower	
  rates	
  of	
  CHD	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Embedding	
  Frameworks	
  
•  Establish	
  your	
  framework	
  
•  Share	
  it	
  with	
  colleagues	
  
•  Share	
  it	
  with	
  suppliers	
  
•  New	
  projects	
  can	
  be	
  designed	
  to	
  produce	
  
inputs	
  that	
  work	
  well	
  with	
  the	
  framework	
  you	
  
are	
  using	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Finding	
  the	
  Story	
  
1.  Know	
  what	
  the	
  quesCon	
  is.	
  Have	
  an	
  idea	
  of	
  
what	
  success	
  looks	
  like.	
  
2.  What	
  is	
  the	
  big	
  story?	
  
–  What	
  do	
  most	
  people	
  do?	
  Why	
  do	
  most	
  people	
  do	
  it?	
  
3.  What	
  are	
  the	
  relevant	
  excepCons?	
  
4.  Determine	
  how	
  the	
  message	
  in	
  the	
  data	
  
answers	
  the	
  business	
  quesCon	
  and	
  cra`	
  that	
  as	
  
a	
  story.	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Find	
  the	
  Total	
  Picture	
  First	
  
Then	
  the	
  relevant	
  detail	
  
Quant	
  
•  Look	
  at	
  the	
  Total	
  Column	
  
•  Look	
  for	
  big	
  numbers	
  and	
  
big	
  paBerns	
  
•  What	
  is	
  the	
  big	
  picture?	
  
•  This	
  will	
  frame	
  the	
  detail	
  
Qual	
  
•  Read	
  the	
  transcripts	
  
–  Unless	
  you	
  conducted	
  the	
  
fieldwork	
  
•  Create	
  notes	
  and	
  memos	
  
•  What	
  are	
  the	
  main	
  
messages	
  
In	
  the	
  context	
  of	
  the	
  Business	
  QuesCon	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Where	
  does	
  the	
  best	
  MR	
  come	
  from?	
  
Column	
  %	
   Which	
  of	
  the	
  following	
  best	
  describes	
  you?	
   Countries	
  Merged	
  
Total	
   Research	
  or	
  
Consultancy	
  
Supplier	
  
Supplier	
  to	
  the	
  
research	
  industry	
  
Research	
  Buyer/
User	
  
Academic	
  +	
  Other	
   English	
  Speaking	
   Non-­‐English	
  
Speaking	
  
UK	
   63%	
   61%	
   60%	
   92%	
   40%	
   66%	
   60%	
  
USA	
   51%	
   52%	
   50%	
   46%	
   60%	
   52%	
   50%	
  
Germany	
   18%	
   13%	
   30%	
   15%	
   60%	
   16%	
   21%	
  
Australia	
   15%	
   14%	
   15%	
   15%	
   20%	
   16%	
   12%	
  
Canada	
   11%	
   8%	
   20%	
   0%	
   40%	
   9%	
   14%	
  
France	
   7%	
   7%	
   10%	
   8%	
   0%	
   7%	
   7%	
  
Japan	
   5%	
   3%	
   15%	
   0%	
   0%	
   3%	
   7%	
  
Brazil	
   3%	
   3%	
   5%	
   0%	
   0%	
   3%	
   2%	
  
China	
   2%	
   1%	
   5%	
   0%	
   0%	
   3%	
   0%	
  
Italy	
   2%	
   1%	
   5%	
   0%	
   0%	
   0%	
   5%	
  
Other	
   8%	
   10%	
   10%	
   0%	
   0%	
   9%	
   7%	
  
None	
  of	
  these	
   11%	
   15%	
   5%	
   0%	
   0%	
   9%	
   14%	
  
Column	
  n	
   109	
   71	
   20	
   13	
   5	
   67	
   42	
  
The	
  wrong	
  approach	
  to	
  starCng	
  analysis	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Where	
  does	
  the	
  best	
  MR	
  come	
  from?	
  
Column	
  %	
   Which	
  of	
  the	
  following	
  best	
  describes	
  you?	
   Countries	
  Merged	
  
Total	
   Research	
  or	
  
Consultancy	
  
Supplier	
  
Supplier	
  to	
  the	
  
research	
  industry	
  
Research	
  Buyer/
User	
  
Academic	
  +	
  Other	
   English	
  Speaking	
   Non-­‐English	
  
Speaking	
  
UK	
   63%	
   61%	
   60%	
   92%	
   40%	
   66%	
   60%	
  
USA	
   51%	
   52%	
   50%	
   46%	
   60%	
   52%	
   50%	
  
Germany	
   18%	
   13%	
   30%	
   15%	
   60%	
   16%	
   21%	
  
Australia	
   15%	
   14%	
   15%	
   15%	
   20%	
   16%	
   12%	
  
Canada	
   11%	
   8%	
   20%	
   0%	
   40%	
   9%	
   14%	
  
France	
   7%	
   7%	
   10%	
   8%	
   0%	
   7%	
   7%	
  
Japan	
   5%	
   3%	
   15%	
   0%	
   0%	
   3%	
   7%	
  
Brazil	
   3%	
   3%	
   5%	
   0%	
   0%	
   3%	
   2%	
  
China	
   2%	
   1%	
   5%	
   0%	
   0%	
   3%	
   0%	
  
Italy	
   2%	
   1%	
   5%	
   0%	
   0%	
   0%	
   5%	
  
Other	
   8%	
   10%	
   10%	
   0%	
   0%	
   9%	
   7%	
  
None	
  of	
  these	
   11%	
   15%	
   5%	
   0%	
   0%	
   9%	
   14%	
  
Column	
  n	
   109	
   71	
   20	
   13	
   5	
   67	
   42	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
0%	
  
10%	
  
20%	
  
30%	
  
40%	
  
50%	
  
60%	
  
70%	
  
Which	
  Country	
  Produces	
  the	
  Best	
  MR?	
  
The	
  Big	
  Message	
  
Big	
  story	
  
QuesHons	
  
Why	
  are	
  the	
  UK	
  &	
  USA	
  so	
  high/different?	
  
Is	
  this	
  true	
  for	
  everybody?	
  
What	
  are	
  the	
  implicaCons	
  of	
  this?	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
The	
  Cartographer	
  and	
  the	
  Journalist	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
The	
  Lead	
  
Nora	
  Ephron	
  
When	
  Harry	
  Met	
  Sally	
  
Sleepless	
  in	
  Sea1le	
  
1st	
  Day	
  in	
  Journalism	
  School	
  
5	
  Ws	
  (Who,	
  What,	
  When,	
  Where	
  &	
  Why?)	
  
	
  
Asked	
  to	
  write	
  the	
  Lead	
  for	
  the	
  school	
  newspaper	
  	
  
“The	
  en3re	
  school	
  faculty	
  will	
  travel	
  to	
  Sacramento	
  next	
  
Thursday	
  for	
  a	
  colloquium	
  in	
  new	
  teaching	
  methods.	
  
Among	
  the	
  speakers	
  will	
  be	
  anthropologist	
  Margaret	
  
Mead,	
  college	
  president	
  Dr.	
  Robert	
  Maynard	
  Hutchins,	
  and	
  
California	
  Governor	
  Edmund	
  Brown.”	
  
	
  
All	
  the	
  students	
  wrote	
  about	
  the	
  5Ws	
  –	
  good,	
  but	
  not	
  
right.	
  
	
  
The	
  Lead?	
  
No	
  school	
  next	
  Thursday!	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Different	
  PerspecHves	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
The	
  Tenuous	
  Link	
  Between	
  Finding	
  the	
  Story	
  
and	
  Telling	
  the	
  Story	
  
•  In	
  finding	
  the	
  story	
  we	
  have	
  mulCple	
  data	
  sources	
  
•  We	
  have	
  differing	
  degrees	
  of	
  confidence	
  in	
  those	
  
sources	
  
–  A	
  conjoint	
  study	
  with	
  consulCng	
  surgeons	
  might	
  be	
  our	
  
best	
  source	
  for	
  finding	
  the	
  story	
  
•  The	
  best	
  way	
  to	
  convey	
  the	
  story	
  does	
  not	
  have	
  to	
  rest	
  
on	
  the	
  ‘best’	
  data	
  
–  A	
  vox	
  pop	
  video	
  with	
  a	
  paCent	
  might	
  be	
  a	
  poor	
  way	
  to	
  find	
  
the	
  story,	
  but	
  it	
  can	
  be	
  a	
  great	
  way	
  to	
  tell	
  the	
  story	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
What	
  are	
  the	
  key	
  findings?	
  
1.  Link	
  to	
  the	
  project	
  objecCves	
  
2.  ‘Need	
  to	
  know’	
  not	
  ‘nice	
  to	
  know’	
  
3.  Supported	
  by	
  paBerns	
  or	
  themes	
  in	
  the	
  data	
  
–  Not	
  just	
  a	
  single	
  data	
  point	
  
4.  Clear	
  findings	
  
–  e.g.	
  In	
  the	
  chart	
  UK	
  and	
  USA	
  were	
  a	
  long	
  way	
  
ahead	
  in	
  terms	
  of	
  Best	
  Research	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Hans	
  Rosling	
  
1.  What	
  is	
  his	
  key	
  message?	
  
2.  What	
  is	
  the	
  story?	
  
3.  What	
  has	
  he	
  le`	
  out?	
   hBps://youtu.be/jbkSRLYSojo	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Hans	
  Rosling	
  &	
  NarraHve	
  Theme?	
  
Key	
  Message:	
  
–  It	
  is	
  possible	
  to	
  tackle	
  world	
  health	
  problems	
  
Key	
  Story:	
  
1.  200	
  years	
  ago	
  short-­‐life	
  expectancy	
  was	
  the	
  norm,	
  then	
  the	
  West	
  
moved	
  ahead,	
  but	
  over	
  the	
  last	
  50	
  years	
  most	
  countries	
  have	
  caught	
  
up	
  
2.  There	
  are	
  some	
  countries	
  sCll	
  behind,	
  and	
  some	
  regions	
  of	
  other	
  
countries,	
  but	
  since	
  most	
  of	
  the	
  world	
  has	
  been	
  solved,	
  the	
  rest	
  can	
  
be	
  
Key	
  narraHve	
  axis:	
  
–  200	
  years	
  from	
  1810,	
  from	
  bad	
  to	
  good	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
What	
  Did	
  Hans	
  Rosling	
  Leave	
  Out?	
  
Numbers:	
  
–  A	
  few	
  dates,	
  3	
  life	
  expectancies,	
  3	
  income	
  levels	
  
–  Based	
  on	
  200	
  countries	
  and	
  120,000	
  numbers	
  
DefiniHons:	
  
–  Which	
  200	
  countries?	
  
–  How	
  did	
  he	
  deal	
  with	
  country	
  amalgamaCon	
  and	
  
fragmentaCon?	
  
517	
  other	
  staHsHcs:	
  
–  GapMinder	
  lists	
  519	
  key	
  global	
  stats,	
  over	
  Cme	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Using	
  an	
  Insight	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
You’re	
  not	
  you	
  when	
  you	
  are	
  hungry	
  
•  People	
  behave	
  differently	
  
when	
  they	
  are	
  hungry	
  
•  Snickers	
  is	
  big	
  enough	
  to	
  
end	
  the	
  hunger	
  
•  Global	
  campaign	
  
–  Local	
  execuCons	
  
•  Sales	
  increase	
  
–  e.g.	
  USA	
  sales	
  +8%	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Developing	
  your	
  narraHve	
  theme	
  
•  Select	
  your	
  primary	
  axis	
  
•  This	
  is	
  the	
  elevator	
  pitch	
  
•  Use	
  a	
  structure	
  that	
  works	
  with	
  the	
  audience	
  
•  Typical	
  USA	
  structure	
  
–  The	
  main	
  finding	
  was	
  X,	
  so	
  we	
  recommend	
  Y	
  &	
  Z	
  
–  Now,	
  let’s	
  tells	
  you	
  why	
  it	
  is	
  X,	
  and	
  why	
  are	
  it’s	
  Y	
  &	
  Z	
  
–  But	
  it	
  can	
  be	
  different	
  in	
  different	
  places	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
The	
  Big	
  Picture	
  
•  Develop	
  a	
  framework	
  approach	
  
•  Define	
  the	
  problem	
  before	
  you	
  try	
  to	
  find	
  the	
  
answer	
  to	
  it	
  
•  Put	
  the	
  research	
  project	
  into	
  the	
  context	
  of	
  what	
  
is	
  already	
  known	
  
•  What	
  do	
  you	
  want	
  the	
  client	
  to	
  think,	
  feel,	
  do	
  
a`er	
  hearing	
  the	
  results?	
  
–  The	
  story	
  is	
  a	
  device	
  to	
  deliver	
  that	
  acCon	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Thank	
  You!	
  
	
  
	
  
Follow	
  me	
  on	
  TwiXer	
  @RayPoynter	
  
	
  
Or	
  sign-­‐up	
  to	
  receive	
  our	
  weekly	
  mailing	
  at	
  	
  
hXp://NewMR.org	
  	
  	
  
Learn	
  How	
  To	
  Find	
  The	
  Story	
  In	
  The	
  Data	
  	
  
Ray	
  Poynter,	
  UK,	
  December	
  2015	
  
Q	
  &	
  A	
  
Ray	
  Poynter	
  
The	
  Future	
  Place	
  
#NewMR	
  2015	
  	
  
Corporate	
  Sponsors	
  
#NewMR	
  2015	
  	
  
Supporters	
  
Schlesinger	
  Associates	
  
Keen	
  as	
  Mustard	
  

More Related Content

What's hot

Ray poynter big data and advanced analytics
Ray poynter big data and advanced analyticsRay poynter big data and advanced analytics
Ray poynter big data and advanced analytics
MROC Japan
 
Ray poynter trends in presenting
Ray poynter trends in presentingRay poynter trends in presenting
Ray poynter trends in presenting
MROC Japan
 
Ray poynter what is hot in market research
Ray poynter what is hot in market researchRay poynter what is hot in market research
Ray poynter what is hot in market research
MROC Japan
 
Ray Poynter - Lecture Series - 2014
Ray Poynter - Lecture Series - 2014Ray Poynter - Lecture Series - 2014
Ray Poynter - Lecture Series - 2014
Ray Poynter
 
Effective Presenting with ‘Think, Feel, Do!’
Effective Presenting with ‘Think, Feel, Do!’Effective Presenting with ‘Think, Feel, Do!’
Effective Presenting with ‘Think, Feel, Do!’
Ray Poynter
 
How to search for insights in survey data
How to search for insights in survey dataHow to search for insights in survey data
How to search for insights in survey data
Ray Poynter
 
Poynter lesson 6
Poynter lesson 6Poynter lesson 6
Poynter lesson 6
Ray Poynter
 
MCG Conference 2020 - Entertaining audiences in a time of crisis
MCG Conference 2020 - Entertaining audiences in a time of crisisMCG Conference 2020 - Entertaining audiences in a time of crisis
MCG Conference 2020 - Entertaining audiences in a time of crisis
One Further
 
Dreams into nightmares
Dreams into nightmaresDreams into nightmares
Dreams into nightmares
Andrew Campbell
 

What's hot (9)

Ray poynter big data and advanced analytics
Ray poynter big data and advanced analyticsRay poynter big data and advanced analytics
Ray poynter big data and advanced analytics
 
Ray poynter trends in presenting
Ray poynter trends in presentingRay poynter trends in presenting
Ray poynter trends in presenting
 
Ray poynter what is hot in market research
Ray poynter what is hot in market researchRay poynter what is hot in market research
Ray poynter what is hot in market research
 
Ray Poynter - Lecture Series - 2014
Ray Poynter - Lecture Series - 2014Ray Poynter - Lecture Series - 2014
Ray Poynter - Lecture Series - 2014
 
Effective Presenting with ‘Think, Feel, Do!’
Effective Presenting with ‘Think, Feel, Do!’Effective Presenting with ‘Think, Feel, Do!’
Effective Presenting with ‘Think, Feel, Do!’
 
How to search for insights in survey data
How to search for insights in survey dataHow to search for insights in survey data
How to search for insights in survey data
 
Poynter lesson 6
Poynter lesson 6Poynter lesson 6
Poynter lesson 6
 
MCG Conference 2020 - Entertaining audiences in a time of crisis
MCG Conference 2020 - Entertaining audiences in a time of crisisMCG Conference 2020 - Entertaining audiences in a time of crisis
MCG Conference 2020 - Entertaining audiences in a time of crisis
 
Dreams into nightmares
Dreams into nightmaresDreams into nightmares
Dreams into nightmares
 

Similar to Finding the story in the data - Ray Poynter - 2015

CIL Stats Workshop April1 2022 Abram Silk.pdf
CIL Stats Workshop April1 2022 Abram Silk.pdfCIL Stats Workshop April1 2022 Abram Silk.pdf
CIL Stats Workshop April1 2022 Abram Silk.pdf
Stephen Abram
 
Poynter lesson 3
Poynter lesson 3Poynter lesson 3
Poynter lesson 3
Ray Poynter
 
Data storytelling sxsw panel submission
Data storytelling   sxsw panel submissionData storytelling   sxsw panel submission
Data storytelling sxsw panel submission
Kerry Edelstein
 
Poynter Lesson 1
Poynter Lesson 1Poynter Lesson 1
Poynter Lesson 1
Ray Poynter
 
Career in Data Science (July 2017, DTLA)
Career in Data Science (July 2017, DTLA)Career in Data Science (July 2017, DTLA)
Career in Data Science (July 2017, DTLA)
Thinkful
 
Lecture #01
Lecture #01Lecture #01
Lecture #01
Konpal Darakshan
 
Getting Started in Data Science
Getting Started in Data ScienceGetting Started in Data Science
Getting Started in Data Science
Thinkful
 
Turning Data into Infographics: An Interactive Workshop for Problem Solvers
Turning Data into Infographics: An Interactive Workshop for Problem SolversTurning Data into Infographics: An Interactive Workshop for Problem Solvers
Turning Data into Infographics: An Interactive Workshop for Problem Solvers
UNCResearchHub
 
Why Every Product Manager Needs to Know Big Data
Why Every Product Manager Needs to Know Big DataWhy Every Product Manager Needs to Know Big Data
Why Every Product Manager Needs to Know Big Data
Jeremy Horn
 
Michael Pocock: Citizen Science Project Design
Michael Pocock: Citizen Science Project DesignMichael Pocock: Citizen Science Project Design
Michael Pocock: Citizen Science Project Design
Alice Sheppard
 
Data Storytelling for Social Change
Data Storytelling for Social ChangeData Storytelling for Social Change
Data Storytelling for Social Change
rahulbot
 
Unicom Big Data Innovation Conference - The return of the narrative
Unicom Big Data Innovation Conference - The return of the narrativeUnicom Big Data Innovation Conference - The return of the narrative
Unicom Big Data Innovation Conference - The return of the narrative
Venkataraman Ramachandran
 
Poynter lesson 4
Poynter lesson 4Poynter lesson 4
Poynter lesson 4
Ray Poynter
 
AMA Iowa - SurveyMonkey (11-13) (Slideshare)
AMA Iowa - SurveyMonkey (11-13) (Slideshare)AMA Iowa - SurveyMonkey (11-13) (Slideshare)
AMA Iowa - SurveyMonkey (11-13) (Slideshare)
Brent Chudoba
 
Poynter lesson 5
Poynter lesson 5Poynter lesson 5
Poynter lesson 5
Ray Poynter
 
Intro to 360giving - BOND Transparency working group
Intro to 360giving - BOND Transparency working groupIntro to 360giving - BOND Transparency working group
Intro to 360giving - BOND Transparency working group
william perrin
 
The ultimate guide to data storytelling | Materclass
The ultimate guide to data storytelling | MaterclassThe ultimate guide to data storytelling | Materclass
The ultimate guide to data storytelling | Materclass
Gramener
 
Telling Stories with Open Data
Telling Stories with Open DataTelling Stories with Open Data
Telling Stories with Open Data
Thomas Robbins
 
Ray Poynter Social Media Research in 2015
Ray Poynter   Social Media Research in 2015Ray Poynter   Social Media Research in 2015
Ray Poynter Social Media Research in 2015
Ray Poynter
 
Poynter Lesson 14
Poynter Lesson 14Poynter Lesson 14
Poynter Lesson 14
Ray Poynter
 

Similar to Finding the story in the data - Ray Poynter - 2015 (20)

CIL Stats Workshop April1 2022 Abram Silk.pdf
CIL Stats Workshop April1 2022 Abram Silk.pdfCIL Stats Workshop April1 2022 Abram Silk.pdf
CIL Stats Workshop April1 2022 Abram Silk.pdf
 
Poynter lesson 3
Poynter lesson 3Poynter lesson 3
Poynter lesson 3
 
Data storytelling sxsw panel submission
Data storytelling   sxsw panel submissionData storytelling   sxsw panel submission
Data storytelling sxsw panel submission
 
Poynter Lesson 1
Poynter Lesson 1Poynter Lesson 1
Poynter Lesson 1
 
Career in Data Science (July 2017, DTLA)
Career in Data Science (July 2017, DTLA)Career in Data Science (July 2017, DTLA)
Career in Data Science (July 2017, DTLA)
 
Lecture #01
Lecture #01Lecture #01
Lecture #01
 
Getting Started in Data Science
Getting Started in Data ScienceGetting Started in Data Science
Getting Started in Data Science
 
Turning Data into Infographics: An Interactive Workshop for Problem Solvers
Turning Data into Infographics: An Interactive Workshop for Problem SolversTurning Data into Infographics: An Interactive Workshop for Problem Solvers
Turning Data into Infographics: An Interactive Workshop for Problem Solvers
 
Why Every Product Manager Needs to Know Big Data
Why Every Product Manager Needs to Know Big DataWhy Every Product Manager Needs to Know Big Data
Why Every Product Manager Needs to Know Big Data
 
Michael Pocock: Citizen Science Project Design
Michael Pocock: Citizen Science Project DesignMichael Pocock: Citizen Science Project Design
Michael Pocock: Citizen Science Project Design
 
Data Storytelling for Social Change
Data Storytelling for Social ChangeData Storytelling for Social Change
Data Storytelling for Social Change
 
Unicom Big Data Innovation Conference - The return of the narrative
Unicom Big Data Innovation Conference - The return of the narrativeUnicom Big Data Innovation Conference - The return of the narrative
Unicom Big Data Innovation Conference - The return of the narrative
 
Poynter lesson 4
Poynter lesson 4Poynter lesson 4
Poynter lesson 4
 
AMA Iowa - SurveyMonkey (11-13) (Slideshare)
AMA Iowa - SurveyMonkey (11-13) (Slideshare)AMA Iowa - SurveyMonkey (11-13) (Slideshare)
AMA Iowa - SurveyMonkey (11-13) (Slideshare)
 
Poynter lesson 5
Poynter lesson 5Poynter lesson 5
Poynter lesson 5
 
Intro to 360giving - BOND Transparency working group
Intro to 360giving - BOND Transparency working groupIntro to 360giving - BOND Transparency working group
Intro to 360giving - BOND Transparency working group
 
The ultimate guide to data storytelling | Materclass
The ultimate guide to data storytelling | MaterclassThe ultimate guide to data storytelling | Materclass
The ultimate guide to data storytelling | Materclass
 
Telling Stories with Open Data
Telling Stories with Open DataTelling Stories with Open Data
Telling Stories with Open Data
 
Ray Poynter Social Media Research in 2015
Ray Poynter   Social Media Research in 2015Ray Poynter   Social Media Research in 2015
Ray Poynter Social Media Research in 2015
 
Poynter Lesson 14
Poynter Lesson 14Poynter Lesson 14
Poynter Lesson 14
 

More from Ray Poynter

The State of AI in Insights and Research 2024: Results and Findings
The State of AI in Insights and Research 2024: Results and FindingsThe State of AI in Insights and Research 2024: Results and Findings
The State of AI in Insights and Research 2024: Results and Findings
Ray Poynter
 
ResearchWiseAI - an artificial intelligence driven research data analysis tool
ResearchWiseAI - an artificial intelligence driven research data analysis toolResearchWiseAI - an artificial intelligence driven research data analysis tool
ResearchWiseAI - an artificial intelligence driven research data analysis tool
Ray Poynter
 
AI-powered interviewing: Best practices from Yasna
AI-powered interviewing: Best practices from YasnaAI-powered interviewing: Best practices from Yasna
AI-powered interviewing: Best practices from Yasna
Ray Poynter
 
Artificial Intelligence and Qual: The Story So Far
Artificial Intelligence and Qual: The Story So FarArtificial Intelligence and Qual: The Story So Far
Artificial Intelligence and Qual: The Story So Far
Ray Poynter
 
State of Research Insights in Q1, 2024 from NewMR
State of Research Insights in Q1, 2024 from NewMRState of Research Insights in Q1, 2024 from NewMR
State of Research Insights in Q1, 2024 from NewMR
Ray Poynter
 
Sudden Death of Beliefs
Sudden Death of BeliefsSudden Death of Beliefs
Sudden Death of Beliefs
Ray Poynter
 
Uncovering Consumers’ Hidden Narratives
Uncovering Consumers’ Hidden NarrativesUncovering Consumers’ Hidden Narratives
Uncovering Consumers’ Hidden Narratives
Ray Poynter
 
Narrative Exploration of New Categories at Mondelēz
Narrative Exploration of New Categories at MondelēzNarrative Exploration of New Categories at Mondelēz
Narrative Exploration of New Categories at Mondelēz
Ray Poynter
 
The Future in Focus
The Future in FocusThe Future in Focus
The Future in Focus
Ray Poynter
 
The Future in Focus
The Future in FocusThe Future in Focus
The Future in Focus
Ray Poynter
 
The State of Insights – September 2023
The State of Insights – September 2023The State of Insights – September 2023
The State of Insights – September 2023
Ray Poynter
 
Research Thinking in the age of AI
Research Thinking in the age of AIResearch Thinking in the age of AI
Research Thinking in the age of AI
Ray Poynter
 
How might AI impact Research and Insights over the next two years?
How might AI impact Research and Insights over the next two years?How might AI impact Research and Insights over the next two years?
How might AI impact Research and Insights over the next two years?
Ray Poynter
 
From Words to Wisdom: Unleashing the Potential of Language Models for Human-C...
From Words to Wisdom: Unleashing the Potential of Language Models for Human-C...From Words to Wisdom: Unleashing the Potential of Language Models for Human-C...
From Words to Wisdom: Unleashing the Potential of Language Models for Human-C...
Ray Poynter
 
ChatGPT for Social Media Listening: practical application with YouScan’s Insi...
ChatGPT for Social Media Listening: practical application with YouScan’s Insi...ChatGPT for Social Media Listening: practical application with YouScan’s Insi...
ChatGPT for Social Media Listening: practical application with YouScan’s Insi...
Ray Poynter
 
Using Generative AI to Assess the Quality of Open-Ended Responses in Surveys
Using Generative AI to Assess the Quality of Open-Ended Responses in SurveysUsing Generative AI to Assess the Quality of Open-Ended Responses in Surveys
Using Generative AI to Assess the Quality of Open-Ended Responses in Surveys
Ray Poynter
 
Exploring the future of verbatim coding with ChatGPT
Exploring the future of verbatim coding with ChatGPTExploring the future of verbatim coding with ChatGPT
Exploring the future of verbatim coding with ChatGPT
Ray Poynter
 
Using Generative AI to bring Qualitative Capabilities to Quantitative Surveys
Using Generative AI to bring Qualitative Capabilities to Quantitative SurveysUsing Generative AI to bring Qualitative Capabilities to Quantitative Surveys
Using Generative AI to bring Qualitative Capabilities to Quantitative Surveys
Ray Poynter
 
How AI / ChatGPT Drives Business Growth
How AI / ChatGPT Drives Business GrowthHow AI / ChatGPT Drives Business Growth
How AI / ChatGPT Drives Business Growth
Ray Poynter
 
Tech for tech’s sake? Learnings from experiments with AI in consumer research
Tech for tech’s sake? Learnings from experiments with AI in consumer researchTech for tech’s sake? Learnings from experiments with AI in consumer research
Tech for tech’s sake? Learnings from experiments with AI in consumer research
Ray Poynter
 

More from Ray Poynter (20)

The State of AI in Insights and Research 2024: Results and Findings
The State of AI in Insights and Research 2024: Results and FindingsThe State of AI in Insights and Research 2024: Results and Findings
The State of AI in Insights and Research 2024: Results and Findings
 
ResearchWiseAI - an artificial intelligence driven research data analysis tool
ResearchWiseAI - an artificial intelligence driven research data analysis toolResearchWiseAI - an artificial intelligence driven research data analysis tool
ResearchWiseAI - an artificial intelligence driven research data analysis tool
 
AI-powered interviewing: Best practices from Yasna
AI-powered interviewing: Best practices from YasnaAI-powered interviewing: Best practices from Yasna
AI-powered interviewing: Best practices from Yasna
 
Artificial Intelligence and Qual: The Story So Far
Artificial Intelligence and Qual: The Story So FarArtificial Intelligence and Qual: The Story So Far
Artificial Intelligence and Qual: The Story So Far
 
State of Research Insights in Q1, 2024 from NewMR
State of Research Insights in Q1, 2024 from NewMRState of Research Insights in Q1, 2024 from NewMR
State of Research Insights in Q1, 2024 from NewMR
 
Sudden Death of Beliefs
Sudden Death of BeliefsSudden Death of Beliefs
Sudden Death of Beliefs
 
Uncovering Consumers’ Hidden Narratives
Uncovering Consumers’ Hidden NarrativesUncovering Consumers’ Hidden Narratives
Uncovering Consumers’ Hidden Narratives
 
Narrative Exploration of New Categories at Mondelēz
Narrative Exploration of New Categories at MondelēzNarrative Exploration of New Categories at Mondelēz
Narrative Exploration of New Categories at Mondelēz
 
The Future in Focus
The Future in FocusThe Future in Focus
The Future in Focus
 
The Future in Focus
The Future in FocusThe Future in Focus
The Future in Focus
 
The State of Insights – September 2023
The State of Insights – September 2023The State of Insights – September 2023
The State of Insights – September 2023
 
Research Thinking in the age of AI
Research Thinking in the age of AIResearch Thinking in the age of AI
Research Thinking in the age of AI
 
How might AI impact Research and Insights over the next two years?
How might AI impact Research and Insights over the next two years?How might AI impact Research and Insights over the next two years?
How might AI impact Research and Insights over the next two years?
 
From Words to Wisdom: Unleashing the Potential of Language Models for Human-C...
From Words to Wisdom: Unleashing the Potential of Language Models for Human-C...From Words to Wisdom: Unleashing the Potential of Language Models for Human-C...
From Words to Wisdom: Unleashing the Potential of Language Models for Human-C...
 
ChatGPT for Social Media Listening: practical application with YouScan’s Insi...
ChatGPT for Social Media Listening: practical application with YouScan’s Insi...ChatGPT for Social Media Listening: practical application with YouScan’s Insi...
ChatGPT for Social Media Listening: practical application with YouScan’s Insi...
 
Using Generative AI to Assess the Quality of Open-Ended Responses in Surveys
Using Generative AI to Assess the Quality of Open-Ended Responses in SurveysUsing Generative AI to Assess the Quality of Open-Ended Responses in Surveys
Using Generative AI to Assess the Quality of Open-Ended Responses in Surveys
 
Exploring the future of verbatim coding with ChatGPT
Exploring the future of verbatim coding with ChatGPTExploring the future of verbatim coding with ChatGPT
Exploring the future of verbatim coding with ChatGPT
 
Using Generative AI to bring Qualitative Capabilities to Quantitative Surveys
Using Generative AI to bring Qualitative Capabilities to Quantitative SurveysUsing Generative AI to bring Qualitative Capabilities to Quantitative Surveys
Using Generative AI to bring Qualitative Capabilities to Quantitative Surveys
 
How AI / ChatGPT Drives Business Growth
How AI / ChatGPT Drives Business GrowthHow AI / ChatGPT Drives Business Growth
How AI / ChatGPT Drives Business Growth
 
Tech for tech’s sake? Learnings from experiments with AI in consumer research
Tech for tech’s sake? Learnings from experiments with AI in consumer researchTech for tech’s sake? Learnings from experiments with AI in consumer research
Tech for tech’s sake? Learnings from experiments with AI in consumer research
 

Recently uploaded

BÀI TẬP BỔ TRỢ TIẾNG ANH 8 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2023-2024 (CÓ FI...
BÀI TẬP BỔ TRỢ TIẾNG ANH 8 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2023-2024 (CÓ FI...BÀI TẬP BỔ TRỢ TIẾNG ANH 8 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2023-2024 (CÓ FI...
BÀI TẬP BỔ TRỢ TIẾNG ANH 8 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2023-2024 (CÓ FI...
Nguyen Thanh Tu Collection
 
HYPERTENSION - SLIDE SHARE PRESENTATION.
HYPERTENSION - SLIDE SHARE PRESENTATION.HYPERTENSION - SLIDE SHARE PRESENTATION.
HYPERTENSION - SLIDE SHARE PRESENTATION.
deepaannamalai16
 
A Visual Guide to 1 Samuel | A Tale of Two Hearts
A Visual Guide to 1 Samuel | A Tale of Two HeartsA Visual Guide to 1 Samuel | A Tale of Two Hearts
A Visual Guide to 1 Samuel | A Tale of Two Hearts
Steve Thomason
 
spot a liar (Haiqa 146).pptx Technical writhing and presentation skills
spot a liar (Haiqa 146).pptx Technical writhing and presentation skillsspot a liar (Haiqa 146).pptx Technical writhing and presentation skills
spot a liar (Haiqa 146).pptx Technical writhing and presentation skills
haiqairshad
 
Film vocab for eal 3 students: Australia the movie
Film vocab for eal 3 students: Australia the movieFilm vocab for eal 3 students: Australia the movie
Film vocab for eal 3 students: Australia the movie
Nicholas Montgomery
 
SWOT analysis in the project Keeping the Memory @live.pptx
SWOT analysis in the project Keeping the Memory @live.pptxSWOT analysis in the project Keeping the Memory @live.pptx
SWOT analysis in the project Keeping the Memory @live.pptx
zuzanka
 
Traditional Musical Instruments of Arunachal Pradesh and Uttar Pradesh - RAYH...
Traditional Musical Instruments of Arunachal Pradesh and Uttar Pradesh - RAYH...Traditional Musical Instruments of Arunachal Pradesh and Uttar Pradesh - RAYH...
Traditional Musical Instruments of Arunachal Pradesh and Uttar Pradesh - RAYH...
imrankhan141184
 
REASIGNACION 2024 UGEL CHUPACA 2024 UGEL CHUPACA.pdf
REASIGNACION 2024 UGEL CHUPACA 2024 UGEL CHUPACA.pdfREASIGNACION 2024 UGEL CHUPACA 2024 UGEL CHUPACA.pdf
REASIGNACION 2024 UGEL CHUPACA 2024 UGEL CHUPACA.pdf
giancarloi8888
 
Stack Memory Organization of 8086 Microprocessor
Stack Memory Organization of 8086 MicroprocessorStack Memory Organization of 8086 Microprocessor
Stack Memory Organization of 8086 Microprocessor
JomonJoseph58
 
Electric Fetus - Record Store Scavenger Hunt
Electric Fetus - Record Store Scavenger HuntElectric Fetus - Record Store Scavenger Hunt
Electric Fetus - Record Store Scavenger Hunt
RamseyBerglund
 
writing about opinions about Australia the movie
writing about opinions about Australia the moviewriting about opinions about Australia the movie
writing about opinions about Australia the movie
Nicholas Montgomery
 
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
GeorgeMilliken2
 
math operations ued in python and all used
math operations ued in python and all usedmath operations ued in python and all used
math operations ued in python and all used
ssuser13ffe4
 
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...
PECB
 
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UP
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPLAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UP
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UP
RAHUL
 
NEWSPAPERS - QUESTION 1 - REVISION POWERPOINT.pptx
NEWSPAPERS - QUESTION 1 - REVISION POWERPOINT.pptxNEWSPAPERS - QUESTION 1 - REVISION POWERPOINT.pptx
NEWSPAPERS - QUESTION 1 - REVISION POWERPOINT.pptx
iammrhaywood
 
How to Setup Warehouse & Location in Odoo 17 Inventory
How to Setup Warehouse & Location in Odoo 17 InventoryHow to Setup Warehouse & Location in Odoo 17 Inventory
How to Setup Warehouse & Location in Odoo 17 Inventory
Celine George
 
Walmart Business+ and Spark Good for Nonprofits.pdf
Walmart Business+ and Spark Good for Nonprofits.pdfWalmart Business+ and Spark Good for Nonprofits.pdf
Walmart Business+ and Spark Good for Nonprofits.pdf
TechSoup
 
B. Ed Syllabus for babasaheb ambedkar education university.pdf
B. Ed Syllabus for babasaheb ambedkar education university.pdfB. Ed Syllabus for babasaheb ambedkar education university.pdf
B. Ed Syllabus for babasaheb ambedkar education university.pdf
BoudhayanBhattachari
 
مصحف القراءات العشر أعد أحرف الخلاف سمير بسيوني.pdf
مصحف القراءات العشر   أعد أحرف الخلاف سمير بسيوني.pdfمصحف القراءات العشر   أعد أحرف الخلاف سمير بسيوني.pdf
مصحف القراءات العشر أعد أحرف الخلاف سمير بسيوني.pdf
سمير بسيوني
 

Recently uploaded (20)

BÀI TẬP BỔ TRỢ TIẾNG ANH 8 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2023-2024 (CÓ FI...
BÀI TẬP BỔ TRỢ TIẾNG ANH 8 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2023-2024 (CÓ FI...BÀI TẬP BỔ TRỢ TIẾNG ANH 8 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2023-2024 (CÓ FI...
BÀI TẬP BỔ TRỢ TIẾNG ANH 8 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2023-2024 (CÓ FI...
 
HYPERTENSION - SLIDE SHARE PRESENTATION.
HYPERTENSION - SLIDE SHARE PRESENTATION.HYPERTENSION - SLIDE SHARE PRESENTATION.
HYPERTENSION - SLIDE SHARE PRESENTATION.
 
A Visual Guide to 1 Samuel | A Tale of Two Hearts
A Visual Guide to 1 Samuel | A Tale of Two HeartsA Visual Guide to 1 Samuel | A Tale of Two Hearts
A Visual Guide to 1 Samuel | A Tale of Two Hearts
 
spot a liar (Haiqa 146).pptx Technical writhing and presentation skills
spot a liar (Haiqa 146).pptx Technical writhing and presentation skillsspot a liar (Haiqa 146).pptx Technical writhing and presentation skills
spot a liar (Haiqa 146).pptx Technical writhing and presentation skills
 
Film vocab for eal 3 students: Australia the movie
Film vocab for eal 3 students: Australia the movieFilm vocab for eal 3 students: Australia the movie
Film vocab for eal 3 students: Australia the movie
 
SWOT analysis in the project Keeping the Memory @live.pptx
SWOT analysis in the project Keeping the Memory @live.pptxSWOT analysis in the project Keeping the Memory @live.pptx
SWOT analysis in the project Keeping the Memory @live.pptx
 
Traditional Musical Instruments of Arunachal Pradesh and Uttar Pradesh - RAYH...
Traditional Musical Instruments of Arunachal Pradesh and Uttar Pradesh - RAYH...Traditional Musical Instruments of Arunachal Pradesh and Uttar Pradesh - RAYH...
Traditional Musical Instruments of Arunachal Pradesh and Uttar Pradesh - RAYH...
 
REASIGNACION 2024 UGEL CHUPACA 2024 UGEL CHUPACA.pdf
REASIGNACION 2024 UGEL CHUPACA 2024 UGEL CHUPACA.pdfREASIGNACION 2024 UGEL CHUPACA 2024 UGEL CHUPACA.pdf
REASIGNACION 2024 UGEL CHUPACA 2024 UGEL CHUPACA.pdf
 
Stack Memory Organization of 8086 Microprocessor
Stack Memory Organization of 8086 MicroprocessorStack Memory Organization of 8086 Microprocessor
Stack Memory Organization of 8086 Microprocessor
 
Electric Fetus - Record Store Scavenger Hunt
Electric Fetus - Record Store Scavenger HuntElectric Fetus - Record Store Scavenger Hunt
Electric Fetus - Record Store Scavenger Hunt
 
writing about opinions about Australia the movie
writing about opinions about Australia the moviewriting about opinions about Australia the movie
writing about opinions about Australia the movie
 
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
 
math operations ued in python and all used
math operations ued in python and all usedmath operations ued in python and all used
math operations ued in python and all used
 
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...
 
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UP
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPLAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UP
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UP
 
NEWSPAPERS - QUESTION 1 - REVISION POWERPOINT.pptx
NEWSPAPERS - QUESTION 1 - REVISION POWERPOINT.pptxNEWSPAPERS - QUESTION 1 - REVISION POWERPOINT.pptx
NEWSPAPERS - QUESTION 1 - REVISION POWERPOINT.pptx
 
How to Setup Warehouse & Location in Odoo 17 Inventory
How to Setup Warehouse & Location in Odoo 17 InventoryHow to Setup Warehouse & Location in Odoo 17 Inventory
How to Setup Warehouse & Location in Odoo 17 Inventory
 
Walmart Business+ and Spark Good for Nonprofits.pdf
Walmart Business+ and Spark Good for Nonprofits.pdfWalmart Business+ and Spark Good for Nonprofits.pdf
Walmart Business+ and Spark Good for Nonprofits.pdf
 
B. Ed Syllabus for babasaheb ambedkar education university.pdf
B. Ed Syllabus for babasaheb ambedkar education university.pdfB. Ed Syllabus for babasaheb ambedkar education university.pdf
B. Ed Syllabus for babasaheb ambedkar education university.pdf
 
مصحف القراءات العشر أعد أحرف الخلاف سمير بسيوني.pdf
مصحف القراءات العشر   أعد أحرف الخلاف سمير بسيوني.pdfمصحف القراءات العشر   أعد أحرف الخلاف سمير بسيوني.pdf
مصحف القراءات العشر أعد أحرف الخلاف سمير بسيوني.pdf
 

Finding the story in the data - Ray Poynter - 2015

  • 1. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Learn  How  To  Find  The   Story  In  The  Data     Ray  Poynter         December  2015   #NewMR  2015     Corporate  Sponsors   #NewMR  2015     Supporters   Schlesinger  Associates   Keen  as  Mustard  
  • 2. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Why  are  we  interested  in  storytelling?   Memorable   ABenCon   Grabbing   Easier  to   understand   Gives   coherent   message   Shows  we   understand  it  
  • 3. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   The  data  doesn’t   speak  for  itself  
  • 4. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Storytelling  –  NarraHve  Theme     Wake   Breakfast   Travel   Work   Lunch   Work   Drinking   Travel   Sleep   Get  changed   Warm  up   Run   Warm  down   Shower   Get  changed   •  Smallpox  emerged   about  10,000  years  ago   •  300-­‐500  million  deaths  during   20th  Century   •  One  of  the  first  to  be  tackled   by  vaccinaCon   •  Declared  exCnct  in  1979   •  One  of  only  2  so  far   (Rinderpest)   •  Let’s  tackle  others,  e.g.  Polio  
  • 5. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Frameworks   Most  of  the  teams  that  reliably  produce  good  analysis   and  useful  stories  use  frameworks   –  Individuals  are  less  dependent  on  frameworks   Elements  of  frameworks   –  How  to  frame  the  problem   –  Linking  the  project  to  a  wider  context   –  A  standard  method  of  organising  the  data  (qual  and  quant)   –  SystemaCc  methods  of  analysing  data   –  A  preferred  method  for  extracCng  the  story  and  linking  it   the  wider  context  
  • 6. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Further  Reading   Published  by  Wiley,  2004  
  • 7. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   From  Data  to  Stories   1.  Define  the  problem   2.  Establish  what  is  currently  known/believed   3.  Check  and  organise  the  data   4.  Find  the  message  in  the  data   5.  Cra`  and  tell  the  story   Starts  when  the  request  for  a  study  emerges.  It   does  NOT  start  when  the  fieldwork  finishes.  
  • 8. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Define  the  Problem   “A  problem  defined  is  a  problem  half-­‐solved”   Sources  of  informaCon:   –  The  request  for  a  study   –  The  proposal   –  Discussions  between  sponsor,  insight  team  and  supplier   •  What  is  the  background  to  the  project?   •  What  would  success  look  like?   •  What  acCons  should  follow  from  the  research?   •  What  do  people  think  the  results  are  going  to  be?   (Or,  what  are  the  prevalent  hypotheses?)   Smith  &  Fletcher,  2004  
  • 9. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Establish  What  is  Already  Known?   •  The  frameworks  approach  avoids  focusing  on   just  the  current  research  project   •  The  analysis,  the  validity,  and  the  story  need  to   blend  research  with  the  wider  context   •  The  context  is  a  web  of  exisCng  knowledge:   –  Within  your  organisaCon   –  Within  the  agency/supplier   –  In  the  public  realm  
  • 10. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Who  is  the  project  for?    _________________     What  is  the  business  issue/problem  that  is  being  addressed?   __________________________________________________     What  does  the  business  want  to  do,  once  it  has  addressed  this  issue?   ______________________________________________________     What  do  we  already  know?    Item  Held  by:  DescripHon   1     ______  ______  ______________   2     ______  ______  ______________   3     ______  ______  ______________     AssumpHons  and  predicHons    Who  What   1.     ______  ______   2.     ______  ______   Simplified  
  • 11. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Assembling  the  Evidence   •  QuanCtaCve   – Standardize?  Missing  Data?  Indexing?  Re-­‐basing?   •  QualitaCve   – TranslaCons?  Transcripts?  Notes?   •  The  nature  of  the  sources   – Credibility?  Bias?  InteracCons?  
  • 12. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015  
  • 13. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015  
  • 14. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015  
  • 15. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Normalising  by  ‘Share  of’  
  • 16. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   ‘Share  of’  is  a  relaHve  measure  
  • 17. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Normalizing  by  Coding   •  SenCment  analysis,  open-­‐ended  comments   converted  to  PosiCve,  NegaCve  and  Neutral   •  DigiCzing  from  analogue  to  binary   •  AllocaCng  to  segments   •  Scoring  different  elements   –  (think  American  Football  or  Rugby,  different  points  for   different  events,  leading  to  points  in  a  league)  
  • 18. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Normalizing  by   Growth  PaXerns   Forbes:  hBp://bit.ly/NewMR_208  
  • 19. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Is  My  Data  Right?   We  see  paBerns,  even   when  they  are  not  there.     Image  from  Viking  I,  1976   Mars  –  led  to  theories  of   intelligent  life.  
  • 20. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Spurious  CorrelaHons  
  • 21. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   HRT  and  CHD   •  Several  studies  showed  that  women  taking  HRT   were  less  likely  to  suffer  from  coronary  heart  disease   •  Some  leading  doctors  propose  that  HRT  was  protecCng   women  against  CHD   •  Randomised  Controlled  tests  showed  that  HRT  created   a  slight  increase  in  risk  of  CHD   •  Huh!   –  Women  taking  HRT  were  typically  from  higher  income,   healthier  groups  in  society  –  who  have  lower  rates  of  CHD  
  • 22. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Embedding  Frameworks   •  Establish  your  framework   •  Share  it  with  colleagues   •  Share  it  with  suppliers   •  New  projects  can  be  designed  to  produce   inputs  that  work  well  with  the  framework  you   are  using  
  • 23. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Finding  the  Story   1.  Know  what  the  quesCon  is.  Have  an  idea  of   what  success  looks  like.   2.  What  is  the  big  story?   –  What  do  most  people  do?  Why  do  most  people  do  it?   3.  What  are  the  relevant  excepCons?   4.  Determine  how  the  message  in  the  data   answers  the  business  quesCon  and  cra`  that  as   a  story.  
  • 24. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Find  the  Total  Picture  First   Then  the  relevant  detail   Quant   •  Look  at  the  Total  Column   •  Look  for  big  numbers  and   big  paBerns   •  What  is  the  big  picture?   •  This  will  frame  the  detail   Qual   •  Read  the  transcripts   –  Unless  you  conducted  the   fieldwork   •  Create  notes  and  memos   •  What  are  the  main   messages   In  the  context  of  the  Business  QuesCon  
  • 25. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Where  does  the  best  MR  come  from?   Column  %   Which  of  the  following  best  describes  you?   Countries  Merged   Total   Research  or   Consultancy   Supplier   Supplier  to  the   research  industry   Research  Buyer/ User   Academic  +  Other   English  Speaking   Non-­‐English   Speaking   UK   63%   61%   60%   92%   40%   66%   60%   USA   51%   52%   50%   46%   60%   52%   50%   Germany   18%   13%   30%   15%   60%   16%   21%   Australia   15%   14%   15%   15%   20%   16%   12%   Canada   11%   8%   20%   0%   40%   9%   14%   France   7%   7%   10%   8%   0%   7%   7%   Japan   5%   3%   15%   0%   0%   3%   7%   Brazil   3%   3%   5%   0%   0%   3%   2%   China   2%   1%   5%   0%   0%   3%   0%   Italy   2%   1%   5%   0%   0%   0%   5%   Other   8%   10%   10%   0%   0%   9%   7%   None  of  these   11%   15%   5%   0%   0%   9%   14%   Column  n   109   71   20   13   5   67   42   The  wrong  approach  to  starCng  analysis  
  • 26. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Where  does  the  best  MR  come  from?   Column  %   Which  of  the  following  best  describes  you?   Countries  Merged   Total   Research  or   Consultancy   Supplier   Supplier  to  the   research  industry   Research  Buyer/ User   Academic  +  Other   English  Speaking   Non-­‐English   Speaking   UK   63%   61%   60%   92%   40%   66%   60%   USA   51%   52%   50%   46%   60%   52%   50%   Germany   18%   13%   30%   15%   60%   16%   21%   Australia   15%   14%   15%   15%   20%   16%   12%   Canada   11%   8%   20%   0%   40%   9%   14%   France   7%   7%   10%   8%   0%   7%   7%   Japan   5%   3%   15%   0%   0%   3%   7%   Brazil   3%   3%   5%   0%   0%   3%   2%   China   2%   1%   5%   0%   0%   3%   0%   Italy   2%   1%   5%   0%   0%   0%   5%   Other   8%   10%   10%   0%   0%   9%   7%   None  of  these   11%   15%   5%   0%   0%   9%   14%   Column  n   109   71   20   13   5   67   42  
  • 27. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   0%   10%   20%   30%   40%   50%   60%   70%   Which  Country  Produces  the  Best  MR?   The  Big  Message   Big  story   QuesHons   Why  are  the  UK  &  USA  so  high/different?   Is  this  true  for  everybody?   What  are  the  implicaCons  of  this?  
  • 28. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   The  Cartographer  and  the  Journalist  
  • 29. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   The  Lead   Nora  Ephron   When  Harry  Met  Sally   Sleepless  in  Sea1le   1st  Day  in  Journalism  School   5  Ws  (Who,  What,  When,  Where  &  Why?)     Asked  to  write  the  Lead  for  the  school  newspaper     “The  en3re  school  faculty  will  travel  to  Sacramento  next   Thursday  for  a  colloquium  in  new  teaching  methods.   Among  the  speakers  will  be  anthropologist  Margaret   Mead,  college  president  Dr.  Robert  Maynard  Hutchins,  and   California  Governor  Edmund  Brown.”     All  the  students  wrote  about  the  5Ws  –  good,  but  not   right.     The  Lead?   No  school  next  Thursday!  
  • 30. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Different  PerspecHves  
  • 31. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   The  Tenuous  Link  Between  Finding  the  Story   and  Telling  the  Story   •  In  finding  the  story  we  have  mulCple  data  sources   •  We  have  differing  degrees  of  confidence  in  those   sources   –  A  conjoint  study  with  consulCng  surgeons  might  be  our   best  source  for  finding  the  story   •  The  best  way  to  convey  the  story  does  not  have  to  rest   on  the  ‘best’  data   –  A  vox  pop  video  with  a  paCent  might  be  a  poor  way  to  find   the  story,  but  it  can  be  a  great  way  to  tell  the  story  
  • 32. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   What  are  the  key  findings?   1.  Link  to  the  project  objecCves   2.  ‘Need  to  know’  not  ‘nice  to  know’   3.  Supported  by  paBerns  or  themes  in  the  data   –  Not  just  a  single  data  point   4.  Clear  findings   –  e.g.  In  the  chart  UK  and  USA  were  a  long  way   ahead  in  terms  of  Best  Research  
  • 33. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Hans  Rosling   1.  What  is  his  key  message?   2.  What  is  the  story?   3.  What  has  he  le`  out?   hBps://youtu.be/jbkSRLYSojo  
  • 34. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Hans  Rosling  &  NarraHve  Theme?   Key  Message:   –  It  is  possible  to  tackle  world  health  problems   Key  Story:   1.  200  years  ago  short-­‐life  expectancy  was  the  norm,  then  the  West   moved  ahead,  but  over  the  last  50  years  most  countries  have  caught   up   2.  There  are  some  countries  sCll  behind,  and  some  regions  of  other   countries,  but  since  most  of  the  world  has  been  solved,  the  rest  can   be   Key  narraHve  axis:   –  200  years  from  1810,  from  bad  to  good  
  • 35. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   What  Did  Hans  Rosling  Leave  Out?   Numbers:   –  A  few  dates,  3  life  expectancies,  3  income  levels   –  Based  on  200  countries  and  120,000  numbers   DefiniHons:   –  Which  200  countries?   –  How  did  he  deal  with  country  amalgamaCon  and   fragmentaCon?   517  other  staHsHcs:   –  GapMinder  lists  519  key  global  stats,  over  Cme  
  • 36. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Using  an  Insight  
  • 37. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   You’re  not  you  when  you  are  hungry   •  People  behave  differently   when  they  are  hungry   •  Snickers  is  big  enough  to   end  the  hunger   •  Global  campaign   –  Local  execuCons   •  Sales  increase   –  e.g.  USA  sales  +8%  
  • 38. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Developing  your  narraHve  theme   •  Select  your  primary  axis   •  This  is  the  elevator  pitch   •  Use  a  structure  that  works  with  the  audience   •  Typical  USA  structure   –  The  main  finding  was  X,  so  we  recommend  Y  &  Z   –  Now,  let’s  tells  you  why  it  is  X,  and  why  are  it’s  Y  &  Z   –  But  it  can  be  different  in  different  places  
  • 39. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   The  Big  Picture   •  Develop  a  framework  approach   •  Define  the  problem  before  you  try  to  find  the   answer  to  it   •  Put  the  research  project  into  the  context  of  what   is  already  known   •  What  do  you  want  the  client  to  think,  feel,  do   a`er  hearing  the  results?   –  The  story  is  a  device  to  deliver  that  acCon  
  • 40. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Thank  You!       Follow  me  on  TwiXer  @RayPoynter     Or  sign-­‐up  to  receive  our  weekly  mailing  at     hXp://NewMR.org      
  • 41. Learn  How  To  Find  The  Story  In  The  Data     Ray  Poynter,  UK,  December  2015   Q  &  A   Ray  Poynter   The  Future  Place   #NewMR  2015     Corporate  Sponsors   #NewMR  2015     Supporters   Schlesinger  Associates   Keen  as  Mustard