#AIIM14	
  #AIIM14	
  
#AIIM14	
  
The	
  Good,	
  the	
  Bad,	
  and	
  the	
  Ugly	
  of	
  
Defensible	
  Disposi7on	
 ...
#AIIM14	
  
Issues	
  
1.  The	
  problem	
  
§  The	
  sky	
  is	
  falling	
  again	
  
2.  Break	
  it	
  into	
  two	...
#AIIM14	
  
Issues	
  
1.  The	
  problem	
  
§  The	
  sky	
  is	
  falling	
  again	
  
2.  Break	
  it	
  into	
  two	...
#AIIM14	
  
The	
  Problem	
  is	
  Over-­‐Reten7on	
  
OrganizaLons	
  have	
  been	
  over-­‐retaining	
  electronic	
  ...
#AIIM14	
  
Why	
  Over-­‐Reten7on	
  is	
  the	
  Problem	
  
§  Organiza2ons	
  keep	
  non-­‐required	
  electronic	
 ...
#AIIM14	
  
Issues	
  
1.  The	
  problem	
  
§  The	
  sky	
  is	
  falling	
  again	
  
2.  Break	
  it	
  into	
  two	...
#AIIM14	
  
Recommenda7ons	
  for	
  Day-­‐forward	
  
§  Addressing	
  day-­‐forward	
  informa7on	
  lifecycle	
  manag...
#AIIM14	
  
Guidance	
  Example	
  for	
  Day-­‐
forward	
  
System/Repository	
   Recommended	
  Reten7on	
  Period	
  
P...
#AIIM14	
  
Issues	
  
1.  The	
  problem	
  
§  The	
  sky	
  is	
  falling	
  again	
  
2.  Break	
  it	
  into	
  two	...
#AIIM14	
  
What’s	
  the	
  Purpose	
  of	
  Your	
  DD	
  Methodology?	
  
§  You	
  must	
  sa7sfy	
  4	
  demands:	
 ...
#AIIM14	
  
It’s	
  Based	
  on	
  Reasonableness	
  
§  To	
  determine	
  what	
  “sa2sfy	
  your	
  reten2on	
  
deman...
#AIIM14	
  
Your	
  DD	
  Methodology	
  Has	
  4	
  Parts	
  
1.  Defensible	
  Disposi7on	
  Policy	
  
§  It’s	
  your...
#AIIM14	
  
Your	
  DD	
  Methodology	
  Has	
  4	
  Parts	
  
3.  Assessment	
  	
  (Sor7ng)	
  Plan	
  
§  Do	
  the	
 ...
#AIIM14	
  
Issues	
  
1.  The	
  problem	
  
§  The	
  sky	
  is	
  falling	
  again	
  
2.  Break	
  it	
  into	
  two	...
#AIIM14	
  
There’s	
  an	
  Awesome	
  Business	
  Case	
  
Classifica7on	
  Technique	
  
Classifica7on	
  
Rate	
  
Prici...
#AIIM14	
  
Analysis	
  and	
  Classifica7on	
  Technologies	
  
§  Many	
  different	
  kinds	
  of	
  technology	
  vendo...
#AIIM14	
  
Sidebar:	
  How	
  Many	
  of	
  them	
  Work	
  
Before	
   Acer	
  
<server	
  XXX,	
  drive	
  G:>	
  
Fore...
#AIIM14	
  
Issues	
  
1.  The	
  problem	
  
§  The	
  sky	
  is	
  falling	
  again	
  
2.  Break	
  it	
  into	
  two	...
#AIIM14	
  
Assessment	
  Approaches	
  
§  There	
  are	
  three	
  categories	
  of	
  awributes	
  that	
  can	
  be	
...
#AIIM14	
  
#1:	
  Environmental	
  Ahributes	
  
Ahribute	
   Evalua7on	
  Technique	
   Tool(s)	
  Used	
   Examples	
  ...
#AIIM14	
  
#2:	
  File	
  Ahributes	
  
Duplicate	
  
Hash	
  Algorithm	
  
Content	
  AnalyLcs	
   Exact	
  duplicates	
...
#AIIM14	
  
#3:	
  Content	
  Ahributes	
  
Key	
  Word	
   Character	
  Strings	
  
Content	
  AnalyLcs;	
  
ClassificaLon...
#AIIM14	
  
Assessment	
  Results	
  
Preserva7on	
   Findings	
  
Unnecessary	
  File	
  Types	
  
(Executables,	
  non-­...
#AIIM14	
  
Assessment	
  Summary	
  
Findings	
   Enterprise	
  Impact	
  
Total	
  that	
  could	
  be	
  disposed	
   2...
#AIIM14	
  
Assessment	
  Implica7ons	
  
§  Given	
  the	
  results,	
  $2.5	
  million	
  in	
  storage	
  expense	
  c...
#AIIM14	
  
Conclusions	
  
1.  The	
  business	
  case	
  for	
  disposiLon	
  is	
  strong	
  
§  Costs,	
  risks,	
  a...
#AIIM14	
  #AIIM14	
  
#AIIM14	
  
Thank	
  You	
  
Richard	
  Medina	
  
Co-­‐founder	
  and	
  Principal	
  Consultant,	...
www.aiim.org/infochaos	
  
Do	
  YOU	
  understand	
  the	
  business	
  	
  
challenge	
  of	
  the	
  next	
  10	
  year...
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The Good, The Bad, and The Ugly of Defensible Disposition

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Most organizations hoard and fail to destroy their piles of files in a legally defensible manner when business and law allow. How do you tackle the monster problem of over-retention of electronic information? The session, Rich shows how to develop and execute the four most important steps in defensible disposition: the Defensible Disposition Policy, Assessment Plan, Technology Plan, and Disposition Plan. He’ll outline business case development and tool selection.

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The Good, The Bad, and The Ugly of Defensible Disposition

  1. 1. #AIIM14  #AIIM14   #AIIM14   The  Good,  the  Bad,  and  the  Ugly  of   Defensible  Disposi7on   Richard  Medina   Co-­‐founder  and  Principal  Consultant,  Doculabs  |  doculabs.com   rmedina@doculabs.com  |  richardmedinadoculabs.com   @richarddoculabs  
  2. 2. #AIIM14   Issues   1.  The  problem   §  The  sky  is  falling  again   2.  Break  it  into  two  problems   §  Day-­‐forward  versus  historical  content   3.  How  to  address  historical  content   §  A  defensible  disposi2on  methodology   4.  Analysis  and  classificaLon  technology   §  Should  you  use  it?  Does  it  work?   5.  Doing  the  Assessment   §  Approaches  and  results  
  3. 3. #AIIM14   Issues   1.  The  problem   §  The  sky  is  falling  again   2.  Break  it  into  two  problems   §  Day-­‐forward  versus  historical  content   3.  How  to  address  historical  content   §  A  defensible  disposi2on  methodology   4.  Analysis  and  classificaLon  technology   §  Should  you  use  it?  Does  it  work?   5.  Doing  the  Assessment   §  Approaches  and  results  
  4. 4. #AIIM14   The  Problem  is  Over-­‐Reten7on   OrganizaLons  have  been  over-­‐retaining  electronic  informaLon  and  failing  to   dispose  of  it  in  a  legally  defensible  manner  when  business  and  law  will  allow   Retaining  everything  forever   Disposing  of  everything  immediately   Having  employees  make  classificaLon  decisions   Having  technology  make  classificaLon  decisions   Hybrid  with  technology  and  people  
  5. 5. #AIIM14   Why  Over-­‐Reten7on  is  the  Problem   §  Organiza2ons  keep  non-­‐required  electronic  content  forever   because:   1.  Classifying  content  (to  determine  what  to  keep  and  what  to  purge)  is   manual  and  expensive   2.  Content  worth  preserving  is  mixed  with  content  that  should  be  purged   3.  Legal  -­‐-­‐  and  others  -­‐-­‐  are  afraid  of  wrongfully  deleLng  materials   (spoliaLon)   4.  AddiLonal  storage  is  inexpensive,  which  makes  it  easy  for  corporaLons   to  buy  more  storage  and  defer  addressing  the  problem  
  6. 6. #AIIM14   Issues   1.  The  problem   §  The  sky  is  falling  again   2.  Break  it  into  two  problems   §  Day-­‐forward  versus  historical  content   3.  How  to  address  historical  content   §  A  defensible  disposi2on  methodology   4.  Analysis  and  classificaLon  technology   §  Should  you  use  it?  Does  it  work?   5.  Doing  the  Assessment   §  Approaches  and  results  
  7. 7. #AIIM14   Recommenda7ons  for  Day-­‐forward   §  Addressing  day-­‐forward  informa7on  lifecycle  management  (ILM)  is  much  easier  to  address  than   historical  content   §  Even  though  addressing  it  messes  with  employees’  day-­‐to-­‐day  business  acLviLes   §  Day-­‐forward:  Ini2ate  ILM  prac2ces  on  a  “day-­‐forward”  basis  first,  so  any  new  content  created  or   saved  is  assigned  a  disposi2on  period   §  DisposiLon  horizons  should  begin  to  influence  behavior  on  where  content  begins  to  be  stored  (as   users  discover  that  those  materials  saved  in  the  “wrong”  system  will  be  purged)   §  Guidance:  Provide  employees  with  explicit  guidance  for  the  acceptable  use  of  available  tools  for   dynamic  content  and  their  associated  reten2on  periods     §  For  example,  retain  non-­‐records  for  3  years,  retain  official  records  per  the  retenLon  schedule   §  Historical:  For  historical  content,  analyze  the  feasibility  of  content  analy2cs  and  autoclassifica2on   §  Recognize  that  cleaning  up  TBs  of  content  can  take  years.  So  conduct  the  analysis  in  2014,  begin   the  cleanup  effort  in  earnest  by  2015,  and  eliminate  a  large  porLon  of  dated  content  by  2016    
  8. 8. #AIIM14   Guidance  Example  for  Day-­‐ forward   System/Repository   Recommended  Reten7on  Period   Personal  Network   Drives  (“P”  drives)   •  Provide  each  user  with  personal  drive  space  of  a  limited  size  for  their  storage,  for  as  long   as  the  user  is  employed   Shared  Network   Drives   (“G”  drives)   •  Make  them  read  only  (which  means  no  network  storage  for  collabora7on;  content  will   have  to  go  into  an  ECM  system)   •  Excep7ons  include  applica7on  or  systems  that  need  to  use  network  storage   ECM  System   1.  Default  for  non  records:  retained  for  3  years     2.  Default  for  non  records  that  have    long-­‐term  value:  retained  for  7  years   3.  Official  records:  retained  per  the  reten7on  schedule   Social  Community   Sites   •  No  documents  stored  in  communi7es  (only  links  to  documents  in  the  ECM  system)   •  Consider  reten7on  periods  for  non-­‐document  content  (e.g.  3  years)  
  9. 9. #AIIM14   Issues   1.  The  problem   §  The  sky  is  falling  again   2.  Break  it  into  two  problems   §  Day-­‐forward  versus  historical  content   3.  How  to  address  historical  content   §  A  defensible  disposi;on  methodology   4.  Analysis  and  classificaLon  technology   §  Should  you  use  it?  Does  it  work?   5.  Doing  the  Assessment   §  Approaches  and  results  
  10. 10. #AIIM14   What’s  the  Purpose  of  Your  DD  Methodology?   §  You  must  sa7sfy  4  demands:   1.  Regulatory  retenLon  requirements   2.  Hold  retenLon  requirements   3.  Business  retenLon  requirements   4.  Cost  impact  of  anything  you  do   §  What  you  do  has  impact:   1.  What  you  do   2.  Effects  of  what  you  do   §  You  can  do  2  things:   1.  Sort   2.  Dispose   §  Your  mission  stated  two  ways:   §  Your  mission  is  to  saLsfy  your  retenLon  demands  (1-­‐3)  while  minimizing  bad  cost  impact  to   yourself  (4)   §  Your  mission  is  to  maximize  good  cost  impact  (4)  while  saLsfying  your  retenLon  requirements   (1-­‐3)    
  11. 11. #AIIM14   It’s  Based  on  Reasonableness   §  To  determine  what  “sa2sfy  your  reten2on   demands”  really  means  for  you,  use  the  Principle   of  Reasonableness  and  act  In  Good  Faith   §  Courts  do  not  ask,  expect  or  necessarily  reward  organizaLons  for   perfecLon.  Courts  do  expect,  however,  that  whatever   informaLon  management  tacLcs  an  organizaLon  undertakes  are   appropriate  to  how  that  parLcular  enLty  is  situated  (size,   financial  resources,  regulatory  and  liLgaLon  profile,  etc.).  (Jim   McGann  and  Julie  Colgan,  “Implement  a  defensible  dele2on   strategy  to  manage  risk  and  control  costs”,  Inside  Counsel)  
  12. 12. #AIIM14   Your  DD  Methodology  Has  4  Parts   1.  Defensible  Disposi7on  Policy   §  It’s  your  design  specificaLon,  your  business  rules  for  DD,  your   decision  tree   §  Specifies  very  clearly  the  objecLves  that  your  methodology   will  fulfill.  It  states  clearly  what  you  mean  by  your  retenLon   requirements  and  what  you  mean  by  reasonable  costs  when   you  are  trying  to  fulfill  your  retenLon  requirements.   2.  Technology  Approach   §  For  SorLng  and  Disposing   §  You  must  use  technology  –  it’s  not  an  opLon    
  13. 13. #AIIM14   Your  DD  Methodology  Has  4  Parts   3.  Assessment    (Sor7ng)  Plan   §  Do  the  legwork  and  look  at  what’s  there   §  What  informaLon  and  systems  you’re  assessing   §  Your  processing  rules    (decision  plan)   §  It  will  be  flexible   4.  Disposi7on  Plan   §  Evaluate  your  assessment  results  using  your  DD  Policy   §  Dispose  (which  ranges  from  keeping  forever  to  deleLng  right  now   with  many  opLons  in  between)   §  Refine  your  DD  Policy  (1)  and  conLnue  as  needed    
  14. 14. #AIIM14   Issues   1.  The  problem   §  The  sky  is  falling  again   2.  Break  it  into  two  problems   §  Day-­‐forward  versus  historical  content   3.  How  to  address  historical  content   §  A  defensible  disposi2on  methodology   4.  Analysis  and  classifica7on  technology   §  Should  you  use  it?  Does  it  work?   5.  Doing  the  Assessment   §  Approaches  and  results  
  15. 15. #AIIM14   There’s  an  Awesome  Business  Case   Classifica7on  Technique   Classifica7on   Rate   Pricing   Total  Cost   to  Classify   Manual  ClassificaLon   10  seconds  per   document   $35  /  hr.   $20  million   Auto  ClassificaLon     (with  95%  machine  and  5%   human  classified,  via   offshore  labor)   Less  than  1   second  per   document   $.005  per  document  for   machine  processing  and     $5  /  hr.  for  those  that   require  manual   classificaLon     $2  million   §  …  if  the  technology  works   §  50  TB  =    ~200  million  documents  (average  of  250KB  per  document)   §  The  following  table  illustrates  the  Lme  and  effort  required  to  classify  200  million  documents  
  16. 16. #AIIM14   Analysis  and  Classifica7on  Technologies   §  Many  different  kinds  of  technology  vendors  are  addressing  analysis,   classificaLon,  and  disposiLon   §  File  AnalyLcs,  Content  AnalyLcs,  Content  ClassificaLon,  ECM,  E-­‐discovery,   Search,  Capture,  DLP,  Storage  Management   §  Products,  hosted  soluLons,  service  providers     §  IBM/Stored  IQ,  HP/Autonomy,  EMC  Kazeon,  SAS,  Kofax,  Equivio,  RaLonal   RetenLon,  Recommind,  Index  Engines,  and  others   §  Most  have  a  sweet  spot  where  they  will  succeed   §  But  it’s  highly  dependent….  on  just  about  every  factor  you  can  think  of   §  E.g.,  your  business  purposes,  your  ECM  environment,  your  “informaLon   architecture”,  your  document  types  and  their  complexity  and  volume,  the  value   and  risk  of  the  documents,  your  success  criteria,  etc.,  etc.,  etc.  
  17. 17. #AIIM14   Sidebar:  How  Many  of  them  Work   Before   Acer   <server  XXX,  drive  G:>   Forecast   summary_121008.doc   Record  =  no   Age  =  2.5  years   Document  type=  departmental  forecast   Keywords  =  forecast,  2008,  drav   Status  =  delete   Confidence  =  9.2  (out  of  10)   1.  Analyze  the  content  and  review  the  retenLon  schedule   2.  Establish  classificaLon  rules  and  train  the  systems  with  examples   3.  Crawlers  and  recogniLon  engines  evaluate  the  content  and  generate  a  classificaLon   4.  For  content  where  a  high  machine  confidence  factor  exists,  content  is  automaLcally  tagged   and  then  staged  for  migraLon  to  the  appropriate  system  or  disposiLon   5.  For  content  with  low  confidence  factors,  documents  are  routed  to  clerical  staff  (onshore  or   offshore)  for  manual  classificaLon   6.  The  results  of  the  manual  idenLficaLon  are  fed  back  into  the  automated  algorithms  to   “teach”  the  systems  bewer  classificaLon   Throughout  the  process,  results  and  samples  are  routed  to   records  management  and  legal  professionals  within  the  firm  for   validaLon  and  confirmaLon   1   2   3   4   5   6     Client   Valida7on    
  18. 18. #AIIM14   Issues   1.  The  problem   §  The  sky  is  falling  again   2.  Break  it  into  two  problems   §  Day-­‐forward  versus  historical  content   3.  How  to  address  historical  content   §  A  defensible  disposi2on  methodology   4.  Analysis  and  classificaLon  technology   §  Should  you  use  it?  Does  it  work?   5.  Doing  the  Assessment   §  Approaches  and  results  
  19. 19. #AIIM14   Assessment  Approaches   §  There  are  three  categories  of  awributes  that  can  be  used  to   determine  what  a  file  is:     1.  Environmental  awributes  around  the  file  (e.g.,  file  locaLon,  ownership)   2.  File  awributes  about  the  file  (e.g.,  file  type,  age,  author)   3.  Content  awributes  within  the  file  (e.g.,  keywords,  character  strings,  word   proximity,  word  density)   §  Various  techniques    and  technologies,  along  with  business  rules,   can  be  used  to  determine  what  a  file  is,  and  whether  it  is  eligible  for   disposiLon   §  E.g.,  a  DOC  file  created  over  5  years  ago  and  not  accessed  for  a  year  may  be   purged   §  This  type  of  purging  could  be  done  aver  giving  users  adequate  noLce  (“move  it   or  lose  it”  or  “hold”  for  90  days,  then  delete)  
  20. 20. #AIIM14   #1:  Environmental  Ahributes   Ahribute   Evalua7on  Technique   Tool(s)  Used   Examples   How  Used   Ownership   Access  Controls   Content  Analy7cs,  Data   Loss  Preven7on,  Storage   Management   Permissions  within  LDAP  list   people  and  infer   department  or  func7on   Large  collec7ons  of  files  can  be   assessed  en  masse  based  on   access  controls   1   Loca7on   File  Path   Content  Analy7cs,  Data   Loss  Preven7on,  Storage   Management   G:/accoun7ng/july2004/temp   Stranded  and  orphaned   loca7ons  are  ocen  easily   eliminated   2   Environmental  Ahributes  (around  a  file)  
  21. 21. #AIIM14   #2:  File  Ahributes   Duplicate   Hash  Algorithm   Content  AnalyLcs   Exact  duplicates   Exact  duplicates  can  be  easily  eliminated   3   File  Type   Extension  or  MIME  type   Content  AnalyLcs   .TMP,  .MP3   To  idenLfy  file  types  that  should  not  exist   in  a  corporate  seyng   4   Block  Read   Content  AnalyLcs   Near  duplicates   Near  duplicates  must  be  assessed  in  the   context  of  other  awributes   Metadata   ProperLes   Content  AnalyLcs   Age   To  determine  old  materials,  materials   authored  by  individuals  that  have  lev  the   organizaLon   5   Content  AnalyLcs   Author   Typically,  these  awributed  must  be   conLnued  with  other  awributed  via  a  rule   to  take  acLon   Content  AnalyLcs   Security  Profile  (ConfidenLal)   User  filename  properLes  to  determine   type   File  Name   Character  Strings   Content  AnalyLcs   GL-­‐USDIST31_093098.xls   Determine  whether  a  file  was  system   generated  vs.  human  generated   6   Content  AnalyLcs   FORMUB92_SMITH   Documents  that  are  based  on  a  specific   form  number  can  easily  be  idenLfied   Ahribute   Evalua7on  Technique   Tool(s)  Used   Examples   How  Used   File  Ahributes  (about  a  file)  
  22. 22. #AIIM14   #3:  Content  Ahributes   Key  Word   Character  Strings   Content  AnalyLcs;   ClassificaLon  Module   “Enron”,  “Guarantee”   To  determine  if  a  document  is   on  Hold  via  a  word  list  per  the   hold  request   7   Character   or  Word   Paherns   “ClassificaLon”   <pawern  matching>   ClassificaLon  Module   Word  proximity   To  determine  the  category  in   which  a  document  may  fit  8   ClassificaLon  Module   Word  frequency   Content  AnalyLcs;   ClassificaLon  Module   “Privileged”   IdenLficaLon  of  PII   Content  AnalyLcs;  DLP   SS#,  Credit  card  #   Regular  Expression(RegEX)   lists;  determined  enLLes  for   hold,  security,  IP,  PHI,  PII,  DLP   Ahribute   Evalua7on  Technique   Tool(s)  Used   Examples   How  Used   Content  Ahributes  (within  a  file)  
  23. 23. #AIIM14   Assessment  Results   Preserva7on   Findings   Unnecessary  File  Types   (Executables,  non-­‐business  pictures,  movies,  etc.)   13  to  15%   Duplicates   15  to  20%   Near  Duplicates   9  to  30%   Risk   Findings   Files  with  PII   10  to  16%   Files  with  Sample  Keywords   3  to  5%   Opera7onal   Findings   Files  10  years  or  older   7  to  11%   Files  accessed  within  the  last  18  months   25  to  35%   Findings  not  mutually   exclusive  (  i.e.,  a  duplicate   file  could  also  be  aged)  
  24. 24. #AIIM14   Assessment  Summary   Findings   Enterprise  Impact   Total  that  could  be  disposed   20%  of  2.5  PB   Enterprise  ImplicaLons   .5  PB  removed  @  $5,000,000  per  PB   Savings   $2,500,000  per  year  in  storage  expense   Technique   Status   %  of  Total   Total   AnalyLcs   Unnecessary     20%   500  TB  (.5  PB)   ClassificaLon   Record   8%   200  TB  (.2  PB)   Non-­‐Record,  Business   Reference   28%   700  TB  (.7  PB)   Evaluated,  Staged  for   DisposiLon  (2016)     44%   1,100  TB  (1.1PB)   Total   100%   2,500  TB  (2.5  PB)  
  25. 25. #AIIM14   Assessment  Implica7ons   §  Given  the  results,  $2.5  million  in  storage  expense  could  be  saved  annually  on  the  disposiLon  of   historic  content,  resulLng  in  $12.5  million  over  5  years   §  Going  forward  with  newly  created  content,  if  similar  techniques  are  applied,  the  saving  grows  to   $34.8  million  over  5  years   §  The  current  cost  projecLons  are  based  on  the  historical  content  growth  rate  of  30%  per  year   §  The  expected  cost  projecLons  are  based  on  a  content  growth  rate  of  26%  per  year   @$5,000,000  per  PB   2012   2013   2014   2015   2016*     Total   Current  Storage  (PB)   2.5   3.25   4.23   5.49   7.14   Current  Cost  (Mill)   $12.5   $16.3   $21.1   $27.5   $35.7   $113.0   Expected  Storage  (PB)   2   2.52   3.18   4.00   3.94   Expected  Cost  (Mill)   $10   $12.6   $15.9   $20.0   $19.7   $78.2   Total  Savings  (Mill)   $2.5   $3.65   $5.25   $7.46   $16.00   $34.8   *In  2016,  the  1.1  PB  or  44%  of  content  from  the  2012  historical  content  assessment  can  be  disposed  
  26. 26. #AIIM14   Conclusions   1.  The  business  case  for  disposiLon  is  strong   §  Costs,  risks,  and  benefits   2.  InformaLon  governance  must  be  addressed  in  phases   §  StarLng  today,  the  program  will  take  years  to  mature   §  Set  expectaLons  according   3.  You  should  probably  address  day-­‐forward  ILM  before  tackling  historical   content   4.  Recognize  that  manual  classificaLon  is  not  an  opLon   5.  The  technologies  are  immature  and  varied,  but  you  can  be  successful  by   matching  the  techniques  and  technologies  to  the  kinds  of  files  you  want  to   target   6.  Your  DD  methodology  has  4  main  parts:    DD  Policy,  Technology  Approach,   Assessment  Plan,  Disposi2on  Plan  
  27. 27. #AIIM14  #AIIM14   #AIIM14   Thank  You   Richard  Medina   Co-­‐founder  and  Principal  Consultant,  Doculabs  |  doculabs.com   rmedina@doculabs.com  |  richardmedinadoculabs.com   @richarddoculabs  
  28. 28. www.aiim.org/infochaos   Do  YOU  understand  the  business     challenge  of  the  next  10  years?   This  ebook  from  AIIM  President   John  Mancini  explains.  

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