Never Give Up! A (Never-Ending) Case Study of Retention Schedule Development at Zions Bancorporation

Transcription

1 Never Give Up! A (Never-Ending) Case Study of Retention Schedule Development at Zions Bancorporation David Fleming, CRM, IGP, CIP VP, Corporate Records Program Manager Zions Bancorporation John J. Isaza, Esq., FAI CEO, Information Governance Solutions 2017 ARMA Houston Spring Conference

2 Learning Objectives Knowledge that there is no single right way to build a retention schedule Understand the various approaches to building a retention schedule Understand that no one can build your schedule for you you can get help, but it will not happen without your participation and organizational expertise. Understand how legal and business considerations drive an organization s approach to retention schedule development. 2

3 About Zions Bancorporation 445 Banking Offices in 11 Western and Southwestern States: Arizona, California, Colorado, Idaho, Nevada, New Mexico, Oregon, Utah, Texas, Washington, Wyoming As of December 31, 2016 Over $63 billion in assets 10,000+ employees 8 Affiliate Bank Brands Operating as Divisions of ZB, N.A. Other businesses include agricultural finance, equipment leasing, securities brokerage, public finance, medical payments processing, registered investment advisors Clients in all 50 states 3

4 History Snapshot - April 2004 No corporate RIM policy for a bank holding company with $30 billion in assets. Rapid growth through acquisition Records stored in 55+ facilities ranging from self service miniwarehouses to state of the art vendor facilities Management decision to utilize vendor provided / hosted software and consulting services Records Management Project kick-off Project scope includes corporate records management policy & retention schedule development, physical records storage clean-up & consolidation, corporate-wide records inventory, electronic records management, archive implementation 4

5 History Snapshot July 2004 Let s get started! 5

6 Commonly Used Terms Taxonomy Record Types Information Categories Record Series Record Class Record Titles Content Types Record Non-Record 6

7 History Snapshot - April 2005 New Corporate Policy and Retention Schedule is implemented Corporate Records Program Manager hired Project is closed out, but Physical records inventory consolidation still in progress Retention schedule contains record types with significant duplication and poor record descriptions Electronic records inventory expected to add 3500 record types to the retention schedule Decision not to move forward with vendor provided software and consulting services 7

8 History Snapshot April 2005 The First Published Version of the Records Retention Schedule 8

9 History Snapshot April 2006 Acquired Amegy Bank System conversion in progress Amegy was two years into RM Program implementation Working with IRCH on new Schedule Using TBA Schedule (approx record types) Updated Corporate Retention Schedule reduced to 750 record types, primarily by eliminating duplicate titles Iron Mountain account consolidation completed IM Connect implementation in progress Users required to classify records before sending off-site Working with IT to develop a system inventory to include information regarding records created / stored Kicking off effort to combine / improve Zions Bancorporation and Amegy retention schedules using IRCH Retention Manager software. 9

10 The Updated Version of the Retention Schedule Getting Better! 10

11 History Snapshot August 2008 Reviewed / consolidated over 2000 record titles and descriptions Reduced number of record types to 345 in 23 general functional categories Re-wrote all descriptions, included notes and examples for each to facilitate accurate classification of records Identified retention start events for each record type Mapped old record types to new schedule Hired Howett Isaza Law Firm (Now Rimon Law) to review schedule and create bank specific regulatory database 11

12 History Snapshot October 2008 Down to 345 with Clear Descriptions and Retention Start Events! 12

13 History Snapshot August 2012 Eliminated or consolidated unused record types Reduced number of record types to 220 in 17 general functional categories Reviewed and updated all descriptions, example lists Mapped 345 old record types to 220 surviving record types (a few records types where eliminated) Completed regulatory database update (Rimon Law) Completed legal review and mapping of all surviving record types to updated regulatory database (Rimon Law) 13

14 History Snapshot August 2012 Down to 220 with standardized Retention Start Events 14

15 History Snapshot July 2015 The quantum leap to Big Buckets! Eliminated functional area references Reduced number of record types to 59 Reviewed and updated all descriptions, example lists Mapped 220 old record types to surviving 59 record types Completed regulatory database update (Rimon Law) Completed legal review and mapping of all surviving record types to updated regulatory database (Rimon Law) For the first time the legal review performed in Virgo platform 15

16 History Snapshot July 2015 Down to 59 Information Categories, New Name: CIRS 16

17 Where Are We Today? Next Steps Minimal changes required to schedule going forward Updated legal review planned Integrating program with Data Governance program Moving forward with application of policy to electronically stored information leveraging the Data Governance program and project delivery methodology Legal review simplified and schedule changes tracked in Virgo platform 17

18 Big Buckets General Observations Focused on common retention periods Goal - As few record classes as feasible Non-records into one or two buckets with short (or indefinite - big data) retention periods Easiest to start from a functional scheme May be easier to take a gradual approach reduce classes in phases Set a realistic goal for optimum number of classes Sell and over sell the concept and advantages! 18

19 Big Buckets (cont d.) Advantages Easier to classify records Leads to more accurate and consistent classification Reduced schedule maintenance More compatible with electronic systems Disadvantages More challenging for event driven retention More likely to result in over-retention More challenging to create useful record classes descriptions 19

20 Software & Methodology 20

21 Lessons Learned There is no easy way to do this, but you are definitely better off if you can start from scratch. It will never be perfect Encourage ongoing feedback and develop a process for periodic updates and legal review Develop a simple taxonomy that will survive organizational changes A one-size-fits-all solution doesn t fit - Each organization is unique and is constantly changing Roll with the (organizational) changes! Know your organization Interviews with and feedback from each business unit Due diligence = accountability and defensibility No substitute for line-by-line legal review by an attorney 21

22 Lessons Learned (Continued) Use outside attorney with specialization in RIM In house attorneys will never get the research done Accuracy of descriptions and document types is critical to accuracy of external legal review Do not create a retention schedule that only you can understand Simplicity is the key to adoption and compliance A retention schedule is not a file plan The fact that your industry is heavily regulated does not mean your retention schedule must be complex You can t please everyone! Some swords aren t worth dying on. 22

23 Do Big Buckets help with electronic records? The growth of options and opportunities for choice has three unrelated, unfortunate effects. It means that decisions require more effort. It makes mistakes more likely. It makes the psychological consequences of mistakes more severe. Barry Schwartz, The Paradox of Choice 2004 After the system went live, it soon became evident that filing into a large number of small buckets was extremely cumbersome significantly affecting the rate of compliance. Richard Marcus, Information Management Journal, 2002 the most compelling reason I see pertains to the application of retention to electronic records where you really can t divide up large database platforms into small granular classes with different retention periods. You need large, default classes where all the records can be classified and retained uniformly. In my experience, once you create large, default classes, people will use them because they are so much easier to use than smaller classes. Iron Mountain Survey participant, 2007 there is no doubt in my mind that making the buckets bigger, thereby reducing the number of record categories, will make auto-classification easier. This is critical for electronic records that may be created or received in volumes far too large for manual classification. Iron Mountain Survey participant,

24 Questions? David Fleming Vice President, Corporate Records Program Manager Zions Bancorporation (801) Office (801) Cell John Isaza, Esq. CEO, Information Governance Solutions, LLC (949) Cell 24