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Records and Information Management Insights From an Industry Expert

by | Oct 1, 2020

Cheryl Ahrens Young – IGP, CIP, APMD, CDIA+, CTT+, ermM, ecmP

For more than 35 years, Cheryl Young has been immersed in the records and information management industry, serving as a business process consultant, trainer, records manager, information analyst, contracts manager and project manager.

She has received certifications as an Information Governance Professional, Certified Information Professional, Accounts Payable Manager (with Distinction), Document Imaging Architect+, Technical Trainer+, Electronic Records Management Master and Electronic Content Management Practitioner.

Additionally, Cheryl was a past Chair for the ARMA International Conference (2004) in Long Beach, CA, and is also a member of the Project Management Institute (AIIM, IOFM). She’s provided solutions tailored for a wide array of clients, from attorney law firms to Fortune 5 companies.

When it comes to the integrity and accuracy of data involved in business applications, Cheryl has seen the good, the bad, and the ugly. Through her experiences, she has noticed several factors that contribute to long-term success and sustainability in regards to records management. She shared some of her expertise and notable insights, posing a variety of questions that all organizations should have an answer for.

 

Important Questions 

  • Is there a records manager on staff? This indicates a value is placed on your records as an asset within the company.
  • Does records management start when folders are placed in a box? This indicates that the asset value is limited to paper records.
  • How many times has the data been migrated? Data that has been through multiple migrations may have been truncated or corrupted.
  • Who is responsible for data mapping? Field names are often labeled differently between back-end tables and the search screens so that ideally, both the business unit and the information systems should be involved. Acquisitions and mergers present particular challenges in mapping data from one system to another, especially if data was not normalized at the acquisition but rather kept in the original system.
  • How many business units touch the data during its lifecycle? Various units will have different interests and ways of naming information, particularly in a Customer Relationship Management system.
  • Are there written procedures available? Screenshots with handwritten notes don’t count—I’m looking for a document with revision history, approvals and step-by-step narratives, desktop instructions and/or storyboards.
  • Was documentation created for the application that spells out the assumptions and limitations of the database? (i.e. what can and can’t be imported, exported or created within the system). For instance, if there is not a 225-character limitation in a text field, is it really a text field (searchable) or is it a blob (not really searchable).
  • How was obsolete data removed? If it was archived, will it come forward in the new initiative? What is the impact? Will a particular set of data look like a false duplicate? If it was scrambled, were all fields scrambled or just the unique fields?
  • What protection was put in place to prevent inaccurate data from being entered in the first place? Were drop downs menus with agreed upon terms and spelling created to standardize data entry. Was there masks put in place for date or specific numerical identification fields? Were look-ups to a System Record created?
  • If many divisions’ databases are being centralized into one, are there potential duplicate “unique” numbers? In other words, did each division or system start with “1” and increment sequentially?

Asking the questions above and remaining persistent in obtaining the answers will provide a better understanding of the tasks involved (and time) to achieve a successful result in a data-reliant project of any size. This translates to “Garbage In, Garbage Out” on a really massive scale if the time isn’t taken early on in the process to clean active data and remove obsolete data.

 

 

Written by WIS

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