IG community connects on career matrix update

IG community connects on career matrix update

Woman looking into the distance at multiple doors trying to choose which one to go through

At the last CHIMA Information Governance Community meeting on October 21, 2021, members met to review CHIMA’s career matrix, following feedback from members looking to see it updated.

To review the matrix, the group first identified its current challenges. Participants indicated its suitability for large organizations with greater separations between roles, making it less appropriate for those with jobs combining several tasks into one.

Participants noted that many of the jobs do not reflect the current digital era, rather a culture of data custodianship and management of paper records. Only one person had a job title that was like what’s currently listed in the matrix. All other IG professionals on the call had unrecognized job titles unique to their organization and specific job functions.

The participants agreed that the data and information governance field is mixed regarding accountability, experience, and placement in any organization. They also agreed on the existence of a variety of audiences for a career matrix. Some include HR professionals looking to understand comparators for data roles, mid-level managers looking to build teams, and HIM professionals wanting to grow their careers. Therefore, there is a need for consistency in the matrix to help advance a culture shift in the profession.

To achieve this consistency, the group decided on an upward review of the matrix by identifying several competencies in the data lifecycle that could potentially lead to more senior roles like a chief data officer. Using the analogy of building blocks, a participant suggested standardizing the definitions of these competencies. These competencies could then be grouped to form job descriptions created to demonstrate career progression.

Seven community meeting participants volunteered to join a working group to review the current matrix, assess job descriptions, analyze language, propose standard models, and compile recommendations for future updates.

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