Teach Middle East Magazine Apr-Jun 2022 Issue 3 Volume 9 | Page 32

INTRODUCING THE COGNIZANCE QUANTIFIER ( CQ ) FOR TALENT OPTIMIZATION IN AN ACADEMIC ENVIRONMENT

Sharing Good Practice

INTRODUCING THE COGNIZANCE QUANTIFIER ( CQ ) FOR TALENT OPTIMIZATION IN AN ACADEMIC ENVIRONMENT

( Realizing and Harnessing Self-Actualization in the Digital Age )
BY : MURAD SALMAN MIRZA

Maintaining a desired pool of capable and engaged talent has been one of the core strengths of exceptional academic institutions in terms of enabling them to dominate their competition . However , the conventional approach for embarking upon such initiatives has largely been dependent upon the personal expertise of eminent HR professionals backed by astute organizational leadership , rather than , a robust framework that can be reliably and robustly adopted / adapted with far less resources to hire premium talent in the HR space while negotiating the trials and tribulations of an apprehensive top management . One of the glaring shortcomings in the respective context are the tantalizingly deficient “ Total Rewards ’ packages lagging in an ‘ invigorating employee experience ’ and designed to hover around the ‘ industry norms ’ that often relegate academic institutions to self-inflicted mediocrity in terms of functional agility , talent relevancy , and organizational competitiveness while meeting the daunting challenges of the Digital Age . Consequently , success in the respective context varies along a wide bandwidth and abnormal attrition rates are a stark reminder of failures in stemming the outflow of ‘ desired ’ talent to opportunistic competitors .

On the other hand , the responsibility on professionals to ‘ take charge ’ of their own destinies has also become increasingly important due to the precariousness of careers in the Digital Age as AI-driven solutions / entities are being increasingly embraced by organizations to offset / minimize the uncertainties / complications related to maintaining a humanistic workforce . This requires a new kind of ‘ selfactualization ’ that can raise the level of ‘ enlightenment ’ among progressive professionals striving to seamlessly navigate the treacherous fluidity of
the continuously evolving corporate environment for staying relevant and competitive through the timely development and astute utilization of a congruent skill set . The term , Cognizant Quantifier ( CQ ), and its associated equation has been created and developed as follows to facilitate such a journey of self-discovery :
CQ = ( Knowledge of Self ) x ( Knowledge of Team ) x ( Knowledge of Function ) x ( Knowledge of Influencers ) x ( Knowledge of Organization )
In a more expanded form :
CQ = ( KSelf ) x ( KSubordinates + KPeers + KSupervisors ) x ( KFunction ) x ( KNetworks + KMentors + KLeaders ) x ( KOrganization )
Note : The value of each component in the above equation varies between 0 ( complete lack of knowledge ) and 1 ( complete mastery of knowledge )
Let ’ s explore the various constituent elements of the aforementioned formulation in more detail :
Knowledge of Self ( KSelf )
This refers to having a clear realization / understanding / appreciation of one ’ s own purpose , motivation , talent , strengths and shortcomings , in terms of alignment of personal goals / objectives with those of the organization in a winwin situation . Following are some of the questions that can be used in the respective context :
• Have I found my ‘ true calling ’ in terms of being a professional ?
• Am I intrinsically-driven in terms of achieving my professional goals / objectives ?
• Do I have the necessary ‘ skill set ’ to stay relevant and competitive in the current and foreseeable professional environment ?
• Do I have a robust and effective plan / approach / methodology to sustain my strengths ?
• Do I have a robust and effective plan / approach / methodology to overcome my shortcomings ?
Knowledge of Team ( KSubordinates + KPeers + KSupervisors )
This refers to having a clear realization / understanding / appreciation of the purpose , motivation , talent ,
32 Term 3 Apr - Jun 2022
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