Child Welfare Quality Improvement Center for Workforce Development (QIC-WD)

 

Date of this Version

5-1-2021

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Document Type

Article

Abstract

When conducting workforce analytics, it can be helpful to adopt a team approach and involve various experts and stakeholders, each of which can make a valuable contribution.

The Big Picture

  • Ensure that you have the commitment and buy-in from leaders who control the agency’s budget and policies.
  • Team membership may vary depending on the analytics goals and the stage of the work, but potential participants include representatives from agency leadership, Human Resources (HR), child welfare, Information Technology (IT), and training.
  • It’s likely that no one person is going to possess all the skills needed; building a strengths-based, interdisciplinary team can be considered the pooling of cognitive resources.
  • Focus on who has the specific skills and capacities needed to engage in workforce analytics, rather than focusing on specific roles or titles.

Identifying Key Personnel

  • Agencies will need to consider who will need to be involved to launch a successful workforce analytics partnership by determining: - Who the champions are among HR and child welfare staff to facilitate partnership conversations - The key personnel in HR and child welfare who will need to access, manipulate, and analyze the data - The key personnel in HR and/or child welfare who can present findings to stakeholders in relevant and actionable ways
  • Agencies will also need to identify the primary staff in HR and child welfare who will need to see, use, and understand the data

Key Skills Needed

The following skills should be represented in your interdisciplinary team (CIPD, 2018):

Macro Skills

  • Ability to link HR and business strategies
  • Ability to assess organizational readiness for analytics initiatives
  • Ability to build the business case for analytics
  • Ability to demonstrate the credibility and value added by HR
  • Ability to use analytical insights to improve talent management processes
  • Ability to define the roles, capabilities, and structures required to maximize analytics effectiveness

Micro Skills

  • Question-driven mindset
  • Ability to calculate descriptive statistics (e.g., means, ranges, and percentiles)
  • Ability to analyze trends in the data and interpret the meaningful aspects of that information within the context of the agency
  • Ability to test plausible hypotheses to establish the root cause of workforce issues
  • Ability to segment data and metrics to highlight specific areas of concern or opportunity
  • Ability to effectively and convincingly present insight and conclusions
  • Ability to examine the correlation, and level of causation, between two or more metrics
  • Ability to build multivariate models (Note that this is a very advanced skill)

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