Threshold is indeed the correct word. The holdback factors from saying we have made it through the door are missing skill sets and data access. Assessment is actually a form of measurement rigor for a business process called staffing. When setting up with closed-loop analytics, the insights can drive decision making that improves the yield of the process. The greatest challenges to taking advantage of this form of analysis are HR and Recruiting practitioners that are hard-pressed to access data and organize it into meaningful clusters.
We have been providing closed-loop analytics for our clients for over a decade. The variation in data resources within organizations is significant and meaningful. From our experience we see it ranging from instant access and exportability to being hard-pressed to know where to begin.
The data needed often lives in various repositories; no one individual has a line of sight or access rights. Key client roles on our project teams include a database advisor and a metrics advisor. Organizations that have internal skill-sets in these two disciplines are in a much better position to walk over the threshold and into the Golden Era of data mining and analytic insights.
If Talent Management is responsible for staffing the organization with productive workers, then it would seem important to know the cost of proficiency. This is a measure of time and dollars invested in acquiring an individual from sourcing, through on-boarding, to the time of self-sufficient performance. In manufacturing terms that is the cost of finished goods. This is essential to understand, document, and calculate the return on investment (ROI) of staffing process improvement. This is the real value selection science brings to a business.
Raw goods that become defects are like new hires that quit or are terminated prior to achieving proficiency. This is staffing waste and causes rework. Dollars to proficiency and time to proficiency can double. Assessment is a form of raw goods analysis. The data from assessment and various metrics and performance ratings on the journey to proficiency are the Golden Data for the Golden Era.
The consolidation of data capture and retrieval service providers, (e.g., Oracle/Taleo, etc.) may lead to easier access to data that can be used for analysis. The overarching structure of talent management needs to integrate data from sourcing through on-boarding to proficiency, and even deeper into employment life-cycle.