PHD has been researching, developing and applying innovative, quantitative solutions for hiring
, succession planning
and performance improvement
for since 1999. PHD operates in the HR marketplace as a predictive analytics provider, but is easily distinguished from nearly all others in this space by providing client organizations with the means to develop customized, predictive performance models, or benchmarks, for almost any position and a variety of strategic applications: e.g., applicant pre-screening, selection confirmation, succession planning, turnover reduction, performance improvement, risk management, performance tracking and employee career development.
These predictive analytics are designed to help business owners, executives, and HR professionals be strategic in their management of their human capital assets. Using these tools, it is possible to learn what's next or needed, now. It is possible to target specific instances of risk (e.g., accident rates; turnover; conflict) and identify &/or re-deploy people who are not predisposed to such tendencies. It is also possible to target performance levels in a position and use predictive analytics to select &/or redeploy people who possess the competencies that were identified as being necessary for the desired level of performance.
PHD recognizes that most organizations have unique employee and performance requirements. Many take great pains to build a distinctive, best-in-class workforce. We strongly believe, therefore, that generic, one-size-fits-all screening and testing approaches cannot possibly address an organization's unique concerns, nor provide it with decision-making tools offering the highest predictive accuracy possible. Many established assessment companies, for example, seek to convey credibility by touting their use of decades-old "norms" containing millions of survey respondents. While such tools may sound impressive, they may be of little relevance to organizations with specific hiring and performance concerns. When relevance is questionable, the predictive accuracy of assessments will be limited. Accuracy will also be compromised if a tool's predictors are not linked in any way with important, company-specific job or performance outcomes.
PHD's data-based decision making tools and predictive analytics are designed to be 100% relevant to an organization's hiring and performance improvement needs. Predictive benchmarks are created by surveying actual employees in a position targeted for improvement. Behavioral and other relevant competency data are then linked directly to specific performance outcomes or standards specified by the organization. In addition, an organization may have the predictive accuracy of its models validated before use which also permits a calculation of expected ROI.
PHD's use of actual client workforce data and its ability to customize hiring solutions for specific and unique concerns assures clients that they are using one of the most statistically accurate, fair, evidence-based and legally defensible systems currently available. PHD hiring and performance management solutions are used by very small organizations to very large, Fortune 1000 firms. Company-specific applications have been developed for nearly all major industries.