Human Capital Analytics

Human resources analytics, also called talent analytics, is the application of sophisticated data mining and business analytics (BA) techniques to human resources (HR) data. The goal of human resources analytics is to provide an organization with insights for effectively managing employees so that its business goals can be reached quickly and efficiently. The challenge of human resources analytics is to identify what data should be captured and how to use the data to model and predict capabilities so that the organization gets an optimal return on investment (ROI) on its human capital.

Today the momentum for human analytics is growing but its potential is unrealized.  While many HR Departments use metrics today, their use and application are:

• ƒ Often inconsistent; different companies employ different kinds of metrics in different ways
• ƒ Data is collected for the sake of collection or to justify some activity
• ƒ Metrics are out there by themselves, and are not tied to business performance or adequately aligned   with organizational strategies

The reasons why analytics are not being more widely used are many, including gaps in stakeholder perspectives. Barriers to fully realizing analytics are:

• Investors pressure companies to meet short-term earnings rather than long-term milestones. Human

capital analytics and its predictive business value is not one of their traditional tools.

• HR has not yet reached the level where it can consistently and quantitatively demonstrate linkage to

value creation, causing many CEOs and CFO’s to view HR skeptically as a simply a cost-centre.

• This barrier is enhanced through differences between industry and organizational size.

The knowledge and experience is often lacking to turn metrics into analytics and analytics into strategies.

• Organizational cultures that foster silos inhibit using human capital analytics. Often data related to

human capital is disconnected from business operations, so the data is not integrated, and relationships

between people and business measures are not connected. Silos create gaps because managers focus on

their own area of control. Manufacturing departments report production output; HR reports people data.

• Lack of standardization of definitions, terminologies, and formulaic elements make metrics different

from one organization to other, and makes it difficult to build on generalizable knowledge beyond one’s

Organization.

•Regulatory and Financial requirements for valuing human capital do not currently exist.

•Whether standards should be pushed upon business and HR by regulators or pulled by demand is a key

question. (FASB, etc) Many believe regulation would be a good thing for HR because if human capital

investments such as training were treated as line-item investments, instead of costs, then investor

communities would see HC as the value driver it is.

•Metrics are often non-linear. Metrics are messy and sometimes composed of soft elements (Shared

valued, skills, style, staff) and can be ambiguous and hard to quantify.

 

While there are challenges to be met, much can be done to operationalize human capital data.

–Conceptualize metrics in three ways:

• ƒ Efficiency Metrics
• ƒ Effectiveness Metrics
• ƒ Predictive Metrics

– HR facilitates the process to involve managers about what metrics are relevant. These are metrics the

organization and managers own; not HR.

– Fewer metrics are better than more metrics

– Simpler is better than complicated

– Usually better to pilot a project with a smaller, human capital supportive/friendly department in your

Organization.

•Efficiency Measures

– Often we over-report efficiency measures because it’s easy

– Cost-per-hire, time-to-fill, number of training hours, HR Costs

• Effectiveness Measures

– Demonstrates how HR practices/measures relate to firm performance

– For example, increased productivity by RsX by lowering time-to-fill, lowered legal fees by RsX for

sexual harassment complaints through mandatory harassment training.

– Increase productivity by lowering voluntary turnover through key HR initiatives:

• ƒ Management training class.
• ƒ Team-building for areas where turnover was higher.
• ƒ Improved communication about how to utilize HR Services.

• Predictive Measures

– Reliably forecasts how HR practices/investments will improve organizational performance.

To Facilitate this process it is important to remember not to isolate the HR:-

– Build bridges with colleagues in other departments; seek to create consensus.

– Finance and Accounting are allies in this effort.

– Discuss with department heads about business metrics for which they are accountable.

– Ask them how employees contribute in achieving those metrics.

– Eventually pick 3-4 effectiveness metrics that you will focus on to report out.