Measuring productivity a challenge

Causal model provides insights into efficiency of knowledge workers

The question of how best to measure the productivity of employees has long been debated.

“The measurement of the quality of work, not just the quantity of work, is critical to determining productivity in knowledge workers,” says Peter Drucker in his book Management Challenges for the 21st Century. “Business practices see manual workers as a cost… while knowledge workers must be seen as a capital asset.”

Research conducted over the last 10 years by Nick Bontis, an associate professor at the DeGroote School of Business at Hamilton’s McMaster University, and others has been instrumental in the development of causal models that demonstrate the organizational factors that appear to drive effective human capital management practices in several industries.

This ground-breaking research was used as a foundation for our causal model study, conducted in 2008 and 2009 with HR metrics data collected from 44 companies across Canada through a Human Capital Benchmarking Survey conducted by the Wynford Group.

A causal model shows the strength of the impact (or cause) of investment in specific human resource programs — such as return on investment, employee engagement and the attraction and retention of employees — on business outcomes. The strength of these causal relationships can be used to prioritize and validate HR efforts and investment in particular HR programs by identifying those that have the greatest ROI. In other words, the causal model demonstrates how HR impacts an organization’s business performance.

With increased pressure on organizational performance and focus on supporting core business drivers and results, human capital metrics and the causal model can be used to identify areas of opportunity for increased value creation by employing human capital more effectively.

Focus on training, compensation and engagement

When there is a strong positive or negative influence, research indicates changes to the causal factor should influence the outcomes of the related factor. The HR factors that collectively have the greatest influence on increasing productivity are training investment, compensation and employee engagement.

How can we prove this? Look at the correlation coefficient, which refers to the number allotted to the relationship between each factor and productivity. The closer the correlation coefficient falls towards positive one or negative one will determine how strong the relationship is.

For example, our study finds training investment (0.7625) has a strong positive influence or tends to increase productivity (measured by ROI of human capital) along with compensation (0.3208). (See chart). Turnover has a negative relationship with other factors, that can be viewed as an indicator of employee retention.

Training is a lead or predictive factor that will predict increases in productivity over time. This suggests investment in focused training programs has a strong likelihood of increasing productivity in the future, providing the workforce remains fairly constant. The correlation of compensation with productivity suggests rewarding performance does have a positive effect.

Another part of the causal model looks at the HR factors that have the strongest influence on reducing turnover:

• leadership (which can include an immediate boss or the organization driving culture)

• HR investment (programs and people)

• compensation (particularly incentives).

These results correspond to the results from a fall 2009 survey by the Wynford Group of more than 200 organizations in ranking the most critical issues to employees: career planning or advancement opportunities, competitive compensation, job security, challenging work, effective leadership, work-life balance and a comprehensive benefit package.

To look at increasing employee engagement the greatest influences are:

• learning opportunities (including career development programs and opportunities)

• leadership

• HR investment (programs and people).

When the factors are interlinked, it is evident there are several factors that have a significant influence on more than one factor including:

• leadership

• learning and development

• general HR investment

• compensation programs.

Therefore, investment and support for these factors should provide the best ROI for HR program funds.

Using the model

This study of critical human capital metrics will enable employers to identify drivers for human capital productivity, demonstrate the linkage between human capital investment and the bottom line, and demonstrate the value of HR programs and initiatives at the executive table. Leadership, learning and training, general HR investment and compensation or incentives are factors that strongly predict success or increased productivity.

Investment in these areas should provide an increase in human capital success in the future. However, it is important to look closely at the specific relationships within an organization to fine-tune this model.

“The benefit of establishing a causal map of human capital management is clear,” says Bontis in “Intellectual Capital ROI: A causal map of human capital antecedents and consequents (2002).”

“Senior management can visually comprehend the antecedents and consequents of various quantitative and qualitative aspects of human capital, thus making clear executive management decisions (based upon) expected outcomes,” says Bontis.

Our results support the use of a causal model of the relationship of HR strategies and business outcomes as an effective tool for management decision-making.

Gail Evans is the president of the Wynford Group in Calgary which specializes in total rewards consulting, compensation and HR metrics. She can be reached at [email protected] or (877) 264-5166 or visit for more information.

Latest stories