Performance-Related Pay

Introduction

Employees are the nucleus of any organization. Effective performance management systems help utilize the capabilities of employees by systematically linking their work efforts, individually and as a team, to the overall performance of the organization. Employee compensation acts as a catalyst to the performance management systems. Hence, the effective design of employee compensation needs to focus on performance management systems. Performance-linked pay or compensation thus has a strategic significance, as it optimizes the cost of compensation and at the same time rewards the good performers, who feel increasingly motivated and see the organization as a more desirable place to work.

However, the practice of linking performance management systems with employee compensation varies across the globe as well as across organizations. The lack of universality in its approach, therefore, suggests experimenting with pay practices to find the approach that best satisfies both ends, that is, increased level of employees’ motivation and retention along with compensation cost optimization.

Any performance-linked or performance-related pay (PRP) method focuses on the achievement of goals and objectives for the organization. From this perspective it is business aligned. Defining key result area– or key performance area–driven performance measures, and thereafter linking the same with compensation elements dependent on those measures, is often seen as the best strategy.

In the central public sector enterprises (CPSEs; which in India are government-owned and -operated businesses) of India, the impact on organizational culture created when PRP is adopted has started attracting attention. However, two reasons oppose its institutionalization: (a) structural bottleneck combined with (b) the systematic reliance on performance goals based on MOU (memorandum of understanding) for departments.

Most of the public sector enterprises (PSEs) in India follow a typical hybrid structure. That structure concentrates the administrative and decision making powers at the corporate level, with unit or department leaders then pressured to achieve the desired performance results from employees. Within this structural bottleneck, assigning MOU-based performance goals with departmental heads, and then expecting them to deliver results, is often meaningless. However, the mandates from the Department of Public Enterprises (DPE) in India require the institutionalization of PRP in public sector companies in an attempt to create a culture of performance. Although the intent to increase performance is a good one, we feel obligated to observe that this is again like doling out performance-based incentives to all, without making any changes in the compensation design and plan—thus making the PRP a futile exercise, with small, incremental changes in the performance of India’s PSEs.

Scope of the Study

This article critically evaluates the PRP systems in PSEs, a policy that was mandated in India by the DPE’s order in 2008. For the evaluation, the author collected PRP-related data from two major CPSEs: Durgapur Steel Plant (DSP), a unit of Steel Authority of India (SAIL), and Oil and Natural Gas Corporation (ONGC). The author visited both organizations and studied their PRP system to assess how the introduction of PRP made a difference in their compensation and benefits program, and in what way the organizations benefited by incremental changes in their performance. Based on the evaluation, the author also suggests what could be the focus in PRP design for CPSEs, with the goal of building a culture of performance.

Background Discussion

Operationally, for many organizations that rely on pay systems based on step increases, the introduction of PRP is difficult. It is new to managers and employees and changes their working relationship. Senior-level employees reach the top of their pay scale and stagnate at the last step. As a consequence, the motivation of these employees declines along with their performance level, and many wait for the opportune moment to change employers.

This is exactly what SAIL experienced in most of their steel plants. As a consequence, SAIL lost many of their experienced employees, who took early retirement (under their previously launched voluntary retirement scheme). It benefited many steel plants under private ownership, as they could recruit quality replacements. A similar fate was experienced by the State Bank of India. Each of these can be attributed to the absence of suitable PRP systems.

Another basic operational issue is the design of incentives without specifying a minimum performance requirement. It means that everyone is eligible for the incentives, as individual contribution is marginally factored in determining payouts. While total reliance on individual performance is not desirable (as it can trigger conflicts), completely ignoring it is also not desirable. When compensation is linked to a combination of individual, departmental and organizational performance, it provides incentives for results that exceed the stated goals.

To reap the strategic benefit of pay for performance, many organizations limit the general base pay increase to the statutory minimum, while increasing the total compensation for those who are good performers. Thus, the organizations do away with the traditional cost of living and seniority principles widely used in some countries.

However, the switch to PRP has both advantages and disadvantages. The advantages are that it reinforces good performance, provides job satisfaction and contributes to better results. The disadvantages are possible problems in implementing and gaining acceptance for the idea, difficulty in identifying appropriate performance evaluation tools and a dilution of loyalty for employees who believe increases should be based on seniority.

Performance-Related Pay

The term PRP encompasses several company-wide schemes, including employee participation and share of ownership schemes and so on and general linkage with the compensation the employees get. PRP schemes are designed and managed based on business needs. They can fail to deliver when not aligned closely to business strategy. PRP can support ongoing change and performance improvement initiatives, but the practice in isolation cannot deliver the benefits, contrary to popular belief. Furthermore, line managers can muddle the process, unless they are supported through the transition.

Despite the possible problems in implementing PRP, organizations continue to adopt it. Some important considerations deserve attention in implementing PRP: labor market competition, cost control, individualization, strategy, system to monitor and evaluate the system and the impact on the culture.

In linking performance to pay, our approach is to identify at the outset the performance measures, and accordingly set our performance goals based on the measures. For example, when customers’ satisfaction is our performance criteria, we expect employees to focus on those activities that can enhance customers’ satisfaction.

Collective relationships in the workplace are a common organizational pursuit to achieve teamwork. PRP is essentially driven by an individualization agenda. We can decollectivize the work place and the employee relationship by individualizing management practices, particularly through reward mechanisms. Also we can use PRP in teamwork, that is, in social partnerships. The problem emerges when organizations switch to merit-only pay increases. Experience shows that effective PRP requires organizations to balance both the individualization and the collectivization. Thus, PRP needs to focus on individualization along with the collectivization and teamwork.

PRP becomes ineffective when it is not calibrated with the strategy of the organization. Introducing PRP and expecting employees to deliver results may not be fruitful, unless it is powered by robust monitoring and evaluation systems. Also, in the process of performance monitoring and evaluation, organizations can identify the pitfalls in the PRP design, and accordingly institute change in the practice.

Also the PRP and culture nexus is important for us to study. Culture varies across organizations. PRP differentiates compensation primarily based on merit criteria. But many CPSEs require valuing diversity, adherence to the principles of equity, factoring in loosely defined qualitative performance criteria and so on. Hence calibrating PRP against the culture of the organization may not be an easy exercise.

The use of PRP as an instrument of management control defeats its purpose of creating an enabling culture of performance. A basic purpose of PRP is to support employee empowerment by providing an incentive to tackle problems as they arise. In other words, it elicits commitment from the employees, and hence using it as a tool to enforce control is not desirable at all.

Reviewing the literature on PRP, we find the practice is based on agency theory, ¹ which governs the relationships between the principals (owners) and agents (managers). For PSEs, government, being the majority shareholder, plays the dominant role among principals. Managers of PSEs can be better aligned with the interests of the shareholders, when PRP based compensation design is developed. Eisenhardt ² and Hart ³ extended the discussions on agency theory to encompassing compensation design issues. The inherent conflict between the principals and the agents can be better resolved through PRP-based compensation design. The arguments for this rest on the premise that managers of PSEs work smarter with the expectation to earn more. Although money as a motivating factor to create a performance culture has been contested by many scholars,^4-7 PRP-based compensation in PSEs has been embraced globally, and India is no exception. The rationale behind the policy change is to bring efficiency in managing PSEs, using PRP as a driver. Vroom’s expectancy theory supports this argument. ⁸

Also, the approach does not conflict with Adams’s equity theory. ⁹ A well-designed PRP provides opportunity to managers (agents) to understand how their work efforts influence rewards; hence they feel motivated to perform better. When PRP is well designed, managers are able to assess the policy as equitable or inequitable, through both internal and external comparisons. ¹⁰

In private organizations, PRP design varies, as they have complete discretion to craft their own compensation strategies, based on their own business interests, while PSEs are constrained to follow the mandates of the government. For India, such mandates come from DPE.

Schuler and Rogovsky, based on their studies on 24 countries, analyzed the link between culture and compensation management practices. ¹¹ Their study reports that PRP works well when it is crafted within the cultural constructs of the country. In a culture of high uncertainty avoidance, employees being more adept to stable compensation, PRP may not work. When PRP places more weight on individual contributions than on group and team performance, it may not be the right fit for a culture of collectivism. The compensation/culture nexus is the best fit in institutional theory,^12,13 as firms’ behavior and managerial practices, so also compensation management practices, as per this theory, are culture congruent.

Success and failure of PRP have been studied by various research scholars across the countries. These studies report conflicting results.

From the literature review above, we can discern that debates on PRP in PSEs can be grouped under two broad categories: agency theories and expectancy theories. We have briefly introduced both the pioneering concepts. But in the context of PSEs, we need to understand its implications for workers’ performance

Overview of CPSEs in India

Since the country’s independence, CPSEs have played crucial role in the Indian economy. Currently, the 220 operating CPSEs account for 6% of the country’s gross domestic product (as of 2011). With a 14.8% year on year growth in investments, and the employment of 1.4 million people, the CPSE’s role is gradually increasing.

To achieve cost-efficiency, transparency and productivity, the Government of India embraced PRP in 2008 in line with the practice in many member countries of the Organisation for Economic Co-operation and Development (OECD). That was when the sixth central pay commission report was announced (although the effect was retroactive to 2007). At present, 28 out of 34 OECD countries have embraced PRP in government organizations (OECD Report 2012; http://www.oecd.org/dac/dcr2012.htm).

The root of PRP in India in public services actually dates back to 1998 when Justice Mohan Committee recommended its usefulness. CPSEs in India implemented PRP linking with the MOU-based performance achievements, with effect from January 1, 2007.

The leaders of each CPSE sign an MOU with the government, which specifies objectives and obligations and becomes the basis for evaluating performance. An MOU includes both financial and nonfinancial performance targets and includes 5-point scales to be used in measuring annual performance. Based on a composite score for all objectives, an overall performance index for the CPSE is determined, known as the MOU rating. The DPE recommended scale for evaluating the MOU rating is presented in Table 1.

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Table 1.

Memorandum of Understanding Rating Scale.

Memorandum of understanding composite score	Rating	Percentage score
1.00-1.50	Excellent	100
1.51-2.50	Very good	80
2.51-3.50	Good	60
3.51-4.50	Fair	40
4.51-5.00	Poor	0

Source. Department of Public Enterprises.

India has 202 MOUs signed as of 2011. A partial summary of the MOU ratings as provided by the DPE is presented in Table 2.

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Table 2.

Performance Ratings of Central Public Sector Enterprises.

Rating	2007, N (%)	2008, N (%)	2009, N (%)	2010, N (%)	2011, N (%)
Excellent	46 (45.1)	55 (49.1)	47 (37.9)	73 (50.3)	67 (42.1)
Very good	37 (36.3)	34 (30.4)	34 (27.4)	31 (21.4)	42 (26.4)
Good	13 (12.7)	15 (13.4)	25 (20.2)	20 (13.8)	24 (15.1)
Fair	6 (5.9)	8 (7.1)	17 (13.7)	20 (13.8)	24 (15.1)
Poor	0 (0)	0 (0)	1 (0.8)	1 (0.7)	2 (1.3)
Total central public sector enterprises	102 (100)	112 (100)	124 (100)	145 (100)	159 (100)

Source. Department of Public Enterprises.

We see in the table that the number of CPSEs rated excellent or very good each year is 70% to 80%, while in the poor performance category there are only 1 or 2 CPSEs. This indicates that the DPE has been liberal in its ratings, presumably to make employees working in the CPSEs eligible for PRP.

To attract and retain the talent, employees in Indian CPSEs are ensured competitive compensation relative to their counterparts in peer companies in the private sector, except for the chairmen and chief executive officers. Although it is argued that the difference for the two jobs is attributable to the higher risks involved in private sector management, CPSEs in India are fully expected to earn higher returns than their peer companies in the private sector. The degree of equity in PRP and compensation as a whole is much higher in CPSEs than in Indian private sectors.

Case Studies

PRP Calculation in ONGC and SAIL (DSP)

For both the organizations PRP formula is crafted in line with DPE mandates. Sixty percent of PRP entitlement is calculated on profit before tax (PBT) and 40% of PRP is calculated on incremental profit.

SAIL’s Performance-Related Pay Formula

Physical and financial performance weights for PRP in SAIL have been assigned as follows:

Weight on overall company performance    77.5%

Weights on specific performance areas:

Saleable steel production 02.5%

Specific energy consumption 02.5%

Yield from crude steel to saleable steel 02.5%

Actual PBT versus budgeted PBT 07.5%

Total 100.0%

Based on the above, DSP has used the following formula for PRP payment:

PRP (1) = 60% × Annual basic pay × MOU rating 77.5% (performance factor for the company as a whole) + 2.5 × Plant’s saleable steel production% + 2.5% × Plant’s specific energy consumption% + 2.5% × Plant’s yield from crude steel to saleable steel% + 7.5% × Plant’s budgeted PBT% + 7.5% × Individual performance rating] × [Grade incentive × Ratio of available to required amount]

+

PRP (2) = 40% × Annual basic pay × MOU rating 77.5% (performance factor for the company as a whole) + 2.5 × Plant’s saleable steel production% + 2.5% × Plant’s specific energy consumption% + 2.5% × Plant’s yield from crude steel to saleable steel% + 7.5% × Plant’s budgeted PBT% + 7.5% × Individual performance rating] × [Grade incentive × Ratio of available to required amount]

−

Adjustments for payments made previously for the year.

ONGC’s Performance-Related Pay Formula

For ONGC, the PRP formula is calculated in two components in line with DPE guidelines:

PRP (1) = Pool proportion (60% of the component) × MOU rating × Grade ceiling × Annual basic pay × Individual performance × Pool availability factor (represents 60% of payout)

PRP (2) = Pool proportion (40% component) × MOU rating × Grade ceiling × Annual basic pay × Individual performance × Pool availability factor (represents 40% of payout).

For calculating an individual’s payout, PRP (1) and PRP (2) are added.

The bonus pool in both the cases and also for all CPSEs starts for budgeting at 5% of PBT. This 5% is calculated as 3% of PBT plus 2% PBT from 10% incremental profit over the prior year. Pool availability factor or percentage is derived by dividing amount available from final profits with amount required.

Table 3 shows the decade-long trend of MOU ratings by DPE for these two CPSEs.

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Table 3.

Memorandum of Understanding Rating by Department of Public Enterprises.

Selected central public sector enterprise	2002-2003	2003-2004	2004-2005	2005-2006	2006-2007	2007-2008	2008-2009	2009-2010	2010-2011	2011-2012
Oil and Natural Gas Corporation	1.29	1.70	1.77	1.43	1.44	1.81	1.70	1.53	1.79	1.22
Steel Authority of India	1.48	1.37	1.13	1.36	1.07	1.13	1.22	1.10	1.09	1.18

Source. Department of Public Enterprises and companies’ financial results.

Interpreting the MOU ratings in Table 3, we observe that both of the CPSEs over the decade consistently performed well. However, in terms of their average rating in the years pre– and post–PRP implementation, we see an increasing trend in the ratings for ONGC, while there is a decreasing trend for SAIL. For example, the average MOU rating for ONGC during the preimplementation phase of PRP, that is, from 2002-2003 to 2006-2007, is 1.53, while during postimplementation phase, that is, from 2007-2008 to 2011-2012, it is 1.61. For SAIL, however, the average ratings fell for the corresponding periods from 1.28 to 1.14.

This prompts the following question: Does PRP really contribute to better performance of the CPSEs? However, the answer at the macro level would be simplistic, until we develop a more in-depth analysis of the CPSEs based on certain known performance indicators.

Considering with the data available for the two organizations, we selected four performance indicators as the basis of our analysis: (a) percentage change in workforce, (b) percentage change in labor productivity, (c) percentage change in employee compensation costs and (d) percentage change in profit and loss figures. These data are presented in Table 4.

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Table 4.

Performance Indicators of Selected CPSEs.

	Workforce (% change)		Labor productivity (% change)		Employee remuneration (% change)		Profit/loss (% change)
Years	ONGC	SAIL	ONGC	SAIL	ONGC	SAIL	ONGC	SAIL
2002-2003	—	−7.3%	—	+9.7%	—	—	—	—
2003-2004	−3.3	−4.2	—	+11.0	+61.4	+27.8	+20	−726.0
2004-2005	−4.8	−3.8	+0.01	+5.0	+7.2	−18.4	−0.8	+171.4
2005-2006	−4.0	+8.9	+19.7	+12.0	+24.3	+9.0	+11.1	−41.0
2006-2007	−2.0	−8.0	6.0	+33.0	+43.0	+22.3	+8.0	+53.0
2007-2008	−2.0	−3.0	+4.8	+7.0	+23.9	+55.8	+6.8	+1.6
2008-2009	+0.1	−5.0	+33.0	+0.5	−21.6	+6.3	−3.5	−18
2009-2010	−0.6	−4.8	+12.0	+6.0	+21.0	−36	+4.0	+9.3
2010-2011	+1.4	−5.3	+12.2	+5.7	+17.6	+40.70	+12.9	−27.4
2011-2012	−1.1	−4.3	+1.5	No change	+1.0	+4.0	32.8	−27.4

Source. Analysis of annual reports of selected CPSEs.

Note. CPSE = central public sector enterprise; ONGC = Oil and Natural Gas Corporation; SAIL = Steel Authority of India.

The performance indicators are all credible indicators of operating results. All well-performing organizations should work to achieve workforce optimization. Using the change in the workforce may raise the question of its validity, as organizations sometimes add employees to accommodate a planned expansion. However, in both the cases, additional capacity building was primarily achieved through the adoption of new technology, which triggered a reduction in required manpower. Presumably, the new technology for both the CPSEs increased productivity of manpower rather than creating the need for new recruitment. Therefore, percentage change in manpower strength can be used a performance indicator.

Labor productivity trend is an accepted performance indicator. Hence, an increasing percentage change in labor productivity is a good performance measure for the two organizations.

Similar to the percentage change in the number of employees, the percentage change in employee remuneration can also be considered as a good performance indicator. Any well-performing organization is expected to optimize the employee remuneration and benefits cost. Hence, when considered with changes in productivity, decreasing percentage change in employee remuneration and benefits can be a good performance indicator.

Finally, the percentage change in profit and loss is a known performance indicator for any business.

In Table 5, we show the average percentage change in the above performance indicators for both the organizations during pre- and postimplementation phases of PRP.

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Table 5.

Percentage Change in Performance in Pre- and Postimplementation Phases of PRP.

	Average percentage change in workforce		Average percentage change in labor productivity		Average percentage change in employee remuneration		Average percentage change in profit or (loss)
Period	ONGC	SAIL	ONGC	SAIL	ONGC	SAIL	ONGC	SAIL
Preimplementation phase	3.7%	2.9%	8.7%	4.8%	34.0%	10.2%	9.7%	(135.7%)
Postimplementation phase	2.7	4.5	10.6	4.8	8.3	14.2	10.6	41.9

Note. PRP = performance-related pay; ONGC = Oil and Natural Gas Corporation; SAIL = Steel Authority of India.

Analyzing the data, we can see that the changes from one period to the next are not significant, except for the change in profitability, which is significant for both organizations. ONGC shows modest improvement on each measure, but then this was during the years of the Great Recession. In the early years, SAIL had large losses, but it did turn around. One cannot conclude from the data that PRP triggered improved performance. This therefore raises the question: How effective is PRP for Indian CPSEs?

Conclusion

This study is not intended to refute the expected efficacies of PRP as a tool to improve performance broadly or specifically in PSEs. Rather, it intends to test through a longitudinal analysis whether PRP delivered better results, and also to determine why the expected outcome is not encouraging? We have argued that for CPSEs, the problem is that performance targets are mandated by DPE through MOUs. MOU performance parameters, among others, emphasize issues that are not part of the core business goals of the organizations.

For example, SAIL’s consistent underperformance as measured by profitability, even after PRP was implemented, did not lead DPE to rate SAIL at a comparable level to ONGC, which produced little difference in the PRP payouts in these two organizations. It is also important to note that the post–PRP implementation phase occurred during the global economic recession. Neither organization experienced any significant decrease in demand (although the enterprises performance no doubt would have been better if the economy remained strong). The study, therefore, provokes the need for investigating the performance parameters of DPE-mandated MOUs for CPSEs to test if the measures are aligned with and accepted by management as realistic business goals. An unanswered question is this: Can they really contribute to building a culture of performance in CPSEs?

Future longitudinal research on PRP in the country’s CPSEs would be appropriate for recrafting the PRP systems, including assessments of the formula for PRP payouts, the process for setting MOU performance parameters and the system’s administration. Even though the study is confined to only two CPSEs, its findings can help to plan for future research.