The HR director creates an HR Scorecard. This shows the cause and effect links among the HR activities the workforce behaviors, and the organizational outcomes.
This scorecard and its linkages reflect certain assumptions on Lisa’s part. For example, based on experience and discussions with the firm’s other managers, she formulates the following hypothesis about how human resources affects hotel performance: Improved grievance procedures cause improved morale, which leads to improved front desk service, which leads to increased guest returns, which leads to improved financial performance. The HR director then chooses metrics to measure each of the factors. For example, she decides to measure improved disciplinary procedures in terms of how many grievances employees submit each month. She measures improved morale in terms of score on our hotel’s semiannual attitude survey and measures high quality front desk customer service in terms of customer complaints per month.
She moves onto quantifying the cause and effect links among these measures. For example: Can we show top management that there is a measurable sequential link between improved disciplinary procedures, high morale, improved front desk service number of guest return visits and hotel financial performance (revenues and profits)? If she can show links, she has a persuasive case that shows human resources’ measurable contribution to the hotel’s bottom line financial performance.
In practice, the HR manager may have to rely on a largely subjective but logical argument to make the case or the cause and effect linkages. But ideally, she will use statistical methods such as correlation analysis to determine if links exist, and (if so) what their magnitudes are. In this way, she might find, for instance, that a 10% improvement in grievance rates is associated with an almost 20% improvement in morale. Similarly a 20% improvement in morale is associated with a 30% reduction in customer front desk complaints. Furthermore a 30% reduction in complaints is associated with a 20% increase in guest returns visits, and a 20% increase in return rate is associated with a 6% rise in hotel revenue. It would appear that a relatively small HR effort in reducing grievances might have a considerable effect on this hotel’s bottom line.
In reality several things complicate this measurement process. It is risky to raw cause effect conclusions from correlation measures like these (for example do fewer grievances lead to higher morale, or vice versa) Furthermore it’s rare that a single factor (such as grievance rates) will have such effects alone, so we may want measure the effects of several human resources policies and activities on morale simultaneously. And (given the huge number of things that influence hotel performance) it may not always be possible to confirm all the links in the measurement chain. If not, the HR manager must rely more on logic and common sense to make her case. The Improving Productivity Through HRIS discussions below shows how computerized systems can facilitate the scorecard and management activities.
How we will use the Hotel Paris HR scorecard
In reality, computerization enables the HR director for the Hotel Paris to create a more comprehensive HR scorecard, one that might accommodate links among dozens of cause and effect metrics. For example, with computerization the HR director need not limit herself to assessing the effects of the handful of employee behaviors (such as percentage of calls answered on time. Instead, she could include metrics covering dozens of activities, from recruitment and election through training, appraisal, compensation, and labor relations. Her Scorecard model could also include the effects of all these activities on a wide range of workforce competencies and behaviors and thus on organizational outcomes and on the company’s performance. In this way her HR scorecard would become a comprehensive model representing the value adding effects of the full range of Hotel Paris human resource activities.