HR Analytics: Human Capital Return on Investment, Productivity, and Profit Sensitivity: A Case of Courtyard Marriott Newark at the University of Delaware

Abstract

The objective of this case study is to apply human capital analytics, more specifically, human capital return on investment, human resources productivity, and compensation efficiency at the Newark Courtyard Marriott Hotel, University of Delaware, and investigate if such analytics adds new outlooks beyond the usual metrics used by lodging enterprises. The study presents quantitative metrics and trend analysis for a 3-year period at this business unit. In addition, the case study provides measures that help management to identify and address inefficiencies, as well as the productivity of its human capital. The study also highlights the benefits of Bridging Practice and Theory.

Appendix: Case Study Questions

• Q1. How can HC analytics help us find where the most investments in HC should be?

Suggested answer: In calculating HC costs, we used all of the following figures:

• Labor cost (wage and salary)

• Employee benefits costs (medical, 401 K, social security, education, relocation, sick pay, paid holidays, and employer contributions to healthcare benefits)

• Training and development, tuition reimbursement if applicable

• Recruiting costs (people, ads, development of position descriptions, etc.)

• Hiring costs (physicals, drug tests, background checks, reference checks, agency fees, referral fees from agencies

• Orientation costs for new employees

• Uniforms issued by firm

• Employee meals and locker room costs

Management can scrutinize any of the above numbers and decide where the savings or additional investment is most appropriate. Obviously, in the lodging business, trade-offs between qualities of service, mainly customer satisfaction data and costs, could be considered first. As we look at the root causes of service issues, we can track back to various components of the human capital costs listed above. For example, costs in support of employees. We know that lack of familiarity with job procedures could be related to investment in training or turnover, both manageable costs. Likewise, corrective action could be taken to increase emphasis or investment in those areas. Each issue can be fully investigated to determine the best way to improve that measure. Management can decide the level of resource allocation based on the HC ROI results and connect it to other data sources considering the severity of the issues and overall impact on key guests’ measures, such as “likelihood to return” or “likelihood to recommend.”

• Q2. Can tying sentiment analysis and guest satisfaction data to investments in people (human capital metrics) give us advance warnings of service delivery problems?

Suggested answer: In addition to direct guest feedback, most hotels have added feedback from user generated sites (Trip Advisor, Google, Yelp) to provide other sources of guest feedback. Marriott currently uses both own customer data and a social media index to analyze hotel performance against peer hotels. HC ROI metrics can expose areas of service improvement opportunity and enable management to focus on those areas. The related costs of that emphasis may well be visible in the component costs of human capital (i.e., training, pay, benefits, turnover). Mining the verbatim comments from these guest feedback sources is vital to getting to root cause, trends, and identification of possible corrective actions.

• Q3. What kind of data can we bring into our data analytics tools and algorithms to better understand HC productivity?

Suggested answer: The productivity algorithm in this case study showed that, keeping other elements constant, an increase in revenue levels and reducing material costs can boost productivity ratio. To improve revenue levels companies can utilize Net Promoter Scores, guest surveys, number of repeat stays, loyalty programs, and customer sentiment analysis on social media to increase revenues. Similarly, companies by monitoring prevailing material costs and its trends can assure the target productivity levels and benchmark with other competitive set.

• Q4. If we have service quality disruptions, how can we most effectively recover?

Suggested answer: Hotels need to prepare for more disruptions in the near future. Disruptions can come from both external and internal (on-site). From an external perspective, general state of economy, consumer mindset, technology, and business platform are critical (Deloitte: https://www2.deloitte.com/content/dam/Deloitte/us/Documents/consumer-business/us-cb-2017-travel-hospitality-industry-outlook.pdf). First, a strong economy can add to demand, which requires accurate workforce planning and recruitment effectiveness that can contribute to productivity. Reverse is the same when economy is not performing or some unexpected risks might be on horizon, such as spread of Zeka, etc. Second, consumer mindset and expectations are in state of flux. Companies need to get customized and personalized data in the hands of those who deliver service at all touch points in order to differentiate their business and service offerings to their clients using their customer behavior measures and social networks. Third, hotels are, to a degree, behind in delivering enabling technologies to their customers. For example, by utilizing innovative apps hotels can enable their customers to book rooms, make various appointments, control their room temperature, and communicate with staff or other guests. The Internet of Things (IoT), by connecting devices, offers numerous opportunities to hotel businesses, such as connecting customer smartphones to various sensors at the hotel to greet a guest by name upon arrival, lead them to their room, open the door automatically, and manage the other needs of customers based on their unique profile. Fourth, new business platforms will be needed as the industry’s organic and vertical growth reaches maturation. That is, hotels engaging in mergers and acquisitions will need to add across travel experiences, such as retail, restaurants, local excursions, etc. to provide personalized experiences. Finally, HC metrics offered in this case study will be helpful to analyze, add people to service areas that have impact on revenue growth, and reduce them where they don’t.

• Q5. How can we link analytics to talent acquisition strategies? Retention? Engagement?

Suggested answer: Although this study focused on strategic level financial metrics of human capital, lodging industry faces many human capital challenges. Other case studies and human capital analytics can help in a number of areas, such as new hires, employee post-hire performance, total reward systems, overtime analysis, and effective benefit plans. Additionally, turnover, resignation, and employee movement are common place in hotel industry. BI methods used in predictive human capital analytics can analyze available data across location, department, gender, age, promotion wait time, pay increase, training, and other factors and relate them to business outcomes.

• Q6. What are potential ethical concerns with respect to leveraging analytics to measure human occipital performance?

Suggested answer: Management and HR need to be mindful of ethical considerations in using BI. Be wary of broad classifications of guests with trends in service issues. We cannot allow our staff to have preestablished perceptions of guests that will impact service and generate reactive behavior from guests (i.e., sensitivity to ADA conditions, race, gender, nationality). The privacy of guest feedback in all areas needs to be respected even if the guest has not taken reasonable precautions. HR predictive analytics tools can build employee profiles, such as engagement, dietary habits, shopping practices, tracking employee sentiments, etc. Companies are using employee data, such as who knows what? Who knows whom? Which employee is likely to quit? Data about surprise events or escalated incidents, etc. (Leong, 2017). Privacy of employees is a critical ethical consideration. Although these technologies are beneficial, companies need to create information governance committee (IG) to analyze their privacy culture, set guidelines, and encourage best practices.