HRM 595 Week 5 HR Tools, Technology and Data Example

From Paper Certificates and Spreadsheets to a Workforce Dashboard: HR Technology and Analytics for Prairie Crest Wind Services

[Student Name]

University of Phoenix

HRM/595: Human Resource Capstone Course

Week 5 Assignment

[Instructor Name]

[Date]

Prairie Crest Wind Services, its systems, costs and data are composites written for a model paper.

The capstone company, a composite turbine maintenance firm, has set objectives for hiring 340 technicians a year, cutting early-career turnover from 31 to 20 percent, certifying 45 blade technicians, developing 80 supervisors and reporting workforce data monthly. None of these can be managed with its current tools. Payroll runs on a mid-market payroll system, recruiting uses email and a spreadsheet, safety and skill certifications are tracked on paper copies kept by supervisors and turnover is calculated once a year. A plan with monthly targets needs monthly data, and an organization that cannot see its workforce clearly will manage it by anecdote. This paper sets out the tools, technology and data Prairie Crest needs.

Current Tools and Data

The inventory found five systems and many workarounds. Payroll holds pay, hours and basic employee data. A safety database in operations records incidents. Recruiting uses a shared spreadsheet. Supervisors keep certification copies in binders and trucks. Training is tracked by the training coordinator in a separate spreadsheet. No system connects them, and HR spends about 30 hours a month compiling basic reports.

Requirements From the Plan

Requirements follow from the plan's objectives. Hiring at scale requires applicant tracking with mobile applications, interview scheduling and source tracking. Skill-based pay requires a skills and certification record linked to pay. Supervisor development and blade training require a learning management system. Monthly targets require reporting that combines headcount, hiring, turnover, skills, safety and development. Field supervisors need tablet access.

Research on HR Technology

Stone et al. (2015) reviewed how technology has changed HR processes and noted benefits in efficiency and access to information, along with risks such as reduced personal contact, privacy concerns and systems that do not fit users' needs. Their review suggests that technology choices should be guided by HR goals and user experience, not by features alone.

Option One: Integrated Cloud Suite

An integrated suite combines core HR, payroll, recruiting, learning, skills and analytics on one database. It simplifies reporting and gives employees and supervisors one mobile app. Estimated cost is about $310,000 to implement and $240,000 a year in subscriptions for 1,050 to 1,465 employees.

Option Two: Best-of-Breed Tools

Separate tools for applicant tracking, learning and analytics, connected to the existing payroll system, offer strong features in each area. Estimated cost is about $180,000 to implement and $200,000 a year, plus ongoing integration work. Reporting requires combining data from several systems.

Option Three: Payroll Vendor Add-Ons

The current payroll vendor offers modules for recruiting, learning and basic reporting. Cost is lowest, about $90,000 to implement and $130,000 a year, but the skills tracking module cannot link certifications to pay, and the analytics are limited.

Comparing the Options

Rated on fit with requirements, integration, usability for field staff, cost and scalability, the integrated suite scores highest. The best-of-breed option scores well on features but poorly on integration for a small HR team. The add-on option fails the skills requirement. The recommendation is the integrated suite, selected through a competitive process with field supervisors testing the mobile app.

The Skills and Certification Tracker

The tracker will record each technician's certifications, such as climbing, rescue, electrical and rope access, with expiration dates, along with skill levels assessed by lead technicians. It will alert supervisors before certifications expire, link skill levels to pay and show which technicians are ready for lead roles. Customers' requests for proof of qualifications can be answered in minutes rather than days.

The Workforce Dashboard

A monthly dashboard for executives and operations managers will show headcount against plan by state and role, hires and time to fill, turnover by tenure and role, certifications and skill levels, safety incidents, supervisor development progress and overtime. Each measure links to an objective from the gap analysis.

A First Turnover Analysis

To show the value of data, HR combined payroll, scheduling and exit data by hand for 2024 and 2025. Technicians on rotations of 21 days on and 7 off left at 38 percent a year, compared with 19 percent for those on 14 and 7 rotations. Technicians whose supervisors had more than 12 direct reports left at 33 percent, compared with 21 percent for smaller crews. These patterns point to rotation design and supervisor span as retention levers.

Using Analytics Responsibly

In their review of the analytics literature, Marler and Boudreau (2017) reported that few firms use HR analytics extensively, that it is most valuable when tied to business questions and that organizations often lack the analytical skills to use it well. Prairie Crest will start with a few questions tied to the plan, such as what drives early-career turnover, and build skills gradually.

From Data to Decisions

Data matter only if they change decisions. Rousseau and Barends (2011) described evidence-based HR as combining organizational data with research findings, professional expertise and stakeholder views, and the turnover analysis shows how. The data point to long rotations and wide supervisor spans; research on turnover suggests both matter; operations leaders confirm that 21-day rotations were adopted to cut travel costs; and technicians said in the Week 1 survey that rotations are a reason they leave. Together these sources support piloting 14-day rotations in one state and comparing turnover and travel costs after a year.

Data Quality

The new system is only as good as its data. Before migration, HR will clean employee records, digitize paper certifications with supervisors verifying each one and standardize job codes. Data owners will be assigned for each area.

Privacy and Security

Workforce data include medical information from fitness-for-duty exams and drug tests, which must be stored separately with restricted access. Role-based permissions will limit what supervisors see. The vendor must meet security standards, and employees will be told what data are collected and why.

Building HR Analytics Capability

The HR information systems analyst will be trained in analytics, and one HR generalist will develop reporting skills. Operations analysts who already work with turbine data will be invited to collaborate, since they understand the field's measures and can help link workforce data to uptime and availability penalties.

Implementation and Budget

Implementation runs in phases: core HR, payroll and recruiting in months one through six; skills tracking and learning management in months seven through 12; analytics and dashboards in months 13 through 18. The total first-year cost is about $550,000. Savings from reduced manual reporting, faster hiring and lower agency use are expected to offset about half of the annual subscription within two years, with larger benefits from retention gains.

Conclusion

Prairie Crest cannot manage a growth plan with paper certifications and annual turnover reports. An integrated system, a skills and certification tracker, a monthly dashboard and a modest analytics capability, implemented in phases with attention to data quality and privacy, will let leaders see and manage the workforce. The first turnover analysis already points to rotation design and supervisor span as levers for retention.

References

Marler, J. H., & Boudreau, J. W. (2017). An evidence-based review of HR analytics. The International Journal of Human Resource Management, 28(1), 3-26. https://doi.org/10.1080/09585192.2016.1244699

Rousseau, D. M., & Barends, E. G. R. (2011). Becoming an evidence-based HR practitioner. Human Resource Management Journal, 21(3), 221-235. https://doi.org/10.1111/j.1748-8583.2011.00173.x

Stone, D. L., Deadrick, D. L., Lukaszewski, K. M., & Johnson, R. (2015). The influence of technology on the future of human resource management. Human Resource Management Review, 25(2), 216-231. https://doi.org/10.1016/j.hrmr.2015.01.002