The Human Resource Management System (RMS) is a fundamental element of any effective organization. It stores information on employees, employee skills, employee schedules, and projects in one globally accessible location. This makes it possible to search for talent and match the right people to the right projects based on their availability, skills, proficiency level, and other factors.
Twenty years ago, the patent for *“Human Resource Management System for Staffing Projects”* was granted to Unisys Corporation, then later assigned to Google. Its 20th anniversary creates an ideal opportunity to take a fresh look at the strengths and weaknesses of this widely-used system.
On the critical side, impressive progress has been made in business, science, and technology making the patent claims a bit outdated. On the positive side, the design outlined in the patent will enter the public domain in April 2020, so it’s possible to update it with fresh ideas. In this blog, we will look closely at the structure of the RMS system when it was patented in 2000, identify gaps in the original design, and point out valuable ideas that were not fully executed since that time.
Then we will describe the requirements for the next generation RMS based on the business demands of today.
The diagram below shows all the components of the original RMS, including the RMS system database, RMS server, controllers responsible for key dynamic functionality (e.g. user interface, calendar management, project assignments), and APIs extending to external databases. Beneath the diagram, we will describe the key modules of the RMS system.
The RMS modules that deliver core value are:
The information in the files of the centralized RMS database is obtained from internal and external corporate databases, as well as from direct entry. This provides a unified global view of the organization and minimizes the time and effort to compile information from multiple sources. A common user interface delivers a standardized view of this information. The RMS system gives users the ability to add to, maintain, and browse employee information in the RMS database. This includes adding a new employee and updating employee details.
Provided identifies human resources who have the necessary skills and availability to be assigned to projects. To define the search, project parameters such as time requirements (duration and level of effort), skill requirements and proficiency levels are entered. Additionally, users can limit the scope of talent search to current employees of the company or broker a request to External Services Vendors (ESV).
Assigns the identified employees to the projects and updates the system calendar to include the project assignments. The primary functions of the calendar are maintaining the details of an employee’s schedule and answering inquiries about the schedule. Calendar entries are generated when an employee is assigned to a project, and different types of scheduled activities are highlighted differently on the calendar display.
The manual calendar maintenance functions are used to enter non-project scheduled time (such as classes, vacations, and meetings), to update existing calendar entries, and to record personal reminders. To keep all information current, RMS provides interfaces between external databases and the RMS database.
To recap its good points, the 20-year old RMS design offers a unified view of employee information and an interface for talent search and project staffing. This makes it possible to create hybrid teams that are made up of internal and external resources. This is an important function that must be carried over.
But the original design leaves a few critical questions unanswered:
The design assumes that the skills are entered into the RMS system manually by system admins, managers or employees themselves. This is not ideal because it’s time-consuming, and decreases on-task employee productivity. Also, employees will add less information over time due to UI fatigue.
The design assumes that accurate levels can be assigned to employees by their managers, which is only partially true. The proficiency levels assigned to managers are subject to significant variation because different managers have different personalities and senses of proficiency and because project complexity varies. Also, it’s time-consuming to assign/review proficiency levels manually.
The RMS design assumes that complete information about resources and multi-faceted search functionality is enough to satisfy complex project staffing needs. But it’s clear that people are subject to their own biases and can’t compete with computers in the volumes of information they can process. Therefore, the search functionality must be extended with AI-based recommendation functionality and algorithms that automate matching of resources to projects.
The design talks about the Training Interface and Training Plans. but it’s limited to only the currently available courses, and the ability to assign people to courses. However, there are more valuable questions that an RMS should answer: Is it better to assign a proven resource to a complex project to minimize the project risk, or let a rising star take on a challenge, grow, and become another proven resource for the organization? Should expert-level resources create training courses, and how should their time be allocated between education and projects?
The design approaches the project staffing problem with an individual resource in mind. But people work in teams, and the success of a complex project depends on the quality of the team and mutual chemistry among the individual team members. And even more than personal compatibility, in today’s global economy most enterprises are geographically distributed, and remote work is taken for granted. Therefore, time zones, languages, and cultural differences are critical to form effective teams.
The design assumes that the calendar serves as the foundation for all information. Also, project assignments happen in a one-directional manner, from HRs and managers to the individual contributors/resources. Only the calendar alerts are used to signify conflicts without further discussion. That’s far from the reality. The RMS system must support a bi-directional dialogue. The resources should have a view into the pipeline of upcoming projects and corporate initiatives, so they can plan their calendars effectively. If there is an interesting project, the resource might cancel a vacation or reschedule some other events. Also, the RMS must benefit from the centralized information and take a global view of the organization and projects.
For example, some project start/end dates can be adjusted if core unique resources are locked or overutilized in existing projects. Finally, the training courses must be developed and assigned with the project pipeline in mind, proactively predicting any shortages in skills and developing a surplus of talent that is ready.
Following the original design patent in 2000, LinkedIn developed a universal professional social network and people search database, which is used more often than internal corporate RMS systems because of its network effects and better features. Oracle/PeopleSoft, SAP, IBM, Workday, and other corporations have built RMS and Human Capital Management (HCM) systems on their own.
Google introduced Google Calendar with existing and new functionality for sharing availability information and later spearheaded Project Aristotle. But according to the questions and requirements mentioned above, clearly, the RMS space is still wide open and ripe for innovation.
To respond to these opportunities, Gigster is working on an Innovation Management Platform (IMP). It helps organizations build dynamic teams, using internal and external talent, and raíses productivity by using Elastic Staffing, which assigns resources on an only-when-needed basis. It also includes ongoing, independent peer review, which lowers risks on individual projects and on entire digital transformation initiatives.
The Gigster IMP includes an advanced RMS system as a module and is based on the latest best practices in people analytics, user interface design, and machine learning. We invite you to join the conversation. Let us know if you want to learn more or would like to contribute.
