HYEMIN | Robert Half Front Office Modernization
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Robert Half Front Office Modernization

Opportunity

At Robert Half, Talent Service Professionals (TSPs) assist in finding talent for clients with the ultimate goal of placing the best matched candidates for the available positions. The primary platform TSPs use to carry out their job functions is a propriety tool called Front Office. Because it is a legacy tool that doesn’t fully deliver on the needs of TSPs, an opportunity to modernize Front Office was identified. Enter Design.

Challenge

Our team was brought on to help with two key phases:

Phase 1
Help with the discovery work to understand the current state experience, pain points, and what is working with with today’s systems and processes to determine the value proposition in modernizing the platform.

Phase 2
Reimagine the Front Office experience by exploring and developing design concepts based on insights from Phase 1.

Phase 1: Discovery & Immersion


Objective

To understand the current state experience, pain points, and what is working with with today’s systems and processes to determine the value proposition in modernizing the platform.

Methods

  • SME & User in-depth interviews
  • Systems survey
  • Reverse demo

Participants

  • 4 Business Development
  • 6 Recruiters
  • 2 Administrators
  • 1 Tech Support Team
  • 2 Project Managers

Phase 2: Design Concepts & Strategy

Objective

Explore, develop, and prioritize design concepts based on insights from Phase 1: Discovery & Immersion.

Visualize and Refine Concepts

A series of concepts developed based on insights from research that depict new or evolved Front Office & Service experiences.

Focus on Jobs To Be Done

Representative jobs & flows that provide adequate coverage of user needs or modalities to create a picture of the future experience.

Assess Business & User Value

Test & validate concepts with real users. Understand impact of new Front Office & Service capabilities to unlock business value.


Concepts

Guided Job Order

HMW simplify the intake process, updating a candidate’s file, and capturing job orders?

A guided Job Order intake breaks down content into logical groupings capturing like-information in a format that requires less cognitive load, saving progress along the way.

Pre-filled recommendations streamline the process and helps the system gathers as much information from the user as possible.

Share Job Order

HMW streamline the process of sharing remote jobs with other branches?

The inherent nature of remote jobs can mean that the physical location of the job may not be the same geographical location with the best candidate.

Machine learning provides smart recommendations and continuously improves as the algorithm collects more data, providing better internal and external visibility.

Match Candidate

HMW enhance searchability to surface better matches and also better integrate/connect information between RH and Protiviti systems?

Match criteria quickly surfaces best possibly matches across internal sources, external sources such as LinkedIn, as well as Protiviti. Criteria can be adjusted as necessary. Machine learning keeps a record of consistencies and trends between job orders and candidates that do eventually get hired to provide better recommendations.

Wireframes

Create Job Order
Job Orders

Job Order Detail

Spotlight

Candidate Matrix

Hi-Fidelity (Lightning Design System)

Create Job Order