Customer Success
Digitalizing Talent Reviews Yields Annual Time Savings of 9,600 Hours by Eliminating Excel-Based Processes.
Overview
A leading global retailer wanted to introduce a new model for assessing and reviewing talent. Managers would assess their teams and the business would use that data to discuss talent, identify high potentials and differentiate their people investment. They had designed everything in Microsoft Excel but asked us to digitize the process for scale, to reduce administration, improve data governance and drive process effectiveness.
Industry
Retail and Wholesale
Implementation
13 Months
Scope
10,000 Employees
Value Driver
Ability to produce talent review packs on-demand for 3,500 managers.
Introduction
Talent management is a critical function for organizations to identify and nurture top talent to drive their success. The process of evaluating employees’ performance and potential can be complex and time consuming, especially in large organizations. A business within the world’s largest retail group faced a similar challenge of identifying high-potential employees and classifying them in a clear and simple way. The existing assessment process lacked scalability, involved significant administrative burdens, and often lead to a misidentification of potential. Their goal was to introduce a new investment matrix model that could evaluate and identify employees’ performance and potential, provide a fully digitalized process for scalability and data accuracy, and improve the overall efficiency of the process.
Challenge
The existing assessment process used an Excel spreadsheet, and nearly 3,000 managers had to answer a series of questions for each of their team members, save the spreadsheet and then email it to their business partner. HR was then tasked with consolidating the data manually, leading to an administrative burden and increasing the chance of human error.
Approach
The first thing we did was to digitalize the process with an interactive online form. We designed change management communication and automated the compliance and reminder management needed for the project. This improved efficiencies, but there was a secondary challenge; Managers were overrating potential, and there was no clear differentiation of talent. We needed to identify a way of supporting managers to make better quality assessments of potential.
Solution
The interactive online assessment improved manager participation to over 96% and reduced the time investment from HR by nearly 10,000 hours across the business. We used TalentPrint behavioural data to validate the managers view of potential and could flag any misalignment for discussion, providing recommendations throughout the process that improved the effectiveness of employee placements and ultimately improving the allocation of development resources.
Results and Conclusion
With an average of 10,000 assessments completed every year and over 4,000 placements improved through data driven conversation, the new investment matrix model now supports the entire talent value chain, from talent reviews to internal mobility, learning, and career development. The process directly connects high potential employees with career opportunities, providing a scalable and accurate solution for talent reviews to this business.
This project improved the efficiency, effectiveness, and scalability of the existing talent management process. By digitalizing the process and providing data that helped validate managers’ views of potential the business could streamline their talent process, making it more scalable, accurate, and efficient, ultimately leading to improved allocation of development resources and career opportunities for high potential employees. Our approach helped the business achieve their talent management goals, creating long-term benefits for their employees and the organization.
Let's explore how our solutions align with your business needs.
Our team is committed to making things better, faster, easier, and more impactful for your business, so you can achieve success with confidence.