How to harness the power of personalization

Cristina Goldt, vice president of HCM products at Workday, is one of the presenters who will speak during the opening keynote, In Data We Trust, at the upcoming HR Technology Conference & Expo, Oct. 1-4 in Las Vegas. HRE caught up with Goldt to discuss the power of personalization, and how new HR-tech solutions are harnessing that potential.

Why is creating workplace personalized experiences important? And how does it enable better employee learning and development?

Employers understand they need to create personalized experiences to meet the needs of the changing workforce, to not only engage employees but to keep them at the company. The No. 1 reason people quit their jobs is the “inability to learn and grow,” according to research from Deloitte. No company can afford that in today’s tight labor market.

Today, through data and technology, we know so much about our people that we can provide recommendations that will improve workers’ lives and enable career growth. Having the data context of an employee’s career goals, skills and interests enables a much richer experience. For example, knowing that someone has an interest in UX [user experience] or has been a people leader before might lead you to put them on a project or team where those capabilities are important, and they can continue to master them.

When people are enabled to do their best work and discover new opportunities, it positively affects overall performance and delivers the best results for their colleagues, customers and company.

What are some AI, machine learning and analytics tools that can help create personalized experiences?

With data, you get a better lens into what drives your people. When you know what people are interested in, you can understand what content will resonate with certain groups. For instance, tools such as Workday Learning provide ML-driven recommendations that make workplace learning more tailored to the individual.

Insights derived from data can also lead to recommendations that assist employees on their career journeys. In employers large and small, aspiring workers may not know the best way to move from one level of work to another, or what skills are needed to make such moves. Data is key.

Also, a tool like Workday’s Opportunity Graph lets employees get a view of the moves that other people in their role have made so they can better chart a course for their own career path. Opportunity Graph is really a fancy name for “What’s my next career move?”

Another tool that can help create personalized experiences is Workday People Analytics, which will give executives, organization leaders and HR business partners a view into the most critical trends in their workforce, and an understanding of the most likely drivers of those trends. Understanding stories such as attrition in a particular region, for instance, can help organizations be more targeted in addressing those specific areas.

What is a talent marketplace? And with more data on skills and people sentiment, how will internal (and external) talent marketplaces enable skill- and job-matching in a more friction-free way?

To help global organizations become enterprises of the future, AI and advanced analytics can re-imagine how they source, train, utilize, develop, reskill, nurture and retain talent to meet evolving business. In order to match people and work, skills need to be the driving factor. An ML-driven, common language of skills is the critical foundation, such as through Workday’s skills cloud, which makes the process of updating employee skill profiles much easier and more automated.

With an accurate view of the skills available in an organization, HR leaders can more easily determine what skills are needed to complete the work that is imperative for the business. The talent marketplace that Workday aspires to create will connect the right people with the right opportunities based on skill set. This will provide a mobility platform that will make it easier to find talent that matches the skills the organization is looking for, as well as provide opportunities to people looking for new experiences and gigs.

Through ML, we can better match people to opportunities. If there isn’t an initial match, we can provide them with recommendations to meet the requirements of a new role—that is the key to upskilling and reskilling.

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