How Flex Used AI To Supercharge Its Skills-based Hiring Strategy

Flex is a global leader in manufacturing with more than 140,000 employees. They help brands across a diverse set of industries design and build products that improve the world. Accordingly, many of Flex’s roles are highly technical and require specialized, hard-to-find skills.

Challenge

Flex needed a more sophisticated way to locate and engage specialized talent to fill its niche engineering roles. Existing role definitions were often too generic, lacked necessary skill requirements, and did not properly distinguish between the types of engineer Flex needed to hire, from metrology to quality and systems engineers. Aligning candidates to roles with nuanced skillsets was challenging, often leading to mismatches and inefficiencies.

Faced with the need for skilled specialized engineering talent in a tight labor market, Flex required a more agile, skills-based approach to strengthen their talent pipeline, and help them advise the business on key talent decisions with greater accuracy.

To do this, Flex sought a partner to:

• Unify and standardize its skills and role data in line with their Workday instance
• Create dynamic insights that are connected to critical talent workflows
• Build a strong pipeline of specialized talent, and strengthen skills-first approaches to hiring.

“Our skills-first hiring strategy required us to effectively connect the dots between various job grades and profiles. We recognized the opportunity to leverage AI technology to enhance our talent calibration process, ensuring that we attract and identify candidates whose skills align more closely with the specific requirements of the roles we are hiring for.” – Angela Athas, TA Partner: Sourcing Strategist, Flex

Flex’s strategic Talent Acquisition team was keen to embrace AI and automation as the most efficient method to gather and organize the necessary skills data from job descriptions, and build a pipeline of engineers with the niche skills required for Flex’s ongoing success.

Approach

Flex needed a partner that could turn unstructured data from a range of sources, including job descriptions, into a cohesive, customized skills framework – which could be used to match relevant candidates to open roles. They selected Beamery, a solution provider with the AI capabilities and expertise needed to give Flex more consistency, agility and confidence in their data and skills-first hiring strategy.

There were three steps to the approach:

1. Create clear, consistent definitions for specialized roles

In just a matter of days, Beamery was able to analyze data from various sources and in multiple languages, in order to:

• Transform more than 1,200 job descriptions into a consistent set of 40 roles, including necessary and desired skills, and the proficiency level required
• Infer additional requirements, including responsibilities and familiarity with specific tools
• Assess core capabilities, highlight any unique requirements for Flex, and align them to Workday’s proficiency scale.

2. Give teams autonomy to maintain their skills data

With Flex’s data structured by role, job family, seniority, proficiency, and required status, Beamery provided the team with a Job Architecture portal where users could easily maintain roles independently, reviewing and editing as necessary, in order to:

• Evolve roles to reflect changing requirements inside the business, new technological innovations, or wider industry needs
• Collaborate with the business and significantly reduce the time taken to review and approve roles
• Help recruiters to hold meaningful conversations with business partners, based on a deeper understanding of specialized skills.

3. Empower true skills-based candidate matching

With this enhanced, skills-based view of specialist roles, Flex could automatically calibrate the search parameters for mission-critical, hard-to-find roles. This gave them:

• Increased quality of matches of candidate to roles, within their talent CRM
• Fewer mismatched candidates (for example, by distinguishing the specific skills defined for a metrology engineer, Flex can easily deprioritize candidates who lacked the skills required to perform the role)
• The ability to pursue true skills-based hiring, going beyond title or pedigree, and diversifying their talent pools.

“I’ve received a lot of positive feedback across our teams that the new skills-based view of specialist roles has really helped users to calibrate the vacancy they are working on, and communicate with hiring managers around: what should we be targeting, what does good talent look like, and which candidates are those we can take action on in the Beamery platform. They love it.” – Angela Athas

Results

“We have successfully updated our skills taxonomy for certain job profiles, which has led to a more refined understanding of our talent pool. The integration of Beamery’s AI inferences has resulted in stronger calibration of our talent, enabling us to make more informed decisions and enhance our overall recruitment strategy.” – Angela Athas

In less than 4 weeks, Beamery defined skills compositions for 40 roles at Flex – a process that would have taken a team 4-6 months to complete manually. This will help Flex create a more agile recruitment process, which will dramatically reduce the time to fill critical roles.

The Talent Acquisition team can now find more relevant candidates, faster. By introducing job architecture and company-specific skills profiles for critical roles across process, industrial, manufacturing engineers and more, Flex’s recruiters have ultimately been able surface better matches for niche engineering roles, improving hiring quality.

Flex’s partnership with Beamery facilitated a technology-enabled approach to skills-based hiring, helping them consolidate data into dynamic, centralized insights that can be used across other HR processes. This has sparked plans to roll out their Job Architecture to other job families and further evolve their skills-first talent strategy.

Impact

• 97% reduction in job description complexity from 1,200 job descriptions into 40 consistent, standardized skills-based compositions
• 17 days from data capture to delivery for critical job profiles inside the organization
• 89% reduction in time spent on consolidating job descriptions, cutting down an estimated 4-6 months of manual work for the client

“This innovative work will significantly support our larger Flex organizational goals by enabling us to adopt a world-class skills-first hiring strategy that enhances our talent acquisition process. By empowering our recruiters to easily unlock and review inferred talent, we can identify solid, qualified candidates who may have otherwise been overlooked. Ultimately, this approach will create a more agile and nimble recruitment process, allowing us to find and hire talent more efficiently and level the playing field in our industry.” – Angela Athas

Read more customer case studies here.

Learn more about connected skills intelligence from Beamery.