Algorithms Aren’t Just for Netflix and Instagram

Beyond Instagram and Netflix
With the explosive growth of social networking sites in the past decade, algorithms have become an integral part of our very existence. Data-driven analytics are ingrained in nearly everything we do—and we’re only beginning to see the broader implications. From platforms like Instagram and Facebook to Netflix and Youtube, a person’s data inputs—such as their likes, saves, comments, history of interactions with similar accounts, and the duration spent interacting with the content—help these social media giants sharpen the accuracy of their predictive analytics. These algorithms are then able to generate personalized recommendations to users based on the content they interact with, in turn providing users with the best experience possible. 

But what if businesses could leverage this level of data and turn it into actionable insights? Algorithms are what generate value for every business—today, they're changing the face of HR management. 

Whether it's to strengthen your core business strategy or improve your hiring process, creating an innovative company requires an innovative workforce—and data analytics can help executives discover candidates and match them to the right roles. CEOs have been trying to gain real-time data with actionable reporting statistics about their people for years, yet most legacy HR systems are centered on experience and keywords, missing important details needed to optimally match people to roles and determine advancement gaps. With an accelerated transition to a digital landscape, leaders are now witnessing a growing workforce optimization trend towards building agile, cross-functional teams; by using machine learning (ML) algorithms, they can plan for impending workforce problems and fill in the missing gaps from within. 

HR Management: Rewritten for the Digital Age
In order for companies to stop reacting to workforce problems after they happen, they need to be capable of accurately predicting future trends. An organization’s people-analytics algorithm is the most valuable asset it can possess—and with a strong one, recruiters can identify the key factors that make for successful employees and influence retention rates. According to Deloitte, only 14% of executives agree that their organization is using their workforce’s skills and potential to their fullest capabilities.  

Using ML algorithms for HR management, such as Claira’s unique ML algorithm, businesses are much more likely to place talent effectively, anticipate change and respond efficiently, and retain high performers. 

But how exactly does this algorithm work? At Claira, delivering continuous value to our customers is of utmost importance, which is why we’ve developed a competency engine that is capable of providing leaders with a new, unbiased dataset that improves over time. 

Like many social media platforms, our algorithm first collects the accumulated unstructured information, specifically inputs coming from employee and company data. Using Claira’s competency statement library, users can then select the statements that most accurately depict their capabilities—and 81% of the time, employees self-report accurate, honest information about their competencies. 

Claira’s algorithm then predicts the potential capabilities of the individual through a combination of these statements and market data. Finally, the algorithm populates the insights dashboard with a dynamic competency map, providing leaders with actionable insights about their people, organization, and recommending business strategies. 

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The Future Demands Agility and Precision
Leveraging algorithms to process these enormous amounts of data can not only boost profitability and increase efficiency of a company, but more importantly creates dynamic value outputs for an organization. While Claira’s algorithm may not be working to maximize user engagement in the same manner as Netflix and Instagram, our platform seeks to improve employee engagement and thus reduce potential workforce problems. 

Leaders who want to get ahead of the innovation curve need to be agile and precise in their strategic decision-making. The future of work demands that workforces become cross-functional and flexible: understanding people’s strengths and growth trajectories can enable leaders to optimize staffing and exceed goals. Planning for the long term using data-driven decisions can also lead to a better recruitment and onboarding process. With a wider array of resources available to the algorithm, leaders can improve the overall quality of their hires while also removing human subjectivity and biases from the hiring process. An ML-based HR system can help businesses realize up to a 98% increase in retention and employee satisfaction, reducing staff turnovers and creating a more positive work environment. 

The opportunity to automate and rapidly expand your organization in terms of speed and scale has become feasible due to the rapid growth of ML algorithms. Data-driven decisions will drive workforce planning in the coming years—and leaders who are early adopters of competency-driven frameworks will see the most significant improvements in talent acquisition, retention, and business performance.