Effective talent sourcing, like any strategic initiative, thrives on measurement. Metrics provide the operational discipline, activity effectiveness assessment, and business outcome validation necessary to optimize your talent acquisition strategy and drive organizational success.
As talent acquisition leaders, the metrics you choose to track (or not) speak volumes. They reveal your understanding of your business impact and set expectations for how sourcing contributes to the bottom line. If the metrics you capture are too limited, you risk not accurately portraying the full role and impact of your talent sourcing. Incomplete metrics signal a talent acquisition function with limited business growth and transformation impact.
We recommend developing a sourcing metrics road map to set clear expectations and showcase your strategic value. This road map outlines what you plan to measure, effectively foreshadowing your contributions and demonstrating the critical role talent acquisition plays in driving business success.
Building a Talent Sourcing Metrics Road Map
Talent sourcing and even recruitment, for that matter, have long suffered from having measures – such as open rates or hiring manager satisfaction – that have no credible connection to an organization’s financial performance. Therefore, their accountability as a business contributor, especially in the context of immediate impact, is often considered weak, undermining their perceived value.
When developing a road map, it’s helpful first to identify what information is the most valuable. The objective is to ensure a comprehensive understanding of the business impact. Key considerations include:
Assessing whether the metrics influence the income statement (e.g., successful placements) or the balance sheet (e.g., the value of talent pipeline as an asset)
Distinguishing between historical metrics (e.g., last quarter’s hires) and forward-looking metrics (e.g., projected candidate lifetime value)
Identifying if the metrics are single-period (e.g., a specific recruitment campaign) or multi-period (e.g., a new talent sourcing platform that will pay off over multiple time horizons)
You should then arrange your potential metrics tailored to your business context. While the optimal sequence may differ across organizations, below is an example of a road map you can use.
A road map to calculate the ROI of talent sourcing
Begin by tracking metrics that evaluate the performance of your candidate pipeline, such as email, phone, and social media outreach. Assess the actual outcomes in comparison to expectations—did candidates respond? Did they share their resumes? Did they interview? Overall, how effective were your talent sourcing efforts? What was the Return on Investment (ROI)? While these metrics are crucial, executives outside of talent acquisition often respond with measured enthusiasm, as they expect sourcing efforts to yield positive results – as well as they should.
So, to get a more accurate view of how sourcing metrics relate to business performance, your pipeline metrics must be supplemented by other metrics with broader enterprise relevance. Metrics such as candidate satisfaction and the talent brand will emerge as critical levers for business growth. These are where talent acquisition leaders will be concentrating their efforts, according to the latest data released by LinkedIn.
Despite a slowdown in hiring over the past year, the competition for talent remains intense. While recruiting budgets are anticipated to remain stagnant or decrease, 60% of talent acquisition professionals foresee substantial growth in investments in the talent brand.
The current talent landscape places a premium on building a strong talent brand. Brands drive growth, engage stakeholders (candidates, employees, investors, and partners), and are key financial assets for the organization. Channels like social media offer a cost-effective avenue for brand-building, and advancements in analytics enable precise targeting, enhancing the effectiveness of talent branding efforts. You should measure the value of your talent brand as long-term assets for the organization – whether it’s the employer value proposition (EVP) or more tactical metrics such as talent pool growth and candidates per hire.
Moving to the capabilities stage, evaluate the value talent sourcing creates by introducing new processes, tools, data, or talent to enhance performance. These metrics will vary between organizations but may include:
Improving the quality of candidate/market knowledge.
Reducing candidate acquisition costs (e.g., by enhancing sourcing capabilities).
Improving candidate profitability and employee lifetime value (ELTV) through better engagement and retention capabilities.
Today, talent sourcing extends its value beyond its immediate function, and the enterprise stage is where you gauge its comprehensive impact. For instance, HR leverages the talent brand in employee engagement and recruiting. Talent acquisition teams leverage employee and market insights to inform choices about the talent pools to target and craft unique value propositions, while talent development professionals leverage personalized learning and engagement strategies to retain and grow employee value.
In its full scope, talent sourcing impacts other areas of HR and the organization, like growth rates, valuation multiples, and, consequently, enterprise value. As sourcing becomes more integrated with other functions, articulating this value becomes increasingly crucial.
To comprehensively convey the impact of talent sourcing, you need to include all efforts and contributions: the efficiency and effectiveness of the candidate pipeline, the pivotal role of successful placements in driving organizational revenue, the intrinsic value of the talent brand, and the far-reaching impact of sourcing on other HR functions.
Implementing a sourcing metrics road map is instrumental in mitigating the risk of relegating your function solely to a support role. It not only sheds light on the activities related to brand, capability-building, and the facilitation of other functions’ work across the organization but also opens the C-suite’s eyes to the broader strategic contributions of talent sourcing.
Even if the full realization of the road map is a distant goal, articulating these metrics serves as a beacon, revealing talent sourcing’s model for delivering desirable business outcomes. This approach ensures that sourcing is recognized not just for its tactical applications but as a strategic driver of organizational success.
Identifying the Metrics That Matter
Three fundamental principles guide the selection of the right metrics for measuring talent sourcing success, applicable across industries, organizational sizes, and maturity levels:
Clarity and Consistency: Metrics should be easy to understand and use. The variables being measured should make sense to those collecting the data and to those using the data for decision-making. Complicated or convoluted metrics may not be as useful, and inconsistencies in measurement across different departments can lead to erratic behavior.
Ease of Replication: Metrics should be easily replicable to enable regular tracking of comparable information from one period to the next. For example, tracking candidate response rates or conversion rates every month provides consistent insights. This becomes challenging in organizations with multiple data sources, where integrating data, such as candidate engagement metrics, across various platforms may pose difficulties.
Actionable Insights: Metrics should provide helpful, actionable information that directly impacts the talent sourcing function and the business as a whole. Simply observing a change in a metric is not enough; understanding how that change is connected to specific actions and behaviors among both sourcing teams and candidates is crucial. For example, metrics on candidate engagement in specific sourcing channels can be instrumental in shaping sourcing strategies and improving the overall recruitment process.
In talent sourcing, the risk of being led astray by easily trackable but less meaningful metrics is significant. Just because certain sourcing activities are trackable doesn’t necessarily make them crucial for strategic decision-making. The focus should be on metrics that align with the larger business goals, such as improving the efficiency of the candidate pipeline or enhancing the overall talent brand.
Rather than succumbing to the pressure of measuring everything all at once, talent sourcing teams should focus on the big picture. This involves aligning sourcing activities with key organizational goals, such as increasing the quality of hires or optimizing time-to-fill. By concentrating on value-based metrics and tying sourcing efforts to the organization’s defining values and purpose, talent sourcing teams can gain insights into the effectiveness of their strategies. For instance, measuring the potential long-term value of different candidate segments can aid in prioritizing efforts and resources.
While the responsibility for developing effective talent sourcing metrics lies with talent acquisition leaders, senior management is crucial in challenging metrics that lack clear relevance or are tied to the wrong questions. Instead of merely asking about performance, senior management should seek to understand the significance of each metric, what insights it provides, and what additional metrics might offer a more comprehensive understanding of talent sourcing’s impact on the organization.
Is There a Better Way to Calculate the ROI of Talent Sourcing?
Establishing a robust metrics framework in talent sourcing is vital for gauging success and optimizing outreach.. Traditional approaches, akin to marketers calculating the return on investment (ROI) by measuring post-engagement sales increases, are often too blunt for the nuanced landscape of talent sourcing. Fortunately, the current data landscape enables a deeper understanding of candidates’ interactions with you or the organization before their application or placement.
Adopting an “attribution modeling” approach is essential for talent sourcing teams. This method attributes appropriate credit to each online and offline contact in a candidate’s journey, providing insights into the touchpoints contributing to successful placements and overall talent brand impact. This modeling allows for a more sophisticated understanding of the candidate’s journey, similar to its application in marketing.
The process of developing an attribution model in talent sourcing can be broken down into four key stages:
Stage 1: Prepare Your Data
Collate data on candidate touchpoints and outcomes to lay the foundation for an attribution model.
Ensure consistency and accessibility of data across various platforms to facilitate analysis.
Apply simple attribution models, such as allocating credit to the last point of interaction or distributing equal credit across all pre-placement touchpoints.
Stage 2: Experiment
Conduct experiments to fine-tune attribution rules.
Assess the interdependence of different touchpoints to identify clusters that collectively contribute to success.
Experiment with variations in sourcing channels to understand their collective impact.
Stage 3: Apply Statistical Models
Progress to more sophisticated attribution models involving multivariate regression analysis.
Utilize statistical models to determine optimal touchpoints, their synergies, and their relative impact on successful placements.
Consider interactions beyond the immediate candidate journey, such as external experiences and interactions with other entities.
Employ advanced statistical methodologies like Panel Vector-Autoregression (Panel VAR) models to analyze the effects of advertising and interactions over time.
Combine statistical models with real-world experiments to validate and refine recommendations.
Implementing these stages gradually enables talent sourcing teams to navigate the complexity of candidate interactions effectively. It’s a journey that involves building capabilities over time, with each stage contributing to a more sophisticated understanding of the talent sourcing landscape. As in marketing, attribution modeling in talent sourcing is a powerful navigation tool, but success requires a commitment to learning and evolving capabilities over time. Remember, you must learn to walk before you run in talent acquisition.
Understanding Sources of Candidate Data to Determine Return on Time Spent Sourcing
The depth and completeness of candidate data are crucial elements often overlooked by many. Various sources, such as resumes, social network profiles, blogs, bios, and press releases, contribute to the wealth of candidate data. However, it’s essential to understand that data is the lowest level of abstraction and to transform it into valuable information, interpretation is key.
Applicant tracking systems (ATS), job boards, and resume databases represent some of the common candidate data sources, particularly resumes. Despite potential debates on their accuracy, resumes typically offer detailed professional information, including a summary of experience, objectives, work history, and address, aiding in assessing capabilities and potential commute preferences.
LinkedIn stands out among social networking platforms for its rich candidate data. While not a resume database, LinkedIn profiles often contain employment qualification-related information comparable to actual resumes. The platform’s search capabilities, coupled with deep data, make it a highly valuable information system for talent sourcing, although some profiles may lack completeness.
In contrast, Facebook and Twitter, for instance, need to be viewed with a more critical lens. Despite their popularity, they are considered shallow sources of shallow data. While useful for branding, marketing, and passive talent attraction, they often lack the depth required for active candidate sourcing. Limited professional data and non-standard terminologies pose challenges, making them less effective for sourcing and recruiting.
Non-resume internet research, using search engines like Google, Bing, and Yahoo, can produce results beyond resumes but often delves into the shallower end of candidate data. Press releases, blog posts, and comments offer less qualified information about potential candidates, making it challenging to gauge their professional experience accurately.
In evaluating sourcing effectiveness, the focus on deep and complete candidate data is crucial for a higher return on investment. Deeper sources, such as resume databases, applicant tracking systems, LinkedIn, and internet resumes, are considered responsible for the majority (80%) of successful active-search-based sourcing and recruiting results, yielding more interested and qualified candidates. In contrast, shallow sources, like Facebook, Twitter, Google+, and non-resume internet research, contribute to 20% of results, often involving more uninterested and unqualified individuals.
The critical decision lies in choosing between contacting more individuals with limited information or focusing on identifying and reaching out to more interested and qualified candidates.
As you continue to build out your talent sourcing metrics, choosing deeper candidate data sources (like ChatterWorks) will help you prioritize quality over quantity, leading to better sourcing outcomes.
Conclusion
We hope our comprehensive exploration of talent sourcing metrics helps you introduce a strategic road map for measuring true impact. By embracing attribution modeling, harnessing the power of deep candidate data, and aligning their efforts with business goals, talent sourcing teams can truly transform into architects of organizational growth. The path to ROI lies in actionable insights, value-based metrics, and a commitment to continuous learning – walk, then run, towards a future where sourcing is recognized as the strategic powerhouse it truly is.
Want to learn more about how ChatterWorks can help sourcing attribution and improve KPI tracking? Book a demo with us to see us in action!
As the right hand to many founders, Shafiur has made operations the secret weapon for many startups. He has built the operational infrastructure and held prominent leadership roles for several companies, including Airbus Aerial, Specright, Connectifier (Acquired by LinkedIn Feb' 16), and Airware. Decades of broad exposure have taught Shafiur which levers make each functional area work and how they must be coordinated for a startup to succeed.
