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Blog Post: Next time you hire a CEO, hire a Recruiting Leader: Next time you hire a CEO. …; Added by Michael Wright at 6:40pm on February 27, 2013

Blog Post: How to Adapt to IT Recruiting Trends in 2016: Added by Hagi Trinh at 4:36am on March 30, 2016

Blog Post: A Founder’s Story: First Hiring Pains and Designing a Culture Around Baseball

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Blog Post: Racism in Recruitment: Review Your Current Recruiting Process and 6 Steps to Remove Unconscious Bias: The recent killing of George…; Added by Ngan Pham at 5:32am on July 23, 2021

Comment on: Topic 'Shally Steckerl - Discusses Tools, Social Media and more': oponent of pushing for more of a decision science within the Talent Acquisition function since first entering the field – even in my early days of recruiting inexperience, I knew that we were not leveraging any of the similar decision sciences I had seen or used among my previous marketing, sales, and/or operations background. Due to the potential complexity of your question, it’s important that we set a few guidelines up front. From a scientific standpoint, it’s important we state our assumptions before attempting to build a model. Let’s quickly do that: 1. First, your question involves web tools that enable ‘identifying and recruiting passive candidates’. Since your question revolves around the ‘passive’ candidate, we can eliminate any job boards and explicit advertising from our answer. In addition, we can also eliminate any non full-time direct-hire employees (as most are aware that short-term contractors usually fall into the ‘active-candidate’ category). 2. Secondly, your question involves the notion of ‘Return on Time Invested’ (ROTI). The notion of ‘Return’ originally derives from the Accounting and Finance function, and is stated quantitatively. As such, there must be a numerator and denominator, and depending on the circumstances, the quotient/product can be stated in one of the following manners: a. Ratio (i.e. x:x, 5:1, 7.3:1) b. Percentage (i.e. 200%, 0.98%) c. Index Score (this will take into account certain independent variables and sometimes allows for a better side-by-side comparison of values.) 3. Thirdly, it is important that we define ‘Effectiveness’ to properly answer this question. The best definition I was able to find is, “The extent to which actual outcomes are achieved, against the outcomes planned, via relevant outputs or administered expenses.” The reason I believe this to be the superior definition is because there is attention given to ‘impact’ as well (this is where well-intentioned HR and TA programs fail as the programs may be effective, however lack true impact on organizational performance). 4. Third-Party Recruitment is concerned with several metrics, however there are 3 true mother metrics that drive all others: a. Number of Placements b. Avg Placement Fee c. Annual Billings [See note below.] 5. Corporate Recruitment is concerned with several metrics, however there are 3 true mother metrics that drive all others: a. Cost-of-Hire b. Time-To-Fill c. Quality-Of-Hire [See note below.] [Note: Some may argue that there are several other important metrics to follow on the TPR side (such as Sendouts:Offer, Sendouts:Month, etc.), however the true mother metrics are listed above. Likewise, some may argue that there are several other important metrics to follow on the Corp Recruitment side as well (such as Interviews:Offer, Recruiter Efficiency, etc.), however the true mother metrics are listed above. The analogy is that we can follow numerous financial indicators for a firm and each metric offers independent value (such as ROE, ROA, Asset Turnover, etc.) . . . however the true mother metrics are Earnings-Per-Share (EPS), Market Capitalization, P/E Ratio, and Stock-Price. This is where the tricky part begins – time allocation in terms of identifying ROTI. For example, we may spend a total of 8 hours ‘sourcing’ for a given role, however only 1 of those hours may have been spent on the actual source/channel upon which we’ve identified the passive candidate. What compounds this is exactly what Shally mentions – the current notion of an ‘integrated’ desk which involves several applications and browser windows open. As such, we may quickly source 10 channels in an hour period, upon which we enter a ‘deeper dive’ depending on our initial results. I only mention this because it’s easy to see just how complex the answer to your question can become. The only ‘real way’ to note true ROTI would be to keep clicking a timer as you move from source to source and from channel to channel. Also, we must ask ourselves whether we are going to allocate the entire amount of time spent on the search itself into our ROTI number. Doing so will truly allow us to answer the question of how much our time was worth (for example, if we spend 40 total hours on a $40k fee, then we can identify that our time was worth $1k per hour on this individual search). However, although this will allow us to identify specifically how valuable our time was, there is no correlation back to the source itself. When I say that, I mean that we’re dealing with human beings and some take more emotional attention, persuasion, and closing than others. Another factor that may serve to greatly complicate our attempts to quantify source value is how many degrees away our placed candidate is from the original source that led us in the candidate’s direction. For example, let’s say we find an initial candidate on LinkedIn, who then refers us to the candidate we actually place. Would that mean LI was not of value to us? Obviously, the original source was of great value, but it’s not so easy to identify this if we’re looking at things with black-and-white ratios. In going through this process, I’ve given the concept of ‘waste’ considerable thought (in the Six Sigma and LEAN sense). I say that because some may say that although we spent 40 hours within a given search, 20 were spent on sources that did not yield a placement or hire. But were those hours technically waste? Not really, as sourcing is an overall process. An analogy would be an engineer that spends 40 hours trying to correct a problem, but spends the final 1 hour reconnecting a wire that was disconnected. Would this mean his prior 39 hours were waste? No, not at all. His previous 39 hours may have led him to the root cause of the problem. Based upon all these things, this is my recommendation: a. Group sources into categories. For example, LinkedIn may be in its own category due to its power as a source. Facebook, Twitter, and MySpace may also be in their own categories. Blog Searching may fall into a distinct category, as may several Boolean search strings using Google and MS Live. This would all be dependent on the individual organization and the differing external talent pools, etc. b. Block out your ‘Sourcing Time’ into 15-minute blocks. By doing so, you will allow yourself to remain committed to a given ‘Source Category’ without overdoing it. c. Source individual projects at a time. When I say this, I mean to focus on a given requisition or job family, etc. This is imperative for tracking purposes later. [Note: I would recommend against grouping too many sources into the same category as this will reduce the power of this technique. If you know certain sources are effective given your personal needs, ensure the source is in its own category for tracking purposes.] By engaging in categorizing out your different channels and sources, blocking out your time spent within each source/channel, and by sourcing individual projects or job families at a time, you’ll be able to track the entire time spent sourcing for a search. Upon doing so, this is how your tracking matrix may look per project or job family: a. Source A (LinkedIn) = 6 hours b. Source B (MySpace/Facebook) = 8 hours c. Source C (Blog Searching) = 2 hours d. Source D (Twittering) = 1 hour e. Source E (Boolean Search ‘xyz’) = 4 hours f. Source F (Direct Sourcing) = 16 hours At the end of a month, quarter, or year, you can return to review your sources and total time spent within them . . . in addition to the mother metrics given your role (TPR or Corp Recruitment). At this point, we can then overlay this time information onto our aforementioned mother metrics. Examples would include the following: Third-Party Recruitment (LinkedIn Annual Review) a. Time Spent Within Source = 240 hours b. # of Source Placements = 12 c. Source Avg Placement Fee = $25,000 d. ROTI = 240 hours / 12 placements = 20:1 (i.e. we make a placement for every 20 hours spent within this source). Third-Party Recruitment (Direct Sourcing) a. Time Spent Within Source = 800 hours b. # of Source Placements = 24 c. Source Avg Placement Fee = $28,500 d. ROTI = 800 hours / 12 placements = 66.7:1 (i.e. we make a placement for every 66.7 hours spent within this source). Third-Party Recruitment (OVERALL Source Review - Annual) a. Source A (LinkedIn) = 20:1 b. Source B (MySpace/Facebook) = 120:1 c. Source F (Direct Sourcing) = 66.7:1 [Note: Obviously, the lower the ratio, the more effective the source.] Corporate Recruitment (Facebook Annual Review) a. Time Spent Within Source = 110 hours b. # of Source Hires = 6 c. Source Cost-of-Hire = $5,500 d. Time-to-Fill = 45 days d. Quality-of-Hire = 3.5/5 Stars e. ROTI = 110 hours / 6 hires = 15.7:1 (i.e. we make a hire for every 15.7 hours spent within this source). Corporate Recruitment (Boolean Search ‘xyz’ Annual Review) a. Time Spent Within Source = 150 hours b. # of Source Hires = 15 c. Source Cost-of-Hire = $4,000 d. Time-to-Fill = 27 days e. Quality-of-Hire = 4.1/5 Stars f. ROTI = 150 hours / 15 hires = 10:1 (i.e. we make a hire for every 10 hours spent within this source). Corporate Recruitment (OVERALL Source Review - Annual) a. Source B (Facebook) = 15.7:1 b. Source E (Boolean Search ‘xyz’) = 10:1 c. Source F (Direct Sourcing) = 200:1 [Note: Obviously, the lower the ratio, the more effective the source.] To conclude, Bill, I would suggest that we look at our Source data in such a way as to accumulate knowledge for targeted use on future searches/requisitions. In this manner, we will be better able to increase performance by using forward-looking projections to formulate leading indicators (an example would be TPRs’ or Corp Recruitment using the knowledge that Pivotal Talent Pool ‘X’ is populated primarily with candidates from Source ‘A’). Our industry is in perfect position for a more intelligent decision framework to be architected and implemented, much as is being done by John Boudreau (Research Director of the Center for Organizational Effectiveness at USC Marshall School of Business) has done with the new notion of "Talentship". I would hope that some of the above answer adds to the growing field of opinions and research in our sector and I look forward to your thoughts and feedback.…; Added by Joshua Letourneau to BillVick.com at 9:15pm on April 25, 2008

Blog Post: How we increased traction by 10X - The story of Simplicity & Scalability

As we embarked upon 2018, we would like to take a moment to reflect on our journey in 2017.

In the beginning of 2017, we essentially aimed at making our 'Technical…

Added by Bangabdi Roy Chowdhury at 1:23am on February 1, 2018

Blog Post: Meet Rayanne Trumbo - RBC's Groove Is In Her Heart: Rayanne ThorneTrumbo, Recruiter

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Blog Post: The Missing Piece to ATS Prescreening Questions: It’s no surprise that the number of resumes stockpiling for HR and hiring managers has increased in the past year. Thus, it’s important now more than ever to have an applicant tracking system (ATS)…; Added by Jake Stupak at 2:46pm on September 11, 2009

Blog Post: Exit Interview: Why Top Talent is “REALLY” Leaving Your Company: We network with top talent on a daily basis, so we always come across top producers that are willing to throw in the…; Added by Bridget Baggett, MBA, MHA at 1:24pm on April 11, 2013

Blog Post: 2014: Tougher than Ever to be a Recruiter