Is there anyone on the employment spectrum who isn\u2019t<\/em> affected by recruiting challenges? Not according to the numbers<\/strong>. While solving talent challenges for its clients and enabling exceptional resources to contribute to the commercial ecosystem at large, the talent advocacy team at Arthur Lawrence repeatedly observes some common patterns that make talent management frustrating: The perception\/reality gap, facts and commitments that don\u2019t fall through, and most of all\u2014the time and effort wasted in finding the right match. The worst part? These issues are chronic rather than episodic.<\/p> What Are Recruiting Analytics?<\/strong><\/p>\n\n\n\n Recruiting Analytics\u2014putting it\ncolloquially\u2014is putting recruitment related data to business use. Although\nyou\u2019ll discover all kinds of software that builds on recruiting analytics, they\nall share a common purpose: To identify ways of bridging the talent\/opportunity\ngap in the most efficient way, for all stakeholders involved.<\/p> Recruiting analytics are formed\nby aggregating datasets from recruitment experiences. So if you\u2019ve just worked\non one kind of recruitment and are looking to expand using your existing\ndatabase, we wouldn\u2019t recommend it. It will be skewed, and your results while\npresenting an accurate picture of past recruitment practices, won\u2019t be\nhelpful in assisting you with future recruitment decisions. Recruiting\nanalytics are most effective when there\u2019s a repository of rich, diverse and validated\ndatasets on which to build those analytics. \n(In another post, we talk about the importance of data wrangling, and\nhow not enough businesses do it). Another\nbenefit of recruiting analytics built this way is that they\u2019ll be highly\nintuitive. You won\u2019t have to plow much to find the answer you\u2019re looking for.<\/p> How Can They Help?<\/strong><\/p>\n\n\n\n Recruiting analytics have an\noriginal solution to many of the hiring problems mentioned above. Because they\nare often architected over historical datasets, with many repetitive patterns\nemerging in the recruitment cycle, one of their most helpful outcomes are predictive\nanalytics. Predictive analytics assist with much more than workforce\nplanning and forecast. They flag questionable behavior in any stakeholder\nbefore it becomes problematic. So\nwhether it\u2019s candidate ghosting, or a client who habitually rejects final\ninterviewees with no reason, these analytics hold a torch to behavior users are\nbest warned about beforehand.<\/em> Such analytics can educate decisions about\ntalent sourcing by going beyond a first-level analysis: what is the time range\nin which a TA (Talent Advocate) can expect to place a specific profile? What\nlong does it take to fill niche consulting roles? We encounter recruiters who\nbelieve \u201cPlacement is 90% luck.\u201d With a recruiting analytics platform at work\nwith you, that simply isn\u2019t true. Even accounting for externalities, recruiting\nanalytics can give you an accurate measure of the time a position will take to\nclose. The lesson here: Invest resources accordingly. <\/p> More than time, it\u2019s the cost\nassociated with placement that\u2019s another source of concern. Recruiting\nanalytics are particularly helpful here, given that they can present drill-up analysis\nby:<\/p> – Cost Vs Time Ratio<\/p> – Benchmark<\/p> – Similar roles in the industry and\/or other industries<\/p> – Average user expenditure to fill the same role<\/p> – ROI per role<\/p><\/blockquote>\n\n\n\n If you\u2019re looking to fill\nshort-term project-based roles, this analysis is invaluable. If such data is made public, jobseekers\nbenefit by directing their own efforts better too. Why waste time on a specific\nposition, when better returns are offered for the same position elsewhere? Likewise,\nif analytics suggest a considerable degree of \u2018ghosting\u2019 for a said position,\npotential jobseekers seriously seeking the job should present themselves accordingly:\nemphasizing commitment and their willingness to start immediately.<\/p> All Stakeholders Benefit<\/strong><\/p>\n\n\n\n Transparency in the hiring\ndecision requires you to make difficult, but quantifiably sound decisions. For\ninstance, the belief that millennials are chronic job hoppers may apply to many\nindustries. But what about the specific position and location you\u2019re hiring\nfor? What does the data say there? Err on the side of reason and caution when\nthe numbers are on your side.<\/p> With the growing influence of the\ngig economy on traditional hiring practices, this is a very important benefit.\nIt assists with fairer negotiations for both parties; transparency and flexible\narrangements that result in win-win scenarios for all stakeholders. The figures\nfrom the analytics dashboard provide the groundwork needed to prepare such\ncontracts.<\/p> Recruiting analytics help clients\ntoo. They attest to the credibility and soundness of the talent management\nsystem. The ratio of placements versus applicants isn\u2019t always bad news, for\ninstance. Often, it\u2019s a reflection of the very thorough testing and validating\nmethodology the talent management team has in its place. <\/p> Dashboards are a good starting\nplace for managers to ask the right questions and uncover the real issues at\nhand. The benefit of an analytics solution is that the dashboards represent\nreal-time data and are almost always easily exportable. (i.e. better than a\nslide deck if you\u2019re hoping to make a collective decision).<\/p> For high-demand roles, there is\nadded emphasis on employer branding. Even if it is a high-growth position,\nemployer branding is key. If your organization has a positive history,\nanalytics can become a powerful \u2018brag point\u2019 for your organization. They\nprovide evidence of:<\/p> Career growth rate <\/p> Salary growth<\/p> Other success stories within that role<\/p><\/blockquote>\n\n\n\n The best part\nis: Since analytics use aggregated data, with filters to anonymize records,\nthis form of advertising is perfectly honest, and completely legal. You achieve\ntransparency without compromising privacy.<\/p> Organizations\nsometimes prefer adding to the capabilities of recruitment analytics by adding\nperformance-based elements to the mix. Drilldown analyses per employee or\nunique hiring scenario can prove to be helpful in complex or hostile conditions.\nIn case there is legal recourse or union activity on the decision to discipline\nan employee, recruiting analytics provide a robust record of employee offences\nleading to that decision. Each incident has a time stamp and visual evidence. As\nwe earlier mentioned, the richer the datasets backing the analytics, the more\naccurate the visual output will be. <\/p>
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