Ashfaq Ahmed’s Post

TODAY, no one talks about this SOURCING Approach & its an age old technique, its time to revive this. If you have ever experienced the art of calling landline numbers to connect to a candidate, persuade them for a conversation & also generate references in a street smart way, then you'd know what im talking about. The art of Persuasion slowly starting fading out with the advent of tools and tech around us. We started going gaga about sourcing hacks and techniques, we sidelined this approach in totality. In the era of AI, everyone has access to data but very few have access to context. Assume you're talking to a Golang engineer who meets your persona in terms of location, CTC, won't this candidate have few more similar ones around him? Yes, he would. But, how'd you weed out the info of his/her colleagues? By asking "Can you give me ref" while hanging up the call isn't really gonna help. There needs to be a structured lead-on strategy blended with storytelling and persuasion, which helps you smartly weed out names. This approach of sourcing can help you save your cost & time of your overall sourcing and these are the KPIs which will make you a top notch recruiter in this era of AI. Don't you think, it's time we head back to our roots? We start doing Engagement the way we did before the era of tools/contact plugins? Thoughts? ----------------- P.S : This is a snippet of batch 18 on how to leverage lead on strategy in your engagement & turn that into a strong sourcing engine for you. Join batch 21 of Mini Dip for TA kick starting in Aug, for details check : https://bit.ly/minidip #recruitingmonk #Post899

How to perform "Data Classifications" while sourcing on LinkedIn? As part of batch 18 of Mini Diploma for TA, we were discussing the importance of not just knowing the role you're sourcing for but also understanding the data sets (other roles) surrounding it. While Sourcing for a role like NodeJS, there are possibilities of bouncing on Java devs, C#, UI devs, Fullstack etc.. Jot down all possible overlapping roles based on the data density & classify each one as either Obvious bad data or Grey data. Such classifications makes your job lot more easier and gives you enough context on what data set you're addressing. This requires in-depth persona understanding & data analysis capabilities. ------------- P.S : Join batch 21 of Mini diploma for TA, kick starting in Aug 1st week. For details check : https://bit.ly/minidip #recruitingmonk #Post898

With the launch of tiktok like short videos on LinkedIn, the video content is getting a crazy 4-5X reach. I've been posting short educational videos for Recruiters frequently from last 10-12 months. Earlier, videos used to get a reach of 8-10K & now it's a whopping 40K+. But the question remains, will we scroll videos on LinkedIn like how we do on Insta/YouTube? 🤔 What's your take? #recruitingmonk #Post896

Here's a curated list of Top Posts for TA folks from Q1 - 2024 (Jan - Feb - March) 1. Prompt to plan talent pipeline : https://lnkd.in/gEXD_qda? 2. How to pitch to a candidate? https://lnkd.in/gTvYUuu7? 3. Fasle Economy : A metric which every TA Leader should focus on https://lnkd.in/gVjVjqnE? 4. Frontend Developer Persona : https://lnkd.in/gasRQkn3? 5. Internet sourcing is cost effective. Yay or Nay? https://lnkd.in/gBKsnXeQ? 6. A short snippet on how to plan your hiring by Savita Hortikar : https://lnkd.in/g8kUUyMC? 7. Interaction with Irina Shamaeva on different scraping methods & bigdata concepts of Sourcing : https://lnkd.in/gZ9vgEgN? 8. What makes Recruiters great? Sourcing? Engagement? Expectation Management with HMs? Nay, none of them, read below https://lnkd.in/gEZqW3mu? 9. Should I click "Similar Profiles" while sourcing on different platforms? https://lnkd.in/gBuaz3f5? 10. Does naukri provide quality resumes only in the first 3-4 pages? Can there be quality profiles even upto 20 pages? Check this out https://lnkd.in/gEc4re49? Above posts had a collective reach of 110,000 impressions. Hope you found the content valuable & were able to derive some insights. :) Do share/nudge in your TA network. --------------- P.S : Batch 20 (July batch) of mini diploma for TA is full. We're onboarding folks for batch 21 kick starting in Aug. You can grab early bird offer, to book a slot ping Yaswanth Lohar Veeravalli #recruitingmonk #Post895

TA folks complaint, Hiring Managers have unnecessarily long interview processes, they ask irrelevant Qs to candidates. But, how about TA Teams when they are hiring Recruiters/Sourcers? Do we ask, most relevant Qs in ref to our hiring? Or, we ask Qs which aren't relevant to our day-day work just to sound sassy and cool? Before blaming HMs, can we start looking within & tweak our interview processes inline to our exact business needs? Thoughts? ---------------------- P.S : This was an answer to Aishwarya srivastava's Question on interviewing & recruiter hiring as part of Mini Diploma batch 17. Join the next batch of Mini Diploma, for details check : https://bit.ly/minidip #recruitingmonk #Post894

Recruiting leaders have you ever thought, are you buying Recruitment Solutions that solve real problems or buying FOMO? Unfortunately, we've been buying FOMO all these years & in the era of AI we continue to buy FOMO. If I've to talk in ref to sourcing, there is one fundamental mindset problem we've coz of which we buy FOMO. Yes, we've a mindset problem. We started our sourcing from job boards & 90% Recruiters love keywords coz of one fundamental reason "MORE DATA". Now this is the mindset we've been carrying from the era of job boards & the Recruiters back then are TA leaders now in the era of AI. You buy, whenever someone comes & tells you : 1. Tools : We've millions of data across the web : FOMO on MORE DATA 2. Trainer : We teach you to source on the internet & help you ditch job boards : FOMO on MORE DATA & less cost. In the era of AI, if you are still falling to the gimmick of MORE DATA, you got to re-look at your strategies. It's not about DATA anymore, it's about context or signals. - Where do I have the most contextual data which can be indexed with ease? - Where do I have the right signals of candidates looking out & candidates of my PERSONA? It's not about DATA any more, its about context, its about signals. We need a mindset change, MORE DATA isn't the solution. "DATA is just a mine, CONTEXT is gold." ------------------------- P.S : Join batch 20 of mini diploma for TA & learn how to contextualise your data and make right decisions in your sourcing, without much tools & gimmicky sourcing hacks. Check out : https://bit.ly/minidip #recruitingmonk #Post893

Do Recruitment agencies offer 3X salary of your exp range? Most of you'd say, hmm no. What if I tell you, there are firms which do? But here is the catch, they don't want just another recruiter. I'm helping one such top notch agency hire a rare Manager or Business Head for them, below is the pre-requisite 1. Have you improved operational efficacy at your work to improve deliverables? 2. Plugged in tech solutions to fasten any of the hiring aspects? (Or maybe you didn't implement, but you've got a list of HRTeck stacks for automating areas of hiring with strong reasoning) 3. You're a data nerd 4. You know how to manage a team of 6-12 Exp range : 6 - 8 years from agency background, Bangalore/Indore location, hybrid. Do you fit into the above pointers? If yes, send me a mail ashfaq@recruitingmonk.com & ensure, you talk about each of the above pointers in detail and add your LinkedIn URL. I don't even need your resume. Grab the eye balls with your storytelling skills on the mail. (Don't use GPT to craft a mail) If you don't fit in above criteria, i'm sorry I don't have any other openings in hand right now. Folks, do you know anyone in your network whom you think would fit the above persona? Help me spot that Recruiting nerd, have got couple of positions. #recruitingmonk

How do you probe your candidates? By asking them, rate of 10 or how many years of exp in a skill? A good majority of Recruiters start their probing by asking direct questions to a candidate from the laundry list of mandatory skills which they have from the JD or HM. Imagine a scenario, you get a call for a Senior Recruiter at a good product company and the person who calls you, asks a laundry list of questions. And one of them being, do you know Xray sourcing? Even if you've not done much of xray, you'd tend to say yes. You feel, before the interview I will brush it up or ask someone who is good at xray and take up the interview. Trust me, same goes with your candidates if you ask them direct & obvious questions. Ditch such vague probing approaches and adopt KRA/KPI driven probing techniques. Thoughts? Don't you think our Probing techniques is vague & doesn't provide any context of the candidate? ----------------- P.S : This snippet is from batch 17 of mini diploma for TA. You can join batch 20 kick starting by July 1st week, for details check : https://bit.ly/minidip #recruitingmonk #Post891

There's one side of D&I sourcing no one talks about. Yes, literally no one talks about. Diversity & Inclusion isn't just about hiring LGBTQ/Female candidates. There are other areas like, skill diversity, education diversity etc .. But, there's one more crucial aspect of D&I in sourcing & that is skill matrix Java + Spring + AWS + Kubernetes Java + Spring + Kubernetes Technically speaking, candidates who work on Kubernetes (any Microservice environment), the chances of them working in a cloud environment is very high In ref to cloud, AWS is a market leader. Guess what, there are approx 40,000+ such candidates in a city like Bangalore, who have not written AWS on their profile but talk about rest of the 3 skills. Skill matrix is about having a deep Persona understanding & reasoning out, what combination of candidates could be suitable, even though they'd not have written some mandatory skills on their profiles. This aspect of diversity is least spoken in the industry. Leverage bigdata concepts to create unique data slices of such diverse talent pool & chalk out different reach out & probing strategies Lets stop assuming, candidates write all the skills on their profile. On a platform like Linkedin, 60%+ data is a dark matter (candidates writing least info). Is your sourcing diverse enough to weed out candidates hidden in the dark matter? Also, can you contextualise each diverse pool separately & weed them out as a unique data slice? Thoughts? ---------------------------- P.S : Join the batch 20 of Mini Diploma for TA, a 12 weeks mentoring program for experienced TA folks. For details check https://bit.ly/minidip #recruitingmonk