How to Install a Recruiting Engine That Saves Time and Money with Carina Clingman, Founder and Principal of Recruitomics Consulting

If you are hiring for your company either now or you're planning to ramp up in the future, this episode is for you. We interview a lot of really fascinating people who are doing their best to build biotechs in their verticals. And I have yet to give you my perspective on this, which is that talent is the bedrock of these companies. Now, I know we talk to other people in the HR space and we've all agreed that that is definitely true. We've talked to lots and lots of founders, we've talked to chief operating officers, we've talked to a lot of people who all agreed that talent is very important. But today I want to give you some actionable frameworks that you can take and hopefully install into your company to make an immediate impact on your talent acquisition strategy and the cost it takes to hire talent. So we're going to go pretty deep on this topic today and I hope it really makes an impact for your company. Welcome to Building Biotechs by Recredomics Consulting. We've helped over 90 biotech, life sciences and venture capital firms strategize and hire thousands of employees employees to scale companies that impact human health. We speak with those at the forefront of growing biotechs to learn their tactics on building these companies from the ground up. I'm Karina Klingman, founder and principal at recredomics Consulting. Enjoy the show. All right, to kick off, I want to go over why it is so important to install some of the systems that I'm going to talk about into your company. Because you can hire amazing talent, especially if you are a scrappy small company with a shoestring budget. And if you're a bigger company with more of a budget, you can still employ a lot of these tactics. It's really amazing what's overlooked in the talent acquisition process. So I want to bring to light some of the most important things that have been very impactful for the companies that I've worked with. So I've introduced a lot of guests on this podcast and you've heard my intro any number of times. But just to remind you, I founded Recruitomics Consulting about 12 years ago and I've worked with lots of different companies in the past decade plus including venture capital firms, small independent companies and nonprofit. So I've really enjoyed seeing a variety of companies and being able to see what makes an impact in different situations. So I'm going to outline some frameworks for you as we move forward that may be really impactful for you. And I'm going to tell you too where Maybe larger companies with a little bit bigger budget could splurge a little bit and perhaps get better systems or better processes the small scrappy companies can do on a shoestring budget. So the common challenges that small companies face. I'm going to talk specifically about, about biotech. But as we know small companies, startups are startups. So this might apply even if you're not in the biotech space. We are resource strapped, right? There's so much to be done and only so many dollars to go around. I often come into small clients and they talk a lot about the pains, right? It's painful to not have all the people you need in place. It is painful to know that you are staring down some sort of funding deadline or some sort of milestone deadline and you don't have the people in place to deliver. And therefore some hires are not made with a lot of real data around why the hire needs to be made and that leads to making the wrong type of hire. So this is sort of, I call it desperation hiring, right? You're feeling the pain, there's not enough hands to do the work, there's not enough people in the lab, there's not enough people on the operations side, whatever it is. And you identify this pain and just make a hire and a few months later, it's not really the right fit, it's not really the right hire. So, so that's a really common problem. It is something that larger companies also experience but to a smaller degree because they have taken some time to put into place some processes and they typically have an in house talent expert who is helping to guide the strategy there. That is not a luxury that many small companies have. Is that strategic oversight of the. Whoa, let's take a, let's take a breath, let's think about this and let's really make sure we're hiring the right person, not just any person. And there is a tremendous cost to, to a bad hire. So it's much more than just the monetary and the time. It's the team's angst, it can be lost productivity, it can be lost funding. So a bad hire has huge ripple effects and those ripples are bigger in smaller companies because think about it, in a larger company, you make a bad hire, it's not the right fit, it's not the right person or skill set that can kind of be absorbed by the people around them. If there's enough people around, then a mediocre or a low performer or just the wrong fit isn't felt as acutely. But take that into a small company. And the wrong hire can be disastrous because you're only talking about a few people. If you make the wrong hire when you have 10 people, it's a big deal. That is a tenth of your workforce. That is not the right person. That's much worse than one out of a hundred. But before we go too deep on this topic, I need to explain the critical concept of chicken math to you. So you may have seen some little memes around Facebook or Instagram. Sometimes it comes up as goat math or kid math, but these are little memes that just demonstrate that in the face of fun, cute things like puppies, chickens, kittens, whatever, logic and science and data just go out the window. So very, very smart people who have lots of degrees might say something like, oh, I have about five chickens, and about five chickens is really more like 20 or 30 chickens. This is a really common phenomenon, and I don't know how to explain it other than we do these mental gymnastics to make it seem like we have a reasonable number of chickens when we in fact do not have a reasonable number of chickens. There is no mathing our way out of that. So why do I mention chicken math? Well, it's really interesting, but we see startup math the same way. So I can't tell you how many times I've gone into a small company and they've said, well, something is, you know, too expensive. A piece of software is too expensive, or a consultant in XYZ area is too expensive. And they have said, let's just keep that in house. That's the phrase. Let's keep that in house. Let's do that in house. Have you said that? I bet you have. Let's keep this in house. We can do this in house. Discounting completely the cost of your time, of your team's time and resources. And this is really felt in a number of areas. But I'm going to be talent centric on this podcast episode. I'm sure if you're listening to this and you're in operations or any other part of the business, you will see instances of startup math in your processes as well. But for me, this looks like the founder of a company who is in the middle of a funding round, sorting through resumes in an email inbox. That is messy. And spending hours doing this instead of polishing their pitch deck, instead of talking to a great mentor who could help them polish their pitch deck, instead of doing anything else related to pitch decks, instead of making money for the company, this looks like having disorganization in the process and not really knowing who you want to interview. And so therefore interviewing too many people, because the phenotype of the person you want to hire was undefined at the beginning. And therefore it took a few rounds of interviews to kind of narrow down on what that person actually is, who you want, what they should be doing. And now you've had seven interviews with candidates, and each of those panel interviews costs well over $1,000. When you add up all of the time it takes to schedule to have those interviews, to have the debriefs, the lost time, in just context switching, right, your team isn't in the lab. They have to go to an interview, and it's not like the interview ends and they're just instantly productive in the lab. No, there are sidebar conversations. They have to get their brain back in the lab. It's not just as simple as adding up the one hour that they were in that candidate seminar presentation, for instance. So when I look at startup math, I see a lot of waste in the process, and that translates to actual dollars, because we are now talking about lost productivity, toward the milestone, toward getting the funding set up, toward doing the really meaningful deep thinking that is required by the founder and the leadership team. So I just want to encourage you to pause here and think of some instances of startup math in your process that you can identify and go, oh, yeah, that was some wasted time. We shouldn't have interviewed that person. We shouldn't have opened that role in the first place. Those are really important indicators of places in the process that we can immediately improve. And I'm going to get to that in a moment. So when I go into a company, the first thing I do is an audit of the processes and systems, and I try and find all of that chicken math in the process. Where are they using email, inboxes and spreadsheets instead of paying a small amount of money for an applicant tracking system that would streamline their process and save them hours and hours each week. When you look at the cost of that applicant tracking system, sure, it's not free, but it's less expensive than managing the process in a disorganized way. Where are they not putting systems into place that could actually have a huge impact on making sure that the process is set up at the outset really well, so that they're only interviewing the right types of candidates, and they're only spending their team's time interviewing the best candidates. That's a really important place to spend some time thinking. So within this audit process, I'm probably going to identify quite a few places that things can be tightened up. But don't worry, Roam was not built in a day. It's not like we're going to throw out everything and redo all the systems at once. There are always a few really high impact things we can do right away. And then we can sort of do the other things. As time allows, as budget allows, we can upgrade systems. We don't have to do it all at once. But sometimes there are some immediate impacts that will shave thousands of dollars off of each hire that we can implement almost instantaneously. So that's the first thing that I focus on because the next stage is to do that. And that is my second phase that I work with companies on. This is installing their hiring engine. And I like to think of it as an engine because there are pieces to it that kind of circle around each other. Once we get the pieces in place, it makes an engine that's really quite sustainable and it allows us to spin up a hiring process quickly and spin it down quickly. It allows us to go through the iterations of the interview processes in a data driven way, in a repeatable way, and in a scalable way. If you need to hire one person, it works. If you need to hire 20 people with some tweaks, it works. I'm going to caveat that with the with some tweaks because if you're a larger company, you may install a more robust applicant tracking system, for instance. But if you're a smaller company, you may install a very lightweight applicant tracking system. And if you were going to need to scale your hiring to 20 people at a time, we may need to opt for a little more powerful applicant tracking system rather than the one we set up at the outset when we were in seed round and we just needed to hire two people. So just keep that in mind that these systems are going to evolve over time and what you start with is not necessarily what you're going to finish with. However, if we know the end goal, there are some really cost effective systems that we can put into place that can take you all the way through your ipo. So we can be thinking about that as early as seed funding round when we are hiring those first key folks in the lab. Just depends on your vision, your budget, and your thoughts about how sophisticated you want to be in the hiring process. So I want to start with what I consider the heart of this hiring engine, which is the applicant tracking system. This is usually a place where we can have a big impact on the Cost of hiring very quickly. And again, this is one of those things where we have to set aside that chicken math and we have to think, okay, how much time am I spending trying to organize candidates in spreadsheets and in email inboxes and folders in my email when I can't actually mine those great candidates in the future for new roles that open up? It's not a compliant system to do it that way. We really shouldn't be emailing around resumes to our team. And it doesn't allow for automations. And that's what a really good applicant tracking system can do for you. It can make it so much easier to sift through the resumes and to automate a lot of the processes that come down the line. So that's kind of pillar two. A very basic applicant tracking system may not come with a lot of automations. You may not need a lot of automations to that stage. But a good, robust applicant tracking system will allow you to track candidates through the process. That's kind of the name of the system, right? Applicant tracking system. We're going to track them all the way through. We're going to make sure they have a great experience, because candidates talk. And if you don't give them a good experience, they may dissuade other candidates from applying to your company in the future. And you definitely don't want that. And it's going to allow you to, at the bare minimum, track the feedback that your team is giving throughout the process. And I'm going to come to that in what I think of as stage three of my framework. But that data tracking is critical to run a good, efficient, equitable hiring process. I have tested hundreds of applicant tracking systems of all different scales, different price points, and different what I think of as power levels. So you've got your enterprise level and you've got your little baby company level and everything in between, right? Within all of those applicant tracking systems, I feel really comfortable recommending several depending on the stage of the company and the strategic goals of their hiring process. So as we understand the burden of your hiring, are you going to hire one person a month? Are you going to hire one person a quarter? Are you going to hire 50 people in the next year? There's so many different nuances there. And I personally try to recommend applicant tracking systems that can grow with you as opposed to doing a really lightweight one that's not going to be able to grow with you and having to change applicant tracking systems. So that's a big strategy point. But that only can come through understanding the process and really knowing what your goals are. The automations that go into these systems vary widely depending on the systems and we're seeing more and more every day. It seems like most applicant tracking systems are trying to roll in some sort of AI. They're trying to roll in more and more automations and we have to be careful about that. Right? There is a real danger to using too much AI in this process, but there's also a real danger in not using any AI or automations and that danger is to your bottom line and your time. So we need to strike the right balance and I see that right balance as being a system that makes it really easy to to sift through the resumes because that is very time consuming and in this market different markets are different. I've seen lots of different markets and today we are getting for, let's just call it a scientist level role. We are seeing between 450 and 900 applications for a well advertised, well distributed role that is up from about 150 applications in the, let's call it 2020, 2021 range when the market was really hot. So who is going to go through those applications on your team? Who gets the dubious honor of sifting through 900 applications? I would argue that it is a mixture of technology and people and I personally do not use AI in this step. It's first of all illegal in some places so we want to maintain really good compliance here. But it is not illegal to quickly be able to evaluate candidates on whether they are the right fit based on what's included in their resume and their cover letter. So with some of the right automations you can really take that large number down quite quickly to a manageable number of resumes to screen. So if you have a dedicated team member that can do that, that is great. Most companies don't if they're very early stage and often it's the hiring manager and what is their time worth? So we really want to get clear on that stage of the engine so that we are cutting down the time. That is by far the most time consuming piece on a week to week basis for I would call it the administrative work bucket. Then within this automation bucket there are so many great things we can do. I'm a big fan of introducing some enhanced applications which is like a chatbot or something like that to allow candidates to expand a little bit on their experience but only if they're selected for that round. So if we have 900 applicants and we want to give the top 5% of applicants the chance to enhance their application. That's still 45 people. That's a lot of people. Right? So with some good enhancements, like some chatbots and the ability for people to explain a little bit more around their experience, we can then give the hiring manager just a little more insight and do another triage step where we're taking that 45 applicants down to maybe 20 for them to actually review in detail at the application level. Then when we do select candidates, we want to proceed on the interview with what are the automations in place to help with scheduling? Who is doing that? How is that accomplished? A lot of times we can wrap that into the applicant tracking system and save a lot of time on the back and forth with scheduling by putting it in the candidate's hands and making scheduling something that people can do for themselves. The next step in this engine is the attraction piece. We really want to be attracting good applicants. We really want to have good syndication for our jobs. And not every applicant tracking system does that. And we definitely don't want to be posting just on your website. That's really, really poor for applicant attraction. So good applicant tracking systems make it absolutely seamless to syndicate the job out to all of the job boards, including LinkedIn on your company LinkedIn page, including Google jobs, which has been a really good source of candidates, indeed, which is a dubious source of candidates, depending on what we're looking for, but still worth doing. Glassdoor is a good place. So we want to make sure that we're syndicating the jobs really well so that we are attracting a large pool of candidates or at least putting the job in front of that pool. We can also do some paid advertising here. And again on a shoestring budget. You may think that that's not a great idea, but the more robust your applicant pool, the less you're going to have to rely on external recruiters. And they are more expensive, trust me. So if we can do a small amount of paid media here, it really can bolster the applicant pool. This is not for every job. And again, this is where a strategist can think about jobs and say these ones perform well in paid and these ones do not. And really understand what is the best use of your money, your dollar, in this recruiting process. But at the very least, we want jobs syndicated everywhere. Hey there, just a quick break. I wanted to let you know that if you're listening to this podcast, because you are exploring careers in biotech, which it turns out quite a few of our listeners actually are you might be interested in the Biotech Career Coach podcast. It is brought to you by our sister company, the Collaboratory Career Hub, which is our career development community. If you would like actionable tips on job seeking and career development, that is the place for you. It is a companion podcast to our Career Coach column that we write monthly in Biospace, but we go a little more in depth and sometimes we have special workshops and all of that good stuff. So if that sounds interesting, click the link in the show notes or search for the Biotech Career Coach on Apple Podcasts or wherever you get your podcasts back to the show. So this brings me to the third pillar of my framework that I like to work with clients on, and this is the knowledge and data pillar. It is so interesting to me that really intelligent scientists who run amazing experiments that are well documented, that are well planned and executed, the data is impeccably analyzed, don't translate that into all of the other aspects of running the company. So again, if you are in operations, if you're in business development, if you're in lots of other verticals in biotech, you're probably nodding along and thinking, yeah, the scientists are just not great at actually doing data outside of the lab. I don't know why this is. I am a scientist, guilty as charged. But I have tried to bring the best data into this process that I possibly can to run a really efficient hiring process that not only saves companies money, but also gives them better confidence in the people they hire. So let's talk through exactly what that looks like. The first aspect of this is the training aspect. Without good training, how can you expect your team to hire good people? It's like. And again, I'm going to go back to the analogy of what happens in the lab. If you get a new piece of equipment in the lab, everybody trains on it. You don't let everybody just kind of go wild with the new, expensive, shiny piece of equipment in the lab, right? You've got a rep who comes in, they tell you how to use it, they teach for your use case, they tell you what to look out for, what could go wrong, and then after all of that is done, you let people loose with the equipment. We don't do that for hiring processes. We don't do that for leadership positions. In biotech, especially small biotech, there's often a complete lack of training because that's just not built in yet. Later on, when the company's much more established and you have an HR team and somebody's in charge of helping with all of the training aspects, that becomes a lot easier. But if you're not at that stage, you probably are just kind of turned loose and it can lead to a lot of problems. So I'm going to tackle the problems in three main buckets. First of all is the systems and processes bucket. Again, this is a lot like having that brand new piece of equipment in the lab and thinking that you could just turn people loose on it. No. Once we've installed this hiring engine, everybody needs to be trained on it. If you are going to be hiring, whether you're a hiring manager or you're an interviewer, or you're helping with the scheduling, you need to know how the system works, and you need to know where you fit into that system, what the best practices are, and what to look for when it breaks. Everyone needs to know this because it is everyone's job to safeguard the hiring engine. So the first part of training is really a very practical training on what to do in the systems and the best practices to keep them flowing. The second part of the training is very important because it's the legalities. In my opinion, no one should be turned loose in an interview process without a basic knowledge of hiring law. This means what you are allowed to ask and what you are not allowed to ask. And this simply boils down to an understanding of the why behind it. Because there's no way I can list out every question you shouldn't ask. But if you understand the concepts behind why you shouldn't ask certain types of questions, then you won't ask them in any iteration. You won't come up with creative ways to ask them. You just won't do it. I like to use a blanket statement. If the question does not pertain specifically to whether the candidate can or cannot do the job, then it shouldn't be asked. And some people feel like this dehumanizes part of the interview. And I will admit it can feel that way. But I think you can get really good at asking good interview questions, which I'll cover in a moment so that you can keep the humanity in it. The way that this manifests totally accidentally and totally innocently is people in interviews asking questions like, oh, so where do you live? Or oh, do you have a family? Just those types of get to know you questions that seem like you would want to ask a candidate. Yeah, I want to get to know them. What kind of a person are they? But that can introduce bias into the process, and it can also open up the company for lawsuits. So in interview training, I really try to impress upon people what types of buckets of questions they should be asking. These are technical questions. These are questions that get at the soft skills required for the job. These are questions that assess the company culture and really deeply probe the person's ability to not only fit the company culture, but augment it, right, be a culture carrier. So that's the third training that we do, which is strictly the interview skills. You should know what you're not allowed to ask, and then you should also know what you should be asking and how. So interviewing is a skill just like anything. Most people are terrible at it when they start. And with practice and guidance, you can get really, really good at interviewing. You can ask deep questions that require thought and stories from candidates, and that's how you get to know them personally. You don't need to know all about their family. You just need to know how they think, how they process problems. What would they do in a tough spot? How would they react when a similar problem that your company has faced maybe happens again? Or what would they have done if they were there? There are so many ways we can get at the way a person will perform in a job without asking personal questions. I'll just say that personal questions often come up too, around relocation. That's one of the main places that I have to step in and go, whoa, whoa. We can't really ask those questions. And they manifest again in a totally innocent way. Often when a candidate needs to relocate, they might ask something along the lines of, oh, you know, do you have a family, young kid, they need to switch schools, things like that, which we really just shouldn't be asking. When in doubt, leave things to hr. And if you don't have HR internally and you really have to do this, learn the ways to ask these questions. That should be your main job. If you're the hiring manager and you don't have an HR or a talent asset within the company or as a consultant to lean on to ask those questions. All right, so once the training's done, which is essential, let me just back up and say, definitely get some training for you and your team. It is so, so important. We want to now think very deeply about the data that we're going to be evaluating for this process. So in this part, I like to teach clients what the big companies do as a gold standard. So here's the gold standard process. This is the pie in the sky. We would love it if every process went like this. Somebody on the team, maybe a recruiter, would have eight to 12 screening calls and no more. If it's the hiring manager, I actually think you can cut that down. But if it's the recruiter, so they're not maybe an expert in that space, the subject matter expert, a scientist, for instance, there might need to be a few more calls while they sort of calibrate in to understand the role really deeply. The hiring manager should really only be speaking to five to seven candidates because you should kind of know what you're looking for. You're the hiring manager. This person's going to be in your team. You should know the skills you're looking for. And so when you're looking at resumes and maybe these enhanced applications, you should be able to select five to seven people that you are pretty reasonably certain would be good fits for the role. So that's the progression. If you have a recruiter or an HR person, maybe they're having eight to 12 calls, the hiring managers having five to seven maximum. This should boil down to three team interviews and one hire. That's the gold standard, is that your whole team, the panel gets involved for three candidates and no more. This should be sufficient to make a good decision. But you need to know this data and you need to track this data in order to know if your process is going off the rails. So just like you would troubleshoot an assay in the lab, we troubleshoot this problem process based on the data that we're seeing. Oh, interesting. The hiring manager actually had 14 calls and we've now interviewed seven candidates with a full panel. That's a problem. Or this hiring manager only interviewed three people. We only had a full panel with one person, and we're making an offer. Should we maybe get a few comparators just to be really certain that we've got the right person? So knowing your numbers, knowing those benchmarks, and then really trying to run the process according to those means that you're going to have more certainty when you come to the end of the process. And the last thing we'll really track is the data around candidates. Again, I'm going to bring it back to the data. We need to be able to evaluate candidates on even footing. So often we will have brilliant scientific teams go and interview multiple different candidates and not have standardized their process in any way. They're not asking the same questions every time. They're not evaluating the candidates on the same metrics. So we come to a debrief session and nobody actually knows what we're evaluating. And the decision is, well, we think we like this person the most. So let's go with that as opposed to having some data, being able to talk about that data in an intelligent way and then coming to a decision. So this is very simple to implement. And this again, can be done with a shoestring budget. I've seen it done in Google forms before. I've seen it done in Microsoft Teams just using a secure document. The point is to establish a standardized scorecard. And this scorecard should be set before we interview any candidates. It should have repeatable metrics. So I love to put the culture aspects on there. What are the things you and the team really value? What are the technical skills we're looking for in this person? What do you really value there? And what are the soft skills that we're looking for in this person? For instance, if we're looking for a project manager, yeah, we want them to have all the technical chops to manage the projects. But do they seem really organized? That might be a really good one, right? Maybe they've managed projects in all the different types of project management softwares, but you just get the sense that they're not very organized. Maybe they didn't schedule their interview very well. Whatever. That's worth noting, right? For certain roles, understanding the soft skills that would be required to excel could go on a score sheet. All right, so you've got your scorecard set up. I love to do it like this. If possible. I love to have the hiring manager start off the day. So the hiring manager should have already spoken to the candidate on phone call or resume. And when we have our panel interview, I like them to speak again with the candidate. They're going to be managing the candidate. They might as well get more touch points with them. But by kicking off the day, the candidate has a friendly face they've already met. To start things off, the hiring manager can then fill out their scorecard first and put it into the secure system. The rest of the team can go through their day filling out their scorecards and putting them into the secure system. Nobody should see the scorecards except for the hiring manager. And the hiring manager should only see the scorecards after they've filled out their own scorecard. And then nobody should change anything. The scorecards are your impression during that half hour, and that is valid. Even if your impression disagrees with someone else's impression, it is a valid point of view. So I want you to hold space for that and just know that in this system, part of the reason we're implementing it is to eliminate group think. This allows us to have a Data driven feedback session where the hiring manager compiles those scorecards, studies them. And I should back up and say that in the scorecards, I like to have the ability to have notes with each of the scores. And really good applicant tracking systems just do this automatically. But to be able to explain your score with maybe just a quick bullet point, one sentence, it allows the hiring manager to then look at your scorecard and understand your feedback. If you gave them one star, why did you think that if you gave them five stars? We also want to know if they were middle of the road. Tell us why you thought that. This then allows hiring managers to assemble the scorecards and come to a feedback session with an average score for each thing we're evaluating and a set of notes. So they can do a round robin and they can say something like, this candidate is five stars down the row for their abilities in the technical space where we saw some discrepancies were around our soft skills. So I'd like to start with their communication. And then you can round robin and you, as the hiring manager can choose who starts to speak first. Because we all know that there are some louder voices in the group than others. And those voices sometimes can sway the quieter, the more reserved members away from their opinion. What I see in a poorly run feedback session is that there isn't any data. Everyone comes together and the loudest voices start to speak and the smaller voices don't get to speak up. And maybe they had a different opinion, but, oh, the group sounds like they're really for this candidate or they're really against this candidate. I'm just going to go along with it and that's dangerous and that leads to poor hiring decisions. So I guarantee you, if you implement a really data driven approach to hiring, when you make the decision, you're going to feel good about it. You're going to know that you had the data, that everybody was heard, and at the end of the day, you ran a really fair and equitable process that was not based on people's gut feelings, their mood that day. Any of the things that we know can affect hiring, we just really want to get to the answer. And as scientists, it is simpler than we think. So, so to recap, my framework is just three steps. I know it sounded like a lot, but first is an audit. You cannot fix what you don't know is broken. So really dig deep in this audit. Think about all the areas where you might have some chickeny startup math going, right? Where are we wasting money because we're keeping Things in house and where could we maybe splurge a little bit, but actually buy back the team's time, buy back some resources or simply eliminate some of the pieces of this process that are not serving the team. Second is to implement really good systems and processes. And this doesn't need to happen all at once, but to know what the gold standard is, what we're going for in this recruitment engine, this hiring engine that we want to install into the company so that we eventually get to where it's just easy to spin up. Anytime we need a new role, we know who we want to hire, we create a great hiring process and we end up with the right candidate at the end for a very reasonable spend, much less than you probably were spending without the systems and processes in place. And third is all around the actual process. What is happening, boots on the ground. There has to be training. We have to train our people if we want them to succeed in hiring amazing colleagues. There is no way around that. We have to think about our hiring in a data driven way. We need to understand what the process should look like and what it shouldn't look like, what happens when it goes off the rails. And we need to come to the end of a hiring process having evaluated candidates fairly by implementing the same type of evaluation across the board for every candidate and then speaking about the candidates in the feedback sessions in a very deliberate, data driven way so that everybody's very comfortable with the outcome, everybody knows they've made the right choice. I know this sounds like a lot, but this is very doable for companies at all scales, at all sizes. Whether you're hiring your fifth person or your 500th person, these sorts of processes are the things that allow companies to grow much more effortlessly and without the high recruitment spend and cost to your team, your team's time and energy. So I hope this was really helpful and actionable for you. So if this seems overwhelming and it is something you would like, help on, just know that I love my job. I am a fractional head of talent acquisition and I love to come into companies and look at their processes, meet them where they are, establish really good data driven, reproducible systems so that they don't have to spend as much money doing recruitment. In the end, they can sit back and know that they're hiring amazing people time after time and they're able to compete with the big companies that already have a great engine in place. You do not need to spend what they spend to get the same result. I guarantee that if you have any questions about this, reach out to me. I'm really easy to get a hold of on LinkedIn and you can always sign up for our newsletter. Every Friday I introduce our podcast guest for the week and I give you some of the headlines from the week in Biotech News. You can always reply directly to that to get in touch. All right, I'll see you next week. Bye for now. Building Biotechs is brought to you by Recruitomics Consulting. You can find Building Biotechs in Apple Podcasts, Spotify, Google Podcasts, or anywhere else podcasts are found. Make sure to click subscribe so you don't miss any future episodes and join our mailing list for a weekly dose of biotech news and a podcast overview. And if you need to install a recruitment engine that saves time and money for your growing company, reach out for a free strategy session. I'm always happy to share my experiment expertise and show you techniques to simplify your hiring process and maximize returns. On behalf of the team here at Recruitomics Consulting, thanks for listening.