We live in the age of data, and everything important to an organization’s people management function gets measured. In this episode of Honest HR, host Wendy Fong speaks with Dr. Milton J. Perkins, Senior Vice President at ActOne Government Solutions, about the transformative potential of people analytics, their role in helping HR professionals create workplaces where employees genuinely want to be, and steps for leveraging them at your organization.
We live in the age of data, and everything important to an organization’s people management function gets measured. In this episode of Honest HR, host Wendy Fong speaks with Dr. Milton J. Perkins, Senior Vice President at ActOne Government Solutions, about the transformative potential of people analytics, their role in helping HR professionals create workplaces where employees genuinely want to be, and steps for leveraging them at your organization.
Earn 1.00 SHRM PDC for listening; details on claiming your credit are provided in-episode.
Wendy Fong:
Are you wondering how to integrate artificial intelligence into your core business strategies? Hear from AI visionaries and discuss this topic in depth with other C-suite executives and senior HR and business leaders this March 4th through the 6th at the AI+HI Project in Mountain View, California. Register today at shrm.org/aihi24-honesthr.
Monique Akanbi:
Welcome to Honest HR, the podcast for HR professionals, people managers and team leads, intent on growing our companies for the better.
Amber Clayton:
We bring you honest forward-thinking conversations and relatable stories from the workplace that challenge the way it's always been done because after all, you have to push back to move forward.
Wendy Fong:
Honest HR is a podcast from SHRM, the Society for Human Resource Management. And by listening, you're helping create better workplaces and a better world. I'm Wendy Fong.
Amber Clayton:
I'm Amber Clayton.
Monique Akanbi:
And I'm Monique Akanbi. Now, let's get honest.
Wendy Fong:
Now, let's get honest.
Amber Clayton:
Now, let's get honest.
Wendy Fong:
Hello, HR fam. And welcome. I'm your host Wendy Fong, manager of Event Technology Innovation at SHRM. This podcast is eligible for one, SHRM-PDC toward SHRM-CP and SHRM-SCP re-certification. If you listen to the full episode, we'll share the activity ID at the end of the podcast. We live in the age of data and everything that is important to an organization is measured. HR is in the business of people, and in business we need data like KPIs to measure back to organizational and business goals which is, drum roll please, people analytics. Although you may be thinking, "I didn't get into HR for people analytics," it is how we prove value with quantitative and qualitative data because remember, everything that matters is measured and this can range from recruitment, talent, acquisition, retention, workforce planning, employee engagement, and even inclusion, equity and diversity.
Today, we'll speak with Dr. Milton J. Perkins on the importance of using people analytics in HR and at your organization. So Dr. P is a senior vice president of ActOne Government Solutions Inc, a subsidiary of the ActOne Group, responsible for pursuing, managing and delivering staffing solutions to government agencies, coordinating government talent solution contracts for all other ActOne Group companies and providing HR Consulting to government private sector and not-for-profit organizations worldwide. With over 44 years of human capital experience, Dr. P has a tremendous wealth of practical research, teaching and consulting experiences, developing innovative organizational outcomes through people. Dr. P has been a SHRM faculty member for nearly 23 years and has assisted SHRM and other HR associations with developing and facilitating content in numerous HR specialty areas such as DEI, people analytics, as we'll get into today, and workforce planning to name a few. He has spoken on various human capital topics in over 41 countries at many SHRM state and national events, at corporate events, virtually and in-person worldwide. And as we're diving into this episode, I just want to say thank you, Dr. P, for being here.
Milton Perkins:
Hello, Wendy. Thank you for having me. It is an honor to be with such a distinguished audience, so I hope we have a bunch of good listeners and they'll reach out to me post podcasts with questions that I'll be glad to answer. So thank you for having me. It was an honor for you to even ask, so thank you.
Wendy Fong:
Well, you're one of our regular instructors at SHRM, especially on the people analytics specialty credentials. So let's just break down for our listeners, what is people analytics and the different key focus areas?
Milton Perkins:
Good question, and most HR practitioners struggle in this area because most people did not get into HR to do numbers. Most people got into HR to help people and then the profession moved and it became much more about HR as a practice, designing, developing, implementing, and then measuring HR related solutions back to organizational key performance indicators. So the lenses, at least the people that I am interfacing with as clients and as students, the lenses that we struggle with is how to prove the value of what we have designed and implement it. So that's HR analytics at its most foundational definition, it's the proof, it's the quantitative and the qualitative data related to what we have designed and implemented in these areas. Talent acquisition, total rewards, performance management, employee engagement, learning and development, and then even when we offboard people, how do we offboard them and measure whether or not the offboarding processes, policies and procedures are valuable?
Everything in an organization that is important is measured. In fact, if it's not measured, it doesn't matter. That's my mantra. If you're not being measured, it doesn't matter. So HR needs to look at the breakdown of analytics through the lenses of HR, HR as a practice and then each of the functions within HR, what are the variables, quantitative or qualitative data elements that you use to prove that what you have designed and implemented is a value? Here's what we normally do that might be a mistake, and this might be jumping ahead to a question you might ask me in the future.
We typically produce a lot of HR in, air quotes, "analytic reports," but it's measuring HR, nothing is correlated back to organizational key performance indicators. And then we produce this lovely report and then we thump our chest and say, "HR is doing great," when in fact you just measured HR. You're not measuring anything back to the business. What I'd like to do as a foundation to everything I've just said, if HR practitioners would embrace this concept. This should be their mantra every day, "It is my job to create innovative organizational outcomes through the human capital infrastructure, and then here's the proof, the analytics." So that was a lot. Measuring all of the specialties of HR correlated back to the business is the breakdown of what people analytics is at its core.
Wendy Fong:
And I'm curious, where did people analytics evolve from? You mentioned, people go into HR because they have a passion for people, for helping the organization with relationships, but somehow evolve this need to measure those KPIs.
Milton Perkins:
Yes. So HR became a profession back in the '40s with the birth of the American Society for Personnel Administrators, and then SHRM was in 47. To be a profession, you need to have a code of ethics, a body of knowledge, you have to have an association. So from that time, 47 to probably right around the year of 2000, HR practitioners chased the proverbial seat at the table. Why? It's because all of the knowledge associated with the profession was written and the practices that we executed were all administrivia and operational. We cut paychecks, we did annual enrollment, we dealt with OSHA issues and safety, and then we got out of the way. The executive leadership would say, "Get the room ready for a meeting and then get out of here. We have an important meeting." What people didn't realize, nothing happens, sends people. So right around the year 2000 based on research, HR arrived, we had the seat at the table, but we struggled.
So for the next few years, until our competency model was reborn around 2011, we struggled with the HR speak thing. So someone would say, "Hey HR, what are you doing?" We would come in and say, "We're doing this," and then we would have no measurements, understanding that everybody at that table, everything important in the organization is being measured. Well, right around 2006, we got the message. The peers at the table was saying, "You guys have to up your game," so the competency model changed around 2011. There was business acumen under which it's included people analytics. We had to understand how to read financials. We also brought to the table, and most organizations realize, 70% of the operating budget is in human capital issues, compensation benefits, total rewards, learning and development, everything associated with humans. So just using a publicly traded for-profit company as an example, I as an investor would say, "You're spending 70% of the dollars that I give you on human capital stuff. How do I get that ROI? How do I get my money back?"
So now HR, with this new competency model and all of this knowledge, the BASK, we are now upping our game to say, "If I design something in talent acquisition, total rewards, performance management, learning and development, all of the subspecialties of HR, I must measure that back to the organization because I have to prove the value of what I've designed." So it happened between the early 2000, 2011 when the analytics concept popped up. We became business people, not just HR, administrivia operational. We became HR strategic people and catalyst to say, "Look, what are the things on the horizon? What do I design? And then what's the proof that the design is working?" We still struggle, by the way. An example, I will ask a person sitting in one of my events if I'm doing public speaking at an event, I'll say, "By raising of hands, how many of you have heard of the great resignation?"
And everybody's hand goes up because, yeah. And I said, "And what did you do about it?" And I just get stares. And if they say, "Well, this is what I did," and I said, "So how do you prove what you did was valuable back to the organization? What are the variables you use to prove that the thing that you designed and implemented actually benefited your organization?" Actually, I use the four-legged stool. "How did it benefit your shareholders, your employees, your customers, and the communities in which you operate? Let's measure it." Everything that is important is measured, and if it's not measured, it doesn't matter.
Wendy Fong:
And I love what you said, the phrase like upping our game. HR, whether or not they accept it or not, the profession has evolved to this level where it needs to be measured, where whether or not you realize that HRs are analyzing these reports, correlating back to the organizational goals to ensure that everyone is in alignment and going in the right direction.
Milton Perkins:
And HR can walk into the room and tell a compelling story not only to the leadership to say, "Hey, we've designed this stuff and it's having an organizational impact as illustrated by this Pearson correlation coefficient between these two variables. I've statistically connected the dots. I did this variable move and it had an impact on this KPI in the organization, and here's the statistical formula to prove it," so I can go in and be able to say that.
So I was saying they tell the compelling story using numbers and quantitative and qualitative data. Not only does HR have to do that, going forward we need to help every people manager, every employee understand, "Your role in the journey of this organization based on analytics, you're sitting there hitting the K-key all day, why? And I need you, employee John Doe, to be able to tell the story. When you hit that K-key 50 times a day, this is what it's going to produce and this is the impact that it has on your department, your function and the organization." When you get an organization to that point, everybody is firing at full cylinders, but it's based on evidence. It's not based on simply us saying we have a HR metrics report.
Wendy Fong:
Okay, let's get into some examples then. For example, you mentioned the great resignation. So as a HR professional, how would you approach that from a people analytics standpoint?
Milton Perkins:
So I would say, this is so common and even to the listeners of the podcast, if I post the question before I explain this to you, I want them to say out loud to themselves the answer, "What is your turnover?" Now people are now saying to themselves, 12%, 16%, 3%, my turnover is $650,000. I am a for-profit organization, so I monetize turnover. If I can look at the great resignation and it is predicted with science that these number of people will leave the organizations, I monetize that and then I connect that number back to my EBITDA or my gross profit margins, or my net profit, whatever the case may be, whatever the key performance indicators are to prove success for my company, so I'm going to connect that turnover. Now, the reverse of that is I'm going to design this solution. Here's the thing, analytics are dominoes.
So if somebody will bring a problem, opportunity or threat to me, it's either they're going to come to me via a report where I'm looking at quantitative or qualitative data. So let's say we've monetized turnover and I get the report. By the way, people analytics is not just developing a report. Our HR practitioners need to help their organization evolve to evidence-based decision-making related to the human capital infrastructure. What's that human capital infrastructure? It's the collective body of humans in the workplace, and I'm designing things to impact them, motivate them, reward them, develop them, engage them, all of that stuff. So back to the example, if I see that turnover has been monetized, when I pull a report, it's a domino. It's going to present to me a problem, opportunity or threat quantitatively and or qualitatively, and I'll explain the difference between the two later. When that happens, I'm going to come up with a statement, "This is happening. Based on these numbers, this thing is happening."
I'm going to do a root cause analysis based on preliminary data, "This is why this is happening," because I don't want to design something against a symptom. I want to design it based on a root cause, so I'm going to use a Ishikawa chart or a Fishbone chart, take my team through a root cause analysis. Once I get to a root cause, I am then able to come up with a hypothesis. Remember people analytics, you have to have the mindset, not of an HR practitioner, but of a researcher. So a problem opportunity and threat research question, preliminary data, root cause analysis, and then I come up with a hypothesis, "Based on preliminary data, evidence, quantitative and qualitative data analytics, it looks like if I do this, this problem will go away or I will be able to better leverage this opportunity or I will mitigate this risk."
That's a hypothesis, an if then statement. What I cannot do is now go out and do it because a hypothesis is an educated guess. I need to validate it, so now I go through a people analytics project and I'm going to go collect data to validate the hypothesis. I'm going to collect data through surveys, interviews, archives or stored data, focus groups or through observation, I collect a bunch of data, analyze it, and that data will say, "Your hypothesis is valid or it's not." If it's not valid, the data will tell me what to do. If it is valid, then I'm going to fully develop that solution, implement it. I've already got the metric or the analytic tool to measure the success. I'm going to enhance it, develop it, implement it, and then the cycle continues. My goal as an HR practitioner is, now we have reports on which we make decisions.
A report is a call to action. The action is not file the report, the action is get together, have a conversation, "What can we do to become better, align with the organization's strategic goal or mitigate risk, anything that may make a stutter step from attaining that goal?" So my job is to help the organization evolve to evidence-based decision-making based on this body of analytics. Here's a warning, do not go out and develop an analytics tool that reports on 5 million things, just a handful, maybe two per lens of HR, talent acquisition, total rewards, performance management, employee engagement, learning and development, offboarding, onboarding. Have a couple each and be able to have a meaningful conversation. Wendy, that was a mouthful.
Wendy Fong:
Well, it almost sounds like a science experiment to me.
Milton Perkins:
It is.
Wendy Fong:
It takes me back to my high school days like coming up with the hypothesis, doing the research evidence-based decision-making, and it sounds like there's a lot of tools and technology and even a team that needs to focus on this.
Milton Perkins:
Yeah. You need to have an analytic team. There needs to be an analytic team. Don't do this by yourself, just don't do it by yourself, bottom line.
Wendy Fong:
I mean, I can see large organizations having the resources needed for this, and it is a much needed arm in the HR world to bring back to your organizations, but scale it down to HR department of ones, which I know a lot of our members and listeners are, how could they approach this and still use it to their advantage?
Milton Perkins:
Wow, that's a good question. That's a very good question. So I know this, what I'm describing is a lot of work. If you're going from a whiteboard to, "Oh, this guy said I need to do people analytics and help my company evolve to being evidence-based decision-making related to anything, dealing with a human in the workplace, a group of humans, a function, everything, and everything I'm doing is tied back to the organization." If I'm a large organization, I might have a project management office. I may have business analysts that have been assigned to HR that can help me do this work and the words out of my mouth to them, they're not foreign. They're like, "I know exactly what you're talking about. This is what I do all day." But an HR department of one, a couple of things. Bottom line, both large organizations and HR departments of one and everybody in between, I would suggest that anyone go out and get a People Analytics class, get the foundational for people analytics.
This may sound like a shingles commercial because this is a SHRM podcast, but SHRM has classes related to the topic. If not SHRM, now here's where my selflessness kicks in, go find a class somewhere on People Analytics so you can understand the foundational principles. I do know this, most HR people are not in HR because they want to do numbers, so you're going to have an analytics team. If you're an HR department of one, at least tap on the shoulder of an external subject matter expert at the beginning and ask this question, "How do I set this up?" And then you tap them out because somebody's going to say, "We can't afford that." My response is, "You can't afford not to do this," and the money you spend with an external expert, it's not a cost, it's an investment.
They're going to put things in place for you that's actually going to pay for the money you slid across the table to get them help. So HR department of one, get an HR expert external to help you start the journey. After you start it, you're going to have an analytics team and you can assign team members by components of the maturity curve, and if you remind me, I'll talk about the maturity curve, and then you come up with a people analytics process, procedure, work rules, and then ultimately a report. That report is full of dominoes that will tell you about problems, opportunities and threats, and then it's a circle. We're getting into evidence-based decision-making. Once I get a number, it's telling me something, I need to do something about it, mitigate a risk, leverage an opportunity or address a problem.
Wendy Fong:
Yeah. I came from the Association of Certified Public Accountants, and it does remind me of how accountants or even certified financial planners approach budgeting, predicting revenue, expenses, having those projections and tying it back to organizational goals. It's almost like HR and people analytics is following a similar process, using data in this world of big data, we need to leverage those tools at hand whether or not organizations want to accept that fact or not, they need to. And as you mentioned, it's an investment for the long-term strategic goals of an organization's viability.
Milton Perkins:
Exactly. In fact, just as an example, the data might allow me, I'm looking at data, I'm reading and I realize that based on this data, I'm fat. I'm overstaffed. I can actually become very lean based on data, it's evidence-based decision-making. This data is telling me something and it's telling me I'm fat. Cut the fat out. I might repurpose people to better jobs or the right job. I've got the right people on the wrong job, and they're inefficient, ineffective, we've over indexed those phrases by the way. Everything I do is evidence-based. If there's not a number, it doesn't matter, and my HR department knows that now. So HR reports to me and when they come, they know the game, their language, the conversation, it must be tight because I'm always going to say, "Where's the evidence? I hear what you're saying, but where's the evidence?" "Oh, well, we don't have it." "Then let's not talk about that because it doesn't matter. If it's not measured, it doesn't matter."
Wendy Fong:
That's very true. I mean, what are some of the best tools that an HR practitioner can start with or technologies that you've seen that can help in people analytics?
Milton Perkins:
Oh, framework for one, and you started talking about how the accounting association, and everybody's approaching... It's kind of a business case model that you learn in B-School. You have to approach HR. Note this, I'm in the business of humans. I'm not HR the department where administrative things take place. I am equivalent to the chief technology officer or the CIO. They're bringing technology infrastructure to make this organization perform better. I am the human person, so I know B. F. Skinner's operant conditioning, Isaac Ashton, theory of planned behavior, Maslow, Herzberg. I know all of these things because I'm the human expert in the workplace. I know how to make people come, how to make them jump through the ring of fire, how to make them leave in a legally compliant way, what they would love, and then I measure everything I talk about. So some of the technologies that I would use, first of all, I would've a model in place, and that leads me to the maturity curve for HR analytics or people analytics. One, any report that I develop should have these levels of variables in them.
One, the report should tell me typically, quantitatively what's happening, descriptively, what's happening? Turnover, turnover is $650,000. That's a quantitative representation of something happening, a number that represents a phenomenon, but I don't know why. So the next level up the report should say, "Qualitatively," using turnover as an example, "I've monetized it. Our turnover is costing us $650,000 a year. Qualitatively, I've embedded into that report the themes and the analysis of all of the exit interviews." So now I know diagnostically and qualitatively why turnover is happening, so I have it, descriptively, what's happening, qualitatively, why it's happening, and I can look back over a couple of years and develop analytic models to predict what's going to happen next year. So I can tell the organization, "This is what's going to happen all things being equal. Now, we have designed," this is the fourth level, prescriptive, "we have designed several solutions that's going to address that issue of turnover, and we're going to take some of that money that's been walking out the door and put it back into our budgets if we are not-for-profit or government, into our profits if we are for profit."
"So here are the solutions prescriptively, we can do A. Here's the investment in A, here's the ROI. We can do B, here's the investment in B, here's the ROI, or we can do nothing, and this is what the future looks like if we do nothing based on our current investment in the human capital infrastructure." So I need to have a model descriptively, diagnostic, predictive and prescriptive model. Here's where I can use some additional technology that is out there. We have, everybody hears this and it's trending and people are fearful and, "Oh my God, it's going to replace me." AI, no matter which, if you use Genie or ChatGPT AI, whatever. I can use AI to say, especially if I collect data from the closed source, our company, I can use the data internally to come up with prescriptions to help me say, "Hey, based on our history and all the things we've done, this is what we should do going forward."
The problem with AI is it could be biased because AI technology is collecting data from the entire cyberspace world, and some of that data may be tainted. It may be biased to say, "Don't hire women, hire men," and then it comes back and tells me I need to do that, which is why I tell HR practitioners, "Set this stuff up, evidence-based analytics, measure everything, produce evidence-based decision-making culture, have these tools measure at these four levels. AI will never take the place of you." So you need to bring your gut and your experience or the team's experience, that diversity of your team, different ages, different experience, different tenures, different perspectives, bring them to the table to say, "We see what the AI technology says, but we need to make an adjustment based on real world within our company close data." So I've given you a lot, have a framework, use technology like AI to help you, but also forget, do not eliminate humans.
Wendy Fong:
Yeah, that makes sense because AI can be inaccurate, right?
Milton Perkins:
Absolutely.
Wendy Fong:
And biased based on the sources too.
Milton Perkins:
Yeah. I actually know somebody who creates AI case studies, this person does this for a living. They sit and they type case studies and upload it into whatever tool that they're using for that AI technology to have access to it. So I asked this person, I said, "Where do you come up with the scenarios?" "Well, I just collect a bunch of things, some things I make." She's a creative writer. She says, "Some things I make up." I'm like, "You're making up reality and AI's going to tell me to make a decision on what you created?" "Yeah." And I'm like, "Oh, so you're never going to forget a human's interaction?" And the diversity of humanity is huge to me. So if we all stand on one side of a rubric cube, a giant rubric cube, and I say, "Wendy, what color is the rubric cube?" You're like, "It's blue."
And I'm like, "No, it's not. It's white," because I'm looking at it from a different perspective. You have a different perspective on the world. I want that diversity in the room to say, "Look, these are the issues we're dealing with based on these numbers. How do you think we need to... ChatGPT or Genie said, we need to do this. What do you think, Wendy?" You're like, "No, absolutely not, not based on my experience and I've been in several organizations, that's going to fail or we need to enhance it. Use that technology foundational data or solution, prescriptive, prescription as the foundation, let's improve upon it."
Wendy Fong:
Yes, and it sounds like AI is still in its very early stages that we don't know yet how it's going to change in the future and impact people analytics.
Milton Perkins:
Yeah, it doesn't scare me though. I'm not afraid of it. I will dive into a Genie or a ChatGPT thing in a minute and say, "Look, I have this data set, help me analyze it," or upload something to it and say, "Help me analyze it." Otherwise, I'm going to be using things, and I'll give you an example, additional technology. If I'm using, and I don't want to brand anybody, but I'm using SurveyMonkey to do research, collect data internally. Remember, I'm a scientist when it comes to people analytic. I'm analyzing the data related to the human capital infrastructure, so I'm going to collect data through five different methods, interviews, focus groups, observations, stored data or surveys. So let's say I put out a survey to the employee population and it's 10 questions and I have a thousand employees and 30% of them responding.
10 questions, 3 of the questions are quantitative. On a scale of one to five measure this is. This is what a one means, this is what a five means, give me a measurement. I can do mid, means medians and modes and standard deviations of those numbers to come up with a model, but that's descriptive. I don't know why something occurred, but now those same 300 people, question number two was, "Tell me why you ranked that thing that way." So now I have all of these open-ended answers and it's 300 people. How am I going to analyze that?
There are additional technologies out there like InVivo, there's Qualtrics, there's a multitude of things that a business BI, I think Google has an analytics tool out there to analyze quantitative and qualitative data. And the technology will say, "I read all 300 answers and these are the themes that I see." You still have to know the data, so I need to read it, but the system actually increased the analysis for me. I might be able to load that up to ChatGPT or Genie and say, "Here's 300 answers. What are the themes?" And it comes back and gives me an answer. So I would use technology, however, I'm the expert at the data I've collected, I'm reporting back to the executive team.
Wendy Fong:
Those are just your tools at hand, but not the end all, be all answer to your conclusion.
Milton Perkins:
Exactly. So I don't rely on ChatGPT for the... It's not something chiseled in a stone tablet sitting on the mountain with Moses by the burning bush. I'm not looking at any of these analytics like that. I'm going to present it and we're going to talk about it.
Wendy Fong:
I mean, back to the framework, when you've seen successful organizations carry out people analytics, what's the timeline that you've seen, quarterly, monthly, yearly? How often should an organization do these type of business case [inaudible 00:35:05]-
Milton Perkins:
To do the reports?
Wendy Fong:
... or do the reports?
Milton Perkins:
No, I would do the reports if you can set them up. If you have a system, so remember on my analytics team, it's going to be multiple people on it because I need their perspective, so I'm going to have somebody from IT who can data map. I'm going to come up with a formula to measure this thing, and that formula is A plus B plus C. I'm going to ask my IT person, "Where's A stored in our enterprise?" He's going to be like, "It's in the finance system." "Where is B?" "It's in the HRIS." "Where is C?" "It's in the ops' system." How often can we pull that data into this, for lack of a better term, Excel spreadsheet? They say we can do it at the close of business every day, or we only go out and fish for that data weekly. So to answer your question, how often do we report?
It depends on your enterprise and the technological savviness of your organization. On the other hand, I may be big enough that I have an HRIS system, an ATS system, a finance system, and it's my ERP. Everything is connected, and embedded in that technology are ad hoc reports. Or as I'm onboarding that technology, I can speak with my vendor, my partner and say, "We need to customize some of these things," and then the data might be ad hoc. I can pull that report right now and pull it 10 minutes from now and it's active and it's live, so I can pull reports at any moment. It just depends on the organization. Whenever you do strategic planning, which you should be doing every year, that's when I will revisit my entire people analytics infrastructure. Because strategic planning looks like this.
The company goes through a process to say, "We are at point A, we're going to point B, here are our objectives, here are our goals. We're going to do some things organically. We're going to do some things through acquisition. We're going to grow the company and get to point B, and then here are the KPIs that are going to prove success in our journey." That plan is handed over to every function in the company, Ops, Marketing, HR, whatever. So HR now does an HR plan to say, "We need to say what body of people do we need to get the company to point B? What do we have? What's the gap? What do we need to do for talent acquisition, learning and development? Do we bill, borrow or buy talent? Are we going to contract people? And when we do these things and design these things, how do we prove success back to what the company said was the goals?"
So now I need to have all of these reports at minimum and directly to your question, how often do I revamp to get to this point of things I'm describing? It's going to take a while. If you are starting with a whiteboard, do not expect that you're going to have a people analytics tool next year that is the most robust. What I tell people is, "How long did it take till you get to here? Nowhere land. You are trying to address things right now, take a baby step. A baby step is still a step. How excited were you when your kid took your first step? How excited do you think your parents were when you took your first step? Take a baby step." So now once you start doing these baby steps towards a very robust, descriptive, diagnostic, prescriptive and predictive tool, then every time you do strategic planning annually, you need to revisit that tool to see if it's measuring the human capital infrastructure in all of the areas of HR correlate it back to the KPIs of the companies.
If you can do it, there's some variables you cannot just correlate back. You may run into it and you're like, "Well, that's measuring HR for HR's sake, but it's not correlated." Also, just as a reminder, there's a difference between correlation and causation because somebody may say, "Our turnover is causing us to lose money." No, your turnover is correlated to losing money. The cause of your company failing is not just turnover. To do causation, you have to do case studies, control studies. To do correlation, that's a statistical mathematical equation. If you look up Pearson correlation coefficient, you're going to see this fancy formula out there that may confuse the average HR practitioner to stand on the curb and jump because it looks like a pretty complex formula, but nonetheless, somebody on the analytics team can do that analysis. That was a long answer to a short question, how often should we revisit at minimum annually when you do strategic planning?
Wendy Fong:
I mean, that makes sense because you want to align those reports and the data you're pulling to the annual strategic goals-
Milton Perkins:
For sure.
Wendy Fong:
... and to invest your time in setting up those reports is where you invest most of your time, and also once those are streamlined and ready to go and ready to pull whenever you want to, then the other piece of it is analyzing the data.
Milton Perkins:
And know this, the data is the data. Unless your formula is wrong or you're pulling data that is biased or skewed... By the way, when you analyze data, your personal biases kick in, I'm thinking something and then my confirmation bias may kick in where I'm looking for data to support what I think. Don't do that. Be aware of the biases that you have and let the data tell you what the is is. So when I'm looking at this data, at least from an HR practitioner perspective, I can't rush to judgment and the data has to be accurate, and correlated and all of those things. It is a cognitive paradigm shift for HR practitioners and it feeds to our credibility as a profession where we're going to have our colleagues now give us more respect because we're measuring things like they're measuring things and we're telling a compelling story with data.
So our credibility goes up, our ability to influence decision goes up, everything dealing with our profession goes up. Here's the thing though, and I'm looking at HR people. We need to up our game. We need to stop talking about anecdotal things and have evidence to support everything out of your mouth or don't talk about it. It's just a nice to have. Analytics increases our value proposition back to the organization. Now, a meeting cannot start, especially if you think about this, on average, 70% of organizations' operational cost is dealing with human capital. It's not the machines. It's the investment in the human capital infrastructure. Comp and benefits, learning and development, turn all of the things dealing with humans, that's where the money is going, 70%. So now as an HR practitioner, I need to go back and say, "You know what? I have a way for us to decrease that a little bit and add some money back to the budget, and we can take that money." And if I'm not-for-profit, I can take that money and go save more whales because that's our mission.
If I am a government agency, I can take that money and better serve my constituents, and if I'm for-profit, I can take that money and put it in my pocket, give some money back to my employees, higher merit increases, all kinds of things I can do with that increased money back to the coffers versus it's just expenses. HR though, our practitioners, your listeners, my people, we need to have a cognitive paradigm shift in order to create this value back to the organization with evidence versus saying, "I'm important," prove it. Prove you're important. "Here are the numbers. This is what I designed. This is how I contributed."
Wendy Fong:
I mean, that's huge. 70% is spent on human capital, and it makes sense too. I mean, to get started with people analytics, you mentioned taking classes. There's tools and technology at hand, but you also mentioned the biases and being aware of the biases you have. What resources are available for HR and their team to make sure that they're aware of those?
Milton Perkins:
Oh, I know of, because I've added to the content, SHRM has two classes. The biases are outlined in the People Analytics class that SHRM offers, also the Inclusive Workplace Culture class, which is basically a diversity, equity and inclusion class that SHRM offers, the biases are there. If somebody wants to email me, I think you put my profile in. I can send people, I mean, obviously I'm not talking to them about it. I can just send them a model of how many biases humans have and then how many show up in the workplace, so they have to then figure out what to do with that. Based on research, I think it's a National Institute of Health, humans, which is what I deal with all day, we have embedded within our psyche, our consciousness and our unconsciousness, about 160 biases. About 20 of those show up in the workplace constantly, and about 90% of our biases are unconscious.
We just behaviorally manifest it, but we don't even know we have it. It may manifest with a frown, a biting of a lip, leaning back in my chair, crossing my arms. I don't know it's showing up, I just did it unconsciously, but the biases show up. So there's a lot of research about bias that will probably bore the average bear. But if you are in Human Resources, my challenge to my colleagues in this profession, you are the human expert, so you have to pull out your old Psychology books, your old Sociology books. You have to be an axiologist. You have to be all the ologists dealing with humans, not an expert, but at least be aware of it, and be a social scientist. "What makes people move?" You need to be curious. "Why is that person doing that? What can I do to help that person do that more or do that less?" And then you design, implement, improve with analytics, that way you came with works to the organization.
Wendy Fong:
Yeah, I think that's a key word that you used, curious. Curious in the data and also curious in the human experience itself.
Milton Perkins:
Yes. If I'm in HR, I must be interested in humans, and not like a nurse or a school teacher where, "I really want to help people," go be a florist, go sell chocolate or something. But if you're trying to come up with innovative organizational outcomes through people, then you have to be a social scientist. How can I make people come to me, stay, be highly engaged, be productive, and when they leave, I mitigate the risk of them complaining about me in social media or with a government agency. I want them to leave with love and be able to say, "Hey, if you need somebody, Dr. P, I'm out of here. I'm getting ready to go fishing and play golf for the rest of my time on this side of the dirt, but if you need something, you can always call me." That's how I want people to leave the organization, as a friend that is always supported.
In fact, I designed employee alumni programs, and then I measured the success of that correlated back to talent acquisition. How many people are you getting from your alumni employee program compared to you branding something and it costs you on any social media employment site? You name them. It costs me to put ads out there. What's the acquisition cost? I think SHRM research shows the average acquisition cost for a human is about $4,500, and it depends on where you fall on the food chain. That's the average, which means there's a number that's higher and a number that's lower because the average is right, the average of all of that. 4,500 bucks is about the average to acquire talent. If I have an employee referral program that I manage and an employee alumni program, I can design that and then measure the success back to the acquisition costs.
Wendy Fong:
And we spend so much time at work. I mean, our work and home life is really just an integration, especially with technology, we're always on. And reading in the news, I see higher increases of burnout and depression, and mental health that we need to be aware of also in the workplace. It's so important what you mentioned, Dr. P, that work should be a place where someone has that social and psychological security and feel safe, and enjoy and love their job. Who doesn't want to come to work and love their job every day and wake up in the morning and be excited to be there?
Milton Perkins:
That's the tagline for SHRM, better workplace for a better world.
Wendy Fong:
It is.
Milton Perkins:
And this is what I tell my HR practitioners and anybody, because I speak to business audiences and groups around the world, literally. I tell people to think about this. There's 168 hours in a week, seven times 24. We generally sleep one third of that away. One third of your life is slept away, so of the two thirds that are left, you spend a substantial amount of time preparing. I'm taking a shower, I'm cooking, I'm not eating. I'm cooking, I'm traveling. I'm doing all these things, and I spend a substantial amount of time, especially in 2023 and beyond and 2024 and beyond, I'm spending a lot of time in cyberspace, flicking through Instagram, Facebook, Tok, Bing, this, dating sites, wherever I go in cyberspace, I'm there. So the rest of my conscious time, which is very minimal, I spend the majority of that, a huge majority of my conscious time in the workplace.
Think about this, when you transition from this side of the grass to wherever the great beyond takes you, on your headstone there's going to be a start date and an end date, your name, and somebody's going to put some nice epitaph, "Wendy was a beautiful person," and then there's a dash between the start date and the end date. That dash is representative of your entire life. So if you've spent the majority of your life sitting in this workplace, I challenge every HR practitioner to design a workplace where people want to be there versus have to be there. They're not there because of a paycheck and I have to pay my bills. They are there because they want to be there. Before we started the podcast, you're like, "Man, you work a lot."
I'm like, "I don't work at all. I do HR stuff, and it is as enjoyable as reading the best fiction book on the planet. I am in love with this body of work, so I don't consider it work. I do me, and then I get the rewards of doing me seven days a week. It's a beautiful world. Don't have a job, will never retire." So now HR, we need to design things through the lenses we started with. How do we tap somebody on the shoulder and say, "Hey, can I talk to you about a job?" And from that point till the time that they leave your organization, it was the most beautiful experience in the world and I can prove it through analytics. I designed these things and I can prove it through analytics. At minimum, I can do an employee engagement survey and say, "What does it feel like to work here?"
They're like, "Could you imagine me taking a survey?" And my qualitative comments like, "This is being in heaven on earth," and then everybody is saying that. You know and you have proof what you have designed is actually going to make that organization get to a better place faster. I can correlate that engagement to client satisfaction scores through a mathematical equation. Every time the engagement scores of an employee goes up, watch the engagement scores or satisfaction scores of a client. That by the way, through a body of research called Service Profit Chain. If employee engagement goes up, client satisfaction goes up. If client satisfaction goes up, clients spend, retention, referrals, and everything goes up for the client. Turnover goes down. The workplace becomes a nirvana. I get excited about this. Why not design a place where people say on Monday morning, "I cannot wait to get to my office," instead of, "Oh my, I don't feel like it today," and I have proof. I have proof, I can do analytic proof to prove that what I designed is working.
Wendy Fong:
Yeah. I love the real talk. Let's have this real conversation about all the conscious time that you mentioned is mostly spent in the workplace, and I feel like your message, Dr. P is enough to ignite all HR practitioners out there. We are there to make better workplaces and a better world for everyone, and that should be motivation enough to want to do more people analytics and want to better serve our community within the workplace and everyone it impacts.
Milton Perkins:
Most people I know, SHRM has it on a lot of its literature, better workplace for a better world. Most people don't. I'm selfish about that. If I create a workplace where Wendy is working all day and it's a beautiful place, when I bump into Wendy at the local grocery store, Wendy is smiling and then we're going to have a legacy experience together. What does that mean? Our interactions are going to make each of us go home and write in our respective diaries, "I met the most wonderful person today and she made me smile and literally changed my life with a nugget of wisdom." Conversely, if I don't think about it deliberately with conscious thought and with intent to design a better workplace with analytics to measure whether or not it's better, then when I bump into Wendy, Wendy becomes the worst person I met today.
My basket is in the way from her reaching for a bottle, a bag of Coco Pops on the shelf, and instead of her saying, "Excuse me," she's dropping F-bombs and expletives, "Would you get out of the F-ing way?" And I'm like, "Really? Whoa." So better workplace to me equals better world. If people have a wonderful experience in the workplace, I'm not measuring the better world part because I'm measuring the human experience in the workplace correlated to business KPIs, but selfishly, I want to run into the person who had a beautiful experience all day. When you get home and you see a McDonald's bag on the curb, you're going to stop and pick it up. If you see the elderly citizen walking across the street, you're going to stop block cars and help them across. Why? Because your day has been phenomenal.
Wendy Fong:
I hope no one ever sees that negative side of Wendy.
Milton Perkins:
Yes. No, I don't think you have. I hope you don't have the persona to ever do that. And I always tell people they don't know what it means when I tell them goodbye, I say, "Have a legacy life. Have a legacy week. Have a legacy day." They're like, "What is that?" And then I explained it to them. Have one of those days where you change somebody's life and they write about you in their diary for good reason, not some Unabomber reason, for a good reason.
Wendy Fong:
Yeah, absolutely. I did want to ask, I mean, where do you see the future of people analytics going?
Milton Perkins:
Yeah. I think AI is going to be the future. Once that concept and that technology is perfected, I think people will be able to embed that technology to analyze close source data, data in my workplace, quickly, and that we can make evidence-based decision-making. I think people analytics as a body of knowledge, I can only guess at this, 10 years from now, we're not going to be having this conversation because the business acumen of the average HR practitioner, I think there's going to be more MBAs coming into HR, more CEOs coming out of HR because people are going to understand the value of humans in quantitative and qualitative ways, so they're going to really focus on it. I think the future is this conversation will be for naught. It's just going to be a part of our profession. Our business acumen will kick up. You're going to have people knowing what Pearson correlation coefficients is, and it's just going to be second nature to us at some point.
Similar to that, I always say, "Here's my prediction. Maybe not in my lifetime, I'm a boomer and at some point I have to transition, exit door left." But I think at some point, the diversity, equity, inclusion, accessibility, civility, belonging conversation will disappear as well. The generation Z, the younger generation Ys, the millennials and the Zs already get it. They're not holding onto your affinity group characteristic and holding it against you. I think people are starting to realize the more we have these weird experiences in the world, the more we're starting to love on each other. I'm throwing that into the universe. So I think analytics is just going to be second nature to the profession, and I'm going to be hopeful that SHRM will continue to push that envelope.
Johnny Taylor, the president and CEO, changed the culture of SHRM when he came in from Thurgood Marshall. And everything after his arrival became different, so hopefully that SHRM will push the envelope on next practice solutions for our profession, and that will include really understanding analytics. So not only People Analytics class 101, which is being offered, but 102, 103, 401, and then SHRM will offer some sort of a thing where you can get a Master's degree in People Analytics through the website. It becomes an accredited university, the SHRM University, and you get your HR degree there. I don't know if that's going to happen in my lifetime, but let's go SHRM.
Wendy Fong:
We'll see. Well in March, we are offering for the first time ever, AI+HI, so Artificial Intelligence plus Human Intelligence, Human Integrity Conference Project in March.
Milton Perkins:
That's great.
Wendy Fong:
So look out for that.
Milton Perkins:
Yep, that's beautiful.
Wendy Fong:
So in closing, Dr. P, is there anything that you want to mention that we haven't discussed yet?
Milton Perkins:
Not that I'm not discussed. I mean, my keep nudging my fellow practitioners, up your game. Look at the SHRM competency model, the BASK, Body of Applied Skills and Knowledge and the competency surrounding that and up your game. If you as an HR practitioner are not cut out to be in the business of humans, then get a different profession. If you came in saying, "I really want to just hug people and help people," and this profession has evolved to being more about the business of humans and you're not feeling it anymore, find a different profession, be a florist. This profession is about the business through people coming up with innovative business outcomes no matter what your organization is through the human capital infrastructure, and HR practitioners, we are in charge of that through those lenses, and we have to prove the value. If it's not measured, it doesn't matter. So I will end on those words and wish everybody that's listening a legacy existence. Have one of those experience where somebody's going to write about you in their diary for good reason. Lend your smile, lend your spirit.
Wendy Fong:
Oh, I really enjoyed our conversation, Dr. P, and sharing your knowledge and feeling inspired and motivated in the HR profession. There's just a lot of potential out there and a lot of good that we could do in this world. So lastly, how can our listeners find and connect with you?
Milton Perkins:
Mperkins@ainone.com, or hook up on me on LinkedIn. Normally people will send me a message on LinkedIn. It's Milton J. Perkins. Just make sure you get the right one. Dr. Perkins is the profile. You'll see my name. Just make sure you're looking at the right person online. Milton J. Perkins and all the initials PhD in HR, not some other dude who happens to own a graveyard in Ohio somewhere. And if you chat with me online LinkedIn messaging, I will probably give you my email address again and tell you email me, and I'm not afraid or I'm open to connecting with people in real time. So I'll tell the person, "Hey, if you email me, here's some dates I'm available. It might be on a Saturday. If you want to noodle for about 45 minutes an hour, let's connect," and then we'll take it from there. So mperkins@ainone.com or hook up with me on LinkedIn.
Wendy Fong:
Great. And we'll keep an eye out for your book. I know you're releasing a book later this year called Scratching the Darn Scars of Diversity.
Milton Perkins:
Yes. And it's an intentionally inclusive framework because historically we have been unintentionally not by design, some people by intent, but the majority of us have been unintentionally inclusive of who's in the workplace. This book tells you how to be intentionally inclusive so that no one is left out. So I give a different framework and I talk about all of the affinity groups, what do they want, how do you deal with them? It's going to be an exciting book, and it's going to hopefully be the movie, Scratching the Darn Scars the movie at a theater, and you're going to have somebody, some big name... It's going to be like the Godfather series. It's going to be huge.
Wendy Fong:
We'll keep an eye out. I'm going to look for the trailer when it comes out.
Milton Perkins:
Exactly.
Wendy Fong:
Well, thank you so much, and thank you everyone, listeners for listening. If you haven't already, please subscribe so you'll never miss an episode. And be sure to rate and review the show wherever you listen to podcasts. As we mentioned at the top of the episode, this episode is eligible for a one, SHRM-PDC toward your SHRM-CP and SHRM-SCP recertification. After you finish listening, enter this activity ID into your SHRM certification portal, 24-2XCZK. That's 24-, the number two, X as in X-ray, C as in cat, Z as in zebra, and K as in kite. 24-2XCZK. This activity ID expires January 22nd, 2025. If you want to learn more about the Honest HR Podcast or other SHRM podcast, just check out shrm.org/podcast. So until next time, be kind. And as Dr. P would say, "Up your game, up your legacy," and take care everyone.