HR Policies for AI with Bill Pierce

How do we navigate the complexities of workforce management in the era of artificial intelligence?

Today's discussion sheds light on the intricacies of HR policies as they adapt to the technological advancements in AI.

I’m joined by Bill Pierce, Chief Information Officer at BioIVT, a visionary in leveraging technology to enhance business processes. In our conversation, we delve into the essentials of AI management, from ensuring the quality of data to implementing robust platforms for AI deployment. 

We also address the vital role of HR policies in nurturing employee engagement, retention, and the alignment of talent development with business needs. 

Bill's insights draw from a wealth of experience and a fundamental understanding of optimizing AI within the human-centric framework of modern enterprises.

This episode offers invaluable perspectives for leaders seeking to foster innovative, tech-savvy, and employee-focused work environments. Tune in now!

Specifically, this episode highlights the following themes:

• The role of foundational data quality and platform robustness in ensuring AI project success
• Strategies for enhancing employee experience and retention during times of talent shortage
• The intertwining of cybersecurity, ethics, and trust in the deployment of AI within HR practices

Links from this episode:

• Get to know more about Bill Pierce: https://www.linkedin.com/in/technologyleader1
• Learn more about BioIVT: https://bioivt.com

Transcript

Bill Pierce [00:00:00]:
I would say the foundations need to be very clear in AI. And there's two key areas. One starts with data. The data is the gasoline for any artificial intelligence. So if you don't have good gasoline, you're not going very far. The second is, I think the MeToo movement, which is people don't really think about the platform of which they're running their AI on. So what do I mean by that? That is, have you really thought through the design patterns? Are you going to have restful APIs? Is it an open architecture? If it is an open architecture, how are you protecting your ip? How are you protecting your data?

Steve Swan [00:00:35]:
Welcome to Biotech Bytes, where we speak with it leaders within the biotechnology industry about their thoughts and feelings on different technical trends affecting our industry today. I'm your host, Steve Swan, and today I have the pleasure of being joined by Bill Pierce from Bioibt. Bill, welcome. Thank you.

Bill Pierce [00:00:51]:
Thanks, Steve, for good afternoon.

Steve Swan [00:00:54]:
So, you know, as I go through a lot of these conversations with some of your peers, some of the other leaders in our industry, and inevitably, like I said, we talk about the technology trends and things going on in our industry. I just like knocking it off first. Everybody wants to talk about AI, right? And it's the big one. It's out there, it's coming, it's going to help us. We're learning how to walk. We're still crawling. But tell me about your thoughts and feelings on AI and where we are and how it's going to help us or maybe how it's affecting you and your business.

Bill Pierce [00:01:26]:
Sure. The promise is huge. I think it feels a lot like a lot of the hype cycles we've had in the past. Whether the Internet error, the.com boom, the Internet of things, SAS pass is big data. We've all gone through a lot of these hype cycles. What's interesting, we all think of Amazon as wildly successful. And I was with a startup company that was funded by the same company that Amazon was funded by and eBay was brought out by. So I was part of that.com and some people made it, some people didn't.

Bill Pierce [00:02:00]:
I think the AI cycle, hype cycle is going to go through the same learning curve. Let me share one statistic with you that really stands out with me that I heard 70% to 75% of all AI projects will fail.

Steve Swan [00:02:16]:
Whoo. Really?

Bill Pierce [00:02:19]:
Yes. Wow.

Steve Swan [00:02:22]:
Okay. I know what I've been hearing in my conversations. What would you attribute that to? I have my guesses, but you're the pro.

Bill Pierce [00:02:32]:
I don't know that I have the answer there. I went through all my successes versus losses. I've had eleven pretty good successes and then three misses that were pretty significant misses. And if my patterns hold true, I would say the foundations need to be very clear in AI. And what do I mean by that? There's two key areas. One starts with data, right? The data is the gasoline for any artificial intelligence. So if you're going to do any kind of machine learning or anything else, if you don't have good gasoline, you're not going very far. Okay, so what do I mean by that? Do you have good clean data? If you have a lot of data that has missing data, null data, you don't know where that data comes from.

Bill Pierce [00:03:16]:
You're munging and merging data, and it's low quality, the results are going to shell.

Steve Swan [00:03:20]:
Right?

Bill Pierce [00:03:21]:
You can still use it, but as we've seen in some of these AI initiatives, the results don't quite come out the way you expect them to. The second is, I think the metoo movement, which is people don't really think about the platform of which they're running their AI on. So yeah, we might have some knowledge graphs in the company, or we might have some other technology that we've done, or we might even have good ontology and taxonomy investments, but we don't really think about the platform of which we're running AI on. And what do I mean by that? That is, have you really thought through the design patterns? Are you going to have restful APIs? Is it an open architecture? If it is an open architecture, how are you protecting your ip? How are you protecting your data? Have you thought about the cybersecurity component? So again, it, people can go down a rabit hole on that one, but it's still that plumbing is necessary, because if you don't figure that out cleanly, the project will eventually come to a screeching halt. And one of my big failures, the attorneys got involved and said, this can't go any further because of the data exposure, the IP exposure that they saw in that. From a technical perspective, it was successful potentially, but from a business perspective, the risk it put on IP, the attorneys had to come in and put a stop to it.

Steve Swan [00:04:38]:
Well, so I'm just going to do some quick math here. You're eleven for 14. That's an 800 batting average.

Bill Pierce [00:04:44]:
Yes.

Steve Swan [00:04:45]:
And you say on average these things are successful 30% of the time. So 300 batting average. So you're more than doubling that. I'm giving you a standing o on that one.

Bill Pierce [00:04:55]:
I think that's pretty good. I made a list of them. I actually wrote them out, and a lot of them are very focused initiatives. So patient sentiment analysis, image detection analysis for oncology, case reporting, form analysis, some pattern identification for safety and risk in clinical trials, biomarker detection. So they were very focused. Right. I had somebody describe it to this to me, and I use this now. At first, I kind of had a negative reaction to it, but actually it's a positive way of thinking about how to get your toe in the water.

Bill Pierce [00:05:32]:
And that is, he said, go an inch wide and a mile deep. So what does that mean? That means when we were doing the patient sentiment analysis, rather than doing everything about the patient, which has thousands and thousands of data elements and petabytes and petabytes of data, we were really focused on what is the sentiment, and what are those keywords and data that go together in the pattern detection to determine what sentiment is good and what sentiment is bad. And so that narrowness. But going so deep to say what in a phrase makes it good sentiment, what in a phrase makes it bad sentiment. And then to do the language learning models, to pick that out and say, you know what? They just uploaded their patient information, and their diary says that this is making them feel horrible. Their sentiment about it is it's a really bad interaction. Right. And so it's an inch wide, mile deep, and that allows the machine learning and models to really do their job, and it actually makes it much easier for you to tune them.

Bill Pierce [00:06:33]:
Tuning is, I think, the key. You're never going to come out of the gate clean. So the ability to run the analysis, react to the data, come back and change those business rules and make it give you a more clean answer, because, again, it's like a human being almost. It has to learn the ability to.

Steve Swan [00:06:52]:
Right. You got to keep tuning it, right?

Bill Pierce [00:06:54]:
That's right. And so I think that's. I had the grace of God of being in an industry, right. The life sciences industry is pretty progressive, and AI is pretty pervasive. Already in the industry, I had the grace of God of being in an industry that has done pretty good with artificial intelligence and modeling as a whole, from preclinical research and computational biolytical analysis all the way to, as I said, commercial sequencing of how to take your drug to market and sequence the countries properly to maximize the financial benefits of that research.

Steve Swan [00:07:28]:
Yeah. Like you said earlier, you started hitting on it a little bit there. The data, right. The data is the gasoline for the engine. And I told you I had my guess as to why 70% of those are failing. That's just my guess. That's what I'm hearing from a lot of the folks that I'm talking. They're saying, hey, listen, if we don't have the data, we can't.

Steve Swan [00:07:47]:
Like you said, fuel the motor, right? It's bad data. You're going to get bad results. And you could try and tune it, but you're tuning it with. Try and tune a motor with bad gas, you can't.

Bill Pierce [00:07:58]:
The beauty is, if we say we're going to tackle this area forecasting or this operational excellence or whatever the problem is, that you can narrow that again, that inch wide, mile deep, I think you make it very actionable. I have my biases on which AI platforms to use. There's a battle of them out there. You can hear some of the larger technology giants talking about their version versus the other version. I think you really have to be, as a CIO CTO, be very explicit with where you're making your bet. It doesn't mean you can't change your bet, but be very explicit where you're making your bet, because that will actually influence the design and the design will influence the outcome of, again, once you got the data problem solved, the platform of which produces the outcome.

Steve Swan [00:08:46]:
I want to go on to kind of like the, we've seen a push right from the business side, and you early on said hype. Use the word hype. Right. There's been a lot of hype. Do you think that it's, I want to almost say warranted? I mean, we don't know yet. We haven't gotten there. But in our industry, I do think based on where we are and where we need to go, that it is really going to help us and save us a lot of time and a lot of money. It's just I don't think we've seen that to the bottom line yet.

Steve Swan [00:09:16]:
Right. So I think that some of these leaders are rightfully pushing for it right at this time. But I just don't think we're quite there and ready to do it. But I think, like we talked about early on, got to learn how to walk before we run.

Bill Pierce [00:09:32]:
I think it depends on how religious you are about the definition of AI. Just give me a little bit of leeway here, because a lot of people take exception to this description. But if you look at the digital twin. So one of the things that I considered a success is having done a digital twin experiment, because AI blurs the line between physical and digital, right? So if you think about an experiment, a wet bench experiment. You've got all the laboratory equipment and chemicals and processes and all that. Well, when you get it digitized now, you can run through that experiment and start changing the data and change your hypothesis just to explore what the quality of that experiment looks like, what the outcomes of that experiment look like, and then start changing it. And that's much more adaptive and much faster than if you did it physically. The city of London has a digital twin of the city of London, okay? It allows them to explore the traffic patterns and when they make a change, what the impact will be before they do it physically and cause chaos right throughout the city.

Bill Pierce [00:10:35]:
Tesla has a digital twin of the Tesla car. It allows them to test everything digitally before they even remotely change it on the vehicle itself. So if you consider those AI wins. I do. I think they were for very specific outcomes, and the model was, again, an inch wide, mild, deep. Some of the successes I had in patient screening actually had. So we were on a gastro study, and we were able to include a whole larger population. 70% of clinical trials are under enroll.

Bill Pierce [00:11:05]:
If you under enroll, you may not get enough data. If you don't get enough data, you don't file to the regulatory authorities. If you don't file, you don't ever make it to market. Right? So there's a definite business correlation to AI today. We see it a lot in robotics and other things. Image detection, early disease, retinal scanning for image detection and early disease detection. It's there. It's working today.

Bill Pierce [00:11:30]:
And you can go into the doctor's office day, and they can look at your eyes, and they'll see disease before it actually manifests itself deeper into the rest of your body.

Steve Swan [00:11:38]:
Right?

Bill Pierce [00:11:39]:
These things exist today. Right. Now, we have to take those small wins, Steven, and figure out how do we turn those into the big wins, right, and really scale them.

Steve Swan [00:11:49]:
Here's the big one, though, right? And you and I, we've touched on this in the past when we've spoken the security around, you know, the proprietary knowledge of a lot of the things that we're doing in our industry and the FDA, right? So we have all that that we have are the, I don't know, the shortcomings, the pitfalls, the things we need to think about as we get closer and closer to reality with this thing.

Bill Pierce [00:12:17]:
I treat it no differently than I treat the security of the rest of my key business data, right? So intellectual property, customer data, patient data, whatever it happens to be, right. There's a lot of sensitivity and a lot of compliance you have to do, whether it's HipaA, PCI, Sarbanes Oxley. We can go through the list of 100 things that every business has to comply with nowadays. I think there's a couple of dimensions. One I think of, can they see it? So if they can't see the data, you didn't expose anything, then you're very safe in that model.

Steve Swan [00:12:51]:
Right.

Bill Pierce [00:12:51]:
So when we think about colonial pipeline, what happened? They saw those servers and the old technology out there, and they used that to penetrate the company. If we think about some of the other big breaches, solar winds, right. They saw an avenue to expose a network, got on that network, and then did real damage. And so if you can prevent step one, people will be able to see it, then they can't access it. You kind of solved a big problem. The second is knowing where the data goes.

Steve Swan [00:13:23]:
Right?

Bill Pierce [00:13:24]:
So we talked about, are you data ready? Once you have that data, that ontology and taxonomy, you can absolutely put classification of sensitive data on top of it, and then put data loss prevention on top of that. So what does that mean? That means if I decide that this nine digit number is very sensitive and it could be a Social Security number, I can put that marking on that data. Then when we go to expose it anywhere, I can either alert on it or turn it on or off and say, yes, that's allowed, or no, it's not allowed. So I really feel like the technology, Steven, is there for cybersecurity. It's the simplicity and ease of which the platform decisions you've made as a business support AI, and that's part of, again, is your infrastructure, is your design patterns AI ready? If you don't have data loss prevention in your company today, I don't personally think you're AI ready, because it's going to mine your data. You're going to open up a database or data source on purpose or by accident, and then you're going to do exactly what that attorney was worried about for me in Europe, which is expose IP, and it's already happened. You can go out there and look, it's already been exposed. You can find cases on the Internet today where people have exposed IP.

Steve Swan [00:14:42]:
I had one CIO say he was doing work with somebody on AI, and they saw some information come up, proprietary information from another biotech. They did some screenshots, got it off to the CIO and said, hey, you might want to check this out.

Bill Pierce [00:14:56]:
Some of your data is going to dispose. If he had data loss or she had data loss prevention, that wouldn't have occurred.

Steve Swan [00:15:03]:
Right.

Bill Pierce [00:15:03]:
It would have stopped it before it occurred. Right. So you got to go through the foundational pain of putting the data classification in data governance, data stewardship. Again, sorry for all that heavy lifting. It's a necessity. And then once you have that, you have the right zero trust or network patterns to prevent people from being able to see it. You didn't expose it by accident. Then when you expose it on purpose, is it going to where it says it is? So I'll give you an example, something very simple, but it's very difficult to do.

Bill Pierce [00:15:32]:
Again, I make sure I address it in my design pattern. Can you screenshot it? You and I are talking today. I could be sharing something with you, right? I could be sharing and you can screenshot it. Now that data is out there in the wild west, and my ip goes. So AI is no different than transacting in any kind of business transaction. I basically say if the business and technology leaders are doing what they should do and putting critical thinking skills into it, they'll address it.

Steve Swan [00:16:03]:
Right. And almost with the zero trust, right, I go visually, right. It's almost like putting locks in a canal. Right. You're only getting this far and then that's it. And then you get that kind of.

Bill Pierce [00:16:17]:
Exactly, yeah. I had a hard time. It's been around since the 1990s, by the way, a lot of people think serverless is new. It's been around, it's a design pattern in technology. It's been around a long time. And I try to explain it this way. In the physical infrastructure world of firewalls, routers, switches, gateways, all that stuff, basically, once you had the keys to the kingdom, you were on the network. You could go numerous places, right? So you could up with the front door and go all the way throughout the house, right.

Bill Pierce [00:16:45]:
You could go upstairs, downstairs, around, and maybe to places you don't even belong and hope that that door, when you're trying to open it, doesn't open. Zero trust is you open the front door and bill only gave you access to a closet, so you only get to see the closet. You don't know what else is there. And that's really when you think about exposing APIs or exposing data, you really need to be very tightly controlled because we've seen more API and data breaches happening as companies get more and more global. So guess what? The problem is only getting harder. It's not getting easier. You really have to lay the foundation, Stephen, again, I had that failure where the attorney said stop, right. That's a failure.

Bill Pierce [00:17:27]:
That's an honestly good failure because we did not think, hey, part of the data that we're using here is very important to this company. And yeah, there's business value to it, but the attorney is going to say risk is not allowed.

Steve Swan [00:17:39]:
Right.

Bill Pierce [00:17:39]:
You can't go forward.

Steve Swan [00:17:40]:
Right. The risk reward is not there. Right.

Bill Pierce [00:17:43]:
Everything's a business decision. Right. So understanding, what's the primary focus? What's the business model focus you're trying to do with AI? And then how do you then put the foundations in place and then how do you deliver on that program?

Steve Swan [00:17:57]:
Sure. If you're not thinking about the business, what are you doing? Right.

Bill Pierce [00:18:00]:
Again, I think hype cycle. Think about this. Right.com. We saw it in Internet things. We've seen it in software as a service. We've seen it. There's a lot of. Me too.

Bill Pierce [00:18:10]:
Right. I just pile on and it's not well thought out and it fails. Right. And I guess the good news is it fails. Right. If it's a weak idea, a weak implementation, et cetera, it fails again, of which I've had failures. The failures teach you a lot. If you use the data and the information to do some critical thinking, you learn from it.

Steve Swan [00:18:32]:
Sure. Absolutely. Now, we hit AI there, right? We did a pretty good job on AI. If there's more you want to chat about on AI, let's go ahead and do that. But I was going to ask you.

Bill Pierce [00:18:44]:
Beyond AI, I have one other thing before we go there.

Steve Swan [00:18:48]:
Yeah, sure.

Bill Pierce [00:18:49]:
It kind of segues to the cybersecurity, where you saw that. I just told you, if you have a good foundation, if the leadership and cybersecurity is not an it thing.

Steve Swan [00:19:00]:
Right.

Bill Pierce [00:19:00]:
It really isn't. It's a business decision. Right. Because it's millions and millions of dollars of investment. But if you've got a good foundation, you've thought about that foundation, you can see it works for the business. And I kind of gave you that zero trust and DLP example. I think there's a fear factor of AI, which I personally think is unwarranted. And it starts with all the horror stories you hear.

Bill Pierce [00:19:25]:
I think you and I chat about this in the past, which is that company in the UK, that's a shipping company, that opened up a chat bot, and then the person didn't get the answer they wanted from the chat bot and they were angry and they managed to get that chat bot to tell an off color joke and get that chat bot to trash the company, which is horrible for your brand. Right. When you think about the customer experience and the branding, right? And we'll come back to that, because that's really, I think, where most companies need to think about. It scares people. They go, I'm never going to do a chat bot. Well, the chat bot was probably a good idea. The implementation was a horrible implementation. So I think they just need to look internally and say, what did we miss? I'll give them some ideas if they want it in a second.

Bill Pierce [00:20:12]:
But we also see, I went to a Harvard conference and one doctor gets up, we're talking about AI and healthcare, one doctor gets up and talks about how his AI initiative helped him find a biomarker he was unaware of. And then he was able to help these two children who were not walking, walk. So you're like, hallelujah, this is the best thing ever. Remember I told you there's real application of AI, real results? And that's one everybody feels good about, right? I mean, he should be so proud of himself. Actually, he wrote a book. And then the next doctor gets up and says, well, AI told me I'm dead. And everybody in the room bursts out laughing. But the fear factor there is such that, yeah, if it told him he's dead and he's the one using Chat GPT, which is, I think he was using, that's not good.

Bill Pierce [00:21:00]:
Right? But I'm going to right that the data Chat GPT had around him kind of led it to the fact that it thinks he's dead. There's probably a doctor similar to him, similar career, some patterns existed in data that it jumped to the conclusion that he's dead, even though it's a horrible conclusion. So what does that mean? I think it means you treat AI like you treat an employee. Why do I say that? It has bias. Right? AI has bias. We saw when Google got sued for having bias. Right? Guess what? Everybody has bias. Employees have bias.

Bill Pierce [00:21:37]:
So what do you do? You put HR policies and procedures in place that bias should not manifest itself, otherwise your employment's at risk. Data privacy and data security and IP protection. Yes. AI can expose of it, so can a human being. 75% of the risk in most companies is the human. The human, not the platforms that expose things. So again, it's like employee ethics. Oh, this is the number one thing I hear.

Bill Pierce [00:22:06]:
Now, with the risk of AI, it could have ethical. Absolutely it can. But guess what, you hire that superstar employee. How do you know they're not unethical and they're not going to lead the company down a garden path, right? And then finally bad decisions. Like, hey, you're dead, right? Yeah. Again, we could have any human being drive a bad decision and jump to a conclusion in a negative manner. So my suggestion to the broader community is stop running with fear and think about the policies and procedures and the testing and validation that you put around something before you let it go to the world. And again, my biggest failure, we almost let something go to the world that would have had a bad ramification, right.

Bill Pierce [00:22:49]:
In the example you gave where that IP was exposed. Unfortunately, there's a validation miss there that the team made, and they have to be honest about that. And then go revisit their testing platform and then make sure they address that testing issue, because not too many people share my opinion there, right. And I think it's just a very rational, data driven opinion.

Steve Swan [00:23:10]:
I think it is too. That's something to really discover. Yeah.

Bill Pierce [00:23:16]:
Most of the meetings I go to on AI, it's pure, oh, you can't do it, bad things are going to happen, right? And then I hear all the horror stories, like the chat bot telling an off color joke or the doctor hearing he's dead, or whatever it happens to be. I hear ethical stuff all the time. And we've seen it, right. With the political viewpoints that were shared in some of these chat bots and other items exposed on, guess what? Human beings made it. And the human beings are flawed. And how it was tested and managed and governed really determines whether it should have made it as far as it made it, right? And so it's not like the AI engine started having 62 algorithms interact randomly, and it all of a sudden became unethical, right? I think we get a lot of hype from our old movies with war games and some of these other movies where really bad things happen, and it just drives the human fear side of us. Well, fear is never a good reason to make a decision or not make a decision in business anyway, in anything, right?

Steve Swan [00:24:18]:
Unless you're running from something chasing you right now. So then applying HR policies. I'm just thinking through this. Can you put AI on a performance review and can you fire it?

Bill Pierce [00:24:30]:
I think you can validate. So if you have acceptable use policies, you should, in your validation process, go through that policy and say, this would be the standard we'd hold a person to. It's acting like a person, right? So if you have a chat bot, right, I'm going to do this big customer service initiative, and I want to have an omnichannel experience. And for people don't know what that means, just adding some technology in its simplest form. And also, I put this chat bot out there. Well, that's acting just like that chat bot that told the op color joke or trashed the company. I'm going to tell you, they didn't test it properly. They didn't put their own policies and procedures in the verification validation of that chat bot.

Bill Pierce [00:25:14]:
Otherwise, if they treated it like an extension of the client services customer services team, it wouldn't have made it out the door. Right. They would have caught that and turned that off. Okay, so it's really, I guess, an gross oversimplification. It's a validation process. You really got to think holistically. How do I validate this now? Can you get rid of bias? Probably not. Can you manage it? Well, yes, you can.

Bill Pierce [00:25:39]:
There's all kinds of mathematical techniques, Kasey and Bayesian, all kinds of sophisticated math of which Wall street makes a living off of tuning their models with all these KZ and bayesian mathematical techniques. Because guess what? Human beings don't do what you expect them to do. And so Wall street would go broke if they didn't have these highly adaptive, highly tunable models. Okay? They put all kinds of bias filtering, because what we find is when the bias goes too far in a direction, you go out of business pretty quick. And we saw that with one big Wall street firm in the past, haven't we? And so Wall street got very sensitive to it, and they put a lot of validation efforts into these models. I think we just got to follow their lead again. Maybe they're not the best example from an ethics perspective, but we could follow their lead from an outcomes perspective.

Steve Swan [00:26:31]:
I like that. I hadn't heard that angle before, and I think that's a new, fresh thought and approach to it and another way to, I guess, sort of wrap your arms around it and make sure that you're really integrating it and using it the way that it can and should be used. Right. For your corporation, for your company.

Bill Pierce [00:26:52]:
Right.

Steve Swan [00:26:53]:
Without stepping on anybody.

Bill Pierce [00:26:54]:
Final thing to consider, and there was a healthcare CEO out in the west coast, one of the largest healthcare providers out in the west coast, and he got up into a conference of all these healthcare companies, and he said, we're not a healthcare company anymore. We're a data company. And I thought, wow, as an it geek, right? Wow, that's very powerful that the CEO of a company would say that. And did he really mean, like, okay, they're going to be all coders and not have nurses and clinicians? No, he did not. But what he did mean is the healthy outcomes and a lot of the analytics that could be put together to drive better experience for the patient and drive precision medicine and better outcomes. That's what he's talking about, right? So he's really being patient focused and outcome focused. And I thought, that's absolutely brilliant. That's the way the CEO needs to think, and then he needs to run that boldly, which he was trying to do by going to a conference and restating who they are and how they work and how they will operate in the future.

Bill Pierce [00:27:56]:
That's not easily done. Right? Most business will keep that very close to the vest and very internal. I think that's pretty bold because that'll invite channel partners and people who can help them. So my other big thing, takeaway for me from my successes where it's not, there's over a thousand technology providers or so that I've looked at in the AI space in some form or fashion, and there's people who produce maps of this stuff. Steven and I constantly leveraged some of those partners. I would say, for anything you don't have, look for a partner who's already got it working. And yes, you might give up some revenue, yes, you might give up some capability, but it'll get your project out the door, and it'll get the learning in the company to develop the skill sets. And then you start saying, okay, I can give my team career opportunities to take stretch assignments or develop skills they've never had or would not naturally have.

Bill Pierce [00:28:55]:
And so you can run these, again, inch wide, mile deep projects very successfully with a partner. Right. My digital twin experiment I did with a company called Lifebit, I would recommend lifebit to anybody. Small UK company, very progressive, they know what they're doing. And so, could I have done that on my own with my internal expertise only? No, I could not. So, admitting that you have a partner, or you need a partner, and using the ecosystem to cover some of your gaps, I think is, again, one of those things that takes that 70% of chance of failure and brings it down 50, and then you address the platform, you get it down to 30, and then by the time you get, you got a 1020 percent chance of failure. That's a much better ratio than 75% chance of failure.

Steve Swan [00:29:39]:
Well, that's where you flew 20%.

Bill Pierce [00:29:43]:
By dumb luck. You made some decisions that played out in my favor.

Steve Swan [00:29:49]:
Yeah, that's good. So now how about other technologies within our sector? What other technologies do you see or that we should be thinking about that's going to affect our industry? In a good or bad way? I guess I never thought about the bad way. I just kind of threw that out there because it came to my mind. Right. But yeah. Anything else that we should be covering here?

Bill Pierce [00:30:08]:
I think the industry, like AI, right. AI is a reinvention of, it's been around a while and zero trust is a reinvention, I think, where you really see opportunities for convergence and reinvention. And so the biggest place I see converging now is what's called total experience platforms or capabilities. And what do I mean by that? That is kind of the intersection of the HR human centric side, which is talent management, talent development, talent champions, digital experience, internal with the external customer experience and digital experience platforms that face the business world, the customer world, and they're converging together. Okay. And why would you think, has anything come to mind, why would you think you want to connect the employee experience and the customer experience together? What comes to mind?

Steve Swan [00:31:05]:
For me, I would say the only thing that comes to mind is you have to let your customers know what's going on inside. You got to humanize it. Right? That's my opinion. Right. You're humanizing what's going on inside it. For the external person saying, hey, this is a real thing. This isn't just some abstract idea, this is a real thing. There's real people behind this.

Bill Pierce [00:31:27]:
And I think it's accenture, don't quote me on that, but I think Accenture did an analysis on this. They said they think there's 25% lift to most businesses if they do this. Right, what you just described there. Right. Which is how do I take the human centric side? What happened during the pandemic, talent shortage and talent leaving is now a much bigger issue than it ever has been in the past. And the US is millions of workers short, so that's not going away. So how do you keep and retain employees? We all know it's connecting them to something bigger, right? It's, yes, I can address the pay and people better be. This year in particular, we see a lot of pay changes.

Bill Pierce [00:32:09]:
Right. But people better dress the compensation, some of the basics. But really it's about keeping that employee is giving them the stretch assignments, investing in them to do AI and ML, giving them things that they might not absolutely be able to experience somewhere else right now, how do you tie that to the customer? I'll give you an example. There's a use case out there with this company called Sage Dental. I think it's a dental practice. And what they did is they took the customer facing data and experience, brought it back to the internal with the employee, and they used AI, came up with a triage process of taking the data that's coming in from the customer and then making sure their initial experience in with the employees is optimized so that the employee has less chaos in the office. And they also give better treatment options to the patient because they have a total experience that they've considered. So they've humanized the back end, they've humanized the front end.

Bill Pierce [00:33:05]:
They put this AI in the middle, and it's been successful from what I hear, from what I was taught. And so I actually think that's a brilliant way of thinking about it.

Steve Swan [00:33:15]:
Right?

Bill Pierce [00:33:15]:
So I think this total experience, which is just taking your digital experience platforms, which have been around for a long time now, most people think of those as like a site core or some platform like that they've been around a long time. You're talking 20 years old in some cases, right? And then we have the CX, the customer experience stuff, which has evolved a lot lately, right? Particularly as the pandemic hit and things became more digital and less bricks and mortar. And then we have the UX, the user experience, and then we have ex, the employee experience. I think all those x's integrate into a TX. And I think personally, what I've talked to my head of HR and some of my leadership about is how do we put this together to drive the employee engagement and retention to our mission vision values, make it customer exposed and facing so that they see it, so that they really have the best possible experience. Because guess what? We sell specimens and biological samples, whether it's fluids or cellular tissue, there's nothing that really is super engaging from an experience about that if it's almost treated like a transaction, because if we tie it to the research outcomes and we use AI, and now we become more of that healthcare company, more of a data company also, we can say not only can we sell you this tissue and this cellular information, we can sell you this blood, we can match those pairs. We can give you healthy and disease state populations, and we can help you with some AI models and data tuning so that as you're running your preclinical or clinical research, we help you get to your end game that much faster, that much better, that much cheaper. Right? That's a great story for your customers.

Bill Pierce [00:34:59]:
And that's really where we're headed with our AI journey. I'm in the foundation, as I just explained to you. First thing I did is get the cybersecurity stuff. Clean. Now I'm in the taxonomy and ontology layer. And once I get through that, then we'll really start to step up our game.

Steve Swan [00:35:13]:
But then the total experience piece brings it back for your employees. They feel a sense of purpose. Right? Like, take everything you just said, right? Everybody they're helping, everything they're doing. Then all of a sudden, I'm like, wow, you know what? Yeah. Maybe I'm doing some it work. Maybe I'm doing some drawing, some, I don't know, drawing blood or whatever I'm doing, right. It's actually I'm doing something. I'm making a difference.

Steve Swan [00:35:33]:
And the total experience, I mean, hallelujah. I hadn't heard that. That's great stuff.

Bill Pierce [00:35:38]:
And how do I.

Steve Swan [00:35:39]:
Great stuff.

Bill Pierce [00:35:39]:
How do I expose some of our scientific and clinical knowledge out to the customer that scales it in a way in which I don't have to have 300, right. I have 30. And I get the scale and the volume out of it enough to keep the projects and the relationships between us and our customers moving in a positive manner. Right. And again, that total experience will really elevate our brand. So Bioibt has the number one reputation for quality, for specimens that we do. That's kind of just to be in the game.

Steve Swan [00:36:13]:
Right.

Bill Pierce [00:36:13]:
So we're in the game now. It's, what's your experience like with Bioivt? And really what we're doing is saying we're going to bend that curve pretty far, right to the point where we're the first person you think about when you have a hard problem. Right. That's a different mindset than am I a transactional person off to the side, and I go find you when I need you.

Steve Swan [00:36:34]:
Right.

Bill Pierce [00:36:35]:
We want to elevate our total experience with our customers.

Steve Swan [00:36:40]:
That's awesome.

Bill Pierce [00:36:41]:
And our internal people. Right. I really want stretch assignments and developmental capabilities. And one of our parts of our mission and vision values is a learning organization where we develop the employees, and so we're going to live and breathe that. We started a whole series of coffee experience. We call it leadership and lates, where we ran around the company and the leaders would sit with employees and talk to them about exactly what you and I were just talking about. How do we connect you to the bigger engine, and how do we bring out more, and how do we give you more opportunity for your career growth and your career development? And even very subtly, what's their responsibility in that? Because nothing comes free, Steven.

Steve Swan [00:37:19]:
Right.

Bill Pierce [00:37:19]:
So what's your responsibility to navigate that complex maze, develop yourself and then get the most out of your employee experience. At bio, I think we're doing a great job.

Steve Swan [00:37:29]:
This is literally the first time I've spoken about this. I'm on my podcast, meaning what I do, right. So I'm about to give you. When I go out and I look for somebody for Bill or whoever, right. I'm doing what I can to make sure that the culture matches. Everything matches, right? I mean, skills, you can read the skills, right?

Bill Pierce [00:37:46]:
Absolutely.

Steve Swan [00:37:46]:
You got to make sure culture, you got to make sure they can work with Bill. You got to make sure they can read a balance sheet, right. You got to make sure they know what they're doing from a finance perspective, and then we all agree. Okay, great. This is going to work. But two years, a year and a half down the road, I don't need more than one hand to count the amount of times in 25 years I've had companies come back to me and say, so and so is gone. It's been two years, a year and a half. Well, why are they gone? It's not something that the swan group did.

Steve Swan [00:38:15]:
It's a retention issue. It's what you and I are talking about. Right. Know I'm not sitting in your lobby every day making sure that that guy or girl's happy, right? I did my best up front, and we all made the right decision at the time.

Bill Pierce [00:38:28]:
So I think TX for Stephen, right, not to interrupt you, is how do you stay connected to that employee? How do you make sure they're engaged and maybe go back to their leadership and say, you're going to lose. I put a lot of energy in getting this person there. You're going to lose them because that engagement factor is not there. You as an individual can't scale across how many people you've placed. That's just crazy. But you with a platform can absolutely do that in a very organized and process driven manner. Right? So I think Steve Swan should look, and the swan group should look at TX and, well, how is the experience of our employees? I'll give you another reason why Steve places me. I have a great experience.

Bill Pierce [00:39:12]:
I do my five years. But now it's time for me and my own career development to move on to the next big and better thing. I'm going to go back to Steve and say, I remember him. That experience was good because not only did he know about me and think about my attributes and my style and my communication process, my educational background, my cultural fit, but he also thought, what's my longevity there? And then how do I do my best work? And really, it sounds so basic, Stephen. Like when I was talking to my head of HR and we were talking about talent development champions, which we all put out there. You put out there, I'm sure. Right? Talent development champions. You got to live and breathe it because the employee knows immediately whether you're a talent development champion or.

Bill Pierce [00:39:54]:
That's just right. It's pretty quick.

Steve Swan [00:39:56]:
Yeah.

Bill Pierce [00:39:57]:
I think these, again, TX platforms, and they're going to mature. All these vendors are going to try to reinvent themselves. If this takes off, I actually think, again, it will take off. So to me, it's the next big thing, right? It's going to be something that just because of the pandemic, starts to get more legs. Because we're all going to be in the war for talent, right?

Steve Swan [00:40:19]:
I think we should be. I was just about to say that I think we have an issue, right. We're not having a lot of kids, right. We're trying to lock down the visas from outside. Not a lot of our kids. And I can speak from my experience. I had to beg, borrow and steal to get my daughter to take any sort of it class. It's not cool, right? Maybe that's different.

Steve Swan [00:40:39]:
Now they see Zuckerberg and whoever, right, making gazillions of dollars, but it's just not cool. And so the Talent is getting tougher and tougher and tougher to come by and to keep and let's see where it goes. But I agree with you. I hadn't even heard about TX, so that's something that I should know about. I should know well about.

Bill Pierce [00:40:58]:
It's, again, just maturing. So please take that for what it's worth.

Steve Swan [00:41:03]:
I'm fine with that.

Bill Pierce [00:41:03]:
And definitely get some legs to it. It's going to take some thought leadership and some poking and prodding and probably have few failures because there's not going to be a blueprint for it.

Steve Swan [00:41:19]:
Right.

Bill Pierce [00:41:19]:
So I think stay employee focused, stay customer focused, blend the two into that TX. And as long as you're 75% directional, it's better than what you were doing before, where you kept these initiatives totally separate from each other.

Steve Swan [00:41:32]:
Right.

Bill Pierce [00:41:32]:
When you connect them, it amplifies. The reason they said, do you think there's 25% upside is it's very basic. It amplifies everything that you're doing, Steven. It just makes total sense. As soon as I read it, I was like, this makes total sense to me.

Steve Swan [00:41:48]:
Yeah, I'm drinking that Kool aid every will.

Bill Pierce [00:41:52]:
I know.

Steve Swan [00:41:52]:
I love it.

Bill Pierce [00:41:53]:
I will tell you, like in the, you know, they, there's something called a buyer's journey. Have you ever heard about this term? It's kind of become an it term, even though it wasn't meant to be. But the buyer's journey is almost like telling a story. How does the customer come in and then how do they buy your products and services and how is that experience? Right. They call that the buyer's journey. And there's been so much work done on that and there's so many design firms and thought leadership, et cetera. I think that can easily pivot to say, okay, how do we take that world now, which is very customer centered, customer experience, and extend that back to the employee, which is, okay, let me just give you the example. I'm that dental company.

Bill Pierce [00:42:37]:
I have this AI and ML that shows me very specific procedures and things I can do. And I'm that expert in the dental office for that procedure. Now you're guiding the patient, right? To me, I have less patient analysis and acquisition. I could focus more on talking to the patient, educating the patient, being patient focused, than worried about where's my next patient coming from, right? So all of a sudden now the expert in the dental office's position is amplified. The patient's experience is amplified. I do. I think, again, it sounds silly, but I think it's just a basic capability that when you put it together, is just a better experience for everybody. And more importantly, talent retention.

Bill Pierce [00:43:18]:
Right. To me, the big thing that stood out for me is, hey, this is really going to help with that talent retention because what I'm seeing in it, just for grins, two to three years turnover time in many cases for your best talent.

Steve Swan [00:43:32]:
Yeah, agreed. Right. I totally agree. Yeah.

Bill Pierce [00:43:36]:
That's a short window.

Steve Swan [00:43:38]:
It is. It takes you a year to find the bathroom, you know what I mean? If you're even going in.

Bill Pierce [00:43:44]:
Yeah. And do I want to force somebody in 25, 30 years, like back in the, maybe even the 50s, where you only work for one company and do one job, your career? No, I want people to be able to develop themselves. But I think two years to your point is such a short window to turn over. And I've done it. I've turned myself in my own career over in two years. It's just because of the fit, right? Like, I had some very purposeful things I was trying to work on and do and it wasn't offered to me. So eventually you just say, I'll pull the report, I can go find this somewhere else. And every time they do that, all that acquisition cost and all that resetting of the organizational design and all the experiences of the employees all change.

Bill Pierce [00:44:27]:
And now they got somebody new to upskill or they got somebody a new personality learned the more senior they are, the more impactful it is. Right. And so I pity. Right. We know the average CIO turnaround is two to three years. It's been that way for as long as I can remember now. Right? Since.

Steve Swan [00:44:43]:
Yeah, a long time.

Bill Pierce [00:44:44]:
Since the 2000s anyway. Early two thousand s, two to three years, a new CIO. I watched it.

Steve Swan [00:44:50]:
Right.

Bill Pierce [00:44:50]:
I've been the new guy and I've been the guy leaving. It's painful to a lot of people who really want that consistency and that experience. So again, I think these TX things might be able to smooth some of that out so that the new leader coming in doesn't have quite the same disruption that they might have otherwise.

Steve Swan [00:45:07]:
Right.

Bill Pierce [00:45:07]:
So if they come in and they immediately know the lay of the land between the CX and the ex, I think they can adjust their style to what's important for both the customer and the employee. It's going to drive the employee talent development up, employee engagement up. You're going to keep your best people. I think it's a win win.

Steve Swan [00:45:24]:
So I got to just say, every conversation we have, whether we're recording it or not, I learn something. I learn a lot, actually.

Bill Pierce [00:45:31]:
Me too.

Steve Swan [00:45:31]:
So this is another one of those. Always love talking to you. Now, anything else in technology, I don't want to know.

Bill Pierce [00:45:42]:
There's a lot of things going on, but most of them are just business as usual. Right? We could do a whole conversation on m and a and integration. We could do a whole conversation on just cybersecurity. These are a lot of business as usual things. I'm happy to discuss those with you, but I think that the two most impactful things that are out there for a company today, we just discussed now.

Steve Swan [00:46:07]:
So in the past, you and I have spoken several times. We brought up strategy and execution alignment and things like that, right?

Bill Pierce [00:46:15]:
Yes.

Steve Swan [00:46:15]:
So how do you feel your strategy to execution alignment is unique compared to other organizations.

Bill Pierce [00:46:21]:
I may not be the norm, and I'll tell you what my norm experience was when being more junior. And that is a lot of disconnectedness, right. As the employee. So the strategy and the goals at the sea levels when it would ripple down to me was so disjointed and disconnected. I really couldn't understand what the business was trying to accomplish and I really couldn't understand. A lot of times my connected to this, about 25% of the companies have gotten better at that. Right. So that has gotten better over time.

Bill Pierce [00:46:51]:
But I think most companies still struggle with mission vision values that are mom and apple pie, and a strategy that is so convoluted that the employee can't engage to the mission vision values and then align their goals to that. What I've done is I try to keep it very basic. I try to cascade no more than three goals, and I try to have strategy on a page, and I try to tell a story out of that strategy on a page. So everything that we were just talking about where innovation is in there. So AI would be a part of that innovation. The employee experience is in there, and I color code it, right? And I show them, like, this is where we're driving the customer, and that's green, and here's why it matters. And this is where we're driving the employee experience, and that's yellow. And that's why it.

Bill Pierce [00:47:39]:
So I try to tell a very basic story. The reason I do that, Stephen, is I literally want them to pin that up on their wall and stop all the chaos. Right? All the chaos. Everything moves so fast. Everything moves at Internet speed. And you're going to have a project come your way, you're going to have a question coming your way. You're going to have something come your way on a minute by minute basis in the email, for God's sakes. And so I want them to be able to focus back to what's important.

Bill Pierce [00:48:03]:
So when everything comes to, you can say, yep, Steve, I'd love to help you with that TX thing, but right now I have to get this done because this is my most important thing.

Steve Swan [00:48:12]:
Right?

Bill Pierce [00:48:12]:
And when I get some time, I'll come back to you and be honest and genuine with their fellow employee or their customer about that. And so that's really all I've done, is to try to simplify that and make sure they're connected. Then when you do the performance appraisal, how do you talk them about their own career development and their stretch assignments and all the things that you're giving them, along with those goals that were cascaded and then interim measures. And so it's a storytelling endeavor, Stephen, which is, by the time I finish it, what good looks like to me is, did I tell that employee a story that they can attach to?

Steve Swan [00:48:49]:
I like it.

Bill Pierce [00:48:50]:
Do they know how to prioritize their time? Do they know how to delegate? Do they know who to say no to? Right. Those are all hard things to do. I think the hardest thing to do for most of us, at least for myself, is to say no. At one company, I got so good at saying no, I got a horrible nickname. I got a nickname of Cino. And that was because I was just trying to focus us, right. I was just trying to keep us focused on what was important, right. Because we go through a massive, massive growth stage.

Bill Pierce [00:49:21]:
So you can't make everybody happy when you're going through a massive growth stage. So you got to constantly wind back. That's nice. Let's put it on the list. It's not a no, it's a when. I wasn't CI. No, I was CI when. But it's nice to have just to.

Steve Swan [00:49:35]:
Set the record straight, right?

Bill Pierce [00:49:37]:
Exactly. At least in my brain. But perceptions are reality, right. If I got that nickname, I know, right. I always teach my employees, look around, right? Navigate the organization, have the human centric feelers out there to understand your brand, your personal brand. And then what your personal brand is, is how people really interpret your expertise. You could be the smartest person in the room. If you come off abrasive, you're going to get shut out.

Bill Pierce [00:50:05]:
It doesn't matter. Again, you know this because you're in the talent management field. But again, for a lot of people that's not obvious to them. It's, I own this, I'm the expert and by God, I'm going to tell you what you need to know and what that can hurt your brand.

Steve Swan [00:50:22]:
Yeah. Doesn't go over well sometimes, right. In corporate simplicity, I think.

Bill Pierce [00:50:29]:
Is that to take that whole story I just told you and brought you in a little performance management journey? I think it's just how simple do you tell this story?

Steve Swan [00:50:39]:
A lot of what you're talking about here, whether you know it or not, I mean, it's almost centered in marketing. Right. There's a book I read that's called traction and a lot of it is centered in what you're talking about.

Bill Pierce [00:50:51]:
Maybe I'm a frustrated marketer and it geeks.

Steve Swan [00:50:55]:
I'm going to send you the link after we're done. I'll send you a link to this book. It's classic, a lot of this.

Bill Pierce [00:50:59]:
I was on a call this morning with external vendor and we were talking through what the strategy roadmap for the year with them is going to be like. Right. Just to try to set through what the sow is and what the financials are, et cetera. And I tried to really dumb it down to them and say, look, in this area, here's the financial target that we have, and here's how you can matter towards that financial target. And I think they were surprised that I brought it down to one item and one item only. And I challenge them. I'm like, look, I'm only telling you what I see. You tell me you live and breathe it.

Bill Pierce [00:51:35]:
Is there anything else that you would do before you do this? No. Okay. And then they thanked me. They were like, okay. That really helped me to focus, and I think that's half my job, is steering the ship, is just to focus people on really what matters. So I felt good leaving that meeting that I gave them the direction they need. I don't want to passively aggressively try to control them or put command and control in them. I know a lot of people think, oh, here's a rain officer.

Bill Pierce [00:52:01]:
He's going to use command and control only on me. I don't do that to people. I give them the boundaries, right? And I use this analogy, right, for the musicians out there, I use the jazz musician analogy like a classical musician. For you and I to play a song, we'd all have to have the sheet music, and we'd have a role in that sheet music, and we'd follow exactly that role. That's not really what I'm looking for in the business world. I'm looking more for the jazz musician, which is, I have my boundaries as the drummer, I have my boundaries as the horn guy. But within my boundaries, I can be as creative and bring my magic and my special sauce to the table. And I call it being jazzed.

Steve Swan [00:52:38]:
Right?

Bill Pierce [00:52:38]:
So the jazzed analogy of being jazzed up and high energy, but really the jazz musician analogy of, you've got a superstructured framework of which you can be creative in, but you know your boundaries. You know, the loose collection of rules to do your best work. And that's really what I was trying to do for them, is here's where I think your boundaries are. Here's where I think your focus is. Go do good stuff, like go help me out. As long as you're a vendor that brings me value, I will stick with you. If you don't bring me value, you're going to find I move on. It's not personal for me.

Steve Swan [00:53:09]:
I had the same analogy somebody asked me about with the kids. With my kids. Gave them boundaries. I gave them a fence. Stay within the fence. But the yard was huge. Gave them a huge yard, but that was a solid fence. You know where that fence is, right? So stay within this.

Steve Swan [00:53:25]:
But the yard, the fence is a lot bigger than most parents give your kids. But like you said, be creative. Do your thing within this fence. Once you hit the side of the fence, you're going to know, don't worry, you'll know when you get close to that. But it's a big yard.

Bill Pierce [00:53:41]:
I have a similar analogy. I've had a lot of people, even my own kids, and my own kids probably took my advice the least. But ask me for career advice, like, how do you manage your career? And I basically say, you know what? It's never going to go exactly how you think it's going to go. I promise you, it's going to go different. But if you're rowing and you see where you're rowing to, you know, you're trying to get to that island on the other side of the lake, row in that general direction, and you're going to have a little left and rights and ups and downs, that things are going to go really fast, and then things are going to go really slow. As long you're going in that direction, you're doing good. Yeah, exactly. And try to take the pressure off them of what I tried to do early in my career was control it.

Bill Pierce [00:54:18]:
Like, I have to be in this role at this time, I have to do this work at this time. And you drive yourself insane trying to control it to that level because it never plays out, Steven, the way you think it's going to play out. Right.

Steve Swan [00:54:30]:
Nothing's ever like this.

Bill Pierce [00:54:31]:
Yeah, absolutely right. And human beings are complex, so you're really hard to predict how they're even going to interpret what you're trying to.

Steve Swan [00:54:39]:
Well, it's also. It's not just interpretation. It's you and I interact. We're like two chemicals in a lab. We don't know. No one knows. I mean, someone could put your personality on paper, mine on paper. We should react like this.

Steve Swan [00:54:50]:
But what if we react like this? Who knows? You never know. That's what I always say. You never know. You can't explain how things happen anyway. Well, thank you very much. I have one final question. Unless you got something else you want to go? No, you're good. Okay.

Steve Swan [00:55:05]:
Thank you very much. So, a minute ago, you were talking about you made a music analogy, right?

Bill Pierce [00:55:12]:
Yes.

Steve Swan [00:55:12]:
So here's my question. I ask folks, everybody, when we close out, what was your favorite live concert or band or act you ever saw in your life?

Bill Pierce [00:55:23]:
Wow, that's a great question. I have a hard time with favorites. Anybody who knows me. So I bounced around the world. My son says, I'm from nowhere. Because my dad was military and I was military, so I don't really grab onto favorites like most people do. If I had to say, I would probably pick. And it's only because I've been to.

Bill Pierce [00:55:45]:
It would be a kiss concert I went to when I was, like, 16 years old.

Steve Swan [00:55:50]:
Nice.

Bill Pierce [00:55:52]:
And it was a little bit of the experience, right? Not that I listened to kiss music anymore, but just the whole experience was pretty cool.

Steve Swan [00:55:59]:
Those fans are crazy. I was going into New York City three weeks ago. I don't even know how many weeks ago it was, but I was on the train and they were doing their last Madison Square garden show, and there were guys older than me, there were girls younger. I heard guys talking about a 1972 show with blue Oyster Colt and this guy talking about. I mean, it was crazy, and I couldn't believe it. It was all over the news. It was everywhere, and the fans. And now I get into New York City.

Steve Swan [00:56:24]:
I come out of Penn Station, I see whole families dressed up like kiss, walking down the sidewalk with their shirts and everything. I mean, everybody was all done up. It's a thing.

Bill Pierce [00:56:34]:
Yeah, it's a thing. Absolutely. For me, music brings me back to place and time, so I have this uncanny ability to hear a song and know what year it was and where I was and what was going on. So, again, I won't gravitate towards a certain banner, because music changes over time, and I enjoy the change, actually. But I do know very specifically what I liked and where I was and what was going on at that time. And I was in a luncheon with a CEO one time, and he had his whole staff around, and he started asking us. I think his question was, and I'm pretty sure it was this, like, rolling Stones or Van Halen and which one do you like and why? And I was like, jesus, I like both of.

Steve Swan [00:57:20]:
Yeah, right?

Bill Pierce [00:57:22]:
And I think most people immediately gravitated to one or the other. Right. And I'm like, I don't know. I like both, right. And so it was a funny question, much harder for me to answer than he ever realized when he asked that question.

Steve Swan [00:57:36]:
Yeah. I would ask him, well, what year was that? So it would have depended on the year. And am I giving you my answer for today, or was I in college or that kind of thing?

Bill Pierce [00:57:46]:
You're giving me insight to your personality. Right. Which is you're analyzing. But I think for him, it was just an icebreaker, conversation starter.

Steve Swan [00:57:56]:
Right.

Bill Pierce [00:57:57]:
Et cetera. Right. So it was fascinating to hear people's answers. Like I said, most people could just answer. And for me, it was really hard. Again, I don't think anybody at that table had an idea of how much was going through my brain like you just did, which is because I would have had a tough one, which Van Halen.

Steve Swan [00:58:13]:
Which year, I wouldn't have been able to do, have. I would have gotten more qualifiers, because I couldn't just straight up say that.

Bill Pierce [00:58:23]:
Yeah. I backed off Steven to what I thought the spirit of his question was, which is have some fun with it.

Steve Swan [00:58:30]:
Right.

Bill Pierce [00:58:30]:
And talk to the person sitting next to you about it and have some fun dialogue. Right. So I thought it was very clever, what he did. It's just way harder, probably, for me, than the rest of that.

Steve Swan [00:58:42]:
Yeah. Well, cool. Bill, thank you very much. This was awesome. Again, I continue to learn every time I speak to you, so I love it. It's great. Thanks for spending some time with me.

Bill Pierce [00:58:53]:
Yeah, I appreciate it.