May 9, 2022
Hear how your organization should embrace change to grow George Swisher is a former marketing entrepreneur and management consultant. He has a 15-year track record of improving company performance and shifting cultures to effective change management. He currently is co-founder and CEO of www.changeforce.ai, a software platform that helps leaders manage organizational change more precisely by analyzing the sentiment of company conversations in real time. A really interesting platform. Remember, I'm a corporate anthropologist who, like George, helps companies change, so I loved this interview. So will you.
Watch and listen to our conversation here
When you begin to change, things aren't all changing at the same time
And you're not quite sure if it's moving at all, and sometimes you're moving a battleship with an oar. You're just hoping it's moving somewhere. But the technology which George has developed can identify where a culture is moving, which areas are strong and which are not.
First, he gathers data about what your culture is currently so you can make smarter decisions, whether you're a frontline employee, manager, director or executive entrepreneur. Then his software analyzes this data to help you scale what you are doing to do it faster, and save money. In essence, he helps you build better change processes of how you get things done so you can inform that process with meaningful information.
In our podcast, we talk a great deal about George’s own personal journey. You will love this conversation. Then come and share your own new ideas and see how they can soar.
For a deeper dive into how to change your corporate culture so you can soar
Additional resources for you
Read the transcript of our podcast here
Andi Simon: Welcome to On the Brink With Andi Simon. I'm Andi Simon, and as you know, I'm your host and your guide. And my job is to help you get off the brink. I go looking for interesting people who are going to do just that. They will help you see, feel and think in new ways so that you can begin to soar again. These have been unusual times. I used to say, if you want to change, have a crisis or create one. I never expected a crisis of this sort. But I also preach, don't waste a crisis. Because it's a time where people will let you change, they will blame it on unexpected things. You'll never know where it can take you.
So today I have with me George Swisher. Let me tell you about George just a little bit, because we have some very interesting and important conversations about technology and transformation to share with you. George is a former marketing entrepreneur and management consultant. He has a 15-year track record of improving company performance, and shifting cultures to effective change management. He currently is a co-founder and CEO of Changeforce.ai. You should look it up. It's a software platform that helps leaders manage organizational change more precisely by analyzing the sentiment of company objectives in real time. It's really an interesting platform.
Remember, I'm a corporate anthropologist, and I like to help companies change. The question is, when you begin to change, things aren't all changing at the same time. And you're not quite sure if it's moving at all. And sometimes you're moving a battleship with an oar and you're hoping it's moving somewhere. And the technology that George has is very interesting as a way of identifying where it's strong or it's not. But today, we want to talk about culture, technology and business so we can see what's happening and where we're going. George, thanks so much for joining me.
George Swisher: Thanks for having me, I'm really excited.
Andi Simon: We are too. Tell the listeners about your own journey, because it's a perfect setup for where you are and where you’re going. Who is George? And what's your journey?
George Swisher: That's great. It's a great way to start. I think you know, in talking today, my hope was to help people understand how technology can really help them. So it's less about the software. It's more about, where were the pivotal points in my personal path that got me to where I realized that I needed to have technology as a utility to make better decisions or be more effective in the work that I was responsible for.
And so I was actually lucky to be a guest lecturer last night at Columbia. My co-founder, Dr. Nabil Ahmad, teaches a class on organizational strategy. He had a young group in there last night. And when I got home, I was taking the train home, and it reminded me of the moment, I remember exactly where I was, how old I was, when there was a huge tipping point where I said, Wow, if technology isn't a part of what I'm doing, I'm not going to be able to succeed at the path that I want. And, this group was really intelligent. So a lot of great questions reminded me of when I was about 19 years old. So I was young.
Luckily, I went into the workforce young, I was going to school and working at the same time. So at 19, you can imagine you're doing all kinds of different things, trying to do studies, trying to get a job done. And I was working for one of the largest railroad companies in the country. I was sitting there and I was a part of a team of about 20 people. It was an operational management and customer service, not the most innovative departments usually. So they had hired a tech consultant who came in and he developed a basic Microsoft access database with a pretty front end on it. That pretty much took the team from 20 people to two people. And I was lucky enough to be one of the two people that got to stay.
And what he ended up doing was figuring out a way to make managing customer service more efficient with less people. Some people thought it was bad. I thought it was brilliant. And that became the moment I was like, Wow, this person just came in and what I thought was my job today just completely changed in less than 24 hours. And it really made him look like a superhero to the company. Now of course the people who lost their jobs, it wasn't great for, but in terms of an organization and leadership, and what they were trying to do, here was this very simple thing that he did that completely changed that organization. And then this was a billion dollar company, right? This was a big, big deal. And it's when I realized that I needed to have a superpower like that if I was going to be able to go from a supervisor, which I was at the time, a young supervisor, to manager to director to executive to leadership. If I didn't have that kind of utility belt where I can just bolt on different pieces of technology to be my superpowers, I was gonna have to go at a much slower pace than I was willing to do. And that just became that time where it was. It was scary because I just watched 18 people lose their jobs because of technology. So I was a little bit fearful of it. But I was very intrigued by that. If I can use it the right way, it will help me beat out other people, bcause that's what I was at that age, that's all I was looking to do was build a career.
Fast forward about five years, I ended up moving up in that company, by using that strategy. So I actually dropped out of school, and decided to spend that same time discovering different technologies, and what could I not do physically, that some type of software or technology could help me either gain information that I didn't have readily available to me, and that can be in many different ways, or to make something more efficient. If it can make it more efficient, it has that ripple effect of scale, speed, cost, efficiency and savings. And I knew if I can do that, that I could beat out a lot of other people who may have more formalized education.
Five years later, I was running about a $50 million business unit at the age of 24, which is crazy to me at times. And that was almost 20 years ago, because I had beat out candidates who had MBAs, who had more work experience, but really couldn't understand how to create that speed and scale and cost effectiveness that I was able to do. And that's how I got into that position. And so last night just reminded me of how many leaders didn't get the luxury that I had to figure that out, as they've been moving through their careers. And what's always funny is when we have these conversations, a lot of times people ask so many questions about the physical technology, like, are you building it? Are you building artificial intelligence? What is machine learning? They get so into the details, which happened last night with these young leaders.
My advice to them was, It's not about learning how to be an engineer, it's more of understanding what can't you do today? Is there some type of technology that can help you do that better, faster, more informed? If you can do that, you'll win the battle, right? If you go to hold it down into the hole, you get lost into the engineering world, which you don't want to. And so, I think that timeframe was really the moment where I just never looked back. Everything that I did, every career decision I made, hinged on the fact that I could constantly explore, and eventually I got into building our own technologies if we couldn't find them. So if there wasn't something out there, and we knew that we could have efficiency, I ended up becoming an entrepreneur at 25 and built a service organization.
In consulting, you had technology enabling IT services, where we progressed really quickly. And that was the first time I had sold a company at the age of 30. And so I always come back to what enabled me to do all that was the fact that I was constantly trying to find ways to have superpowers beyond what I was able to do in a human capacity. And it ended up being some form of technology that did it. And that's why I feel like it's important to listeners.
Andi Simon: Let me ask you a question as if I'm your audience asking you the question. Let's assume that we are like your Columbia students last night. What would be three things that are important for the listeners? Let's assume they're on the brink and they too want to soar. What is it they should look at and what should they see? How should it feel? What are we thinking about here, because you made an important point. It's not about being an engineer, it's not about the details of AI or machine learning or robots. It's a bigger picture that you're preaching. And if I hear you, which is that society is going through a great transformation, it's almost as big as the introduction of farming or fire or in the transformation. But if my audience is like your students, some of your observations would be very helpful to share your thoughts.
George Swisher: So I will try to do three. One would be understanding what information you can not get your hands on today? I always love this idea of this concept, and there's a company that's called What If. They've done a great idea just to sit in a room and go, What if I could gain access to this information? And whatever that is, right? Information we hear now is data or big data, just get rid of the words. Just think about information, if you could figure out what information would inform you to make better decisions so it doesn't matter what role you're in. If I can get information about currently, it's going to enable me to actually make a smarter decision whether I'm a frontline employee, manager, director, executive entrepreneur, it doesn't matter. So I think number one it is to focus on that: what information do you need that you currently can't get today? And then try to find where you can get that. And the reality is, there most likely is some way to get that. You don't always have to build it. But there is some way that you most likely can put two softwares together. That's where you work with your engineers and go, Hey, take these two things, and put them together and give me the output because that output is going to allow me to make a decision that's going to scale what I'm doing, do it faster, save money. I think that's that one piece of finding information.
Two is kind of the next step to that, which is, Is there a way that I can be more efficient in what we are trying to do. So if I'm a leader in an organization, I have one departmental kind of view, and then I understand what the company objectives are. How do I ladder up to that? Most of the people in the organization don't know how that works. There's huge limitations and where you can have efficiency. And I think efficiency is such a great, powerful tool, if you can figure out a way to get things done faster, more cost effectively, at a larger reach, you can have a greater impact. I think that is where you can turn information into a viable use. And so no matter what role you're in, if you can take those two things, and apply it before you make your decision and go, Is there information that I don't have access to? Can I get it? And then where's the efficiency in what I'm trying to do? Are there things out there that can help me do it more efficient, because then when you make your decision, you'll invest time, money, and resources behind those two things. Getting more information makes me make better decisions, being more efficient in the way we're trying to do something, which has a greater impact.
I think the third part I was mentioning before and the advice that we gave the group last night is actually at the same company that I had that technology awakening. After that happened, and I stopped, I told my general manager at the time, Hey, I'm going to leave school, I want to invest more time in learning technology. And I said, You know, how does my job affect you and your job and what the company is trying to get done? Because I want to make sure that I don't go anywhere. I just watched 18 people be let go and I don't want to be let go. So as innocent as that was, my general manager at a very big business said, Have a seat. I got to learn how my job fit in as one of the cogs of the whole big picture.
So as I continue to make decisions, I learned how this contributes to the bigger picture. Whether I agree with it or not, I think this is the ego you have to almost put aside. How do I fit into that bigger picture? Because I'm trying to fight my way up the ladder, how do I know what that ladder is and where I connect the dots? So I think that's the third advice. Third point that I would make is, If you can master those three things, you can become an incredibly effective leader, entrepreneur, decision-maker, which is where I personally believe that's where you want to invest your time. There are skills that you need to learn. But if you can master those three things, and know that technology fits into two of them, you can really move in the direction you want, better and faster.
Andi Simon: Let me ask you my slightly burning question. A number of years ago, I taught several times for healthcare strategists, Your data is talking to you, can you hear it? As I'm listening to you, the challenge that leaders have is understanding what the data is telling them, the information and insights. The challenge was an abundance of data, not necessarily at the time the tools to analyze it for them. It wasn't artificial intelligence that was doing data analytics and telling you what to do as a result. There was just raw stuff. And part of that was, How do I turn it into the right stories for the right people to listen to so that they could make the right decisions and act in the right way?
Think of a healthcare system. The stories they had to tell the C-suite were different from the ones they told the doctors, which were ones that were going to be different from facilities management, or from people who are going to be taking care of patients. They didn't understand that it wasn't one story. This was one pie chart. Those were the stories that they told, that affirmed what they already knew, not what the data was telling them. And they only found the data that conformed to that mind-story as opposed to transformed it.
So I found it was very challenging to help them understand that the data was telling them something different from what they believed to be true. The expression, The only truth is, there's no truth. Like you are now opening up a whole, I won't call it a can of worms, but an interesting opportunity for leaders to understand what the data, the technology, can provide for the things that you mentioned: scale faster, and save money. That's a whole new strategy. So how do we help them as leaders understand what's upon them? I bet you were having that conversation with your general manager when you said, I don't want to leave, what do I have to do? You're smiling at me. So share with the listeners your thoughts about how they really warm up to this new stuff? Don't be afraid?
George Swisher: I think bravery is an incredibly powerful emotion that can help you overcome a lot of things. And I think I feel that I was lucky because I was mentored that way to have that bravery and just go at things and take the risk. I think this is not an uncommon theme that leads to just being okay with failure. Sometimes you're gonna make mistakes and you can fail fast and fix it fast and learn from it. You know that speed is the critical part. And I agree with you in the sense that we are in information overload. There are so many different sources of data that people don't necessarily know what to do with that, and it's kind of just thrown at them. This is what you don't have access to, you figure out what to do with it. I think if you haven't been trained to look at data, it's difficult. I feel like this kind of led me to the current path of doing work similar to yourself and the consulting side.
The more I could understand how people were feeling or what was going on, specifically related to my objectives, the more informed I would be. If I give a tangible example, think of employee engagement surveys. This has been a hot button for five, six years: post surveys, all that stuff. It's great, but it is a ton of information. And a lot of times I feel like teams are getting that information from a manager for a department that came from the HR team and so forth. They're having to interpret it and relate it to what they're actually responsible for as the decision maker. This to me is the breaking point. That can we're opening up to say, information is important, but I want information specific to what I'm responsible for. And if I'm in a role that's connected to also what the company is trying to achieve, get rid of the noise and just give me that information so I can make effective decisions.
So in a professional setting, I think that is where we have gotten to a stage. Let's take the healthcare example. What if something could actually tell you if you had an objective, which was to improve patient care. But as broad as that is, which is usually what objectives look like, super, super broad, there was a defined what is considered a good outcome and a bad outcome. If I'm the leader that's responsible for improving patient care, if I define that improving patient care, a good scenario, and outcome would be that our patients are so happy when they leave here that they make sure that their family members come back here, as basic as that sounds. A bad outcome is people check out of your hospital early and file lawsuits against us because they think that we are not treating them correctly. Let's just say that that's the two ranges we're working with.
If I was the person responsible for putting tactics in place, so hiring people, putting new tools in place, better processes and procedures, if I could know how all of the people who affect that decision, so think of the facilities teams, think of the technology teams, they took the doctors and the patients, these are data streams, if I could analyze those data streams and say, Wow, within this specific hospital versus this other hospital, we're scoring on the negative side of that outcome. But in this facility, we're scoring on the positive side. Where would I concentrate my money and my resources and my time? The facility that had the positive information vs. the one that had the negatively reporting information coming back? This is what technology has advanced us to today that we can actually figure out by looking at different communications how relatable that communication is to a specific objective that I'm responsible for. And it can rate that communication. And if it's closer to the good or the bad outcome, you can get that instantly.
Andi Simon: I love what you're saying. It isn't about that individual who is attempting to make sense out of the data, turn it into information and make insights out of it. The technology is able to assess the data information and create the insights so that you're wiser. Because then the technology now is your partner in this, not simply a servant delivering raw stuff, that you've got to cook, am I correct?
George Swisher: You're right. You have the ability now as a leader to tell the technology what you lead. An example of that was like an objective and a good outcome and a bad outcome. If I tell the technology to only give me information back contextually related to that, and then tell me what's good and bad, because I already told you what the range was, how powerful would that be? In any decision that you were making?
Andi Simon: Well, it takes away all of the complexity and uncertainty as long as you trust the data collected. The endless agony in healthcare we're having is that the doctors are very fast at discounting the data. And now the technology has to build the trust that it's great data and not bad data. Because I've been with too much poor data, people who are trying to convince not just the doctors, but the leadership, that the story that they're crafting is correct, not just "trust me." The uncertainties and unknowns become threatening to people who have very different stories in their minds about what the data ought to look like and what they believe to be true.
You are developing content. We talked a little bit about what you've developed because I do think it offers a very powerful solution since I work with companies that need to change. One of the challenges is how we are changing. Talk a little bit about your platform because I think change force has enormous power, and people should be aware of it and people should start to think about how to use it.
George Swisher: Let's talk about the mission that we're trying to do and I think it relates back to what we were just saying. Let's use a different topic other than something in healthcare. Your book you wrote about women progressing in the business and leadership role, I think is a great, great topic. Our mission is to help leaders be more informed of the sentiment around the objectives they are trying to achieve in a very specific lane. There are all different ways that companies like yours, persons like yourself, and companies, are trying to help build better change processes of how you get things done. We just want to be able to inform that process with very meaningful information.
So the way that we have focused that mission as the starting point has been where we can analyze communication platforms such as Slack, Microsoft Teams, employee engagement, survey data, emails, things like this, where our software, using artificial intelligence, natural language processing, is able to contextually understand the messages that are inside of those Slack channels, and how relatable they are to the objectives you're trying to achieve. So let's just say that we know that diversity, equity inclusion is a huge topic inside most organizations. Let's just say they have one of those objectives around empowering women to be better leaders and availability of being leaders inside the organization. You define a good outcome and a bad outcome. A good outcome is we are open and have every resource available to empower women to get through the ranks and become leaders in the organization. A bad outcome is we have complete roadblocks, biases and all these things are going on.
Our software can actually analyze all those communication channels, contextually map and say, These are the conversations that are related to that specific objective around empowering women to become leaders in the organization. And it will read it from a score of A to F. Just go back to grade school above where those communications sit. So you have the ability to understand the specific contextual sentiment, not just negative positives. It's hard to kind of figure out what that means. If I know that good has a specific, measurable piece, and bad has a measurable indicator, and this is sitting in that range, I can understand what that means, as the decision maker. And the way that we've done it is, we allow our customer to compare that set of information across all different types of indicators.
For example, you know locations, or, you know roles within the organization, employee type, almost any type of information stored in the human capital management software. It's like the workdays of the world. You can slice that data and go, Okay, well, I can see in this empowering women to be leaders in our organization, our scoring has been over in this region, or this department, or this age range of our company. And over here we are scoring an F. So the idea is that we're just trying to figure out what's going on.
What we've been able to see now is, especially with the pandemic, it's forced people to use more digital communications. Some companies are upwards of 90% of their communications that used to be verbal and in person is now some form of digital communication. We now can read that communication, and just give you some indication of where the barometer is today, and then track it over time. So if you make decisions to say, Okay, well, this one department is scoring in the D level around this. We need to put some training in place or some new processes or some new people in place. Our software actually does that analysis over a period of time so we can tell you whether it got better or worse. As you made a decision today, 30 days from now, it can see if that contextual sentiment got better or worse as you put those changes in place.
Andi Simon: George, let me ask you to clarify just for my sake. Way back in Algebra 101 many, many too many years ago, the professor said, Out of context, data does not exist. And what I hear you saying is that we've been able to take through the technology that artificial intelligence, machine learning, all of the communication being done, and contextualize it. So we understand its meaning, and can give you insights into the conversations taking place around diversity, equity and inclusion, using that example. Am I correct to what I just said? And that is powerful, because data by itself has no meaning. So now the question is, an individual isn't contextualizing it. Artificial intelligence is putting it into context. And you're comfortable that it's doing it in a very accurate and insightful fashion.
George Swisher: How fascinating. And this came back to your healthcare example, which is the trust of the data coming in. And so from today's state, the biggest advance that we've seen is the ability for natural language processing to start to truly contextualize data. Whether it's images, whether it's audio, whether it's text...doesn't matter. And that's what we are leaning into. Now, that is only as smart as the sources of data it's analyzing, where it's going in the future to continually build trust by adding more data.
For example, within our software, connecting to communications is one kind of viewpoint. But if we then connect to task management software, we connect to Glassdoor reviews. We connect to company social media channels. We connect to performance reviews. So at every one of those data points, the great thing about the technology now is, it kind of works like our brain, where it can cross-reference multiple data points to come to the conclusion of what that sentiment score is. So it's almost validating what it believes. It thinks from the Slack message against what it read in a task inside of a task software and what it saw inside of the performance review. That to me is where the trust factor will just continually get better for humans under the realization that technology can process information and contextualize it faster and better than we can at some point because it can process so much information that we can't.
Andi Simon: I sometimes get emails that I simply don't understand what they mean. And unless you understand that, meaning is not simply in the words or the sentence, but the underlying implications, meaning the feeling that's there. And so what you're telling me is that by pulling together all of these data points, we can in fact, contextualize the conversations going on and understand them. That is, maybe I will say, very true, very powerful, and weird. I mean, they're sort of like, I can't figure out what you just emailed me, I better call and find out what you meant. And I can't tell if you were angry, or happy or sad or frustrated. In the five words are the sentences that you put together, but the AI can do it better than I can. Now that is one powerful system.
George Swisher: That's where the future state is. It will be able to contextualize it better than we most likely can. We're not there yet but it's getting there and it's advancing quickly. Part of what we do to train, if it's accurate or not, is to validate the response from a human. So in that same example of empowering women in leadership in an organization, let's say that it scrubbed all of the Slack or MSTN channels you have and it makes it a C. Well, we can actually open it up to let you know that leaders in the organization agree or disagree with that and score it with a B and it will train the model to get smarter the next time it tries to analyze another Slack message. And so you have this validation. That is where we will start to build trust as human beings without knowing it through the validating AI driven technologies. The biggest example of this is, most people have used some kind of support bot before. The support bots says, Did we answer your question? You say, No, you didn't. And here's what you didn't do. It is actually training the model to do an excellent contextualization that takes into account what you said.
Andi Simon: I'm sitting here smiling. We're just about out of time, but I'm sorry, it's hard enough for humans to communicate well. Now we're adding something that might help us do a far better job of communicating well because we'll better understand. We all know the situation where I say one thing to you, and then I go and type something to someone else. The complexities of human beings in an AI world, and it is truly going to be a wonderful future. I was going to ask you what you see coming, but I have a hunch, I already know what's coming. In a sentence or two, what's your future prediction?
George Swisher: I feel like the future isn't that we're going to be replaced by robots or technology, I think that we will become almost like superheroes. We're going to be able to attach technology to us that will make us incredibly smart or powerful. And I think that's where this is going to meet. And there are some people who are trying to physically do that. You know, Elon Musk has got some interesting things going on. Whether we morally believe he should be doing it or not, but feeding these contextual data sources and things like this directly into our bodies, and our brains, I think is where it is actually going.
Andi Simon: The coevolution that's happening is making us realize that from the time we became meaning-makers, 50,000 years ago, we have been creating the environments in which we live. We're the only species that's completely global. But there's still one of us and 40,000 species of ants, but somehow we keep changing ourselves, and our minds and bodies are evolving. And this is going to be a really interesting next phase that we're unsure of. But we've always been unsure. And now the trick is, how do we stop for a moment and say what role do I want to play with this? You can’t resist, you can get so attached to that shiny object, you won't leave it. But the world is changing. And it would really be cool if you let go and began to lead forward, because I do think we're going to need some real smart people to help us leap forward like yourself.
George Swisher: I think my last point would be, we went through this you mentioned earlier, it's kind of like industrial evolution. Think about if you were here, 150 years ago, when we had industrialization for cars.Imagine how afraid people were that it was turning the horse and buggy into a machine. And we're no different than that, we just evolve with it. I think that's the fear, we all just need to remember that we constantly have been in this state. This is just a different type of state. And we just need to be okay with that.
Andi Simon: Well, and I do think once you get okay with it, it's really quite exciting. Then to your point, for 4,000 years, we rode horses, and then came this car. And next thing you knew, they were putting barbed wire and throwing rocks into it, they were terrified of this car. And now we're getting electric vehicles that are autonomous. Who knows where we're going next? So welcome to the world of humans. George, thanks so much for being here. I'm not going to ask you three things for people to remember. But I am going to ask you, How they can reach you if they'd like to know more about what you're doing. Because I think that the whole conversation today is about all the things that we don't want them to forget. And I do think this is a time where the technology, the person, and the way we live is all through great transformation. So you've got to pay attention and lead on. How can they reach you?
George Swisher: I think the best way is to reach me at George Swisher on LinkedIn, or George@changeforce.ai. Those are the two best ways to get to me and I'm happy to continue this conversation with anyone. I think my effort is to help share what we've learned, not to sell software. So whatever we can do to help. Nabil and I both always have that same kind of educational angle.
Andi Simon: You are a perfect guest on our podcast because our job is to get off the brink and help people soar by helping them see, feel and think in new ways. And to be honest with you, I don't think this is an incrementalist time. This is a transformational time. It's not doing a little better. And what we used to have, it's a battle, a whole new way of doing things. And I am excited to share your thoughts and to help people realize that they don't have to just get stuck.
People keep asking when they're going to go back to what was. And I tell them, They're just not coming back. But neither are we sure what's coming next. So enjoy the journey. It's a great time to be alive and enjoying a whole new way of seeing things. Thanks again. For all of my listeners, thanks for coming to On the Brink. My job is to help you get off the brink to help you see, feel and think in new ways. You can read my books: On the Brink: A Fresh Lens to Take Your Business to New Heights on Amazon as well as Rethink: Smashing The Myths of Women in Business.
To George's point, our job is to help us smash those myths that are holding people back, women in particular, and open up the door because we are transforming the way our society both embraces women or not, and then begins to realize that the world is changing. So let's all get behind it and move forward. You can reach me at info@Andisimon.com. And I love your emails. We're in the top 5% of global podcasts. Thank you. Thank you for coming. Refer more people to us like George. They are great and they bring us great joy. Thanks, George for being here today.