54 | Supercharge your Revenue Operations to Unlock New Efficiencies and Profits with Michael J. Goldrich

0:00Hello, and welcome to Leveraging AI, the podcast that shares practical ethical ways to leverage AI, to improve efficiency, grow your business, and advance your career. This is Isar Maitis, your host. And as you know, I've been running businesses for the past 20 years. And in the past few years, the role of RevOps became more and more common across multiple companies in multiple industries, started more on the tech side, but now it's almost everywhere. And the goal of the RevOps team or person is to make sure that processes across other departments like marketing and sales and customer success teams is streamlined and hence creating higher efficiencies.

0:42In other words, higher revenue for less effort and with less uncertainty. And now I know what you're thinking at this point. This is cool, but what the hell does this have to do with an AI podcast, which is what you're listening to? I'm glad you're asking that question because AI also enables to increase business efficiencies and to break down barriers and to eliminate silos of data or organizational silos. So why not combine the two? Why not create an AI rev ops officer or position or committee that would be focused on delivering AI-infused revenue generating processes within the company? I hope now I got you thinking and excited about this topic because this is exactly the topic that we're going to explore today.

1:32So my guest today, Michael Goldrich, has spent most of his career running rev ops and revenue generating teams in multiple different companies in different sizes. And in this past year, he's been holding a fractional leadership position in multiple organizations doing exactly that, but also doing it while infusing AI capabilities into the revenue generating process. He's also a program leader for data strategy for generative AI platforms at the Kellogg School of Business. So he brings into the table both the theory on how to do this, as well as the practical implementation across multiple companies, which makes him the perfect person to have this conversation with.

2:15And so I'm really excited to welcome Michael to the show. Michael, welcome to Leveraging AI. In the next few years, AI technology will change our world dramatically. Whether you are a business executive trying to catapult your business forward, or just somebody who refuses to be left behind and want to advance your career, This is the show for you. I'm your host, Isar Maitis, a serial entrepreneur and an AI enthusiast. You'll hear invaluable practical tips from innovative business leaders, AI practitioners, and some of the brightest AI minds in our world today on how you can leverage AI in ethical ways to advance your career and grow your business.

3:04That was great. Thank you. I'm very excited to be on the show today. Very excited. I'm excited too. It's one of my favorite topics. And I know you've been doing this and helping businesses do this. So let's really start in the beginning of how does this work? If I'm a company, I'm like, oh, this sounds awesome. I really want AI in my revenue operations. What are the things that I need to think of, kind of like high level before we dive in, that I need to think of as a business leader in order to get started with this concept? Right. So I imagine that, first of all, AI, a lot of companies just think about AI and think are not really sure where to start.

3:45So they might procure a couple of tools and just go that route. I personally am not a fan of that because I think that's very piecemeal and not very strategic. My approach is really to start at the beginning, first do a general training to the company as to what is AI, and then put together a task force. And the task force are multiple departments, multiple levels, and really say, okay, we have this AI thing, we're trained in this. And I focus really on the revenue generating departments where sales, marketing, even customer success, and then I layer in human resources in there. And really get them to find out, I work with them to identify the use cases.

4:27And then once we have the use cases, really pilot a couple of them per department, really want to go for low risk, high feasibility, really good opportunity where it can succeed. And one of those pilots, one of those things really is maybe it could be a tool, could be an automation, could be an agent, or it could be a person. Now, the thing is, after you go through this AI transformation and you do that approach, Then what? Then companies, some departments might be more adapt to it and embrace it more versus others. And then what happens is you have some departments are moving forward, others aren't.

5:06That is why a role such as this RevGen AI, what I call it, is so critical. I look at it as the glue of the organization. and it's the glue because this person or this group needs to know what's going on in each of the departments and then needs to embrace and help them work with it. I think having a committee might be an interesting approach. It's not a way to have it sustained and I think you need this type of role for a company to continue to sustain, to grow, adapt because this role, in my opinion, What they do is they're aware of the latest sort of things that are happening in AI. It's always something new is happening on a daily basis.

5:55New tools, new ways to use tools. As it is, like companies that have tools, you use maybe like 10 % of the tools. And they have too many tools, and they don't use it to the full capability. This person in this world can actually help maybe narrow down the tools that companies use, but really leverage this capabilities to do so much more. So they're also a, this type of role also is the one that works across departments, is aware of all the latest kind of technology changes, and also I think is responsible working with HR to make sure that the policies and the guidelines that whatever they've agreed upon with the task force saying, here's our AI policy, here's what we will never do, here's what we'll sometimes do, and this is what we'll always do, it's part of their role is to make sure that they're not necessarily the police, but making sure that people are aware of that and training towards that.

6:51So they're really looking to be almost like the AI police, so to speak. But they also should be measuring success, measuring how much productivity is gained, how much revenue is generated, how much cost savings there is. And so that's what this role, in my opinion, will do. And once this is incorporated into an organization, it really only at that point can the organization start to truly mature with its AI usage and really see the true benefits. Because apart from that, it's sort of onesies, twosies. So that's my take on it. I love it. I recently released an episode called the seven things you must do in order to apply AI in your business in 2024, which not surprisingly is the most successful episode I've ever released.

7:44It went crazy as far as number of downloads, but you touched on many of the same exact components and you and I did not coordinate stories before. So I guess this approach actually works. And if I want to summarize quickly that the key topics that you touched upon, the first thing that you said is education, right? Somebody has to make sure that there's continuous education within the organization. And yes, some people will do this organically because they're geeks like me and they're going to be interested in it, but the vast majority has work to do and they have life and kids and after-school activities and shopping and stuff that they need to do other than deal with this stuff.

8:20So somebody has to own the education side. And like you said, things happen almost every single day. The other thing that you said is you touched upon the difference between a committee and a person. And I think the committee is a good place to start because it harnesses people from the different departments and with different knowledge gaps of different sections in the organization. But I think in the long run, what you're suggesting makes a lot of sense that even if the committee stays, still somebody needs to own the reins, right? Somebody needs to drive this AI initiative. And so I think having a role like this, especially in bigger organizations, makes perfect sense to me.

9:01The other thing that you said is having policies in place. And I think this is critical. There's multiple research that has been released that is showing that people are using AI, even in organizations that are not allowing AI to be installed on the computers. So people are using them on their mobile phones, but for work-related stuff. So you're not really preventing people from using AI, you're just sticking your head in the sand and hoping that everything is going to be okay. So if you want to benefit from AI, show people what they can do, show them how to do it safely, tell them specifically what not to do, and encourage them to do the things that they are allowed, keep it an open conversation, and then you can enjoy the benefits while probably not eliminating the risk, but reducing the risk.

9:53So I think you touched on a lot of very critical points. Right. A hundred percent. And I think the other thing is about accountability. So I'm working with a task force right now, and there's different levels of participation, different levels of commitment, and no one true owner. People are just part of it. So I think you need a role. That's why I was thinking about this. This role, make sure there's accountability, there's transparency as well. And so I think that's why it's really key. I'm going to raise another interesting point that I want your opinion, or it's a question, and I want your opinion.

10:31Both you and I right now are basically holding this role for several different organizations, but it's a part-time partial thing. Do you think that's the right approach? Meaning, do you think that organizations should hire people like me and you to help them in the transition and then in the long run either raise somebody from the organization into that role or hire an external person like what do you think is the right process in order to get things moving as quickly as possible but yet still have what you're suggesting obviously the first choice would be internal but the thing is this is all so new and the skill sets are so varied you need to first understand ai you need to have good project management skills good communication skills, good reporting skills, that I think it'd be unusual to find somebody within an organization.

11:22You might find somebody with some of them. So that's why I think that companies will initially need to outsource and whoever they outsource to needs to work with somebody internally to actually build up their skill set. So I think that is, I think this is something that should be in-house. However, until the company can do it in-house, they probably will need to bring people in out of house on like a few hours a week just to help them set up the structure to go forward. That's in my opinion that I think that is because I think it's really going to be really hard to find these people. And also as your program ramps up to pay for somebody full-time when you don't necessarily have full-time work that also is inefficient.

12:09So you want to strive for efficiency wherever possible. So that's why I would think at least initially that you'd look maybe to outsource it and then really understand what your needs are. Yeah, I think that makes perfect sense. I would say that your chances of finding somebody that is really educated on this topic that has the right frameworks and processes in place already figured out and you don't have to figure it out on the fly will get you up and running much quicker while training somebody internal and grooming them for that job and speaking of processes i know you have your process or framework let's go into that let's go step by step and see if an organization does decide to do this themselves what would be the steps you recommend that they would do to bring a person like this in-house?

12:56No, like to, I know you have your process. Oh, through the whole transformation? Yeah. Ah, so from, for me in terms of transformation, so first education, which I shared with you, and then you have your task force and the task force needs to have representatives from each of the departments. And then at that point, apart from them working on the guidelines and policies, which we talked about, I've put together about 200, 250 use cases per department. And what I've done there is over a four-week period, I break those use cases into four different segments and really help them drill down as to what happens in each of those use cases.

13:38Really understanding what happens before, what happens after, what does success look like. Really kind of drilling into the use cases. And at the last piece, after they've really thought about the use case, I ask, is it generative? Is it analytical? Is it repetitive? All that. So then, and then I ask also finally is how much time? How often do you do it? And how many hours is it? So that way you can figure out the use case and which ones are the big blocks of time. And those are the opportunities to really save a significant amount of time for people. so you can really leverage the opportunity cost for a time saved to do something else.

14:18Now, after you do through all these use cases, then you come in and go deeper. And you go deeper within an assessment. You do an assessment based off of content, tools, process, and also the talent. And then once all of that is done, where you have a full assessment based on all these use cases done, at that point, you figure out, okay, maybe these three things are the best way forward for marketing. For sales, maybe it's these three things. For HR, these things. And for customer success, maybe it's these things. And it could be as simple as a prompt. It could be something as a tool. It could be just a different way for them to do the work that they're already doing now and just say, okay, you're doing it like this.

15:08But if you did a little bit of change management and focused on that, that would be a significant saving. So not everything is going to be like an AI tool necessarily. Some of it might just be someone coming in from out of the organization just saying, why is it done this way? If you do it like this, here's an opportunity. I love this. Again, very similar process that I do. I have this fancy Google Sheets file that I've developed that I use with all my clients that basically does everything that you mentioned, meaning it has a breakdown of a gazillion different processes that happen per department.

15:42And companies can go and change them as needed. But basically, it creates these drop-down menus that they can choose from. And then for each one, they say whether it's repetitive, whether it requires human input, whether it's whatever, all these things. And in the end, it's how long does it take per week or month, doesn't matter. And then how much money does it generate if it's revenue generating? And what's the cost associated with it? When most of the cost is obviously human cost. But there's a big difference because some of our clients have offshore employees and US employees. So one hour could cost you$200, but it could also cost you$6.

16:22So the fact that it saves you one hour, it may be not the same thing. So we try to combine both time savings and dollar savings on the savings side, but also look at revenue generating opportunities on the revenue side. and just like you're saying it's not always oh there's an ai for that sometimes like maybe there's a simple way to do this or there are a few things that could be automated without ai there are actually a lot of things that could be automated without ai and then that's another input that goes into there to evaluate okay and i think the biggest difference and i'm actually interested in your thoughts about this when i think about what needs to be automated with or without AI, the difference is the amount of required quote-unquote human input.

17:11Meaning when a process is just repetitive, I don't need AI. There's multiple amazing automation tools out there that can do stuff like this. When it requires some human input, like feedback for something or writing content or creating images or coming up with ideas for a new something, but not as sophisticated as a new business strategy where you want actual humans. So limited level of human input is where I think AI shines when it's combined with automation. And I really want to know what you think about it. No, I agree with that. And obviously different departments, different benefits, right?

17:54so marketing i think marketing is a gimme for this stuff pretty much everything marketing does you can leverage this technology and automation and you have limited risk because you're not dealing with a lot of pii and all that other stuff uh but then i think as you go into sales then it's like what the sales team do they are constantly prospecting or they're so it's a matter of the automation there is, okay, they are on the phone a lot. Let's say certain phone calls are converting, certain phone calls aren't converting. And you've got this playbook that they're in theory, they're supposed to be following.

18:33So you got the playbook, you got the calls that convert, you got the calls that don't convert. The AI here in terms of automation, you say, okay, let's look at the calls that convert versus calls that aren't converting. And let's see what the differences are there. So that's like an automation there. And then let's compare the converting calls against the playbook versus the unconverting calls versus the playbook because maybe the playbook just needs to be updated yeah so that that's again that's an automation going through all the recordings as long as people are comfortable having their calls recorded so certain people they don't like that so then you'd get into maybe uh custom 6s where they're constantly just responding to people asking them for information so it's possible that they can give them a little chat bot or they automate that instead of going into the email that goes into the ticket system that goes triggers this email that kind of goes blah, blah, blah.

19:29Maybe you can just centralize it into a client facing chat to understand here like the five or 10 different things that happen and just try to manage it from this perspective. And then only when something seems to be an urgent, kick that out into some sort of automation. But I think what you need to do is just limit touch points. And if AI can help you limit the touch points, that's a huge win because there's so many tools out there. There's so many tools that you have. Marketing's got a lot. Sales has a lot. Revenue's got a lot. Customer success. If you can limit those number of tools and find a way to do things smarter, then people will be so much more efficient and more effective.

20:18And effective is what we strive for. Not necessarily efficient. Efficient is good, but if efficient doesn't drive the revenue, that's pointless. So he needs to be efficient, which is nice, frictionless, but then effective is actually impacting the bottom line. That is the goal. Bottom line, savings, bottom line, more revenue. I love that. Great points. I want to add one small thing to what you said. And I recorded an episode a while back about the four concepts that I talk about a lot when I speak on stages and with my clients and so on. And one of them is we are so trained as business professionals to look for small incremental efficiencies in small steps of long processes, right?

21:02So we have flow charts and we look at the flow chart. And I'm going back to the example you used, customer service. Okay, so somebody sends an email. The email is converted to a ticketing system. Somebody needs to, some of it is automated, some of it is manual to prioritize those tickets. And it'd be based on the size of the client and what's the urgency and how much revenue it's revenue. And then they do this. And then it goes to different customer service agents based on their skills. And then they need to prioritize their stuff. So we're trained to look for small incremental solutions for each and every one of those steps.

21:36So what if we don't prioritize here, but we use this? The reality is today with AI, you can sometimes skip multiple steps. So that the way we're trained to think as business professionals of looking for those small incremental things is sometimes not relevant anymore. I'll give a very extreme example of what you said. There are companies today that are providing call center agents that actually can speak over the phone, that are AI driven, that are connected to the entire database and history of everything customer service in the company. Meaning they know probably 95 % of the answers to all the questions.

22:18They can answer any question right there and right then. Zero prioritization, zero processes, zero human in the loop, and most importantly, happy customers because they get an answer in five seconds instead of, oh, we'll get back to you within 24 hours. So going back to what you said in the beginning, that evaluation of needs and looking for the right AI solutions for each and every one of them is a very critical step because it's not the right approach to look at every single step in the process and try to look for an AI solution for that because then you might be missing on really huge efficiencies because you're trying to get all these small efficiencies along the way.

23:02A hundred percent. I think this is, AI presents an opportunity to think differently, but you have your goal and the starting point. And everything in the middle could potentially be different, But you have an opportunity to do things differently with less humans along in each step or different humans and along the way that done differently. But I think that is the opportunity is to really think about how work can be done, maybe a little bit different way that will ultimately have huge gains. You're right, because you can you can look to tweak different process and try to find this, optimize this or here.

23:47But just throw it all in there and just say, you know what, we probably can do X, Y and Z. And this is going to make significant gains. But if people just, if you're so close to it, sometimes you can't see it because you're so used to doing it this way. That's why sometimes bring someone like yourself or even myself to say, why? Sometimes just why is it done this way? And maybe it was just somebody that set it up like four years ago and they brought a consultant in that this is how you do it. And that's how you do it. So I think this is a great opportunity for companies to reevaluate how work is done and what is necessarily work.

24:30Because some of this stuff is maybe some of the work we do is, you know what? Because I know like when I'm in the office and I go physically go to a meeting, I feel like I'm getting a lot more work done versus if I'm just going to Zoom call. Because I have to get out of my seat. Work feels different when you're in person versus remote. And I think this AI can also make work different. And I think that different makes some people uncomfortable. I won't take a project that will let people go. I want to empower people. I want people to be more successful. I want people to have more time with their family and friends.

25:06I am not looking to say, oh, let's get rid of that job. We can automate that. No, that's not exactly anything that I'd want to do. I want to look to a way to help people to be more successful. Leveraging this technology, it's a tool. It's not a replacement of people. It's a tool to empower people. And that's my take on that. Beautifully said. I think it's a great summary of everything we talked about, putting it all together under how you need to think about it. Michael, this was really great. I think we touched on a lot of points in a relatively short amount of time. If people want to follow you, connect with you, work with you, know more about what you do, what are the best ways to do that?

25:46Go to lavanderadvisors.com. That's my company. You can check out my book. That book, I just published it last month. Too many hats, too little time. I talk about some of this AI stuff there, but I talk about virtual advisors. So that's a little bit different from what we chatted about today. But yeah, if you go to vivander.com, you'll find me. Awesome. Perfect. Thank you so much, Michael. This was a really important topic. And I think doing it early in the year is even more important because I think people will have time. A lot of people are now looking for how to do this in 2024. And I think the information you provided is definitely going to be helpful.

26:23So thank you so much. Thank you for the opportunity.

26:53Thank you.