Leveraging Artificial Intelligence In The Sales Motion With Jeff Mize
AI helps businesses thrive by making things easier and more efficient. Innovation is the key for any business, and incorporating AI is very beneficial for sales growth and business prosperity. Chad Burmeister talks with the CEO at PostProcess Technologies, Jeff Mize, about tools and ways of leveraging artificial intelligence into products and sales processes. Jeff shares his extensive professional background, what his company does, and the comprehensive system they have in advanced technology, data analytics, and machine learning. He explains different areas in AI and strategies to eliminate redundant tasks that humans are doing today, emphasizing his heavily focused mindset on artificial intelligence. He also shares powerful insights on the value of AI from a human capital perspective driving a vitalizing and energetic spirit for companies.
Listen to the podcast here:
Leveraging Artificial Intelligence In The Sales Motion With Jeff Mize
I'm here with Jeff Mize. He is the CEO of PostProcess.com. Jeff, welcome to the show. I'm glad to have you here.
Thanks, Chad. I'm excited to be here and I've been looking forward to this conversation.
It sounds like you may be one of the subscribers of the show and listened to a handful. I hope you're enjoying the show and we're glad to have you as a guest. I like our audience to get to know who's talking first. If we rewind the tape and go back to when you were a youngster, what got you up in the morning? What were you excited about? Try to help us connect the dots between then and now, how did you get to here?
I had three primary interests from the time I was a little boy. Music, electronics and sports. From a music perspective, my dad is a musician. When I was a little boy growing up on the Southwest Side of Chicago. My dad is in a jazz trio. I would practice in our basement during the week. I'd go to bed at night, listening to them play and started piano lessons with my dad's piano player at the age of six. By the time I was in high school, I was practicing four hours a day. It’s a real love for piano, jazz and music overall.
Saving your time is one benefit of AI. It allows us to build essential relationships and be successful as a company.
The secondary was electronics. I enjoyed Math in school. For those of us that are old enough, I had a 50-in-1 Radio Shack electronic kit. I spent a lot of time playing with that. Probably some of the most fun I had around 10, 11 or 12 years old was learning how to turn the gain up on my Citizens band radio so that I could come through the TV and radio of neighbors down our street. In fact, my handle on my CB radio was Piano Man.
The third area was sports. I played a lot of sports growing up. I still lift weights several times a week, try to get a couple of Peloton rides in. It helps me keep a clear head. Thinking about those three areas of music, electronics and sports, they all carry through to college. I studied Electrical Engineering and had my undergrad from Illinois. I played in one of the Illinois jazz bands. Due to all the weightlifting, I was a bouncer at a campus bar. The cool thing was that I had three pretty distinct groups of friends in college with very little overlap. There was never a dull moment.
How do you think those three things tie into the work you're doing? I don't think you're doing any sounds or music through PostProcess.
No, although we have quite a few talented musicians. Both at our headquarters in Buffalo and then internationally. In my junior year in college, I was at a crossroads. Should I pursue music? I was a good piano player but I wasn't great. Should I finish my Engineering degree? Through strong coaching from my parents, I decided to finish my Electrical Engineering degree. It was the right thing to do and it was great advice. I still play once in a while. I haven't played professionally in a long time but having that technical background has proven very helpful. I've spent the last many years of my career taking analog processes and digitizing them, which I first got to start in that field back in 2001 at Navteq. I didn't call it AI at that time but it was a combination of data analytics, machine learning and artificial intelligence. My last three startups have been very heavily focused on artificial intelligence.
My son is in Electrical Engineering at Colorado School of Mines and he said he's either debating between working at the golf course again or on an internship. If you guys are doing internships, he might be a good person.
We absolutely are looking for interns all the time, as well as full-time engineers. I don't know how much time he spent in Buffalo but it is a fun place for a college kid to spend a summer. You haven't sent me his resume and we're always looking for electrical, mechanical, computer science engineers.
He's on the fence between Electrical and Computer Science. He may end up doing both. Tell me about artificial intelligence. You said you did a little bit of artificial intelligence at Navteq. It sounds like, within PostProcess I believe that you're leveraging Einstein in the application. Tell us about how you leverage AI in your product.
I break it into two categories. 95%, if not 98% of artificial intelligence machine learning centers around our solutions and product. Just to back up a little bit. At PostProcess, we take care of the third step in the overall additive process. Design, print and post-print. The first two steps of design and print are digitized and very well-connected. That third step, many years into the industry is more of to finish Arts than Science.
AI is very interesting to explore because it's very difficult to replicate that manual process in terms of repeatability and consistency.
If Daniel Hutchinson, the Founder of PostProcess was on here with us, he would say that we are on a mission to digitize the tribal knowledge of the technicians that are doing a good job in terms of finishing parts but in terms of repeatability, consistency throughput, it's very difficult to replicate that manual process. We're focused on digitizing that third step in the process for a variety of reasons. Two of the primary drivers are the first time right and utilizing machine learning and artificial intelligence to minimize the amount of experimentation and breakage.
In some cases, for example, in the medical market, some of our customers, when they were using traditional tools and manual labor had up to a 50% breakage rate. We can eliminate breakage once we dial in the recipe for a particular 3D-printed part. The second area is leveraging the power of computing to eliminate as much of the redundant tasks that humans are doing and that they find mindless and treacherous, as you all know, and allowing them to focus on higher value-added activities.
I talked to another person on the show and they take aerial photographs through helicopters, drones, airplanes across all of the different power lines in America. What they find is there's something like 5.1 million trees and foliage around them. There are only X thousands of humans who could look at them so they ended up seeing only 1% or 2% a year. California had a $7.4 billion ask to hire more people to go look at the power lines. This company builds a second worldview of the power lines and then they make some estimations with AI and predictions of what's going to happen. He said, "You can get 100% coverage for a small sliver of the cost that you would normally invest. It makes the world a safer place. It's lower costs. There are a lot of benefits. Thinking in terms of that level of impact, what would you say if your product didn't have AI and machine learning, would you even be a company? What's the value from a human capital perspective?
It would be very hard to have any differentiation or any sustainable competitive advantages. We'd be another one of those traditional tools that have been in use for decades, if not longer. Let me share two examples. Going back to my last startup Climate Corporation, we were the first company to digitize the farm. In that situation, it's similar to power lines. We would ingest. We had this phenomenal team of data scientists based in Silicon Valley that built a platform that could ingest data from thousands of sources and we would process terabytes per day.
It's something that the human is incapable of doing. We take that data. We'd analyze it, provide insights and recommendations to farmers. We learned a valuable lesson there on what we call the data science value stack. That data, which is the new oil as it's often referred to is very important to have and the more of it that you have the better but data on its own isn't valuable. Analytics is good but most customers aren't willing to pay for just analytics. When you start providing insights and then recommendations that's when you are able to solve major customer pain points, also monetize the data analytics and artificial intelligence. Bringing it to nowadays’ PostProcess, we're focused on several different areas when it comes to AI. Data analytics, machine learning, AI blend together overall.
I'll share three examples. One is machine behavior. Secondly is operator behavior and the third is recipe generation. If we did not have the data analytics and software capabilities that we've built and continue to expand rapidly at PostProcess, we would understand how our machines are behaving. One great example of leveraging AI is preventative maintenance. If we know that a particular component, let’s say a pump, which is an integral part of several of our solution and it is approaching its end of life. Having one of our application engineers go out and change that pump ahead of it failing increases the amount of customer uptime.
The second example would be operator behavior, by tracking how the operator is doing button pushes, the settings they're using, screen views, we can turn that data into insights to maximize operator productivity. It’s something where AI excels versus doing traditional human analysis falls short. The third area of recipe generation is we're collecting data on how our particular part finishing recipe is performing and we could make real-time changes to further optimize the process or as we collect all of this different information or a new material comes out or a new print technology comes out, we can have based on doing the data analysis and the AI has a recipe. That's probably pretty much dead on versus all the experimentation that goes nowadays with the technicians trying to finish these parts with manual labor and using traditional unconnected tools that don't have a data element.
It reminds me of a biotech conversation I had with someone. They worked with companies in phase 1, 2, 3 clinical trials. Traditionally, they would have to go out and identify what's the population that could be served by this. Some new mixture and bio. That was hard. Which population should benefit from it? How can they narrow it down to the top two? With AI he said, "Normally, it might take 2 to 3 years to do something like this." Now they're able to collapse it down to literally 1 or 2 quarters. They can just trial things a lot faster and get things to market more quickly. There's very much parallel to what you guys are doing in terms of cutting down the cycle time. Why waste all that money when you could leverage machine learning and AI to do it better, faster, cheaper?
Utilizing machine learning and artificial intelligence minimizes the amount of experimentation and breakage in some cases.
We also measure attended technician time versus unattended. Through leveraging the data science component of our offering, we're able to allow the technician and then sometimes engineers to go off, do much higher-value-added activity versus holding apart and using a wet blaster to clean that part off. They're the attended versus unattended technician time was one-to-one whereas we're able to reduce the typical attended technician time in the 80% to 95% range. Because of the software and the machine learning components, we're continuing to improve that, increasing the throughput and speeding the time to market.
One of the key benefits of additive manufacturing versus subtractive manufacturing is speed to market. What we're finding is with the growth and volumes, that third step of post-printing is becoming the bottleneck that's causing things to not be as fast as they could be. The automation component is absolutely critical as we go forward and we see more companies starting to use additive manufacturing not just for prototyping but also for production.
That reminds me of another interview I did where the population is aging. There are 10,000 people that turned 65 a day in the United States. He said that 70% of those people need to hire someone to monitor what's going on. That makes me think of the attended versus unattended. Typically, one attendant that comes around to houses could maybe monitor 2, maximum of 3 people over 65. Think about when you go through the TSA. When you put your arms up and it shows you if you have a red dot on your shoulder, that's what they're putting into these houses. It's not an actual physical video but it monitors for, “Did you fall down in your house?” They've deployed 1.2 million of these and now a human could monitor 7, 8, 9, 10 65-year-old plus versus the standard 1 or 2.
It becomes a force multiplier.
We've talked about AI in your product PostProcess. What about from a selling perspective? Have you looked at leveraging AI at all in the sales motion? There are many tools with email, voicemail and social. How are you selling this? Do you partner with channel partners? What's the sales motion look like?
That as much as we should be doing based on the deep understanding we have of the technology, applying it in our solutions. We use Salesforce. Our head of marketing, Diana Robbins is fantastic at ensuring that our sales team provides Accurate, Complete, Consistent and Timely data, which we call ACCT. As a result of that, we started to use lead scoring, the basic version of Einstein, which is helpful. We were doing a lot of that on our own and trying to interpret a lot of data. Having a machine do that to supplement human interpretation is definitely beneficial. If you would go deeper with Einstein or MadKudu on the show, what would be the pros and cons? Do you have an opinion?
I wouldn't necessarily say I have an opinion on that. There are many tools these days and what I'm finding is just like Siri or Amazon Alexa, you could list out a book full of different technologies. I've been speaking in front of audiences and I say, "Raise your hand if you're using AI in your sales motion," and a couple of people raised their hands timidly. Alligator arms. You then say, "Is anybody using ZoomInfo?" Eighty percent of the hands go up, "You're then using AI, you just don't know it."
There are a lot of powerful tools out there. When you've never heard of Balto software. If you had a team that's on the phone doing customer success calls all day or upsells, cross-sells then this tool can listen to the conversation and serve up on the right-hand side in a sidecar what to say next. If they say something about your competitors, for example. It's real-time call coaching powered by artificial intelligence.
AI is not going to fully replace humans. It helps with tasks and frees up time for more valuable things.
Another one is we're using an email tool. We had a person go in and check all the emails before they push send. It turned out 98.9% of the time the AI got it right. It was human attended and then our partner said, "You could turn it on automatic and we'll help you solve for the 1% by changing a couple of the emails that you send out." There are many. I know of Einstein but I have not heard of the other one. Maybe I'll have to reach out to the inventor and have them on the show.
The other areas where we're exploring, utilizing more AI is training so that there's easier and faster access to information and also have our people going through the training and we have to through it with a go-to-market strategy. We have channel partners that we need to train along with our direct salespeople. Having them go through, we use Litmos as our learning management system platform but I think there's a lot more we can do from a training perspective.
The second area would be Insight Sales. One of the opportunities there is to implement things like Smart Chat. Diana and her team are in the very early stages of determining what tools are available. The one thing I have learned all my years in leadership, most of them in the sales and marketing arena is you need to be careful that the tool doesn't become the job. There are many out there that we want to do an assessment and try to figure out what's going to give us the biggest bang for the buck at this stage of the company which we're in massive scale-up mode. The third area is upselling and cross-selling, a more intelligent and effective approach in this area as well. I believe there are some developments there that we could apply at PostProcess that would accelerate our growth and velocity in our pipeline.
There's a customer of ScaleX called MicroMain. They have a sales team of a handful of people and they were talking to their customers every often. Probably like a lot of companies. You get to the renewal period. You're 60 days ahead and, “I better talk to this customer.” They ended up using what's called Agent-Assisted Dialing to ensure that they talk to their customers more frequently than that. More like once a month and worst-case is once a quarter. It's amazing because you think of your customers as a bunch of plates that are spinning and you never know if it starts to slow down. A lot of times, if you send an email or you do a chat, you might not know but if a human-to-human phone conversation is automated and now I'm definitely going to talk to you once a month or a quarter, no matter what my phones are going to keep calling you until I talk to you.
I used to do that with my sales team on the East Coast for a company and we called it National Account Bingo. I said, "There's a CEO, CMO and CRO. Those three roles may have a need for our product." One or all of them may have purchased. Let's try to get every single one of them on a call date and timestamp it. At the end of the quarter, everything clears and we start over again or play the National Account Bingo again. There's some automation in these areas that are continuing to do well whether it's email, social or voicemail drop. There are many things you can do nowadays that are pretty magical. Last question for you. It's the future. You can talk from two perspectives. One is inside of your product and one is in the sales motion. Where do things go a few years from now on both fronts?
Let me touch first on our products. One thing we've done is expanded our board of directors. A gentleman by the name of Dr. Usama Fayyad was one of the world leaders on experiential AI has joined. Most of our discussions with Usama have been around what we're doing from a product perspective but in part by reading to some of your shows, we've been talking beyond just the product itself. One of the things that Usama talks about is that if you can take the output of the last product in our case that we've finished and had that serve as an input to the next product, that short cycle in terms of being able to improve the process will allow us to continue to extend our lead in the market overall.
A variety of different applications we're working on from an AI perspective and a machine learning perspective. It's the biggest area of investment for our company overall on the technology side. When it comes to the sales and marketing side, I also believe it's a must-have to stay competitive. Replacing the repetitive behavior also the ability for individualization is definitely huge. The more we can replace the mundane tasks that a computer can do and free up time for any of our customer-facing employees whether it's our outside sales team, application engineers, insight team, our C-level executive team and to build those relationships and trust. I often get the question, “From being in the data science business for the last years, do you see a day when AI is going to replace humans?” I never see the day when it's going to fully replace humans. I do see it replacing certain tasks.
Like with our business on the technical side, the more time we can free up for a technician to not be standing apart, let one of our solutions do that automatically and let them go spend that time on a much higher value activity, the better. The more time we have to understand customer's problems, establish strong communication channels at different levels across different departments and build that long-term mutually beneficial relationship. That's where I see a big benefit of AI freeing up the time to allow us to do that and build those relationships that are essential to be successful as a company.
In the opening dialogue of the book, Dr. Joël Le Bon says, "In sales, time kills deals. In modern sales, AI kills time." That's exactly true. What takes years can take minutes. What takes 10 people can take 2. It focuses on mundane tasks, stuff that not a lot of people love to do. Data entry and converting voice-over to texts. There are many things that can be done in an automated way. I think of my brother, who's an anesthesiologist. Would you send him out to the parking lot to say, "I can do your anesthesiology."
You don't put the highly paid person on the task that could be done by a computer. That's what a lot of people have to get their arms around. When they realize it's not going to cut out a whole host of people. It's going to open up new markets cause companies to create entirely new businesses. I've heard people say that, “AI will be 5 to 10 times bigger than the internet.” I wholeheartedly believe that and I don't think that the world's necessarily seen it that way yet.
With the hundreds of customers that we have around the world, I can't think of one that has reduced its force as a result of implementing our automated solution. They've taken those employees and put them on higher-value-added activities. As a personal anecdote, I implemented ClickUp. It's a productivity software tool to keep track for me, much better track of how often I'm touching base with key decision-makers at our customers, channel partners and vendors.
I did it all manually on a Google Spreadsheet. I implemented ClickUp and I thought, "I've been in technology my entire career. Why did it take me so long to take that mundane task out of entering much data and trying to have a system that reminded me when was the right time to contact a particular customer?" With ClickUp, it sends me automated reminders. That makes me look much better organized than I am.
What a great conversation. We've been talking with Jeff Mize, the CEO of PostProcess. Jeff, it’s great getting to know you. Thanks for sharing so much about how your company leverages AI both on the sales side as well as within your product. Thanks for your time and for being on the show.
Thanks, Chad. I appreciate it.
About Jeff Mize
Jeff Mize, our CEO, brings an extensive background in rapidly scaling technology startups and creating fast, flexible and fun environments – as well as mastery of the power nap. He was the commercial leader behind the rapid growth of Climate Corporation (digital agricultural platform) and NAVTEQ Corporation (digital maps), selling for $1.1B to Monsanto and $8.1B to Nokia, respectively. Jeff received a B.S. in Electrical Engineering from the University of Illinois at Champaign, so he can hold his own in meetings with our really smart Engineering team.