I had absolutely no background in technology as well as no at no formal education at all. So I was coming straight from high school when I went into the IT department and started working in IT. So that’s where the the hustling came in, right? And I started slowly doing little side jobs, doing little IT projects, doing little things to eventually graduated with an associates, a bachelor’s, a second bachelor’s, another associates degree, several certifications, a master’s degree, and now I’m back reenrolled at Purdue. [Music] Welcome to another episode of Tech Unhinged, where technology meets human. I’m your host, Rabia Javeed, and today I’m joined by someone whose journey in tech is nothing short of inspiring. With over 20 years of experience across cyber security, data operations, and automation, Brendle Kmer is now leading global tech efforts at Kalanova. She’s broken barriers as the first female IT leader in her department and continues to push boundaries through her IT leadership and excellence. Welcome to the show, Brendle. Thank you so much for that great introduction. I’m very excited to be here today. Well, uh, we’ll just dive into the line of the questions that we have. You’ve had such an inspiring journey from starting in tech to becoming the first female IT leader in a maledominated department. what first drew you to technology and what has kept you passionate about this over the years? Thank you so much. That’s incredibly kind to hear. My journey in technology is a very interesting one that started in animation in family entrepreneurship. Back in the ‘9s, my dad actually owned a commercial technology company and he bought an Amigga 2000 computer with the intention of animating commercials and producing those to sell for his business. Unfortunately, that computer started collecting a lot of dust as he wasn’t able to exactly figure out how to do the coding, how to do the animations. So, when my 10-year-old self came up and said, “Dad, I’m bored.” One summer, he challenged me and offered to pay me to figure out how to use that computer to make an animate commercials that he could sell. So I took on that challenge at just 10 years old, produced a commercial for my dad and then eventually started producing short clips for a major television company. So imagine 10 years old in the summer watching my commercials that I had animated at only 10 years old on the actual television while my dad sat there beaming with pride that he was successful and that his daughter was on TV or at least my animations were on TV. That’s really is what has inspired my journey into technology because it was a simple challenge from my dad. Hey, figure this out. You’re bored anyways. And I learned through that that with technology, there are no barriers. You can be 10 years old, you can be a female, you can be a male, you can be whatever culture or background you come from. If you have a computer, you can code, you can do science, you can do mathematics, you can create programs, and you can automate commercials. It’s just boundless the art of possibility if you’re willing to accept the challenge and step up. I mean, when you were 10 years old, you had you had it all figured out. All right. So, you know, moving to our next question, when you think back to some of the first major automation initiatives you led. What did success look like then? And how has that definition shifted over time as systems got smarter and expectations got higher? You know, I really enjoy this question because it highlights how both professionally and technically we evolve over time and how the art of possible keeps shifting. You know, one of my first automation projects was to solve a data transformation job failure. We had performance capacity issues with jobs running simultaneously which would cause them to fail. The solution was a manual restart. Eventually, we automated the manual restarts. Now when I look back with the tools that we have available today, I would approach this entirely differently. I would use PowerBI to create a heat map to track system traffic and build a holistic scheduling tool so we can prevent the failures before they even happen, not react to them. You know that same expectation shift is also happening in AI. When Amazon first came on board, you had to script predefined prompts to cover all versions of a particular question, you had to literally think of every individual way you could say a question in order to get it to prompt an answer. Now with large language models that comes with predefined language data sets that have already been trained. So now it’s just simply ask the question and get an answer. The evolution of technology has literally changed the definition of what success looks like and it’s forced us into a very agile mindset. The rules of rigidity are broken and now we’re in an environment where creativity can really thrive. Well, uh, Brenda at Kellanova, you’ve overseen massive automation rollouts. You know, while I was going through your bio in from global service now ticketing to SAP data operations, you’ve sort of done a lot. How do you decide what to automate versus what to leave in human hands? That that’s a great question. For me, the decision to automate it always comes down to the human element. We need to understand how work gets done today. What are the pain points that exist for the current team and what’s preventing them from operating at their highest potential? We listen. We gather feedback. We’re talking to process owners, frontline teams, business stakeholders so we can understand where the challenges are with repetitive work, manual rework, and delayed insights. And those are the things that you look to target first when it comes to automation. The goal is to is to enable people to do things faster so that they’re freed up for more of the creativity tasks, more of the human element tasks that allows them to be their best selves. we have once we understand the human challenges like repetitive work, manual rework or delayed insights there, I look for patterns. For example, if there’s a repeatable manual task that’s prone to errors, that’s something I would target for automation. These types of processes are usually high in volume but low in complexity, so they’re ideal for automation. But one thing that’s equally as important is deciding what should stay human. If a process requires contextual understanding, collaboration, or even more importantly, empathy, it’s a sign that automation should support, not replace the human decision-making. At the end of the day, my goal is to elevate people, freeing up time for higher value thinking, improving process quality, and helping teams spend more time on strategic, meaningful work, not repeatable processes. Well, well, that was, you know, uh, an impressive answer, Randall. Moving to our next question. Given that you’ve led global transitions where automation played a key role in driving good success and operational improvements, from your experience, how can automation enhance efficiency while still maintaining trust and team morale? Yeah, like I mentioned in my earlier example, it always begins with a human element because automation isn’t just a technical solution. It’s a people centered transformation. When it’s done well, automation enhances efficiency because it respects and elevates the work that people do. The key is to involve teams early, listen to their pain points, and co-create solutions that makes their jobs easier. I found that when employees see automation as a tool to remove their most frustrating, repetitive tasks rather than something just being done to them, right? They become champions of change. The trust is built through the transparency and morale always improves when people feel heard and especially when they can gain time back for meaningful work when they see that leadership is is focused on making their jobs better not faster. that makes a lot of sense and uh when things are pretty much people centric I believe that there’s a certain room that you’re giving to people and trusting them and you know trusting always sort of leads the way when it comes to operating in high functional teams and leading you know at the forefront like yourself predake system like finance and data governance accuracy is everything I believe how do you build automation frameworks that still leave room for human judgment especially when things go off the script in high stakes environments ments. The challenge isn’t just automation. It’s intelligent automation. You have to focus on frameworks that leverage either AI or data analytics for anomaly detection and pattern recognition so you can flag when things go off script or you’re having quality errors. This can be accomplished through AI, but even more lowcost, low entry type solutions like PowerBI and pivot tables and Excel, those are effective tools where you can do things like heat maps, KPIs, look at various graphs to help identify areas where you need more white glove support. It’s important that you’re constantly doing these quality checks, looking at your KPIs, looking at your analytics to find those anomalies. And you know, more and more I’m seeing partners in the industry that are creating these unique solutions to solve this even better. They’re utilizing AI to create individualized and specific solutions that can target some of the areas where accuracy needs to be really high, but there’s a lot of room still for that human element and that human judgment. You know what? At the end of the day, nothing will ever fully replace the value that you get from human judgment. Even as we continue to see AI evolve, it will always be a human element that takes precedence. You know, I I I saw that you’re currently pursuing advanced AI education at Purdue. How is that shaping your perspective on the next wave of automation in IT and what emerging capabilities excite or concern you the most? You know, I am so excited about my journey through Purdue to learn about artificial intelligence. Their program is very detailed and they have a lot of examples that kind of tailor me in, get me excited, but then also concern me. So, just last week in our live class, we talked about bias in weights and how they’re how they contribute to the answers and the prompts that you get with artificial intelligence. One of the things we talked about was how there was an artificial intelligent bot, right, that was deciding whether or not mortgage loans should be approved. Well, the interesting aspect of this was that it was actually using whether or not your cell phone battery was fully charged or not fully charged as a bias, as a weighted measure to determine whether or not your mortgage loan should be approved. To me, that’s mind-blowing, right? Because you’re taking something like the cell phone charging and using it to make a decision about mortgage loan and using that as a risk measure. For me, that concept blew my mind, you know, and it’s critical that you think of those types of small aspects when you think about artificial intelligence. But you know what else? That’s where I also get concerned. So when you talk about, hey, what concerns you the most? We have to be equally mindful of the risks around data privacy and accuracy of information. Coming from my data my data governance background, I’m very aware that the data feeding models has to be accurate in order for the output to actually be accurate as well. You can get a lot of misleading and even harmful information if that’s not done correctly. You know, one of the very first complaints with chat GPT was that it often failed on basic mathematical models like predicting race times or averaging bowling scores on a couple of games. Now, while that may seem very minor in its implication, imagine if instead people were using Chat DP to calculate medication dosage. This is why as an IT professional, I’m both excited about the potential for AI, but I’m also very mindful of the things like biases, weights, and measures, data privacy, and data excellence. But then what makes it makes this entire thing really impressive is that you know you you get to practice all those things right away because you’re already in that senior managing position, right? So I love it. Yeah. Yeah. You know, I’m so glad for you. Taking me to my next question. So, uh, rental automation can flatten hierarchies, removing layers between action and insight. As someone who’s mentored and managed global teams like yourself, how do you help people stay connected to purpose when tech starts taking over the tasks? That’s an absolutely great question. Automation can absolutely flatten hierarchies, but it doesn’t replace purpose. It amplifies our need to stay grounded in it. I always encourage my team to center on the why. Why are we deploying this tool? Why are we automating this task? How do we stay aligned as a global organization? You know, at Kelanova, our purpose is very clear. We feed and we nourish people to help them be their best. Whether it’s a wholesome snack or a breakfast food, that mission drives everything, including how we use technology. When teams stay anchored in a shared purpose, automation becomes an enabler, not a disconnect. It allows us to focus more on impact and less on process. While we stay connected to each other and the people we serve, you have to always stay centered on your why. Whether you’re doing automation, AI, or any technology impact, that’s how you stay connected with people. So Brendle, with your pretty impressive experience leading global teams and managing external partnerships, how do you maintain accountability and cultural alignment when automation creates distance between action and the people behind it? You know, it’s not just a company culture, but it’s also the people culture. So a company culture is formed by its people and its purpose, right? Automation can streamline execution. and can streamline processes, but it’s not a substitute for human connection. I make it a point to tie automated outcomes back to business impact and to recognize the teams behind the scenes who maintain those systems. Whether it’s through regional forums, shared dashboards, or storytelling, I aim to reinforce that every task, even automated ones, contribute to a bigger purpose. That’s how we keep people engaged, accountable, and aligned across borders. Again, like I mentioned earlier, it’s centering on that why. Why are we doing these things? And why as a team are we coming together and what is our ultimate purpose? When teams stay anchored in a shared purpose, automation becomes an enabler, not a disconnect. It allows us to focus more on impact and less on process and technology. It allows us to stay connected to the people that we are ultimately serving and feeding. The last and very important question as a leader learner and advocate for women in technology. What advice would you give to future leaders who want to blend you know technical fluency with emotional intelligence in an increasingly automated world for future leaders especially women in STEM. I always say speak up, stay curious and stay connected on your purpose. The STEM field can be intimidating. You know, as Rabbia, as you mentioned earlier, I was the only female in an entirely maledominated department. That was very isolating, but I stuck to my purpose and I centered on my why. I loved it. I loved technology and I continued to use that passion to continue to grow in my career and my purpose. In a world where the IT environment is always accelerating and changing, that’s where we stay grounded to our purpose and our why. If I can leave you with one thing, it’s say yes to all challenges and remember to lead with empathy. Well, Brendle, thank you so much for sharing your journey and your insights. You know, it’s clear that the future of it isn’t just about systems and tools. It’s about people like yourself shaping it. Thank you so much. Yes. And thank you so much. This has been an absolute pleasure. And to all the women considering a career in STEM, do it. Say yes. Speak up. Say yes to those opportunities. And always stay curious. Well guys, we had Brendle today with us. And for all of you, if you enjoyed this episode, do not forget to subscribe, share, and leave us a review. And remember, here on Tech Hinch, we don’t just talk tech, we talk about the heart behind it. Until next time, stay curious and stay human. [Music]