Trent Mayberry of UST Global: “Sometimes simple is better”

Sometimes simple is better. The design principle “keep it simple” should pervade more and more products and services in the future. Very complex interfaces are giving way to touch screens and Natural Language interfaces. I recall working on software developed by one of my colleagues that was functional, but complicated. The effort to maintain it […]

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Sometimes simple is better. The design principle “keep it simple” should pervade more and more products and services in the future. Very complex interfaces are giving way to touch screens and Natural Language interfaces. I recall working on software developed by one of my colleagues that was functional, but complicated. The effort to maintain it was significant and we ended up re-writing it and simplifying it in order to make it more effective.

As a part of our series about cutting edge technological breakthroughs, I had the pleasure of interviewingTrent Mayberry.

Trent Mayberry is UST Global’s Chief Digital Officer responsible for creating disruptive digital transformation for the company and its customers. Trent leads the Digital Business Group aiming at capturing business values through digital innovation in the financial services, healthcare, retail and communications industries.

Trent held several senior leadership positions in strategy, client delivery, and technical development. Before joining UST Global as CDO in February of 2019, Trent spent 29 years at Accenture as Managing Director, Digital in North America and Asia Pacific, and Managing Director, Emerging Technologies. In his role, Trent led digital transformation teams specializing in digital architectures and large-scale implementations of cloud and analytics solutions. He began his career as a Software Developer for IBM in the satellite division.

Trent is an industry thought leader, author, and expert on digital transformation, and often shares insights through conferences, board-level discussions, and publications. He leverages his experience in rapid innovation and data-driven experimentation with fortune 500 companies, to help scale delivery programs, and deliver high-impact customer engagement and product differentiation strategies. Aside from his professional responsibilities, Trent is a digital mentor for startups in Asia and the Middle East, including support for Female Founders, an independent non-profit organization committed to promoting gender equality.

Trent holds a Bachelor of Science degree in computer science from the University of Illinois. He is currently based in Chicago.

Thank you so much for doing this with us! Can you tell us a story about what brought you to this specific career path? Can you share the most interesting story that happened to you since you began your career?

I’ve always had a passion for finding creative ways to solve meaningful challenges for people and their relationship with technology. I remember creating a multi-media application to explain complex financial products to banking customers. The project took months and required our team to create a 3D gaming world to deploy on a kiosk in a bank branch, which pushed the capabilities of technology at the time. The application wasn’t delivering results in the early trials that we expected, so I visited one of the pilot branches. I overheard an employee intercept a customer looking for the kiosk, and let the customer know that they would solve the issue much more effectively than the technology. So, with 20 seconds of conversation, the employee found a way to prevent the technology from ever reaching the customer.

I realized that the technology was seen as a threat to the employee, and that all stakeholders must see benefits for a disruptive change, or people may misuse or avoid the technology.

Can you tell us about the cutting edge technological breakthroughs that you are working on? How do you think that will help people?

At UST Global, we’ve been working on helping companies better leverage Artificial Intelligence and Machine Learning. We see these as essential tools to offload complex tasks and free up people to work on more nuanced services for the benefit of customers. We’ve embedded AI/ML into most of our products and platforms. We’ve used it to parse conversations, automatically identify action items, and generate actions that will improve customer service. More recently, we’ve used it to help companies alter their demand forecasts in real-time, based on multiple variables in the supply chain, enabling organizations to rethink retail supplies in response to daily updates on the local pandemic numbers. We are working to enhance our developer platforms to bring data scientists and developers onto the same platform — making it easier to embed AI into the development process.

How do you think this might change the world?

As more and more companies struggle with the volumes and veracity of data, AI/ML will be embedded in many products and services — from credit worthiness scores, to product recommendations, to real-time decisions self-driving cars make that must keep people safe. Companies will use AI/ML everywhere to simplify processes and deliver new value to customers and employees. This will drive demand to tightly integrate software and analytics development into a single platform — for example DevSecOps and MLOps.

As AI is combined with Edge Computing, and in turn embedded on more and more smart devices using advances like TinyML, we can expect decisions to be made at the edge more quickly and efficiently than ever before.

Keeping “Black Mirror” in mind can you see any potential drawbacks about this technology that people should think more deeply about?

This edge-based decision making that is driven by machines, not people, also introduces risks such as machines making decisions that are logical, but not always appropriate. I can also imagine exchanges of “insight” between two AI-enabled devices that may not be well understood or predicted by humans, causing unplanned issues. Consider AI/ML algorithms used to identify health issues for customers using wearables and enabling these wearables to make recommendations to adjust the electrical behaviors of a pacemaker based on the data and the population norms, rather than personal norms. Depending on context, this could be quite dangerous for the individual. How do we embed human insight and awareness into the AI so that a preventative intervention isn’t triggered at an inappropriate time? We need traceable AI and human judgement working in tandem to ensure that we train our AI to interpret and act effectively for people first and foremost.

Was there a “tipping point” that led you to this breakthrough? Can you tell us that story?

I recall an airplane with software-driven decision making that took decisions based on a faulty sensor data, which the human pilots were unable to override. The consequences were catastrophic and led to lengthy investigations and tests to resolve the issue. There was also an instance where an AI agent that helped screen applicants among a large pool of candidates had an undetected gender bias that no one had predicted at the start of the development cycle. Both issues highlighted the challenges in adequately training and supervising software using AI/ML.

What do you need to lead this technology to widespread adoption?

We will need a simpler way to train AI/ML algorithms — by decomposing complex problems into simpler learning steps requiring less supervised learning; we’ll need traceable solutions that enable human verification and corroboration; and we’ll need software frameworks and guidelines to verify ethical and appropriate decisions are being made.

What have you been doing to publicize this idea? Have you been using any innovative marketing strategies?

At UST, we’ve been partnering with leading researchers in academia and the industry to make rapid advances in Natural Language Processing and traceable decision making. We’ve been putting CI/CD controls into Machine Learning Ops and harmonizing them with our DevSecOps platforms. We’ve also created open dialogues with industry leaders to surface challenges and share breakthroughs in this rapidly evolving field.

None of us are able to achieve success without some help along the way. Is there a particular person who you are grateful towards who helped get you to where you are? Can you share a story about that?

My mentor, Glenn, helped me step beyond my relentless focus on emerging technology to focus on delivering business value. He pointed out that there are many interesting gadgets in the market, but real impact comes when technology is applied with purpose. It has led me to put more focus on problem definition and needs analysis, before exploring potential technology solutions. It has helped me put technology to better use in the real world.

How have you used your success to bring goodness to the world?

At UST Global, our goal is to transform lives. I am collaborating with my colleague Stephen on finding a way to use digital signals, AI/ML, and trust-based frameworks to enable safe data sharing in local communities — with the goal to help small and medium businesses be more successful — thereby improving the resilience of the local community. We want to help companies derive greater value from the sharing of data and make more resilient businesses and communities. It will also allow investors to trace the use of their investment dollars for a specific purpose — such as environmental or social causes. With such information available, funds can be channeled to worthy organizations more easily, which may be faster at bringing out meaningful change than regulation or historical reporting.

What are your “5 Things I Wish Someone Told Me Before I Started” and why. (Please share a story or example for each.)

  1. Sometimes simple is better. The design principle “keep it simple” should pervade more and more products and services in the future. Very complex interfaces are giving way to touch screens and Natural Language interfaces. I recall working on software developed by one of my colleagues that was functional, but complicated. The effort to maintain it was significant and we ended up re-writing it and simplifying it in order to make it more effective.
  2. We learn through adversity — so failing fast is essential to learning. I’ve seen organizations with complex approval processes try to innovate. The challenge was the effort to secure an investment was so great that the team did inordinate amounts of work to guarantee when they asked for money that it would be successful. That team struggled with breakthrough thinking. A colleague and I had an idea to simplifying parking meters and go fully digital. From idea through design through development and intro production took 2 days through a low code, assembly approach. It enabled us to test out the idea and validate feasibility very quickly, at a low cost. Not everything worked at first, but we were able to experiment quickly and refine the solution before making a larger investment.
  3. Know your audience. Everyone has a different frame of reference, and often, to convince someone, you need to speak in their language. The work should be on the presenter — don’t share a bunch of technical details with a non-technical audience as they won’t appreciate it. My team recently worked on a proposal, where we went and interviewed the end users and documented their challenges and needs before we wrote the proposal. The evaluation committee had not heard some of those issues from their own users before, and it opened up the team to different priorities than were originally requested. Understanding a need from your customer’s perspective, or your employees’ perspective, is essential to capitalize on many opportunities.
  4. Everyone has opinions, but teams need goals. In today’s world, decisions are often made at the edge. That means, decisions will be made at the point closest to the need and data will be needed to justify that decision. Goals need to be communicated and agreed up front, and decisions need to be supported by facts, if they are to have the greatest chance to contribute to the goals set out by the organization. A lot of automation activities benefit from this principle and from avoiding long chains of present-review-approve cycles.
  5. Take care of your people. Change is difficult for most of us — and the demands we face continue to accelerate and often more nuanced. Diverse teams are better able to understand those nuances and will certainly come up with better solutions. Diverse teams will need multiple approaches to maintain high performance — challenging work, public feedback, freedom to learn, and stress relief. We all need to work together to take care of each other, so that we can be ready for the next seismic shift we may face. I like the principle of Servant Leadership that is emerging in modern management frameworks — the leader must be a servant to the team — equip them with the tools to be successful, listen to their needs, trust the people on your team — and good things will happen.

You are a person of great influence. If you could inspire a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger. 🙂

Celebrate differences — diverse teams create better solutions more quickly than homogenous teams. Assemble multi-disciplined teams, from different backgrounds. Share data, insights and uncertainties — as transparency will help teams co-create outcomes more effectively.

This has never been so apparent as when many of us moved to remote working. Our team members had to find new ways to collaborate on activities, while being at home, and simultaneously being a worker, a parent, a teacher, and a contributor. For me personally, I’ve enjoyed being able to spend more time at home, speak with my wife in person rather than on the phone, and have shared dinners together every day. It has made it harder to maintain distinct boundaries between work and life, but I am so grateful for the opportunity to do so. We all handle this remote work differently, and some of the best advice I’ve gotten in managing this challenge has come from people with very different circumstances than my own.

We’ve been re-writing our advice to development teams doing agile — shifting from distributed teams to distributed team members. We’ve tuned our approach to daily standups and collaboration for this new paradigm.

Can you please give us your favorite “Life Lesson Quote”? Can you share how that was relevant to you in your life?

“Bad news doesn’t get better with age”. I remember early in my career, I was working on a difficult project, and realized that one of the teams had spent quite a bit of effort in a set of solutions not in our scope. I really didn’t know how to recover the schedule and budget and hesitated to bring it up to my manager until I had a solution. I recall being nervous in bringing the issue up two days later, but he thanked me for sharing the issue and helped me resolve it within the hour — much less time than I had already spent on the less effective solution. He smiled, and said at his level, he gets issues like that every day. It was a lesson in humility and transparency that I will never forget.

Some very well-known VCs read this column. If you had 60 seconds to make a pitch to a VC, what would you say? He or she might just see this if we tag them 🙂

Last year, I was working on a concept for a fleet of inspector drones for bridges, buildings, trains, and more that could evolve to also do minor repairs. That idea hasn’t gotten off the ground yet, but I am certainly open to collaborating on the topic.

How can our readers follow you on social media? @pmtrent on Twitter

Thank you so much for joining us. This was very inspirational.

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