As we enter 2024, IT leaders will be at the forefront of driving growth and innovation. And we know the path from strategy to growth requires vision, agility, and deep knowledge of this evolving market. Recently Tech in Motion hosted a roundtable discussion of IT strategies for seizing transformation opportunities in the year ahead.
Industry experts Mark Tierney Co-Host @ The Wages of Cybercrime Podcast, Benjamen Pyle CTO @ Curantis Solutions, Stephanie Rollis Chief of Staff, Network Product Solutions @ Ericsson and John Rosenbaum CIO @ Motion Recruitment Partners shared their insights for navigating recent market shifts, prioritizing investments, avoiding common pitfalls, and cultivating a highly skilled workforce while maximizing AI returns and so much more.
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Tierney: What are some of your top IT strategies for 2024?
Rosenbaum: Strategy is not a one-size-fits-all. We have an array or portfolio of things that we are working on around data, maturing our legacy technologies, and optimizing our business processes.
Also, some of the things we're doing to grow the business such as using AI to help automate a lot of the processes and help us do more with the resources we have.
Finally, we have a strategy around transformation. What are we doing to transform our industry? What are we doing to transform our company? What are we doing to get new revenue and new market share?
Rollis: Our strategy is always to make our networks perform better. Number one focus is cybersecurity. The threat landscape is constantly evolving, and we need to ensure network security. Number two is digital evolution. Using emerging technologies like AI to make informed decisions about how to automate our processes, not just our networks but the processes we use to run our businesses
Pyle: We are focused on growth and growing our businesses. During COVID we leaned into technology, migrating to cloud, and adding to our platform. This year is all about how to use data. How can we use AI, and how we can use Amazon tooling to make the most of that data, and not necessarily from purely analytics, but how can we enhance user workflow and patient experience, as well as optimization.
Tierney: What are some specific projects that are exciting in your spaces?
Pyle: In our industry billing systems are pretty antiquated, so we are leaning into event-driven billing systems. On top of that it is our data strategy, to drive new insights focused on workflow efficiencies and making patient experiences better.
Rosenbaum: We are always thinking about what our business can handle and what are we able to provide within that framework. We believe that if we spend time doing that, it is going to allow us to mature and be able to deliver some of the things the business is demanding.
We're a company that's grown rapidly over time and our data has been siloed in a bunch of different systems. There are duplicates, there is dirty data we can't do anything until it's cleaned up. It’s not glamorous but slowing down to take a look at the data quality and making sure we know how to liberate that data so we can do things with it, is a big Initiative for us.
The second thing is that we have some great software partners embedded and embedded within those products are some new tools around generative AI to improve candidate sourcing and matching.
Keep in mind the “human experience” of hiring has not improved. You have an immense responsibility of using AI, but not losing touch.
Our clients come to us to find the best person. We want to offer them choices and try to balance efficiency without losing the human touch. We are not wanting to replace recruiters. If it is searching for a database or sending an email, we want that to go faster. On the other hand, we don’t want you to be communicating with a chatbot. How do we make emails personal, without ignoring the efficiencies of marketing automation tools? I don’t have a perfect answer.
Rollis: There has been a huge transformation in the wireless space into the largest cloud network in the world. The complexity of networks and running them is like nothing we have ever known. We are focused on the cloudification of networks. Before we get to AI, we need to automate those manual processes increasing efficiency across everything we do in the business.
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Tierney: Returning to the data issue. We often hear “Our data is a mess until we get that fixed, we can’t do anything.” Is this true?
Pyle: We have created our own problem. We end up creating these silos of data for all the right reasons.
Who has heard of microservices? You isolate and block off and build boundaries around these systems so you can scale and build independently and do all these wonderful things. So, then you create data siloes. We're trying to be we're trying to be Agile we're trying to reduce time to market, but we didn't do it with that broader perspective. We have to re-unify all these data and bring it back together. We are using Amazon tooling to help us here, but it is a challenge. There is no silver bullet to fix this.
Then there is a security issue wrapped around all our data. For every piece of patient information we collect, there is always some bad actor trying to target it.
There are so many processes around timing, quality, and codification of the data. How are you going to take care of it in motion? How are you going to take care of it in rest? It almost creates a separate product line that we're having to manage.
Pyle: A lot of companies don’t retreat data science and data as a product. Most companies treat data as a commodity, and it is not valuable. The mentality of “I can always generate it again” persists.
With the Internet at scale these days, data is coming faster and faster. There is just too much to handle. Data just sitting on the floor being ignored, is not a strategy.
Rosenbaum: It’s just an education. If you want to innovate and take advantage of AI and not get left behind, you need to take your data strategy seriously.
Tierney: Let’s talk about talent development. What are some of the key issues about fostering growth for employees?
Rollis: The half-life of technology skill is 18 months. So, if you're not training constantly then in 18 months from now you are less valuable and less effective than you used to be. So, we are fostering continuous learning. We are providing space, resources, and continuous learning encouragement for employees to upskill, so they will be ready for the future.
Pyle: It’s tough. Today, there is only so much time in the week, and now I want you learn to skills that are going to atrophy in 18 months. It is almost easier to find the skills we need with candidates coming right out of college.
As leaders, our responsibility is to create a culture that supports continuous learning. You've only got so many hours in a week. You've only got so many user stories you can accomplish. You've only got so many meetings you can attend. But yet I want you to now understand skills and things that are going to atrophy in 18 months.
Rosenbaum: There are plenty of tools out there that plug into our existing stack to help automate communication with candidates. But we need to really understand the pain points in our value chain. Some of it is humility and learning what these pain points are, not just the technology behind it.
Tierney: With AI now in the mix, is how we look at talent fundamentally different? Do we need to step back and develop talent differently and why?
Pyle: You have to understand use cases. Generative AI is all over health care, but it's not going to be well received at the moment in my space so it would make no sense for me to start hiring and bringing in talent and upskilling people on a skill set that's not going to be consumable by my customer base. Understanding that you then can come back to what skills you need. As a hiring manager, I do see a lot of misuse in hiring space. You can sniff out AI-generated resumes, cover letters, and emails, or an auto-generated AI picture. If you create an old-fashioned intimate approach, it is much more appreciated.
Rosenbaum: It is not so much about us building tools with AI, it is applying those to our jobs. We are an achievement-oriented world, and so when things don't work, we tend to put our heads down. But creating a space where you can try a new tool in a specific way, that may or may not work is important and it gives people space to try fail, learn, and grow.
Rollis: Based on what we said earlier about the half-life of technology, I would encourage talent to not be so specialized and switch to an end-to-end expertise. That positions you better to grow within the role.
Pyle: Over the years I have picked up skills that are of no value today; they don’t mean anything anymore. Without understanding fundamentals and principles, experts in the hot tools of today will not be valuable five years from now.
Rosenbaum: Engineers have to understand the impact on the entire business value chain and how we really make money and drive value.
Pyle: Can those skills make us faster and more efficient? Same thing with AI.
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Rosenbaum: Being able to understand what the business can handle. It can be frustrating to engineers who have a great idea, but we can’t do it right now.
Pyle: If you have a great idea, what impact is it having on business? Nobody wants to swap our X for Y if it makes no sense. The cost of getting the organization up to speed is too high. You need to quantify the impact
Rosenbaum: It has to do with readiness or organization on three levels. One level is they are very siloed in their teams or departments. Marketing, sales, finance have a bunch of ideas but are not thinking end to end.
Next, is to think of a business end-to-end, as an ecosystem and you have to get the support of those groups.
Third is external, let us look at competitors and the market and see how these will change. Most companies are at one of the first two stages of readiness. And there is no easy way to mature.
Pyle: We tend to look at innovation the same as feature developments. Need to put discipline around that process. Everybody understands value and impact. Seeing it through a single funnel is good from a governance standpoint.
Rollis: We embrace research and development within our culture. Engineers doing things the way they've been doing them for the last 20 years — that is a barrier, especially when you get into emerging tech like AI. A lot of people want to build it first, automate later. You are no longer just an engineer writing code in the back room. Build it with automation in mind. We have not ingrained that yet. That is the biggest mindset shift that needs to happen.
Tierney: What are some suggestions for the coming year? Especially for students or entry-level.
Rollis: Find mentors. Be purposeful. These people who you work with, make purposeful connections with people and keep up with them.
Rosenbaum: Understand what business does, how they make money and what can I do to help them do it better.
Pyle: Find a way to be useful and valuable right away. Community is important. Find people who are like you and are similar to you and other people who are passionate, and you will grow faster. It will be easier to grow in a pod of people.
Something I heard that was great for engineers was, “Creating content in public is like interviewing at scale.” If somebody comes to me with a new grad or little experience, if they've got a GitHub repo with tons of samples, they've written articles, contributed to stack Overflow — all those things are like a public resume and I think in the absence of tons of experience it really makes a difference.
I hired a guy this year on a Legend of Zelda prototype he built on a private repo. I asked him, “How are you not employed?”
He said, “Nobody will give me a chance because I have no experience."
I said, “You're a diamond in the rough you're hired.”
Rosenbaum: Also look at what kind of attitude they bring to the team. Working hard to fix a problem while being humble, is huge.
Tierney: OK, how about at C-level? How do you care about people and innovate all these new technologies at the same time?
Rosenbaum: Progress, not perfection. Even if we failed, we learned something. This idea is being embraced more. Embracing risk is hard when quarterly profits are on the line, but it must be done.
Pyle: Don’t be afraid of bringing bad news. There is a humility aspect to it. Leaning down to the intimacy idea. From being on scrum teams, and working 60-hour weeks, I can tell you that whipping me harder was not going to make me work harder.
Rosenbaum: If you are the smartest person in the room, you are in the wrong group. Challenge each other. Speak up. You can challenge your boss. That’s how new ideas turn into innovation.
Tierney: Finally, the question everybody is asking. What do you think about the future of AI? Will it replace engineers?
Pyle: In computer science, there is an art to building software that needs to be shipped to a customer. I don't know that you can replace the human experience and a human's ability to relate to other people to empathize with other people in order to build something that's meaningful to another user. So fundamentally I don't believe that we will be replaced as programmers.
I do believe, however, that AI can be used as a tool to help me do my job better. Why would I want to write 500 lines of code that I’m probably going to get wrong when I can have software do it then I can go back and check it for accuracy, in a fraction of the time?
Rollis: I remember all the talk about how email was going to destroy the telephone industry. That didn’t happen. A couple of years ago we weren't using Zoom and Teams and now that's all we use. Technology evolves and your brain evolves with it as well. If you effectively use those tools you become more effective yourself, with more time to think critically.
Rosenbaum: AI is not going to replace people on the team, but people on the team who don't use AI will probably get replaced.