Create a culture and framework for experimentation within your organization. Whether it’s product design and finding product marking fit or just finding and tuning your marketing message, the ability to try new things and measure the effectiveness of them by carefully designing for measurability is critical to your initial and ongoing success.
Ihad the pleasure to interview Alex Fly. Alex is the CEO of Quickpath, a data science platform that bridges the gap between data science analytics environment and the IT operational environment, can speak on this. Alex has over 20 years experience in AI and focuses on enabling businesses to make automated, intelligent decisions throughout their organizations using machine learning and artificial intelligence.
Thank you so much for joining us Alex! Can you tell us the story about what brought you to this specific career path?
I’ve spent years working with Fortune 500 companies applying advanced analytics and predictive modeling techniques to their traditional, digital, and marketing strategies. I’ve continuously helped them to deliver personalized customer experiences based on real-time context and behavioral data.
After years of delivering custom solutions through our expert consulting organization, we developed and launched the Quickpath Platform, a production data science platform that provides seamless collaboration between data science teams and IT Teams, allowing them to take their data science models and deploy and integrate them effectively into their business and customer-facing applications.
Can you share one of the major challenges you encountered when first leading the company? What lesson did you learn from that?
While it’s now easier to build quality machine learning (ML) models with popular open-source frameworks, AutoML, and citizen data science tools, companies truly struggle to integrate and manage machine learning. This means they cannot access real business value. On the whole, only 13% of models built are used in production decisions, which is quite low. The problem is production implementations average 6–9 months, cost several $100Ks, and the resulting analytic and technical debt taxes future productivity. Left unchanged, the majority of ML initiatives will fail to deliver value. I realized there has to be a better way for companies to actually use ML, which is why we developed Quickpath.
What are some of the factors that you believe led to your eventual success?
I’ve been working in AI for the past 20 years, and previous to starting Quickpath, my co-founder, Trent McDaniel, and I worked in a consulting capacity. One of our company mantras is to “strive to automate yourself out of your current job”. It’s been our experience that there are always more interesting, challenging, and valuable problems to be solved beyond the ones that you’re currently focused on. That philosophy has allowed us to design software and solutions that are meta-data driven, self-documenting, transparent, and scalable and has allowed us to scale our team and business to provide cutting edge AI solutions that are simple and safe for our customers to use to optimize their business decisions and customer solutions.
What are your “5 Things I Wish Someone Told Me Before I Became CEO”? Please share a story or example for each.
1. Finding the right team is crucial, especially in the world of high-tech. The skills gap is very prominent but having the right mix of talent and expertise ultimately enables you to scale.
2. Start small. When I was starting out, I was able to identify an existing (and relatively low risk) business process or customer interaction to augment with AI. This took off and allowed me to help build Quickpath.
3. Watch other startups and companies around you. See what they build, what gaps there are in the market, and try to figure out a valuable product that is useful for your customer.
4. Surround yourself with supportive friends, family, and advisors that will both cheer you on when you’re getting it right or need support as well as give you constructive advise when things aren’t working. Even if you are working on an innovative solution that will transform an entire industry, there are people with experience blazing those types of trails and can help you be more successful in your journey — find and listen to those that have gone before you.
5. Create a culture and framework for experimentation within your organization. Whether it’s product design and finding product marking fit or just finding and tuning your marketing message, the ability to try new things and measure the effectiveness of them by carefully designing for measurability is critical to your initial and ongoing success.
What advice would you give to your colleagues to help them to thrive and not “burn out”?
Maintain balance with your personal life. Startup life can be all-consuming and is definitely a rollercoaster of results and emotions. You need a healthy personal life to ground you and provide a safe harbor from the extreme highs and lows of being the CEO of a startup business.
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?
My co-founder, Trent McDaniel, and the whole team at Quickpath. Working together, we’ve led the enablement of a data science factory model at one of our Fortune 500 Financial Services customers where we created a highly repeatable and easily managed path to production for ML-enabled applications.
What are some of the goals you still have and are working to accomplish, both personally and professionally?
Companies are absolutely struggling with their early AI initiatives. And that is where we can help. There are many challenges that enterprises face with AI adoption that the giant technology companies that pioneered them did not have to face, including legacy application architectures, data silos, regulatory and compliance requirements, lack of access to talent and skillsets, and organizational structures and priorities. We can help enterprises extract real business value from AI.
What do you hope to leave as your lasting legacy?
A thought-leader in the AI space. I’d like to continue to make it simple and safe for companies to adopt AI and make automated and intelligent data-driven decisions moving forward.
You are a person of great influence. If you could start a movement that would enhance people’s lives in some way, what would it be? You never know what your idea can trigger!
The use of ethical AI is increasingly important, so something in that realm. It’s an interesting topic at all the AI conferences due to the intersection of changes in our social and political landscapes, customer privacy, and the advancements in AI capabilities. Interestingly enough, I feel that this is one area that the large, more traditional industries have a head start on compared to the technology companies now leading the way on AI.
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