Welcome to CPO Rising’s all-new feature, the Future of Work Influencer series, which will highlight innovative voices in the evolving world of work. This exciting new series will be a go-to spot for progressive thoughts on how technology, transformational thinking, and revolutionary ideas are changing how work gets done. Be sure to check out past articles in this series here.
For this week’s Future of Work Influencer feature, we are excited to chat with Sean Chou, co-founder and CEO of Catalytic:
Christopher J. Dwyer: Hi Sean, thanks for chatting with us. Tell us a little bit about yourself.
Sean Chou: I’m the CEO and co-founder of Catalytic, a leader in cloud-based automation. You are probably quite familiar with Robotic Process Automation (RPA). We are not RPA, but we integrate and complement those solutions. We provide businesses with an intelligent layer to easily manage complex processes that include people, RPA bots, and an extensive library of services (i.e. OCR, invoice-processing, language services). The platform helps employees focus on higher-value challenges while helping businesses be more profitable, efficient, and compliant.
I started life as a technology consultant but quickly concluded that I wanted to be in software. I got that chance in 2000 when I met Jai Shekhawat, who was just starting what would become Fieldglass. We built that company over a 14-year period before selling it to SAP for $1 billion. At Fieldglass, I was the CTO and EVP of Services, and oversaw basically everything other than sales and our back-office functions. I was responsible for product, engineering, marketing, strategy, accounts, implementation, and customer care. It was a great education in learning how to become a CEO.
CJD: My research has been laser-focused on the Future of Work for several years now. Two of the biggest components of the technology side, at least from my perspective, of the Future of Work are artificial intelligence and RPA. Why do you feel these elements are so crucial to how work gets done?
SC: Those are great elements to call out and I would like to add that we should talk about automation technologies in general. Both AI and automation technologies represent very different ways in which technology will impact the future of work. One category is to be able to perform the sorts of tasks that we can’t possibly perform because we lack the raw data storage and processing capacity. Problems such as being able to cross correlate every single legal precedent in seconds, or processing millions of pages of documents in a few minutes. Humans just can’t do it. In fact, we couldn’t even coordinate enough people to get it done via brute force. The second category are those tasks that are incredibly easy for people to do. Problems such as looking up a value on a web site, filling out a form with data from an email, or other sorts of common business activities. We shouldn’t be doing these types of tasks at all and bots can do them faster.
AI and automation technologies can help with both of these categories, although I think AI is often focused on the former and automation on the latter.
CJD: One of the interesting elements of the Catalytic platform is that it not only enables businesses with the ability to automate tactical elements of their organization, but also helps them (via Catalytic Predict) to build forward-looking scenarios from which to make strategic decisions.
SC: Yes, we’ve really combined a lot of different concepts on automation with some AI technologies to solve the simple tasks that can be automated. But in doing so, we automatically build up the data to be able to help in future decisions and provide more operational intelligence that wouldn’t be detectable via brute force observation.
CJD: You’ve been in the technology industry for over 20 years now and have experienced, first-hand, everything from the initial rise of cloud-based software to the contingent workforce industry’s largest technology acquisition. What are some of the most impactful things you’ve learned from your history that you’re now applying to Catalytic?
SC: Good grief, that makes me sound old. I’ve learned a lot but let me go ahead and cherry-pick a few things.
The rate of technology is not linear or exponential. It’s in the form of stairsteps. In my career, I’ve witnessed the rise of the internet, the cloud, and mobile. Each step up brings a big wave of disruption and opportunity. The stairstep function we’re about to see is the rise of AI. Big Data and data science were all just a predecessor to AI.
Corporate purchasing has evolved pretty significantly, and as a result, style adoption has as well. The days of the hard sell and shifting all risks onto the buyer upon contract signing are largely fading. With the advent of SaaS, vendors are on the hook to deliver real value and to continue to deliver value. For the engineering-oriented software company, that’s been a good thing because it places a lot of value on the product. From the customer perspective, purchasing has become a much more consensus-driven decision, which can be challenging (and lengthy) for vendors, but ultimately creates a better adoption path.
Experience matters, but not nearly as much as people think. It doesn’t provide a playbook for success, but does provide a richer tapestry for learning quickly. Anyone I’ve ever met who thinks that their experience will give them all the answers has ultimately been disappointed. Those who remain intellectually curious and have the humility to learn from everyone else make good use of their experience. But honestly, I’d much prefer hiring and working with the inexperienced person with smarts, drive, and good intuition over an experienced person who thinks they know all the answers.
CJD: Why do you feel that Catalytic is one of the purest technological representations of the Future of Work? And, what do you hope to accomplish with Catalytic not just in 2019, but in the years ahead?
SC: We are focused on augmenting human capabilities, and a Future of Work where people are working side-by-side with digital workers. We are moving rapidly from a world where humans are operating on systems and acting as human-system translators (also called data-processing) to where systems are much more capable and able to take some of the more dehumanizing workload off of people.
Our dream at Catalytic is similar to how we look back in horror at things like performing calculations on paper or bookkeeping on paper ledgers; someday, people will look back at the sorts of data-processing and other low-value knowledge work that they do today and cringe at the thought of going back to the “way it was.”
Connect with Sean on LinkedIn, or visit www.catalytic.com for more information on Catalytic.
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