AiThority Interview with Alan Holland, CEO and Founder of Keelvar

Hi, Alan. Welcome to our Interview Series. Please tell us a little bit about your journey and what inspired you to start at Keelvar.

I grew up in an entrepreneurial family in Ireland, and was immersed in business at a very young age.  At 13, my brothers and I would be taking calls on behalf of my father’s business as  part-time receptionists. Yet still, I was more interested in pursuing further education in math and computer science than I was in business. I initially pursued the Irish international Olympiad team for mathematics, and ultimately ended up being one of the first PhD students at the University College Cork’s AI research lab, which was just starting up at the time. It was there that I realized how artificial intelligence and computer mechanism design could solve some of the issues my parents had encountered in their business – issues I soon realized businesses of all sizes were experiencing.

At the time, there was a growing understanding that procurement was broken. Sourcing teams simply couldn’t collect the information needed to make quick, intelligent decisions with suppliers that fit their unique needs. As the world grew more globalized and volatile, demand was rising for a solution to ensure business continuity and supply chain resiliency amid significant risk.

Keelvar was created to solve this problem by using intelligent automation and optimization to help teams make quick, strategic sourcing decisions that reduce risk, increase savings and help build a stronger overall business.

Tell us about the enterprise-level supply chain ecosystem that you are currently focusing on and how it changed in the last 3 years? How did the pandemic change the landscape?

A chain is only as strong as its weakest link, and if you’re a global Fortune 500 company, you’re relying on hundreds of thousands of links in order to deliver your product or service to customers. Over the last three years, businesses were forced to recognize the fragility of their chain when the pandemic struck different locations at varying times – forcing many suppliers to suddenly pause or shut down operations. As a result, organizations had to quickly re-source to avoid disruption to their supply.

However, identifying reliable suppliers, controlling costs, and making quick, effective sourcing decisions that fit an organization’s unique criteria around ESG and more was challenging. Without technology, teams could not keep up with the pace and scale of sourcing decisions that were abruptly put on their plates due to disruption.

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The pandemic underscored the importance of making the sourcing process simpler, smarter and faster in order for businesses to react quickly to market changes and major risk events. Keelvar focuses on arming blue-chip companies and enterprises with an easy-to-use platform that provides the intelligence and agility needed to navigate these new complex landscapes, especially amid rising costs and a recession.

What are your core offerings? How do you incorporate various advanced technologies to create your products for large and mid-sized companies?

Keelvar is a pioneer in sourcing automation and optimization technology. Sourcing automation solutions boost productivity, scalability and responsiveness by enabling suppliers to better manage the increasing numbers of smaller, often reactive sourcing events as market and supply chain changes occur. New events can launch in minutes, and up to 90% of tedious, manual tasks are offloaded so sourcing teams can focus on strategic initiatives and have the optimal award scenario delivered to them for review.

By automating all tactical aspects of a sourcing event, teams can pivot fast when they encounter supply shortages, capacity scarcity and geopolitical disruptions. Plus, through the use of AI and ML, our solution seeks to identify patterns in past events to better understand an organization’s sourcing process and preferences, becoming an extension of the team.

Our automation leverages our sourcing optimization platform, which focuses on ease-of-use, workflow automation efficiencies, supplier engagement, and scale. It allows sourcing teams to go beyond simplistic supplier award decision-making that is driven solely by a lowest-cost model. Buyers can collect a wide range of price and non-price bid information from suppliers, and then analyze multiple awarding scenarios based on those criteria and other constraints across different spend types and sizes. Sourcing optimization technology offers an immediate return on investment – using it for just a single event will pay for the entire subscription of the tool in almost every case.

What is the opportunity for organizations when it comes to utilizing AI and Machine learning in their operations?

AI can uncover a new perspective on everyday processes or scenarios, because it’s able to explore strategies more objectively, and with greater insight, than humans. In sourcing, AI can quickly determine how to best negotiate with suppliers depending on the setting, as well as identify new suppliers that may have been hidden from view. This process of discovery is a huge advantage to business owners because it can help them uncover new suppliers who are a great fit that otherwise would have been overlooked.

AI not only uncovers new opportunities, but it continuously drives excellence on a level that wouldn’t be possible for human workers to achieve. Each time AI enters a negotiation or encounters a problem, it learns from that experience and then applies that learning to every single event from that moment on.

Machines are better at exploring strategies than humans because humans are inherently risk averse, and naturally shy away from strategies that break with tradition. Humans tend to find one way that works well, and then continue to work that way until something goes wrong, whereas AI is continuously adapting, improving, and learning with each new insight it uncovers.

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ChatGPT and Google’s Bard have taken the tech industry by storm. Could you let us know how generative AIs could transform intelligent automation?

Right now, generative AI’s reliability is fairly shaky when it comes to sourcing and procurement. This is largely due to the fact that in order to generate answers for standard issues like identifying alternative suppliers, negotiating strategies, or finding alternative services, you need access to information that is largely proprietary and kept within private systems. Another key issue is that the objective for large language models is to generate tokens in a stream that matches previously viewed patterns, and that model doesn’t include logical reasoning or make inferences that complement language models. To enrich generative AI so that it really impacts present performance, there will need to be major advances in data access and richer logical inferences.

What are your views on the future of supply chain optimization with ChatGPT and other AI techniques?

The future of supply chain work will be powered by humans plus automation – the two aren’t mutually exclusive. Not every supply chain scenario can – or should be – handled by AI. While automation can improve the quality and efficiency of sourcing events and identify optimal scenarios, some events require relationship building and trust, especially those that are highly specific, large-scale and done infrequently. Those scenarios are better handled by humans with optimization, because users can run events manually and communicate with suppliers while still guided by machine-backed insights.

However, AI is evolving faster than we ever thought possible. I myself didn’t foresee generative AI getting to the standard that it has so quickly. When I was working as a researcher in an AI lab, we used to debate whether an AI poker bot would defeat the world champion – most people thought it was too big of a challenge, even for a machine. Then, five years ago, it happened. A researcher from Carnegie Mellon led a team that built a bot to defeat the poker world champion. The same way AI changed poker, it will change supply chains.

There are specialized applications for different AI techniques that are currently in development, and those will eventually work in tandem with people to revolutionize procurement and supply chains. Eventually, Machine Learning usage will progress to a point where if you’re not using it in your business, you’re falling behind.

Do you foresee any challenges brands will deal with as a result of AI-based optimization and automation?

One of the biggest problems facing businesses around the implementation of AI is the misconception by human workers that they will be replaced by automation. The reality is the need for workers isn’t changing, the nature of their work is. It doesn’t make sense to have humans managing tasks that can be done quicker and more effectively by a machine. That’s going to change the type of skills human workers need and practice in the workplace.

Business leaders need to consider the ethical considerations of AI use as well, especially when it comes to sourcing and procurement. AI is the master of unintentional bias, because even though it can identify the best options for any given event, it’s not able to truly comprehend the information it’s supplying you. For example, if AI is trained to score against spelling mistakes, it could unintentionally develop a bias against non-English speaking suppliers, which could seriously hamper diversity, equity and inclusion efforts. Training AI to act on these types of classifiers can be problematic, and it’s critical that business leaders lean on human workers to oversee AI-derived insights with empathy.

Thank you, Allan That was fun and we hope to see you back on AiThority.com soon.