Thank you so much for joining us in this interview series. Before we dive into our discussion our readers would love to “get to know you” a bit better. Can you share with us the backstory about what brought you to your specific career path?
I grew up in DC, and I was always very interested in technical subjects, especially complex systems, and international relations. Complex systems that spanned both macro and micro behavior patterns, such as the global economy, were especially interesting.
In undergraduate and graduate school I studied engineering, political science/international relations, and languages (French and Chinese). I was very lucky to find the field of global commercial activity / supply chains, which allowed me to combine my interests in complex systems and international trade. Out of grad school, I was the first data scientist and then head of data science at Panjiva, a global trade market intelligence company. After we sold Panjiva to S&P Global in Q1 2018, my co-founders and I saw the opportunity to build a platform allowing true multi-tier management of global production chains. We started Altana in Q4 2018.
What do you think makes your company stand out? Can you share a story?
At Altana we have built the first large-scale multi-tier view of the global supply chain. Our dynamic, intelligent map of the global supply chain is constructed across billions of records from commercial and proprietary sources in a novel federated manner that allows trusted parties to share insight without sharing sensitive information. This platform enables both the public (US, UK, and more) and private sector (Maersk, Prologis, Lloyds, Boston Scientific, and more) to collaborate in constructing trusted and resilient production networks.
We are thus applying cutting edge technologies, including modern AI/ML, to understand global production at scale and solve critical problems of supply chain security and resiliency. Our work touches on key issues of geopolitics, human rights, environmental impact, and industrial production. Both the technology and the impact is extremely distinctive.
You are a successful business leader. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?
Grit, grounded creativity, and vision.
Grit: starting a company is extremely hard. We had to persist and grow, while serving major governments and multinational corporations, through multiple challenges including a global pandemic. It would have been much easier to give up than to persist — Ben Horowitz is exactly right in “The Hard Thing about Hard Things” that your grit and persistence has to be at some level irrational.
Grounded creativity: by this I mean you have to be able to creatively solve problems worth solving. There’s no commercial case for “solutions in search of a problem”, and simultaneously, most easy problems have already been solved. Thus, you are going to have to think creatively about building new products that people want, combining technologies in novel ways. In Altana’s case, we saw the unique opportunity to bring AI deployed via federated systems to construct a view of the global supply chain that could incorporate both commercial and proprietary information while respecting data privacy and sovereignty. We developed the platform, and the applications upon it, through this grounded creativity.
Vision: to do big things you have to have a big vision. In our case, we are revolutionizing global supply chain management — a large-scale multi-tier view of the global supply chain has never existed before. The previous era of just-in-time manufacturing was inherently fragile as most parties could only ever see one degree out. We saw the opportunity to make a large impact on the world and bring tremendous value to our clients in the private and public sector, and we seized it.
Let’s now move to the main point of our discussion about AI. Can you explain how AI is disrupting your industry? Is this disruption hurting or helping your bottom line?
AI, along with federated systems, has opened up completely new opportunities in management of global supply/production chains. Altana’s platform ingests and processes billions of records across most major languages to construct our digital twin / knowledge graph of the global supply chain, as well as analyze the resultant network representation of 100s of millions of nodes and links. This construction and analysis would be impossible without AI’s semantic understanding of the underlying data and the network.
Advances in AI thus have opened up extremely novel opportunities for Altana. We’ve been using AI/ML since the start of the company, and the most recent advances in LLMs open up even more exciting possibilities that we have actively integrated into our product. Because we have a distinctive and defensible data asset, advances in AI help Altana’s platform value — we are able to provide ever more distinctive insights based on a unique source of truth.
Which specific AI technology has had the most significant impact on your industry?
Advances in deep learning and federated systems have opened up truly novel opportunities in management of global production chains. Computers are now able to understand the semantics of text data and network information in ways that were only dreamt of a decade ago, and this semantic understanding opens up entirely new possibilities in managing global supply chains at scale. Federated systems and learning allow the deployment of software, models, and data in a way that respects data sovereignty, privacy, and security while enabling trusted parties to collaborate, sharing intelligence/signal without sharing sensitive data.
Before these advances, Altana would not have been possible. With them, we have the opportunity to truly manage large-scale scale production networks covering 10s, 100s, or 1000s of thousands of companies at scale. The scaled nature of AI allows previously impossible optimizations, boosting resiliency, compliance, and efficiency.
Can you share a pivotal moment when you recognized the profound impact AI would have on your sector?
Seeing the ability of AI to process and semantically understand billions of records at scale, both constructing a digital twin from messy data and then generating insight at the same scale on resiliency (concentration risk, proactive and reactive management of supply chain disruption), compliance (identifying illicit fentanyl production, forced labor, sanctions evasion, etc), and other applications was game changing. When we realized that we could truly analyze the full world at scale via AI, we saw the opportunity for a sea change in how the global economy functions. Via synthetic intelligence, we have the opportunity to finally have trusted, fair, and efficient networks resilient to coming shocks.
How are you preparing your workforce for the integration of AI, and what skills do you believe will be most valuable in an AI-enhanced future?
AI’s increasing acceleration will change the nature of work — by some estimates 50% of US workers are already using AI at least occasionally. Workers who adapt and incorporate the newest advances into their day to day will benefit the most, realizing dramatic gains in productivity. Creative thinkers will be able to construct new products more quickly than ever before, often putting together systems that would have taken full teams before AI.
Altana is deeply focused on making sure our teams are using AI both for internal productivity (programming copilots, onboarding / FAQ assistants, summarizers of meeting notes, etc) as well as are familiar with cutting edge technology to integrate into our product. We have increased our pool of AI/ML talent, and we host team member focused AI/ML education sessions for both internal and product usage of AI.
What are the biggest challenges in upskilling your workforce for an AI-centric future?
AI improvement has been so impressively fast that constant upskilling is required. Sporadic education sessions are not enough — instead the requirement is a culture of attention to the newest developments and constant learning for all team members. At its heart, the team must embrace the rapid pace of innovation or fall behind in both internal productivity and external product offering.
What ethical considerations does AI introduce into your industry, and how are you tackling these concerns?
Safe and responsible AI development is of course essential. By building an underlying source of truth that backs all our AI systems, we provide explainable and justified insights that minimize mistakes and hallucination. Through this backing source of truth (our digital twin platform of the global supply chain) we minimize costly mistakes.
It’s important, however, to not hold AI systems to a higher standard than existing processes. Currently, public and private-sector organizations in global supply chains are confronted by a complex and ever shifting world that may involve thousands to millions of parties that directly or indirectly impact their business. Inefficiencies, fragility, crime, and abuses flourish in such complexity. AI is essential to better mapping of and decision support upon the global supply chain — we will not fix the myriad problems of globalization without these new technical solutions.
What are your “Five Things You Need To Do, If AI Is Disrupting Your Industry”?
Four key actions that I recommend are:
- Seize the opportunity: AI is massively disruptive because it boosts efficiency and makes new products possible. It is a threat only if you let it be a threat. You must seize the opportunity for gains in internal and external productivity. Internally, use tools like copilot for coding, LLMs for onboarding/summarization/translation/writing assistance, and generally innovate in boosting employee productivity. Externally, what processes and products in your offering can be improved? In Altana’s case, we are able to offer an improved map of the global supply chain, new natural language interfaces and assistants, explanatory capabilities, and more. Think deeply about what you can now offer that you couldn’t before. New product lines will be possible.
- Understand the technology not the hype: Balance planning for the future with living in the present. Use AI for use cases it can currently satisfy with acceptable quality, not future use cases that are not ready for productionalization. For example, AI is not ready to autonomously run a supply chain. But it is essential as a decision support tool to assist in managing the complexity of global supply chains.
- Build an internal culture of growth mentality: AI is growing in capacity at an astonishing pace. Some experts predict artificial general intelligence will be achieved within a decade. Your team must have a growth mentality and constantly monitor AI developments for new opportunities for internal and external productivity. Parochial or outdated thinking, such as thinking of AI as just a “stochastic parrot” is the enemy — you of course need to live in the reality of what can currently be achieved (see point 3), but you must update that reality constantly. If your team is constantly discussing foundational critiques of AI (e.g. Chomsky) and is hesitant to even try these new systems, you have a problem of culture you need to fix. If your team is not proactively trying and using new tools and capabilities, similar. This proactivity requires the backing and example of leadership.
- Don’t “innovator’s dilemma” yourself: Watch out for competitive AI products that are cheaper than yours but also worse. Your current output may be better than an AI system alone, but this will be very unlikely to persist. You must be prepared to adjust your products and in some cases business model to survive such challenges — don’t “Blockbuster” yourself by insisting on an old format and outdated methods.
What are the most common misconceptions about AI within your industry, and how do you address them?
AI is sometimes misconceived as unreliable (prone to hallucinations), unexplainable (black box), or incompatible with data privacy and security. Naive systems may indeed suffer from these problems, but more sophisticated approaches can solve these issues.
Reliability and explainability is achieved by building an underlying source of truth (in our case the Altana Atlas) that provides direct input into AI decisions and clearly cited justification for human users. Data privacy and security, while still allowing the benefit of the most modern techniques, is achievable via federated systems that share insight without sharing the underlying data through federated and transfer learning. In other words, the software and systems can be brought to the sensitive data, not the other way around, and fine tuned upon it in situ.
Can you please give us your favorite “Life Lesson Quote”? Do you have a story about how that was relevant in your life?
I’ll give you two — “100% of zero is zero” and “there is no easy path to the stars”
Regarding the first, it’s so important that teams focus on growing the pie rather than dividing the pie. Ego and organizational conflict will destroy an organization. Myopic focus on roles, titles, and scope are kryptonite at a startup — you have one goal and that is to succeed in building a massive business. Your career trajectory is the trajectory of the company.
Regarding the latter, the personal and organizational growth required to achieve any big goal is extremely painful. But failure to achieve your goal is more so. Don’t let the pain and discomfort of growth distract you from the reality that there is no easy path to what you seek, personally or professionally. Nurture and select for grit in yourself and those you work with. Personally, I’ve tried losing and I’ve tried winning — I prefer winning.
Off-topic, but I’m curious. As someone steering the ship, what thoughts or concerns often keep you awake at night? How do those thoughts influence your daily decision-making process?
We sit at the intersection of AI and global production networks — I am constantly focused on how we can best serve our public and private sector clients with the best possible technology in increasingly turbulent times. We want to run towards rather than away from difficult technical, economic organization, or geopolitical challenges — otherwise we will not achieve our goal of fixing globalization.
You are a person of great influence. If you could start 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. 🙂
Tech needs to focus on solving difficult problems with clear benefits. We should focus on deep problems in science, technology, industry, and society — medicine, industrial production, national defense, human rights, and fundamental science/mathematics are all examples of worthy pursuits. Yet we see so much talent go into advertising, social media, and similar applications that are generally neutral or negative for society. At the end of your life, you have to ask yourself, what have you done with that time? While not being blind to the sometimes harsh realities of this life, we must unify around producing a better and safer world through hard work and human ingenuity.
How can our readers further follow you online?
You can follow me at https://www.linkedin.com/in/pgswartz/
Thank you for the time you spent sharing these fantastic insights. We wish you only continued success in your great work!