Can AI automate enterprise decision-making? It is an exceptionally broad and challenging task – assuming it is within the realm of possibility. But that’s what startup Arena claims to be doing, fueled by a funding round ($32 million) led by Initialized Capital and Goldcrest Capital along with Founders Fund, Flexport and a colorful cast of characters including retired General David Petraeus, Peter Thiel and Y Combinator CEO Michael Seibel.
The New York-based Arena is the brainchild of Pratap Ranade and Engin Ural, who co-founded the company in 2020. The two were inspired to build a platform that, using predictive algorithms, could help companies formulate strategies to navigate “uncertain” environments – like a global pandemic.
Ranade, who visited Stanford and Columbia, was previously an associate partner at McKinsey and co-founder of web scraping startup Kimono Labs, which was acquired by Palantir in 2016. Ural was an app developer at Goldman Sachs before joining Palantir as an engineer, where he met Ranade.
Arena’s services are packed in a lot of hyperbolic language, but they’re relatively simple in execution. One of the startup’s tools uses AI techniques to simulate an economy, testing millions of product pricing configurations to arrive at an optimal model for a business. It’s reminiscent of the AI Economist, a research environment developed by Salesforce that similarly runs millions of simulations to come up with plausible tax policies.
In addition to pricing, Arena can ostensibly simulate things like inventory management. Ranade also claims it can explain “anomalies” in the economic environment, such as headwinds from snappy supply chains, when making recommendations to customers (i.e. executives).
“Without Arena, enterprises have traditionally approached such decisions in a few ways: hire large teams of people to make these decisions, purchase decision support software to help people in operational roles make data-driven decisions, or do nothing and continue with traditional processes. ,” Ranade told TechCrunch via email. “Each of these approaches has merit, but they are a long way from AI’s full promise: truly intelligent machines that work autonomously, on our behalf, to increase human potential.”
Arena customers feed the platform data such as SKU-level sales, prices, location-level inventory, and shopper behavior during e-commerce sales. Arena complements that data with context from what Ranade calls the “demand chart,” which provides broader, real-time market signals. Together, these inputs are used to create the simulations mentioned above, which in turn produce models for pricing, inventory, and marketing that are then aligned with global data.
“Today, when the most advanced, data-driven business-to-business companies are promoting, data scientists analyze past data to determine the best type of promotion for a specific product in a specific market. Then they load the promotion into their enterprise resource planning system, and weeks after that they will analyze the performance,” said Ranade. “With Arena, this whole process is autonomous… Under the hood, Arena’s AI actively adapts to changing price elasticities and personalizes customer behavior, making adjustments while learning in real time to increase bottom line impact .”
Ranade makes the notable claim that Arena’s customers — including: Anheuser-Busch InBev and other “selected” Fortune 500 brands in e-commerce, automotive, manufacturing and financial services — have been able to reduce the cost of goods and services and make their supply chains more resilient thanks to technology. It is unclear to what extent that is true. But for what it’s worth, Ranade says Arena is currently making “millions” of decisions across both digital and physical channels.
“We have found Arena is driving a step change in value as we not only introduce a new paradigm of decision making for the enterprise, but also comply with C-suite and the existing infrastructure of their companies where they are located,” Ranade said. “The pandemic was actually a reaffirming moment for us. Our technology is specifically designed to absorb shocks – instances where data from the past no longer represents the future. The pandemic has shown that our technology is delivering significant, measurable results for our customers, especially in highly volatile decision-making environments.”
The closing of Arena’s Series A today marks the company’s first external raise, Ranade tells TechCrunch. The company had grown “profitably” until then. But Ranade and Ural believed that going the venture route would allow them to expand Arena’s core technology while expanding into industries such as manufacturing, renewable energy and financial services.
It will certainly require a substantial war chest to compete in the growing market for data analytics products. O9 Solutions, which applies analytics to supply chain and inventory planning and management, recently raised $295 million in a funding round that values the company at $2.7 billion. Unattended, Pecan.ai and Noogata compete more directly with Arena, providing tools designed to make predictions about metrics such as customer lifetime value, churn and retention, sales, and on-time deliveries.
xCash flows freely when it comes to business analytics – the global big data and business analytics segment could be worth nearly $700 billion by 2030, depending on which analyst you put your trust in. But the challenge for suppliers like Arena is to convince potential customers that they keep their promises. A recent NewVantage Partners survey found that many established companies still struggle to become “data-driven,” with less than a third saying they have a “well-articulated” data strategy. For many — especially small and medium-sized businesses — the return on investment remains unclear.
Arena’s workforce today stands at 50 people, 90% of whom are members of the technical, data science and product development staff at the startup’s downtown headquarters. Ranade did not respond to a question about whether Arena plans to hire within the next year.