By Alan Young, Hospitality Industry Advisor, College Professor, and Co-Founder of Puzzle Partner
The technology sector is defined by constant motion: the relentless exchange, disruption, and evolution of big, innovative ideas brought to the table by bold, innovative minds. The most influential players in the space are those with a seemingly insatiable appetite for change and optimization, and it is precisely that hunger that has occupied Jens Munch throughout his career. Within the hospitality industry, Munch is known as the Founder and CEO of Pace Revenue – a platform created in 2016 to revolutionize how hospitality approaches revenue management (acquired by FLYR). Today, Munch is the CEO of FLYR for Hospitality – a platform that, under Munch’s tenured guidance, promises to unlock the power of AI for truly optimized revenue management, decision intelligence, and data-backed hospitality insights.
Recently, I had the opportunity to sit down with Munch and discuss the impressive journey of his career in tech, the need for commercially relevant data in hospitality, and the paradigm shift machine learning offers the industry, and so much more.
Munch first stepped onto the tech scene in 2007 when he joined the ranks of Google. “The first few years of my career were spent at Google disrupting traditional advertising with digital advertising,” he shares. “At that time, we were moving budgets from a top-down model to a cost-per-acquisition (CPA) or cost-per-click (CPC) model, and by 2012-2013, I began working on Google Wallet, in addition to a couple of retail initiatives. Google Shopping, in particular, opened my eyes to the world of point-of-sale (POS) payments and the amount of innovation unfolding in that space.” Much of this innovation, he noted, could be attributed to Jack Dorsey’s company, Square, the financial services company aimed at small and medium-sized businesses in the US. His interest piqued, Munch turned his attention to the European market, where he came across iZettle (now known as Zettle by PayPal), effectively the European and South American version of Square. “I joined their UK team as the Managing Director and, after little over a year, I became iZettle’s Chief Strategy Officer,” he explains. “During that time, I had a front-row seat to the disruption in the payment and POS space. I was also increasingly interested in artificial intelligence and machine learning.”
By 2016, iZettle was headed for an IPO, and Munch was already considering the next tech wave. “I really love building companies in disrupting industries, and I was ready for the next project,” Munch notes. “The more I thought about it, the more two things became clear – one, I loved the B2B space, and, two, I loved software-as-a-service (SaaS) and demonstrable revenue impact. As a B2B SaaS provider, you’re either saving people money, giving people money, or generating money. In other words, it’s either a cost-saving, revenue, or profit augmenter, and I was interested in the latter.” At the same time, Munch noted, the proliferation of machine learning and AI technology was setting up a paradigm shift bound to impact all industries. “With this in mind, I wanted to find an industry that was large enough – and laggard enough to require a platform that combined all of those elements, and then I wanted to spend the next ten years building it.” One of the people Munch discussed this idea with was Jason Pinto, who co-founded Pace Revenue with Munch in 2016, along with a third co-founder, John-Paul Clarke.
Notably, though, Munch, Pinto, and Clarke were entering a space with several incumbents, so what made them so confident in their ability to disrupt the market? The way Munch sees it, every company has “multiple foundings” – in other words, its first iteration rarely reflects what the company later becomes. “When we founded this company, we thought we were building a real-time pricing engine effectively, which would work for all perishable goods,” he explains. “We were industry agnostic at the time, and it took six to twelve months for us to zoom in on hospitality, specifically. Realistically, we didn’t initially think we were competing with anyone – we didn’t know the space well enough yet. This was a blessing in disguise, in a sense, or perhaps blissful naivety. Because when you’re already on the journey, if you have enough competitive spirit and keep pressing forward, you will succeed.”
However, it didn’t take long for the Pace Revenue team to realize that you cannot build anything related to pricing or commercial decision-making in isolation. “You have to understand all of the elements of the commercial landscape to make it work because they’re all interconnected,” he explains. “For example, it’s easy to have a point solution for the sale of single tickets but as soon as companies run into wholesale deals, group deals, discounts, vouchers, and different channels, things get complicated. We realized that to win this battle, we have to move from a simple point solution that handles pricing decisions, to a full commercial platform. This was, essentially, the second founding of the company.”
Realizing they had significantly more work cut out for them, Munch, Pinto, and Clarke set out to raise more capital. At the same time, they brainstormed ways to aggregate all of the commercially relevant data for hospitality under one roof and, in turn, empower all stakeholders within the organization. They also realized the importance of cross-team visibility and collaboration. After all, if the sales or marketing team employs a strategy contrary to the strategy of the revenue team, the organization ends up fighting against itself. “We realized that we needed to capture all the decision-making across an organization and, at the same time, we needed to leverage machine learning to optimize the decision-making process,” he shares. “We were very measured and thoughtful about where we started and where we inserted machine learning.”
Interestingly, even as Munch details his entrepreneurial journey into AI-powered revenue management, he rarely mentions revenue management.
When I asked him about this, Munch flashed me a thoughtful smile. “That’s a good question. The initial conversations around this company pertained to revenue management, so we were not ignorant of what the discipline was. Clarke had spent 30 years dealing with revenue management and optimization for airlines – he had impressive credentials in operations research in that space,” Munch explains. “The classic revenue management segment forecast yield paradigm is a linear process. But in reality, once you’ve priced or repriced, you will have to re-forecast, and your segments aren’t static. They will change based on your forecasting. So, we’re looking at a circular motion continuously segmenting, forecasting, and pricing.” According to Munch and his team, a large part of what we think of as revenue management (and what is taught as revenue management) are the simplifications required to make sense of the true complexity of demand optimization – particularly when it has traditionally relied on one person and an excel spreadsheet.
When asked what he considers the foremost challenges hoteliers face when trying to figure out how to manage the complexity of the revenue management side of business, Munch noted that data is often neglected. “When I talk to the CEO of a hospitality operation, I like to ask them, ‘Do you know who owns data in your group or your business? Who is the custodian? Internally, apart from the spreadsheet, who owns the data strategy?’ They need to know who is consuming what and which team is producing data and, more importantly, how to bring it all together behind a single pane of glass for everybody to see and leverage,” he notes. “What’s the right occupancy number for December? Who owns that? Is it the finance team? Is it the revenue team? The answer is that nobody owns data in 99% or more of the hotel industry. There’s no data strategy and no function for data. And guess what? The revenue team is the team that really could – and should own data. They understand numbers, have a lot of the data on a deep level, and understand the systems. This is one big challenge.”
According to Munch, the biggest challenge is to start with what will generate impact. “Revenue management teams often worry about the wrong things – what do the GMs want to see? What do the owners want to see? How do I please all these different stakeholders? Instead, a truly empowered revenue function should use the data to identify what initiatives will generate the biggest revenue uplift over the next six months,” Munch explains. “Rely on the data to defend your decisions.”
Hospitality, Munch notes, is a fantastic industry with a seemingly endless supply of great, passionate people who genuinely love the experiences they’re in the business of curating. “That’s one of the things that I’ve noticed repeatedly – just how passionate and involved hospitality professionals are in their industry. It’s not just a career; it’s a tribe and something that people live and breathe. So if I were to pinpoint what’s holding the industry back, it’s most certainly not the people, but rather, the dynamics of the industry,” Munch elaborates. “It’s this fragmentation between hotel chains, owners and operators. Unfortunately, this has meant that sometimes the right people have been unable to push for the right things.” Hopefully, with visionaries like Munch leading the way, these legacy structural challenges of the industry will soon become a thing of the past.
Following its inception in 2016, the Pace Revenue platform found industry-wide success as an all-in-one RMS that sat between a hotel’s PMS and the distribution landscape to help hotels realize their full commercial potential. In 2022, FLYR – the purpose-built technology company leveraging deep learning to help airline and cargo commercial teams – acquired Pace Revenue to expand its target customer base to include hotel teams. With Munch’s leadership and an international team of industry and domain experts passionate about improving the travel and transportation industry, FLYR for Hospitality offers hotels best-in-class commercial intelligence, revenue optimization, proof of value, and customer-built design.