There's a conversation in progress in our industry about AI and the potential that it offers pricing and revenue management (PRM). It came to my mind recently as I was reading Stanley McChrystal's book, "Team of Teams," in a section entitled "Big data will not save us."

It's a great book, which draws parallels between the new reality of asymmetric warfare and the forces of disruption in the business environment. In this particular section, McCrystal talks about the huge potential of new and sophisticated analytical capabilities to deliver insight into trends, customer preferences, and anything that can be analyzed, particularly where huge data sets are involved. But he cautions the reader of the limitations of using data analysis to predict the future. Stakeholders in multifamily performance should take heed.

Getting real about AI

Before we get into the core analytical point, let's talk about the volumes of data at play. McChrystal describes models with enormous data sets, but in multifamily housing, lease duration leaves us with tiny data sets to work with. Large retailers or intelligence agencies, for example, have terabytes or even petabytes of data, and hence enormous potential to deploy AI technologies to mine new insights. Multifamily operators scarcely have even gigabytes of data available for pricing analysis, making it unclear what value AI will add.

But even if we were to find a way for AI to pan for gold in the limited waters of multifamily pricing data, it is the use of the outputs that give McCrystal pause. Predictive models, like those in PRM systems, provide a range of likely outcomes based on historical and current demand as well as market conditions. As in war, where the enemy famously gets a vote, what happens in real life has the potential to be different from what models predict. 

I've now heard enough times from enough operators that "AI is the future of revenue management." At the same time, and often from the same companies, I've frequently heard through this downturn, "The PRM system doesn't react as quickly as I expect it to and it causes us to miss opportunities." Sentences like that, which one hears all too frequently from property and asset management professionals, say a lot about how some companies are still using PRM technology.

Models work when they are fed and watered; they do not work well when they aren't. Human experience and judgment lead good revenue managers to change system parameters. One could imagine an application of AI that would help make parameter changes more proactive, for example. But how would AI handle a problem that it has never seen before? The answer is probably “no differently from current models.” We should be realistic about the limitations of predictability, as well as the value AI may or may not offer.

"From predicting to reconfiguring"

McChrystal uses his experience as a military leader in Iraq, and the change in mindset required to combat a fragmented, unconventional adversary. He describes a mindset shift "from predicting to reconfiguring" as the capacity to adapt as things change became at least as crucial as predicting the future. Through this pandemic, we have posted many words in these pages about the need to understand a range of possible situations and be ready to adapt your game plan accordingly.

I am excited about the possibilities that AI brings to multifamily, and as I research the forthcoming 2021 edition of our 20 for '20 white paper (the outlook for multifamily technology based on 20 conversations with senior multifamily executives), I can tell that COVID plus another year's experience has changed the perspective on AI and how it will change our industry. I do not, however, see how AI naturally improves price optimization (yet).  

With McChrystal's words in mind, we should stop throwing the Hail Mary pass of "AI pricing" and think of how these new technologies work and what that could mean for price optimization. SPOILER ALERT: it will still involve people understanding how pricing works, and the rewards will still accrue to the companies that set themselves up to make better decisions. That was the insight of the book - which I thoroughly recommend - and a valuable lesson as we get ready for 2021, which is bound to be full of surprises.