Peter Demarzo will serve on an interim basis as dean of Stanford’s Graduate School of Business beginning August 1 as the search begins for Jonathan Levin’s replacement. Levin becomes the university’s president that day. Stanford photo

The dean’s office at Stanford Graduate School of Business is moving from economics to finance. As Jonathan Levin, an econ prof and GSB dean since 2016, prepares to move up to the university presidency in August, the B-school has named an interim successor: long-time finance professor Peter Demarzo.

Demarzo, Stanford’s John G. McDonald professor of finance who has taught at the B-school altogether for more than a quarter century, assumes the deanship August 1 and will keep it until a permanent successor to Levin is named.

“Peter will provide important continuity for the school during this transition, and we are grateful to him for being willing to accept this responsibility,” Stanford Provost Jenny Martinez says in a news release.

DEMARZO TEACHES CORPORATE FINANCE & FINANCIAL MODELING

Demarzo earned his Ph.D. and a master’s in operations research from Stanford in the 1980s. He taught at the school for two years in the 1990s, then returned for good in 2000. He teaches MBA and Ph.D. courses in corporate finance and financial modeling; he also founded and serves as faculty co-director of the Stanford LEAD Online Business Program.

Before joining Stanford, Demarzo was on the faculty of UC-Berkeley’s Haas School of Business and Northwestern’s Kellogg Graduate School of Management; he was also a national fellow at the Hoover Institution.

Demarzo’s research is in the areas of corporate finance, asset securitization, financial contracting, and regulation. According to his online bio, “He is co-author of Corporate Finance and Fundamentals of Corporate Finance” and “has served as president of the Western Finance Association and the American Finance Association. He is a fellow of the Econometric Society and the American Finance Association, and a research associate of the National Bureau of Economic Research.”

LEVIN LOOKS ‘TO STANFORD’S FUTURE’

Stanford on April 4 announced that Levin, dean of its business school since 2016, will become president of the university on Aug. 1.

Named Dean of the Year by Poets&Quants in 2022 for his success in bringing stability to a school that had been wracked by scandal, Levin’s more important achievements include putting Stanford in the lead of all business schools on diversity and inclusion, making the GSB the first major institution to publish an annual report on its diversity progress.

 “As I look to Stanford’s future, I’m excited to strengthen our commitment to academic excellence and freedom; to foster the principles of openness, curiosity, and mutual respect; and to lead our faculty and students as they advance knowledge and seek to contribute in meaningful ways to the world,” the 51-year-old Levin said in a statement in April.

DON’T MISS STANFORD NAMES BUSINESS SCHOOL DEAN JONATHAN LEVIN ITS PRESIDENT and A DAY IN THE LIFE OF A STANFORD MBA STUDENT

Experts in the pursuit of harnessing nuclear fusion will assure you that the technology is coming — just 30 years away, according to their projections.

The joke is that if you wait three decades and ask them where it is— they’ll say the same thing.

In finance and procurement, the concept of zero-based budgeting has long been a bit like the pursuit of fusion power: more of an aspiration rather than something any real-world corporation can actually implement today. 

Which is unfortunate. Like the idea of the world utilizing the free, non-polluting energy that a fusion plant would offer, on paper ZBB promises objective, data-based baselines for every budgeting phase that would allow decision-makers to only work with what’s real and current, not what happened last year, or even farther back.

The proposal with ZBB is that by mandating a comprehensive justification and validation of each expense, rather than relying on historical spending patterns, organizations can remove possible blockers within their procurement processes. This approach aims to ensure that what you’re doing is the numerically provable best case for the specific circumstances at hand.

This approach certainly holds immense appeal, so much so that Jimmy Carter tried and failed to make federal government adhere to this discipline in the second half of the 1970s. However, ZBB never really gained traction or widespread adoption, and so its aspirations were largely relegated to the realm of “theory taught in business schools but lacking practical viability.”

The factors putting ZBB back on the table

History and controversy aside, the core idea of ZBB is clear — it presents CFOs with an approach that mandated comprehensive justification and explicit approval for all expenditures during each new budgetary cycle, typically at the outset of the financial year. This process ostensibly offered CFOs a way to make relevant decisions against a true picture of the company’s cash flow.

But ZBB never truly went away. In fact, it is experiencing a resurgence. Consulting firms like McKinsey have reminded us that if we could weigh the value of every dollar and start afresh with every budget cycle we could mitigate the risks associated with operating on outdated information and boost overall performance outcomes.

ZBB idealism is also happening at the micro-level, with social media influencers hopping on the ZBB bandwagon. Influencers like Beth Fuller have attributed their ability to pay off credit card debts to following online content creators who advocate for ZBB principles.

The question then becomes how would we make ZBB, long an ideal but one that proved too difficult to implement, work at the enterprise level? It turns out, a viable way exists, or at least we can start the process to get there. 

And you won’t be surprised to learn that the game-changer here is AI.

A way to open the door to ZBB

Currently, the spotlight within the artificial intelligence domain is on finding use cases for AI to solve real business problems. Organizations have been at the forefront of this endeavor for several years through an approach we term “autonomous sourcing.”

Specifically, organizations using an autonomous spend management approach source can purchase as many new services and vendors as they need within a given budgetary cycle. However, this process is underpinned by not just genuine and up-to-date market data, but also with the benefit of a corporate knowledge bank.  This knowledge base facilitates multidimensional comparisons, enabling organizations to evaluate purchases not only longitudinally (against previous periods) but also orthogonally, meaning across different business units within the enterprise. 

This may not be the precise dictionary definition of ZBB. But it represents a radical change from the lack of data and visibility CFOs have struggled with and a way to open the door to the underlying vision of ZBB: data-driven financial accuracy.

This autonomous spend management approach resonates with organizations seeking to rationalize and optimize their budgeting processes, often commencing with their procurement operations. These forward-thinking entities inherently grasp the transformative potential of leveraging machine learning and generative AI capabilities to tackle the sourcing problem.

And the convergence of machine learning, generative AI and autonomous sourcing platforms presents organizations with the ability to realize approximately 90% of the ZBB ideal in the present day. That’s happening via organizations using autonomous sourcing to consciously and strictly seek to rationalize every purchase and make data-driven decisions on every vendor relationship.

The commitment to data-driven evaluation of vendor relationships is actually super-important on the path to any form of zero-based decision-making basis. Why? Because it’s your best way of ensuring that you’re not locked into any partnerships or contractual arrangements that aren’t continuing to add value.

Even starting to explore this area of spend with proper data and analytical tools can move organizations off the proverbial sandbar of inefficiency. Last year, for instance, the Mays Business School published research that concluded the simple act of tracking a single category of expenditure can catalyze a reduction in overall spending.

The exciting prospect lies in the potential for modern businesses with diverse spending categories like marketing, HR, sales, IT, finance, and others to capitalize on significant cost-saving opportunities through AI-powered procurement solutions, e.g., accurate supplier sourcing and matching, e-negotiation and automated awarding capabilities.

ZBB’s future is now, not 30 years off

President Carter’s administration wanted to achieve such objectives and possibly on paper could have done — if they had all the time in the world, and exclusive access to the entire computing power of the United States at the time.

But even under those circumstances ZBB might not have worked — as without the efficiencies afforded by AI, ZBB would require manual sourcing, selecting, bidding, negotiating and awarding for every single purchase and vendor relationship in the business. 

The truth is, fulfilling every aspect of ZBB manually, as envisioned by its originator, Pete Phyrr, is an insurmountable task for humans. However, using the power of AI to automate numerous processes, alongside giving  individual business units the autonomy to source and complete their own purchases through autonomous sourcing, means ZBB becomes not just practicable, but essential in today’s dynamic business landscape.

Weighing it all up, maybe we can retire the notion that ZBB is the accounting industry’s version of fusion.

Instead, we can use the power of autonomous sourcing to perform the equivalent of fusion in the back office.