My story at St. Joe
When I joined The St. Joe Company, it was at a real inflection point. St. Joe was a public company with unusual complexity. On one hand, it owned roughly 170,000 to 180,000 acres of land accumulated over a very long period. On the other, it owned a growing collection of operating businesses and real estate assets: hotels, golf courses, retail, residential communities, apartments, insurance, hospitality, commercial properties, and more. It also had several hundred million dollars of cash and investments.
But despite those resources, the company was in a difficult position. It had an interim CEO, it was cash-flow negative, the market narrative around the company was poor, and many investors viewed it as a kind of slow-motion liquidation story rather than a business with a credible path to scalable growth. The company had substantial assets and substantial optionality, but it lacked a clear financial framework for understanding, valuing, and deploying those assets.
That was the environment I entered. Initially, I reported to the SVP of Finance, but within about a year the company restructured following leadership change, and the finance team was reduced significantly. From that point on, I worked in a very lean structure, reporting directly to the CFO. In practice, I took on much of the strategic analytical scope that had previously sat at a more senior level.
My role became, in essence, to answer questions and solve problems for the CFO, CEO, and Board.
The first major problem was foundational: before the Board could decide how to allocate capital, it needed to understand what the company was actually worth.
That sounds straightforward in theory, but in St. Joe’s case it was extremely difficult. The company’s assets were numerous, varied, and spread across many categories. There was no single complete and trusted inventory of all assets. In some cases, if you asked three different people for acreage figures on a parcel of land, you got three different answers. Even just constructing a reliable picture of the company required a cross-functional effort.
So I built that picture. I worked across departments, gathered information from senior stakeholders, reconciled inconsistencies, and partnered with the head of GIS to establish an official source for acreage that was comprehensive, mutually exclusive, and usable in analysis. Then, piece by piece, I built valuation models for the company’s assets and businesses.
The result was what became known as the Asset Book: a comprehensive, Board-level analytical framework that described and valued the company holistically and in detail. It ended up being more than 300 pages long, with a valuation and investment case for individual assets as well as a sum-of-the-parts view of the enterprise. For the Board, it was the first time they had seen a complete, coherent picture of the entire company summarized in a way that was both analytically rigorous and easy to understand.
The Asset Book gave the Board a much stronger basis for capital allocation decisions, especially around share repurchases. Since joining the company, St. Joe ultimately spent roughly $590 million repurchasing shares, and my valuation framework was a major support for those decisions. I continued updating that valuation quarterly, showing what had changed in intrinsic value, why it had changed, and how that compared with the stock price over time. It became a recurring Board tool, not a one-time project.
As I developed the Asset Book, I also created a database-oriented, heavily automated system that made the work scalable and flexible. That allowed me not only to update the analysis efficiently each quarter, but also to slice and analyze the data in ways management and the Board had not previously seen. Over time, that framework became a broader decision-support system for understanding the company’s economics.
The next major chapter came when a permanent CEO was appointed and introduced a new strategic plan.
That plan had two core ambitions: first, to make the company cash-flow positive through recurring revenue; and second, to create a scalable model for long-term growth by deploying capital into new businesses, projects, and partnerships.
But strategy at that level needed to be translated into finance. The Board had to know: what would this plan do to revenue growth, cash flow, liquidity, returns, and value? Could the company fund all of it internally? Would it eventually generate enough recurring cash flow to support a dividend?
To answer those questions, I built a consolidated long-range cash flow model for the company. This required building and integrating around 100 underlying cash flow models for existing businesses, projects, and future developments into a single enterprise framework with a 20-year forecast. The model showed historical and future cash flows at the project level and at the consolidated level, allowing the Board to understand the impact of the strategic plan on liquidity, returns, capital needs, and long-term value creation.
This work became one of the financial backbones of the company’s strategic planning process. It helped the Board understand whether the company could both fund growth and eventually support returning cash to shareholders. It also supported the Board’s decision to initiate a dividend.
At the same time, I was heavily involved in underwriting and evaluating new investments as the first phase of the strategy was executed.
St. Joe began developing roughly 30 new businesses and projects, both independently and through partnerships and joint ventures. My role was to provide the financial analysis needed to decide which opportunities to pursue and how to structure them. That meant building pro forma models, three-statement forecasts, scenario analyses, valuation frameworks, return metrics, and sensitivity analyses. It also meant going beyond the spreadsheet: researching market dynamics, competitive positioning, regulatory issues, site selection, partner economics, and execution risks.
In aggregate, I supported analysis and modeling tied to over $800 million of new investment and more than $100 million of debt financing.
One example was Latitude Margaritaville Watersound, a strategically important large-scale residential joint venture with Minto Homes. The project involved thousands of residential units and large up-front infrastructure investment. I was asked to build the pro forma model and financial statements for the project, determine its attractiveness, and evaluate St. Joe’s potential cash exposure under different scenarios. Given the stage of negotiations, I had about a week to complete the work. The model itself was complex because it required phasing, sequencing, financing, infrastructure timing, sales timing, and repayment assumptions to all work together dynamically. I designed the model with an inputs-drivers-calculations-outputs framework so that scenario analysis could be done cleanly and quickly. That work helped leadership gain confidence in the project and proceed.
Another example was WindMark Beach, where I developed the valuation analysis used as the basis for buying out partners in a joint venture so that St. Joe could become the 100% owner of the project.
Another was Watersound Closings & Escrow, where I was asked to evaluate whether St. Joe could turn a recurring cost center into a profit stream by entering the title and closing-services business, either through acquisition, joint venture, or internal buildout.
In each case, the job was not merely to build a model. It was to create an informed recommendation under uncertainty.
At the same time, I also handled a number of adjacent strategic finance responsibilities that were important to the company’s capital allocation and governance.
For a period when St. Joe held roughly $300 to $400 million in financial investments awaiting deployment, I created an internally built analytical system to manage the accounting, auditing, controls, and budgeting implications of that investment portfolio. The company did not want to buy expensive software, so I essentially built a heavily automated internal tool that saved recurring labor and turned what could have been a full-time role into a much more efficient process.
I also supported debt financing and covenant-related work, managed analysis around financing alternatives and refinancing, authored Board memos on topics like cost of equity, EPS impact of buybacks, financing strategy, tax law changes, and CARES Act implications, supported enterprise risk management, negotiated and managed a major hurricane insurance claim, helped reduce property taxes through valuation work, and partnered with business leaders in newer operating ventures such as insurance and airline businesses to improve their understanding of business economics and target KPIs.
One thing that is important to say clearly is that I worked with a high degree of independence.
The CFO was extremely busy and did not have time to manage work in detail. Assignments often came in broad language rather than narrow instructions. There was no one checking each step of my work. I was trusted to take an ambiguous problem, figure out what needed to be done, gather the right people and data, execute the analysis, and deliver something that would hold up with the CFO, CEO, and Board. If something went wrong, that was on me.
That shaped how I worked.
I became highly anticipatory and process-oriented. In my performance reviews, the CFO repeatedly highlighted that what he valued most was that I thought a few steps ahead: if a question was likely to arise, I was often already prepared for it. That mindset became especially important in Board preparation. Before I took over much of that process, Board meetings were often “fire drills,” with stress and scrambling near deadlines. Over time, I redesigned the work to be more automated, scenario-ready, and reusable. I would think months ahead about possible requests, build flexibility into the analyses, and prepare well in advance. As a result, Board materials became timely, higher quality, and far less burdensome for the organization.
I also had to work by influence rather than formal authority. Many of the people I needed information from were senior to me. To get things done, I had to explain the objective, what was at stake, what I needed from them, and why it mattered. Then I had to monitor the workstream, keep deadlines moving, and make sure the final output held together analytically. The Asset Book was a good example of that. It required cooperation from multiple departments and continuous updates as the business evolved.
There was also a strong ethical dimension to how I worked. One example involved an acreage discrepancy issue, where information provided internally had turned out to be wrong and there was pressure to soften the explanation. My view was that the chairman of the Board would value honesty and see through a stretched narrative anyway. I argued for transparent disclosure of the issue and ultimately convinced my boss to address it directly. That experience mattered to me because it reinforced a principle: senior leadership and Boards may forgive complexity and error more readily than they forgive a lack of candor.
Looking back, the simplest way to describe my impact at St. Joe is this:
I helped give a complex public company the financial self-understanding and decision architecture it needed to allocate capital intelligently, evaluate strategic choices rigorously, and move from a fragmented asset story toward a more coherent growth and value-creation story.
That is why the experience is so relevant to finance roles. The work was not routine reporting. It was enterprise-level capital allocation, long-range planning, project underwriting, Board decision support, and building analytical systems from scratch in an ambiguous, high-stakes environment.
My story at Zscaler
When I joined Zscaler, the company was in a very different kind of strategic-finance environment than St. Joe.
Zscaler was a high-growth public SaaS company in cybersecurity, scaling rapidly during a period when the market was undergoing major structural change. The shift from on-premise networking and security toward cloud-based architectures accelerated dramatically during and after COVID, and Zscaler was one of the clearest beneficiaries of that shift. Growth was extremely strong when I joined — ARR was growing around 50%, RPO around 100%, and the company was approaching $1 billion in revenue. By the time I left, it had surpassed $2 billion in revenue and was still growing revenue at roughly 30%.
That growth, however, came with intense pressure.
Zscaler operated in one of the fastest-moving and most competitive areas in enterprise software. Cybersecurity was evolving constantly. New threats emerged constantly. Competitive categories were shifting. New entrants and adjacent players were trying to carve out their own narrative. Investors were paying close attention not just to revenue growth, but to platform depth, competitive durability, macro sensitivity, and whether the company’s valuation premium was justified.
That external scrutiny mattered because Zscaler was not a sleepy public company. It was a premium-multiple SaaS company trading at over 10x EV/revenue at times, with more than 40 covering sell-side analysts and a large buy-side audience trying to determine its long-term trajectory. Investor perception had real business consequences. Since stock-based compensation was a significant part of the employee value proposition, the company’s valuation and credibility in the market affected recruiting, retention, morale, and strategic flexibility.
I sat on an integrated strategic finance and investor relations team, and that structure was important. At Zscaler, strategic finance was not just about internal planning and IR was not just about communication. The two functions met at the boundary between internal business reality and external market interpretation. Our job was to understand the company deeply enough — financially, strategically, competitively, and operationally — to help leadership make better decisions and communicate them effectively.
That meant investor relations at Zscaler was nothing like a conventional communications role. It required a real understanding of the SaaS business model, the company’s platform and products, the mechanics of ARR, billings, CRPO, cohort behavior, contract duration, pipeline conversion, unit economics, competitive positioning, macro trends, and how sophisticated investors and analysts were likely to model and question all of that.
My role evolved into being a kind of translator and architect across those domains.
One of the central problems we faced was that the outside world was constantly trying to explain Zscaler through simplified metrics — often billings, CRPO, or various versions of net new ACV — while the true underlying mechanics were more nuanced. Leadership needed a better internal understanding of those mechanics so they could distinguish between genuine changes in business momentum and mere timing effects or contract-structure effects.
To solve that, I built a series of drivers-based models and analytical frameworks from scratch.
One of the most important was a bottom-up long-term model that decomposed the company’s bookings, billings, and CRPO behavior by cohort. The purpose of the model was not just internal forecasting. It was also to understand how analysts were likely to interpret the company and where misunderstandings could arise. I looked at how past quarterly cohorts flowed through into future billings periods, how contract duration affected timing, how non-cancellable recurring billings created lag effects, and how all of that could make near-term growth appear weaker or stronger than the underlying business actually was.
This became especially important during periods when billings guidance was expected to come in below consensus and investors were becoming skeptical about growth durability. By decomposing those mechanics and isolating structural versus timing-driven drivers, I helped leadership understand that some perceived slowdown was more mechanical than fundamental. That, in turn, helped us shape earnings messaging and investor discussions around the true health of the business instead of allowing the conversation to collapse into a simplistic “growth is breaking” narrative.
Related to that, I built a bottoms-up CRPO forecast model designed to give leadership an early, highly accurate read on one of the company’s key SaaS metrics before the formal close process was complete. The challenge was that the “perfect” inputs did not exist until well after quarter-end. So the problem was not “can we get 100% accuracy?” but rather “can we get 99% accuracy early enough to matter?” I built a cohort-based model using TCV, duration, and other inputs that were available within a couple of days after quarter-end. The result was a model that came within about 1% of the final CRPO number but could be generated in two to three days instead of two to three weeks. That gave the CEO and CFO much earlier visibility into the quarter and also produced fast reads on related metrics like RPO and revenue.
That pattern — prioritizing decision-useful insight over perfect but late reporting — captures a lot of how I approached strategic finance at Zscaler.
Each quarter, I helped build and deliver Quarterly Business Review presentations for the CEO and CFO. These were not just reporting decks. Their purpose was to translate a mass of imperfect, messy, rapidly changing data into a strategic understanding of what actually happened in the quarter, what mattered most, what management should do next, and how those dynamics would likely be perceived externally. We looked across financial results, pipeline, rep productivity, conversions, customer wins, bookings, billings, product trends, geography, cloud marketplace activity, peer earnings, macro developments, and investor sentiment. The idea was to get to the signal before the company found itself in full reactive mode. Those presentations often became the earliest comprehensive strategic review of the quarter that leadership would see.
I also worked on more specialized frameworks that helped the company understand how it was being viewed from the outside. For example, when software valuations came under pressure and analysts became highly focused on operating efficiency, I reverse engineered a methodology used by some sell-side analysts called a “SaaS X-Ray,” which normalizes or rethinks margin structure in order to estimate what a software company’s profitability would look like under a more mature growth profile. I rebuilt that framework for Zscaler, compared it to our long-term model, and used it as a way to understand how external observers might judge the company’s efficiency and margin potential. That kind of work helped leadership prepare for the questions the market was going to ask, not just the ones already being asked.
Similarly, I reverse engineered investor methods for interpreting federal contract databases and deriving implications for Zscaler’s results and guidance. I also reverse engineered the various analyst methods for estimating net new ACV. In each case, the point was not just intellectual curiosity. The point was to understand how investors would try to outsmart the company, so that leadership could respond from a position of clarity rather than surprise.
Another major part of my role was helping shape messaging during periods when market interpretation was especially fragile.
One of the clearest examples was during the software slowdown in 2023, when growth across the sector was decelerating, rates were rising, valuations were compressing, and investor anxiety was high. Zscaler’s fiscal Q2 2023 was particularly sensitive because results reflected macro pressure and the company was also announcing a modest workforce reduction.
At that point, earnings messaging was unusually high stakes. Internally, the instinct from some stakeholders was to front-load the negatives heavily in order to establish credibility. That approach has a logic to it, but my concern was that if we over-indexed on short-term weakness, we would inadvertently reinforce the most bearish interpretation of the business and weaken the long-term framing needed to support valuation.
So I pushed for a more balanced narrative: transparent on the near-term pressures, but anchored in durable fundamentals, competitive advantage, and long-term growth vectors. I played a major role in reframing the CEO/CFO earnings script accordingly. When we reviewed the revised script with the CEO, he responded very positively and explicitly thanked us, noting that the messaging reflected a more holistic and deeply thought-through perspective.
The workforce reduction section was also delicate. It needed to be clear enough to satisfy investors, but also careful enough not to create unnecessary alarm among employees listening to the call. I took primary responsibility for drafting that section, studying how peers had handled similar disclosures and thinking through how language could be misinterpreted by both analysts and employees. I deliberately wrote it to be precise, factual, and compassionate, avoiding language that could imply deeper business weakness than was actually present. The result was that the layoff generated little friction during Q&A, analysts broadly understood the rationale, and the language was later reused internally in employee communications. That was an example of where strategic finance, investor understanding, and organizational judgment all came together.
Over time, I became increasingly involved in earnings messaging more broadly. Starting in fiscal Q1 2023, I wrote CEO/CFO scripts, built Q&A documents, and drove significant messaging evolution around the company’s competitive advantage and growth story. One quarter, I introduced the company’s first-ever earnings call presentation, which materially improved the clarity and consistency of communication across 40-plus covering analysts and was later praised and copied by peers. I rebuilt the investor deck from the ground up around a clearer investment case, redesigned the IR website, and developed new frameworks for quarterly Q&A based on systematic tracking of investor feedback and peer earnings results. These materials ended up having impact beyond investor relations — parts of them were adopted in internal all-hands contexts, sales and marketing materials, ESG reporting, and even executive keynotes. That to me was a sign that the work was not just “IR content.” It was helping the company articulate its strategy and identity more clearly across audiences.
A related theme in my Zscaler story is helping leadership move the market conversation from narrow concerns toward broader opportunity.
As growth naturally decelerated from very high levels, investor attention often gravitated toward questions like “where does growth bottom?” or “how much of this is competition?” I worked to reposition that conversation by anchoring more of the narrative in platform expansion, product adjacencies, and underappreciated growth vectors. I developed messaging around concepts like ROI, Rule of 40, Zero Trust SASE, AI, and broader platform depth in ways that were both strategically grounded and externally resonant.
One example was our positioning around SASE. At one point, the tendency internally was to minimize the importance of the label. My view was that if we simply dismissed it, competitors would use it against us. So I argued for a reframing: the real substance of SASE was direct-to-cloud architecture combined with zero trust, and Zscaler’s strength was precisely in “Zero Trust SASE.” That framing was later used by the CEO in earnings-call Q&A.
Similarly, when generative AI began emerging as a major theme after the release of ChatGPT, I was an early adopter and started building internal messaging around the relationship between AI and Zscaler’s platform. I created a framework and a set of slides summarizing the company’s AI opportunity, and that messaging was later adopted more broadly across the company.
My role also had a significant external-facing component. I participated in a very high volume of investor engagement — well over a hundred investor meetings per quarter at times, and over a thousand total by the end. I often led meetings independently, represented the company at conferences and fireside chats, handled finance and business questions in executive settings, and became deeply comfortable operating in live Q&A environments. Because I knew the business mechanics and guidance framework well, I could answer questions not just as an IR conduit, but as someone who understood the underlying model.
One of the best examples of that was the Goldman Sachs and Wolfe conferences in September 2024. In those meetings, I worked alongside the SVP of Product — he handled the deepest technical product questions while I handled business, finance, and strategic questions. I approached the meetings with a deliberate strategy: steer the conversation away from near-term guidance fixation and toward where the company’s growth story and platform depth were underappreciated. In that context, I used the framing that some topline effects were “mechanical” — a term the CEO liked and later adopted himself. That language began appearing in analyst reports and helped reshape how the company’s near-term numbers were interpreted. We received strong investor feedback from those meetings, and one major hedge fund explicitly told us it initiated a position as a result of the discussion. While stock-price movement is always influenced by many factors, the meetings clearly had tangible positive impact.
Alongside all of this, I contributed to more traditional strategic-finance work such as M&A diligence and strategic projects. I led financial diligence and modeling for multiple acquisitions, including work on TAM, growth trajectory, revenue synergies, cost structure, integration risks, and long-term margin impacts. In one case involving Canonic, my analysis went beyond the base model into issues like real estate consolidation, lease economics, founder expectations, office strategy, and the practical implications of how cost-cutting could affect people and integration success. I also supported business strategy analysis, TAM sizing for new growth areas, scenario modeling, peer benchmarking, and work with business leaders on emerging opportunities such as branch connector and API security.
What ties all of these pieces together is that my value at Zscaler came from helping leadership see the business more clearly at a time when both internal complexity and external scrutiny were very high. I was not just reporting on what happened. I was building the tools and frameworks to understand why it happened, what it meant, what investors were likely to think, and how leadership could respond in a way that preserved both credibility and strategic ambition.
That is why I think the Zscaler experience is especially relevant to modern strategic finance roles. In fast-scaling SaaS businesses, strategic finance is not just about budgeting. It is about understanding growth mechanics, anticipating investor and market interpretation, pressure-testing guidance, evaluating strategic options, and helping executives tell the truth about the business in a way that is both rigorous and useful.