Culture, culture, culture. Every tech CEO and founder, fiddling in their proverbial garage, dreams of building a company founded on principles partially informed by childhood readings of Alexandre Dumas: All for one, one for all. And, by the way, let’s change the world.
This team-focused, ideal-driven mantra flies in the face of everything corporate culture stands for, and that’s exactly how storybook Silicon Valley/Silicon Alley like it.
If there’s one word that murders the mojo of this daydream, however, it’s this: budgets. Worse than even 360 performance reviews, budgets reek of a decidedly corporate stink. For starry-eyed founders, the thought of hiring someone to sit in your company and focus on pennies spent (how anti-big picture), five-year plans (didn’t Stalin come up with those?) and getting your receipts together to start preparing for your first audit (don’t even get me started) almost induces one to self-inflict extreme physical pain.
And yet, at some point in the life cycle of a company, hiring a finance professional is inevitable. The good news? The financial role is evolving, from helping to optimize cloud costs to useful pricing analyses for new and existing products. The not-so-good news? Budgets, well, they’re not going anywhere. But it’s a necessary medicine, and, if the right finance professional is hired, shouldn’t be a painful, arm-wrenching process.
For many companies, depending on size and stage, cloud spend is the second-highest cost after payroll. Of course, the current slew of cloud wars between the industry’s best and brightest — Amazon, Google and Microsoft — are helping the costs to reduce themselves, but this sort of passive maintenance is far from ideal. By working in conjunction with the Systems team, a plugged-in finance teammate can reduce cloud costs by another 25 percent (at least).
Let’s assume your company is on AWS, which is an easy example. By working with the Systems team and analyzing instance usage data from the last few months (if the Systems team uses Splunk or similar software, this is a straightforward exercise), prepaying for instance usage reduces the hourly cost significantly, and optimizes instance type for necessary memory and CPU usage (many engineers can grossly overestimate, launching a c3.4xlarge when a c3.2xlarge or even c3.xlarge would have sufficed).
Alternate solutions — like Mesos clusters — live more in the Systems domain, but a clued-in finance person could be very helpful in optimizing the make-up of these clusters from a cost perspective.
There is no underestimating the power of well-calculated, defensible numbers displayed on a page. Many CEOs will have a rather good gut sense of paths that work best for their company — from pricing analyses to company-wide resource allocations to 5-Year P&L and cash forecasts — but until all relevant numbers are put on a page, it’s not possible to make a truly informed decision.
Slapdash data with unrealistic assumptions can be misleading and destructive.
A finance person can help tell a story with well-sliced data and, if necessary, a few well-explained assumptions. It is difficult to argue with well-calculated numbers, and there’s no better sense-check for a company’s current state or trajectory. Of course, anyone could enter a few functions into excel, pound the table to defend certain assumptions and declare themselves a data genius.
A model is only as good as the person building it and the assumptions layered into it. It’s therefore very important, especially if a CEO would like to lend any credence to the analyses put before him/her, that the finance hire be a good one. As helpful as correctly calculated data can be in critical business decisions, slapdash data with unrealistic assumptions can be misleading and destructive. Not to mention it can leave the company’s board unimpressed if unrealistic data — or constantly changing data — is set before them.
Following in this vein, and specific to pricing strategies, a product’s story isn’t fully told until a finance person is given the opportunity to dig into a pricing/profit analysis. While a business development or marketing professional should have a good sense of pricing stratagems that work in the market, a finance person should have a firm understanding of the various cost drivers that inform the creation and management of a product.
When running through what-if pricing scenarios, it is this handle on cost drivers that informs the ever-important margin calculations. While seemingly straightforward, this gut check is surprisingly often overlooked.
And now, the fundamental portion of a finance professional’s role: budgeting (I’ve saved the best for last). Budgets should be put together and conducted with as much granularity as possible, because such finely detailed data can lead to extremely useful analyses and quarter-over-quarter comparisons down the road.
This sort of painful attention to detail is unfortunately exactly the type of housekeeping that allows for well-informed boards, tidy investor packages and grounded five-year-plus forecasts — not to mention that it further lends a level-headed dose of reality to oft-runaway startup spend.
Budgets reek of a decidedly corporate stink.
If the correct infrastructure is put into place early on in the company’s life cycle, budgeting becomes a once-monthly 15-minute nuisance for anyone outside the finance team, and provides outsized value for data-driven decisions down the road.
These are all functions that a finance professional could lend a startup early on in its trajectory, well before IPO preparations and before even your first 409a valuation (although you should probably get that done as soon as you can more or less easily swing the fee). Further, if hired correctly, the finance team need not put a damper on a startup’s uniquely geeky, fast-paced, entrepreneurial culture.
While we cannot deny that finance is a corporate term, if correctly hired, it can be more tongue-in-cheek “red stapler” and less dry-and-withered red tape.