How to Build a Finance Function for a DTC Brand Without Hiring an Analyst

Luke Novak spent years in finance at Goldman Sachs and HumanCo. He knows which numbers matter. When he started TIES, a doctor-formulated men's fertility supplement sold direct to consumers, the problem was not knowing what to track. It was finding the hours to track it.

Hiring an analyst at that stage was not something he could justify. Building the models himself meant updating them by hand and answering every question from a snapshot that was already out of date. So TIES did something different. It built its finance function around one live model instead of around a person. The results, according to TIES: six figures in analyst build cost avoided, four months of integration work skipped, and finance and marketing planning in the same model.

This post walks through how a DTC brand can do the same: what a finance function actually has to do, the order to build it in, and what TIES found once the numbers were connected.

What a DTC finance function actually has to do

A finance function for a DTC brand is the set of routines that tell you whether growth is making money. It is not the same thing as bookkeeping, which records what already happened, and it is not the same thing as a title on an org chart. (It also has nothing to do with the Depository Trust Company, which owns most search results for “dtc finance.” We mean direct-to-consumer brands.)

At the early stage, the function comes down to four questions:

• What does each unit really cost us once it lands in a customer's hands?
• How much cash will we have in 30, 60, and 90 days?
• How much inventory do we need, and when do we have to pay for it?
• If we spend more on marketing, what happens to margin and cash?

Notice that none of those require a headcount. They require data that agrees with itself and a model that stays current. That is the part most founders get stuck on, and it is where the analyst hire usually comes from. For the metrics behind each answer, see our guide to ecommerce finance for consumer brands.

Step 1: Put your sources in one place before you build anything

Most early DTC finance problems are plumbing problems. The books live in QuickBooks. Orders and refunds live in Shopify. Warehousing and shipping costs live in a 3PL portal and show up weeks later as invoices. Each system is right about its own slice and wrong about the whole.

TIES connected QuickBooks, Shopify, and its 3PL data into a single model that updates automatically. That is the step that let it skip about four months of integration work. The practical lesson: connect your sources first, and build the model on top of the connected data. Building the model first and wiring data in later is how you end up with a spreadsheet only one person understands.

Step 2: Build a fully blended unit cost

Unit economics are only as good as the costs inside them. During onboarding, TIES combined product-level COGS, inventory, and 3PL warehousing into one blended cost per unit. That produced the first honest view of product margin the team had seen.

It also changed the plan. Luke found that TIES was underestimating warehousing costs and overestimating shipping cost per actual unit. That matters because it changes which levers you pull and which partner you call. If you believe shipping is the problem, you negotiate shipping. If warehousing is the real gap, that conversation goes somewhere else entirely.

The model also surfaced refund and 3PL cost issues that had not been in the forecast. None of those showed up in a revenue report. They showed up because cost, inventory, and fulfillment data were sitting in the same place.

If you only do one thing from this post, do this: calculate a landed cost per unit that includes storage, pick and pack, shipping, and refunds, then compare it to the number you have been using.

Step 3: Plan marketing and finance in the same model

For most DTC brands, marketing spend is the biggest lever and the biggest risk. It is also usually planned in a different file from the one finance uses. The two never reconcile, and the finance view of the quarter lags the marketing view of the quarter.

TIES runs one model where both are planned together. Luke uses the Drivepoint desktop app to test marketing spend and inventory scenarios before committing to either. The question changes from “did we overspend last month?” to “what does this spend do to cash and margin if we place this inventory order?”

That is the real value of a scenario: you see the P&L, cash, and inventory impact of a decision before the money moves. One model, with marketing and finance on the same page, is also a lot easier to defend to an investor than two files that disagree.

Step 4: Stay close to the data yourself

Luke is direct about founder involvement. In his words, every founder should be in the weeds as much as possible on their finance function, because nobody cares about your business the way you do.

We agree, with one condition. Staying in the weeds only works if the weeds are not a full-time job. The point of automating the data layer is not to move the founder away from the numbers. It is to let the founder spend time on decisions instead of upkeep. TIES reports exactly that shift: more time on data and decisions, less on maintaining the model.

TIES also chose a tool with secure, read-only access to its financial data over pasting financial models into a general-purpose AI tool. For a founder who wants AI answers about their own numbers, that is a reasonable line to draw. The AI engine answers questions about the brand's own data and draws benchmarks from consumer categories, and it does so on top of a model the founder can still open and check.

Step 5: Decide when a person is the right next step

None of this argues against hiring. A fractional CFO, a controller, or a first FP&A hire can be exactly right. The question is the order. If you hire first, your new person spends the first stretch connecting Shopify to a spreadsheet and cleaning history. If you build the platform first, the same person starts on strategic finance on day one.

For TIES, the platform came first, and the analyst hire did not make sense at that stage. For a brand with a bigger team, the same platform makes each person more effective. Drivepoint customers improve EBITDA margin by 6.7 points on average in their first year, and one exceptional finance person with Drivepoint does the work of three without it.

A starting checklist for your DTC finance function

1. List the four questions above and write down who answers each one today, and how old the data is.
2. Connect your books, storefront, and 3PL into one source of truth.
3. Calculate a blended landed cost per unit, including storage, shipping, and refunds.
4. Put marketing spend, inventory buys, and cash in the same model.
5. Test the next big decision as a scenario before you commit.
6. Revisit hiring once the foundation is live, not before.

What TIES shows

TIES is early. It is a founder-led DTC brand with a clear product and a broader men's health platform ahead of it. It is also a company that made a finance decision before it had to: build the foundation first, and let the team grow into it.

You can read the full story on the TIES customer story page.

Want to see what a live model for your own brand would look like? Book a demo.