Jessica Lachs, vice president of analytics and data science at DoorDash Inc.
PHOTO: DOORDASH INC.
WSJ’s CFO Journal talked to Ms. Lachs, who reports to Mr. Inukonda, about how analytics support DoorDash’s financial operations, particularly at a time of high economic uncertainty. Her responses have been edited for length and clarity.
WSJ: How do you see analytics corresponding to the finance function?
Ms. Lachs: It’s all about our desire to measure as much as possible. When we roll out a new product feature or program to customers, we can run an experiment and actually quantify the true impact that it had on the business and all of those things can then get incorporated into our forecast. These features range from in-app changes like a new carousel on the home page to the performance of new machine learning algorithms to our release of the pickup map in the DoorDash app. By understanding what we’re seeing in the data, we can make better investment decisions.
WSJ: Is the slowing economy affecting the company’s approach to forecasting?
Ms. Lachs: We are keeping a watchful eye on everything that’s happening in the market, particularly as it relates to inflation and consumer softening. A cool thing that we did that empowers our CFO to make good decisions is by building out what we call the DoorDash item price index. We have our own internal price index that tracks and measures changes in the average item price on the platform weekly. The index uses the most popular merchant items ordered on the platform. We track against the U.S. consumer-price index on a monthly basis to understand if prices on our platform are increasing at an accelerated rate compared to [the] overall prices in the economy.
We are tracking price indices on fixed and floating baselines in order to show the marketplace’s health from different points of views. The fixed-weight index shows price changes that are independent of changes in consumer choice. The fixed-weight index will stay flat if merchants do not update prices. The floating-weight index shows price changes with the impact of consumer choice. It can change either due to merchant price updates or consumer purchase shifts.
WSJ: What is the floating-weight price index showing you?
Ms. Lachs: Consumers are ordering fewer items per cart. But interestingly, they’re keeping higher-priced items. It makes sense because they’re more likely to be an entrée. As where you maybe had ordered an entrée and a side, now you’re just keeping the entrée. Or, if you had ordered an appetizer, two entrees and dessert, maybe you’re not going to order dessert now.
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We are watching these indices and how they track to the broader CPI like a hawk because we want to make sure that any trend break we see we can incorporate into our forecasts. The net result from what we’re seeing was a slight increase in subtotals, and we incorporated that into our forecast because that is something that we expect to continue.
WSJ: Do you have a cost-savings target associated with your analytics effort?
Ms. Lachs: Our goal isn’t specific to savings. We will have a goal on savings that we might want to get through quality improvements, for example. By having higher quality on the platform and reducing defects, that results in less credits and refunds, which obviously has a positive impact on margins. So that may be something that we set a goal for. The teams across product, operations, engineering and analytics will have that goal. And then it’s analytics’ responsibility to identify the key drivers of defects, to really understand what’s happening on the platform so that we can figure out the big opportunities for us to improve quality so we can hit whatever the goal is that we’ve set on reducing cost.