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DTC needs a new operating system.
There. I said it.
The practice of building and launching a brand that primarily sells directly to its customers (heretofore referred to as DTC) is broken and needs to be fixed.
There is cognitive dissonance in this statement. eCommerce as a Sales Channel has continued to outpace traditional retail over long time horizons. eMarketer recently reported that eCommerce grew by 17% in 2021 and is projected to grow at an average rate just shy of 10% through 2026. In the United States, eCommerce accounts for $1 Trillion in Sales - which is expected to grow to $1.5 Trillion over the next 4 years.
DTC — while a tiny slice of the eCommerce pie — is growing at a faster clip than both eCommerce and retail Sales, now estimated at ~$130B annually.
With this information in mind, you may be wondering what could possibly be broken about a business model that, by all accounts, is growing rapidly into a rapidly growing market.
The answer? A faulty operating system.
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In order to properly understand and diagnose this problem, we must travel back in time to the heralded period of legacy retail. I use the term legacy liberally to generally describe the brands and businesses of yesteryear. Think: Ralph Lauren, Gap Inc, Brooks Brothers, Levi Strauss & Co, and so on.
Over time, these brands have become household names in the United States. They’ve reached this critical mass with one common catalyst: the ability to harness, commercialize and operationalize creativity to service consumer needs or wants (a.k.a. demand).
Operationalizing creativity is a complex problem to solve, and like all complex problems, it requires an operating system to manage all inputs and outputs, to scale efficiently, and maximize value creation. A strong operating system paired with a consistent and repeatable process yields the opportunity for a complex problem to be solved with repetition - and at scale.
In framing the gap that exists in the current DTC operating system, it’s important to understand the systems and processes of past legacy brands. This narrative is rooted in one key software tool: Enterprise Resource Planning (ERP).
Enterprise Resource Planning systems are relatively new to the merchant world. In the 1990s, the research firm Gartner coined the term ERP to describe the successor of more rudimentary MRP (Materials Resource Planning) systems. These MRP systems were designed to manage the conversion of raw material or parts into finished goods. The first example of this was J.I. Case, a 1960's manufacturer of tractors and construction equipment.
Previous to the 1990's, this technology had been limited to large organizations, but the proliferation of personal computing - along with the internet - allowed for the retail industry to implement more modern ERP solutions.
ERP systems evolved beyond manufacturing through the 1990's into the 2000's. Finance, human resources, logistics, merchandising, and retail were functionally built into ERP systems. These systems became a network of data and modules that allowed all functions of an organization to work horizontally and in concert. Leaders in this technology emerged and became giants, with notable providers such as SAP, Oracle, JDA, and Microsoft.
The fundamental underpinning of the value of an ERP system can be boiled down into one simple statement:
An ERP System is a source of truth.
ERP systems act as data hosts for Master Data. Master Data refers to the atomic elements of business, as listed below.
Legacy brands poured their Master Data into ERP, engineering processes to work alongside this data in a slow but steady orchestration, which then moved in tune with their product lifecycle. They spent time, energy, and resources honing their value chain, recognizing that in most cases, creating unique and long-term value was a practice that required patience and persistence.
The most critical element and output of this legacy operating system is planning. Capturing data and understanding where a business stands is necessary; planning into the future across all of the atomic elements of business is mission-critical.
The most critical element and output of this legacy operating system is planning. Capturing data and understanding where a business stands is necessary; planning into the future across all of the atomic elements of business is mission-critical.
I will be the first to admit, the pace of business during this era of brand building was slow — at least in relative terms. The product and marketing lifecycle took shape over months, if not years in some cases. This slow, steady plodding resulted in one key shared outcome: product, marketing, and sales channels existed in harmony. Investments across these key areas of the business were made with shared understanding and alignment.
When inventory was purchased for a new product launch, the investment and the marketing plan were tuned together. Brands made the best (let’s be honest: most commercial) products they could conjure. Marketing assembled the largest top-of-funnel rain cloud they could muster. Channels (Retail, Wholesale) were invested in and constructed to collect as much of the Product x Marketing rain as possible.
All of these strategies and tactics, as well as the tools and processes that powered them, were oriented towards a specific time window in the future. Like an army assembling and preparing for a future battle, the organization was preparing as if this was their one shot to make a splash. Once the battle ensued, they knew that the most important factors in definiting the outcome were preparation and execution. Changes in strategy or tactics on the battlefield would not win the day.
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Direct to Consumer in the modern digital era has gone through a number of step-function iterations. The founding brands of the DTC era built themselves in the shadow of legacy brands, leveraging a similar approach to brand building, process, organizational structure, and operating system.
There were, however, two key differences between legacy brands and DTC 1.0 brands:
Leveraging eCommerce as the primary means for transacting with customers is critical to the value proposition of Direct to Consumer as a business model. This was true back in 2007, the same as it true today, and will be tomorrow. This modernization of commerce has allowed brands to capture rich data about their customers.
Although the DTC 1.0 crop of brands modeled themselves against their legacy predecessors, new tools needed to be assembled as the legacy ERP tools and other systems were far too “heavy” and oriented towards an old-world way of business.
Entire eCommerce platforms were built from the ground up to support these brands, prior to the inception of Shopify. Similarly, the dominant digital channels we use today to generate demand and awareness were either nascent or non-existent.
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Facebook launched its advertising platform in November of 2007. Six years later, Instagram began selling ads in 2013. Social media platforms like Snapchat, Pinterest, and TikTok joined the chorus of options.
As many marketers of the early digital advertising era can attest, it was a gold rush - and in some ways, the rush still remains. After seeing the value of digitally native brands, a dramatic influx of capital for DTC 1.0 and DTC 2.0 era brands began to pour in.
This avalanche of growth capital was voraciously allocated to, well, growth. But not necessarily growth in the slow, careful, process-oriented methodology of legacy brands. Instead, this capital was strapped to ad rockets and fired aggressively into whichever advertising platform would drop the highest return out of orbit.
The reliance on digital marketing for growth morphed everything about how DTC Brands were constructed.
Once word spread that there was gold in the hills, and Shopify did what Shopify set out to do (make it possible, nay: EASY, for any merchant to launch an online shop), many more miners joined the expedition. Quickly, they crowded out not only the availability of our most precious resource - customers- but in doing so, also washed away the approach of how real, long-standing value to customers is created.
This is a bold assertion.
I stake this claim on the grounds that what is good and what works in modern digital marketing is often not congruent with the long-term value creation that a brand, product, and/or service should generate.
The tactics to cut through the din of the gold rush have skewed into the world of stunts, gimmicks, "virality", and any number of discounting hoops conceivable -- all designed to make it easier for the consumer to jump through. These are not value propositions, these are tricks. And of course, they work, because they are relatively easy to pull off. Building a well-constructed and consistent Value Chain is exceedingly difficult and laborious by contrast.
The outcome of this practice is that much of DTC is fast and reactionary.
For example, an ad focuses on a specific product and contains an offer for that product. It works and the marketing metrics (pick your favorite flavor of marketing KPI) are through the roof. Intuitively, marketing spend shifts into that ad. The ad scales up, reaches more people, drives more transactions, and ultimately burns through the inventory available for that product - like harnessing rays of sunlight through a magnifying glass.
Ok, great — we did our job. We created demand and we acquired customers. We’re now sold out, but we’ll get back into stock soon for this product so we can run it back.
Narrator: They will not.
This scenario happens all of the time to any number of brands in the DTC ecosystem, and even when it doesn’t, less troublesome scenarios arise from this practice.
The "test-broadly-and-back-the-winners" approach to marketing is discordant to the back end of the business. Modern supply chains largely remain slow in relative terms to this front-end activity. Product creation and Go To Market lifecycles span weeks at best, often months.
It’s a shell game that whiplashes the back end of the business and can be destructive to the broader Value Chain. It’s like any alcohol. Some is good, too much will make you sick.
The "test-broadly-and-back-the-winners" approach to marketing is discordant to the back end of the business. Modern supply chains largely remain slow in relative terms to this front-end activity. Product creation and Go To Market lifecycles span weeks at best, often months. The result? The tail end of the Value Chain and Go to Market process is wagging the dog.
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The lead-up above suggests that the legacy method of building a business is good, and the modern way of growing and scaling a DTC brand is bad. Neither is true.
Digital marketing is not an inherently bad practice. Speed, reactivity, and flexibility are super-powers for modern DTC brands relative to the lumbering giants of old. Most of the ‘shiny’ new picks and shovels are very useful and valuable. There are lightweight, powerful options across the entire operating stack for brands to integrate and deploy.
The smorgasbord of tech stack solutions — particularly on the front end — has never been more plentiful and the various ways in which these tools can be oriented and implemented are nearly limitless. This is a good thing.
That being said, DTC lacks a central nervous system. Do we have arms and tentacles meant to gather all forms of data and pipe them in via API to send synapses back to the Brain? Yes, we do.
But without a central nervous system to interpret these signals, tie them together in some meaningful way, and send them to the brain for deep learning rather than reaction, we are doomed to escape the Gold Rush.
My viewpoint is that this Central Nervous System would carry the core elements of a legacy ERP system, but go a step further to harmonize the Front End (Demand Side) of the business and the Back End (Product/Service, Operations Side) of the business.
Let’s revisit the atomic elements of business and master data: Product Library, Vendors/Customers, Costs, Sales Channels, and Transactions.
All of these atomic elements are combined and powered by human capital to generate profits. In order to maximize these profits, we must understand the chemistry at play between the atomic elements. How are they connected? How are they bonded?
Most importantly, what are their attributes and where can we find correlation or (much less likely) causation between these attributes?
If we deploy a piece of marketing, we must ask ourselves: What are the attributes of the audience that consume the ad? What are the attributes of the product, and where do they overlap for the customers that ultimately transact? How do we stack-rank these relationships and how do we focus our energy and attention on:
And most critically: How do we translate all of these relationships, map them to the resources at our disposal, and create a myriad of scenarios that stretch out into the future for how the business will grow with this newfound knowledge?
The legacy approach of the past was laced with issues that don’t fit into the modern approach to business: too slow, too heavy, too many resources required, too much maintenance, and so on. However, the lack of data and computer processing power of the 90's and 2000's, as well as this slow cadence, forced businesses to align and focus on building into the future. It was much more rudimentary. It was much more successful at scaling.
Adopting this practice and leveraging an Operating System that can power it in the modern sense moves DTC away from the reactionary state that plagues the industry and into a future state.
Dashboards that tell us what is happening in real time are fantastic. Farming data from downstream systems/hosts through API and bringing it into a central environment that allows business rules to guide action is valuable — but again — reactionary.
Honestly, I wish we had these tools 10 years ago. But they do not serve the long-term goals of the business in a holistic way — at least as they are currently constituted.
As an operator, I don’t need a weather report, despite it being helpful to decide how to dress for the day. I don’t need to know that it’s raining. I can feel the raindrops on my forehead.
What I need is to be able to make the weather. I need to be able to gather the information at my disposal, synthesize it, add a dash or two of gut instinct and intuition, and push all of that out into the future so that I have a picture (even if fuzzy) of what it might look like. From there, I can carve harness the creativity and ingenuity of the organization, and forge the path forward.
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