Why Data Fragmentation is Stifling Your Growth (And How to Overcome It)

Cohesive data is the foundation of any brand's inventory management strategy. However, it's common for retailers to have this data siloed across many internal systems, making it near-impossible to understand true business dynamics and scale effectively.

This flawed practice is one that we often witness firsthand at Moselle. Over the years, we've conducted 300+ interviews with leading DTC retailers to understand their inventory hurdles, and every single one listed data fragmentation as a crucial operational bottleneck obscuring their path to growth.

So, how can your brand avoid falling into this trap? In this guide, we'll dive into the causes and effects of data fragmentation and how solutions like Moselle can deliver the single source of truth that transforms inventory management into your competitive advantage.

How DTC Data Becomes Fragmented

Data fragmentation has become a common reality in today's DTC landscape. High-growth brands are most likely to fall into this trap as they scale operations to support their momentum. The most common growth initiatives that lead to data fragmentation include:

Rapid Expansion to Multiple Sales Channels

Entering new channels to drive revenue seems like a no-brainer, especially for rapidly growing consumer brands. However, as these brands often prioritize sales growth over operational readiness, marketplace expansions are often executed without extensive planning for how their data will be monitored, integrated, and analyzed across systems. 

The result of this rapid scale is a patchwork of disconnected platforms, each with its separate dashboard, data organization, and analytics capabilities. To make informed decisions about their stock and budget, brands need to manually cross-match information across their sales channels, 3PL portal, and accounting software.

As SKU count and order volume increase, repeating this manual reconciliation process becomes more complex and time-consuming, compromising data visibility and strategic inventory management.

Onboarding Diverse eCommerce Solutions

As brands continue to grow, the simple Shopify-and-Quickbooks setup that powered their early stages can quickly transform into a complex web of specialized tools for fulfillment, data analytics, and revenue optimization. However, while the adoption of these solutions can streamline critical functions, it also progressively spreads data across the tech stack.

Why is this the case? Since these tools integrate with each other, most brands assume that their data flows smoothly across systems and thus stays synchronized. In reality, each specialized solution collects information according to its own unique formatting and standards. So when it shares data with its integrated platform, some bits and pieces get lost in translation.

The result? While a brand's tech stack remains connected, there isn't a single source of truth to provide a reliable, comprehensive picture of their business. Adding to this complexity, legacy software often remains siloed. In the end, brands resort to manually piecing information together from each platform to determine key metrics like inventory turnover and stockout rates — all without any assurance that their calculations are accurate.

The Hidden Costs of Fragmented DTC Data

When DTC data lives across disparate systems, it affects nearly every aspect of a brand's operations — from daily inventory management to strategic long-term decisions. Here's how:

Time-Consuming and Inefficient Data Analysis

Without a centralized location for DTC data, extracting actionable insights becomes a complex puzzle. Operators gather, clean up, and reconcile information into a unified spreadsheet. Building this stock view takes hours at a time, meaning that it not only delays business decisions but is also outdated by the time they've compiled it.

More importantly, these records are not just stale — they're prone to input errors due to the constant copy-and-paste across sources. With multiple data points to manage, these mishaps can easily slip through the cracks and snowball into costly discrepancies. For instance, missing a zero during data transfer — typing 100 instead of 1000 — could cause a brand to underorder inventory, stock out unexpectedly, and rush additional units at a higher production cost.

Limited Data Visibility Affecting Business Performance

Every platform in a brand's tech stack presents information differently — so teams working without a centralized location for their data often end up using different numbers to evaluate performance.

Here's a typical scenario: a marketing dashboard shows 500 units sold based on completed checkouts, while an accounting platform reports only 475 units since it excludes orders with pending or failed payments.

Without accurate numbers, these teams have no reliable way to calculate metrics like sell-through rates and order fill rates. The impact of this limited visibility ripples through inventory management operations, increasing the risk of restocking too late and carrying excess stock. This is not uncommon — 34% of retail businesses shipped an order late because they sold an out-of-stock product.

Inaccurate Forecasting and Stalled Growth

A ready-made view of SKU performance across time and channels enables reliable forecasting. Without it, brands resort to consolidating years of historical data for every SKU and channel in a spreadsheet. When they layer on monthly forecasts for every data point for a year in advance, their files often buckle under complex data analytics operations or run out of rows.

Most often, brands end up operating in the dark — either working with an inaccurate or incomplete view of their inventory or without any forecast at all.

With limited information to support their growth, they can't plan future POs to reliably meet demand, prepare for seasonal fluctuations, or optimize cash flow. What's more, external stakeholders (like investors or lenders) have less clarity into their business dynamics, which could impact their access to capital.

3 Common Remedies to Data Fragmentation (And Why They Miss the Mark)

To break down data silos, brands explore three common "remedies" to unify their information. On the surface, these approaches seem to offer the initial promise of providing critical insights to drive business growth. However, each falls short of achieving a cohesive data view — here's why.

1. Consolidating Data in Manual Spreadsheets 

Many brands try to centralize their data into Google Sheets or Excel files, treating them as an ad hoc source of truth. While this cost-effective strategy might work in the early stages of their business, it quickly becomes unsustainable as they scale.

To build these spreadsheets, brands spend countless hours transferring information by hand and building complex formulas that break as their data multiplies. Before long, these makeshift databases become riddled with errors and crash because they’ve grown too large.

2. Implementing an Enterprise Resource Planning (ERP) System

Larger brands often turn to ERPs, hoping that a comprehensive system can be the silver bullet solution to data fragmentation. However, these platforms are usually too rigid and costly to support their business.

While an ERP might centralize core DTC data, brands also need to shoulder high subscription fees and invest significant time in team training. And even after all these efforts, they might still return to spreadsheets if the system offers limited integration and customization capabilities.

3. Building a Custom Software Solution

Some brands choose to develop a proprietary system to unify their data streams. While these solutions are always custom-tailored to their business, they can quickly become another complex platform to manage and troubleshoot.

Custom software demands significant engineering resources and ongoing maintenance to operate smoothly and keep up with updates from third-party platforms. Ultimately, teams spend more time revising API connections and debugging failed data syncs than leveraging the solution for sustainable growth.

How Growing DTC Brands Can Create a Single Source of Data Truth

While patchwork solutions like spreadsheets and ERPs might provide some inventory visibility, they quickly reveal their limitations as a business expands. To drive profitable growth, DTC brands need a dedicated solution that will deliver comprehensive, accurate insights without time-consuming maintenance or hefty fees.

This is where modern inventory management platforms shine. These systems seamlessly connect to your tech stack to unify all critical data in an intuitive overview. The best solutions harness this centralized data to generate customized reports and robust forecasts — everything a brand needs to optimize its inventory strategy and further scale the business.

Unify Your Critical Data and Fuel Sustainable Growth With Moselle

While there are many dedicated inventory management platforms that deserve your attention, Moselle goes the extra mile to help you drive sustainable growth. Our platform provides a single source of truth for your disparate data by connecting with over 60 tools that DTC brands rely on in their day-to-day operations — from sales channels like Amazon and Shopify to SaaS solutions like Quickbooks to your WMS and 3PL. These options are consistently expanding, with custom integrations available for your unique business needs.

Once your data is connected, Moselle automatically creates a live overview of your inventory, as well as customizable weekly and monthly stock and sales reports. After setting up your catalog and bill of materials, you'll get automatic forecasts showing projected stock levels for every SKU month by month.

Fast-growing brands like Loisa lean on these capabilities every day to meet surging demand. The culinary brand consolidated all sales, inventory, and PO data for their 80+ product catalog to unlock actionable insights about their business.

Now, their team makes informed decisions about the timing of their purchase orders and their reorder quantities — driving some significant results:

• 104 hours saved annually on inventory management
• 100%+ YoY sales growth supported by seamless inventory operations
• 50% of orders come from repeat customers

Ready to transform fragmented DTC data into powerful insights? Get started today.