Customer Story

Bedding Products Manufacturer Finds Comfort in Reliable, Integrated Data — Accelerates Growth

About the Manufacturer

This direct-to-consumer company is shaking up the bedding industry with their high-quality products at affordable prices. Since the company’s launch in 2014, they have soared to success, growing into a $100 million brand recognized nationwide for their wide range of bedding, bath, and home decor items.

With plans to open 20 more brick-and-mortar locations and add two new distribution centers in the coming year, the manufacturer is continuing to expand and solidify their successful business model without sacrificing the quality and comfort they provide their customers.

Goal

The company is on a mission to double their global reach and expand their brick-and-mortar locations and distribution centers. To sustain their commitment to quality products at an accessible price point — they need to operate an efficient supply chain and be able to access and analyze critical data points like inventory, profitability, outbound freight costs, revenue, budgets, and forecasts across the organization.

The manufacturer needs to improve their ability to quickly and accurately navigate their growth and provide their CEO with a unified view of the business and the executive team with accurate KPIs to report to the board.

Problem

The business had already invested in a modern data architecture that included FiveTran, dbt, Snowflake, and Looker. However, while the internal data team was leveraging their modern data stack to get insights into sales and marketing initiatives, they did not have access to essential data from brick-and-mortar stores or the supply chain.

The missing data was necessary for understanding if a product was selling better in one channel or market versus another. This lack of insight prevented the company from making informed inventory allocation decisions.

As a result, they faced the following challenges:

  • Business users — within different business units — needed to extract data from multiple locations to gather information needed for critical analysis.
  • There was not a single source of truth or a unified view of the business.

The company was in a reactive mode without accurate reporting and needed a solution that would allow them to easily access, analyze, and report their KPIs in real-time so they could make more informed and strategic business decisions.

Solution

The manufacturer turned to Analytics8 to complement their internal data team, to integrate and model their supply chain and brick-and-mortar data, and to build an analytics solution for their executive team and board of directors.

We started with conducting a comprehensive evaluation of their existing architecture and processes to identify areas for improvement, reduce redundancies, streamline processes, and speed up the development cycle around data modeling. With this information at hand, we:

  • Implemented modularization of code to eliminate duplication of effort, ensure consistency of KPI definitions, and reduce drift — resulting in a more scalable and efficient solution.
  • Used dbt snapshots to manage current and historical inventory data from volatile data sources, enabling analysis of seasonality and trends over time.
  • Introduced channel reporting and inventory and profitability reporting, positioning the company to incorporate future locations in their data model without additional logic.
  • Created multiple dashboards around inventory, profitability, freight and fulfillment, and executive-level KPIs.

Results

Our solution provided the manufacturer with a stable and improved modern data architecture and an advanced data visualization platform so they can make data-driven decisions quickly and accurately, while providing the CEO with a single source of truth and the executive team with accurate KPI data to report to the board. With the integration of supply chain and retail data that was previously missing, they now have a comprehensive understanding of the business.

The analytics platform we developed included the following dashboards:

  • Inventory dashboard gives the business access to a snapshot of the inventory levels at all warehouses, as well as the ability to analyze high volume products to ensure that inventory levels will support orders and not result in backorders or lost sales.
  • Merchandise profitability dashboard provides insight into the top performing products that represents the highest gross profit percentage and overall percentage of revenue. It is used heavily for promotional planning around Black Friday events or the holiday season.
  • Freight and fulfillment dashboard provides metrics around costs and delivery volumes at the warehouse level along with comparing to the prior year’s numbers. It also tracks all charges incurred for each carrier. This dashboard is expected to provide significant cost savings by allowing the company to assess additional costs incurred and determine the reasons for those costs, such as shipping from a location further away than a closer warehouse.
  • Executive summary dashboard brings all the key metrics into a single executive level view, including inventory and profitability KPIs, Sales Orders, Product Net Revenue, Shipping, Returns, and Net Realized Revenue. These KPIs are compared against the prior year, budgets, and forecasts.

Data modeling provided a major benefit by enabling the company to integrate data from multiple sources into a cohesive data warehouse. By following best practices in modeling the data from their ERP system, they were able to create connections to other commonly used data categories, allowing the team to combine sales and fulfillment data with other sources — forecasts, budgets, and product details — resulting in more comprehensive reporting.

Overall, our solution provided the company with the ability to get a better view into all their data, increase efficiency and reduce costs, helping them work toward their goal of doubling their reach with additional brick-and-mortar locations and distribution centers around the world.

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