Supply Chain Performance Analytics for Inventory, Supplier, and Fulfillment Management

By Bruce Brownlee

A real-time live-data supply chain dashboard with actionable analytics can be a powerful tool for optimizing inventory, supplier, and fulfillment performance.  The tools we show here will enable a logistics vice president, brand manager, category manager, or operations vice president to optimize supply chain performance.

Actionable Warehouse-Centric Supply Chain Model and Data

Here we model a warehouse-centric view of a the in-country supply chain for a national toy distributor.  Sixteen Chinese manufactures ship containers of toys to the distributor via the ports of Los Angeles, Miami, and Houston. 

Containers are moved by truck to the distributor’s distribution centers in Los Angeles, Dallas, Miami, and Pittsburgh, where the distributor inventories and fulfills orders for 49 different products from 28 different brands of children’s toys in 6 categories, ranging from “Toys for 1 Year Old” to “Toys for Girls 8-11 Year Old”.

The in-warehouse-centric dashboard we’ll review here gives us the tools to analyze what’s going on and to understand problems.  The actionable information delivered enables us to review and improve

  • Inventory performance,
  • Supplier performance,
  • Fulfillment performance, and
  • Distribution center utilization

 

In later blog posts, we’ll discuss supply chain optimization over the entire logistics network, including multi-echelon logistic networks with transshipments.

In the sections following, we’ll dive into each of six pages that offer actionable insights on each of the warehouse-based performance concerns.

Real-Time Data Integration

The data for the dashboards shown here, in production, will come from multiple systems like Salesforce, SAP, Oracle, and many others.  Glimpse dashboards are integrated with a fabulous back end data gathering and transformation system built by Activ Technologies.   When Glimpse is delivered, data integration is included, making Glimpse adoption trouble-free.

Inventory Performance

The Inventory Performance dashboard, as do all others shown here, has a date range selector in the top right corner.  Pull-down menus across the top allow you to select one or more distribution centers, any or all of the suppliers, brands, categories, and products.  For the combination of distribution centers, suppliers, brands, categories, and products selected five key metrics are shown:

  • Inventory Turnover
  • Day Sales on Hand
  • Out of Stock Rate
  • Average Storage Cost per Cubic Foot
  • Gross Margin ROI

 

Each of these is calculated for the date range selected.  Inventory turnover is the cost of goods sold during the period divided by the average inventory for the same period.  Day Sales on Hand represents the number of days of inventory available, another representation of Inventory Turnover.

Out of Stock Rate is the fraction of all products for which there is no inventory on hand.

Average Storage Cost per Cubic Foot is an average across the selected distribution centers.  Typically, distribution centers equipped for automated order fulfillment have a higher storage cost, but inventory turns are higher there too.  In practice, storage cost for “normal size” cartons is less expensive than for very large containers.  Storage costs in ordinary warehouse are, in turn, less than those for a distribution center.

Gross Margin ROI is literally the gross margin on sales divided by the average inventory cost for the period selected.  That is, (sales – cost of goods sold) / average inventory.  Carrying an excessive amount of inventory will quickly reduce Gross Margin ROI.

This page charts Inventory Value against Turnover for selected products.  At a glance, you can spot trouble – large investments in inventory that isn’t selling chart in the southeast corner of the chart.  Low-cost inventory with lots of turns gravitates toward the northwest corner.  This is what “actionable” means.

This page offers Sales by Category and Inventory Value by Distribution Center column charts.  The user can click on any category or distribution center to filter all the data on the page.

Inventory Management

The Trouble Table tab on this page calls out specific products that are either out of stock, down to the last 20% of typical order quantity, or that don’t have enough inventory to last until the next replenishment order arrives.  If the next order will not deliver sufficient inventory, resulting in a subsequent stockout, there’s a warning for that as well.  Suggested actions are shown as a prescriptive measure.

Recent Shipments and Upcoming Shipments tabs provide a consolidated view of what’s happening with product inventory.  With the information provided, the category or brand manager or operations VP can prevent future stockouts, plan for product replenishment, and plan replacements where needed.

Supplier Management

Here three key metrics let you understand supplier performance across all suppliers, or for a specific supplier.  You can even drill down to a specific product.  For the vendors, vendor, or product selected, metrics are shown for

  • Delivered In Full On Time
  • Accurate Order Rate
  • On-Time Delivery Rate

 

An accurate order is one for which each line item is delivered in the quantity ordered.  Delivered In Full On Time is the product of Accurate Order Rate and On-Time Delivery Rate.

The Inventory On Hand and Inventory on Order by Suppler chart provides an at-a-glance view of what’s already in stock versus what’s on order.  This provides actionable information – making it easy to see where large inventory positions of unsold products are being followed up with large incoming orders (that might best be cancelled).  Clicking on a column in the chart filters the list of orders at the bottom.  It’s also possible to see if large orders have been placed with non-performing suppliers.

Fulfillment Performance

Perfect Order Rate is the product of

  • Customer Acceptance Rate,
  • Accurate Order Rate, and
  • On-Time Ship Rate.

It is a measure of your outbound fulfillment performance that affects your customers.  In this page Perfect Order Rate is shown in charts by distribution center, supplier, and for products with the lowest and highest perfect order rates.  Clicking on any of the product bars in the charts will filter the entire page to just that product.  This makes it easy to identify the source of the problem – customer returns, inaccurate orders, or late shipping.  For example, clicking on the Flybar Master Pogo Stick bar in the Products with Lowest Perfect Order Rate make it clear that a very poor On-Time Ship Rate is the first problem to fix.

The Return Reasons pie chart calls out the leading reasons for which customers are returning product.   This can provide an actionable insight for the category manager or logistics VP, and help identify viable approaches to reducing returns.

Distribution Center Capacity Management

Charts on this page show three charts with timelines:

  • Distribution Center Utilization (storage capacity used)
  • Value of Inventory by Distribution Center
  • Inventory Turns

 

The data show an increasing inventory and value of inventory, but also increasing inventory turnover rate, which is good.

Each chart, and the list of products at the bottom, can be filtered by distribution center, supplier, brand, category, or product in order to drill down to find specific performance.

Distribution Center Stock

This very visual page enables you to filter by product in the scrollable list at the bottom, and then view every storage location where that inventory exists in any of the four distribution centers.  You can also click on an inventory storage location and see the details in the scrollable product list at the bottom of the page.

Interested in seeing the Glimpse dashboard in action? 

About the Author

Bruce Brownlee is a data scientist and product manager with an undergraduate math and engineering degree and an operations research graduate degree with a focus on stochastic processes and mathematical optimization.  He’s worked as an industrial engineer, software developer, marketing director, data scientist, and product manager across a broad range of industries where analytical skills are required.  His special interests include financial modeling and machine learning applications.

Bruce Brownlee

Product Manager at Blackstone+Cullen

Read more from Bruce Brownlee
LinkedIn