SolutionsAllocation Optimization Replenishment Optimization Markdown Optimization Transfer Optimization
Number of Employees 11.000+
Number of Stores 650+
Number of DCs 15
The FLO customer success story at a glance
FLO is one of Europe’s largest footwear retailers, currently operating in 21 countries and 3 continents. The retailer serves millions of customers everyday through its wide retail network of 650+ stores and its multi-brand e-commerce channels.
The retailer aimed to increase forecast accuracy, maximize availability, and optimize inventory smartly to improve supply chain efficiency. FLO also needed superior omni-channel inventory planning capabilities to reduce lost sales, increase sell-through and improve fulfillment efficiency.
FLO rolled out Invent Analytics’ AI-based retail planning solutions, including Allocation Optimization, Replenishment Optimization, Transfer Optimization, and Markdown Optimization. As a result, leading footwear retailer has reduced out-of-stocks and inventory, lowered fulfillment costs, and improved gross profit.
With Invent Analytics, we have accelerated our demand forecasting, allocation, replenishment capabilities significantly. Invent Analytics not only has the right inventory optimization solutions, but their approach and their deep understanding of omni-channel retailing enabled us to adapt and thrive in the omni-channel retail space.Burak Ovunc, CEO, FLO
The challenge: Making optimized allocation and replenishment decisions
As a leading footwear retail chain, FLO wanted to generate highly accurate forecasts at all levels of granularity and determine the right amount of inventory required in their stores and distribution centers.
The retailer needed to replenish stores, DCs, and hub-stores with the right amount of inventory at the right time in anticipation of omni-channel demand that could be fulfilled from every possible source.
Gaining a full-season perspective to enable more accurate and timely allocations and making profit-optimized inventory decisions was also critical for FLO.
Choosing Invent Analytics
After evaluating multiple vendors, FLO selected Invent Analytics to meet their evolving omni-channel retail needs.
Invent Analytics’ margin-driven, profit-optimizing science, tailor-fit algorithms, and AI-powered probabilistic demand forecasting offered everything we’re looking for. Their solutions enable us to achieve the most profitable inventory levels using a sophisticated economic model that analyzes demand patterns, inventory costs, margins, and other parameters.Hakan Ugur, Chief Merchandising Officer, FLO
Upgrading inventory decisions to a financial optimization-driving process
FLO implemented Invent Analytics’ tailor-fit solutions. Invent Analytics delivered speed to value and proved the benefits of its profit-optimal solutions with pre-go-live simulations and A/B testing.
Following the implementation, FLO upgraded its inventory decisions from a judgment-driven, KPI-measured process to a financial optimization-driven and measured process. The retailer was able to deliver superior omni-channel customer experiences while increasing margins.
Benefiting from AI-powered demand forecasting
Every day, Invent Analytics’ system generates forecasts at all levels of granularity. The solution using explainable AI and fast learning algorithms predicts how, when and where FLO’s omni-channel customers want their orders to be fulfilled.
Advanced allocation and replenishment optimization
With Invent Analytics’ Allocation and Replenishment Optimization, FLO sends the right amount of inventory to its stores, reducing left-over risks at stores and early stock-out risks at the distribution centers.
As a result of the dynamic and smart positioning of inventory, FLO gets higher sell-through and reduces overall fulfillment costs. The retailer optimizes inventory by anticipating omni-fullfilment of demand and easily calculates optimal inventory levels for each item-store-day.
While balancing lost margin from out-of-stock and the cost of carrying inventory, FLO ultimately achieves better inventory planning.
Size and case pack optimization at a store-level
Invent Analytics’ Size Optimization predicts FLO’s future sales and inventory needs by size and determines the profit optimized case-pack configurations to meet customer demand at a store level. Using AI-based advanced analytics, the system identifies stores with similar size selling patterns to create more granular profiles. It clusters them by size-demand ratios and match size profiles to forecasted demand.
Integrated with Initial Allocation and Replenishment systems, Invent Analytics’ Pre-Pack Optimization system evaluates and optimizes product packages and makes new assortment suggestions. It also determines size-level store needs and matches case packs to fulfill demand for each store. The system helps FLO to improve operational efficiency, increase sales, and reduce lost sales and markdowns at a size level, contributing to a 4.7% net profit.
Financial impact of pre-pack optimization
Optimally timed markdowns
With Invent Analytics’ Markdown Optimization, FLO accelerates its margin growth by optimizing markdowns throughout the product lifecycle.
Invent Analytics’ Markdown Optimization solution optimizes FLO’s markdown path through the season and directly improves the retailer’s margin and end-of-season sell-through.
Increasing omni-channel profitability by rebalancing inventory across locations
Using Invent Analytics’ Transfer Optimization solution, FLO rebalances inventory across locations for maximum efficiency. By moving products from underperforming locations to other locations where demand is higher, FLO minimizes lost sales and markdown losses.
Increased availability, reduced lost sales
With Invent Analytics, FLO has achieved significant business results, increased its availability from 71% to 94% and reduced lost sales from 15% to 3%.
Future-ready next step: Omni-Network
In 2021, FLO started its new Omni-Network Project with Invent Analytics. FLO focused on knowing the network structure best positions their supply chain to fulfill omni-channel customer demand.
The retailer wanted to assess how many DCs and hub stores they need to serve to which locations of stores and customers. And more importantly, they wanted to see what alterations of network structure are necessary to better position their inventory to reach their online customers on time and in the most cost-effective way possible.
“With Invent Analytics’ Omni-Network, we were able to move from 62 omni-store network up to 360 omni- store network to be able to obtain 2.7% improvement in their annual sales revenue. That also means around 17% improvement in shipment duration while obtaining 1.1% additional gross profit and 0.9% additional net profit without any additional inventory,” said Burak Ovunc, CEO of FLO.
Download the case study and find out how FLO reduces lost sales by 12%.
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