Store Replenishment

Q: Automate Inventory Management Process

Inventory Optimization working with store/DC capacity, store replenishment frequencies and other operational considerations Load-balancing for DC work orders Integrated with warehouse PO management for fewer manual interventions Automatic selection from 30+ forecasting methods for best fit, including promotion effect and pricing options Improve inventory productivity and reduce lost sales

Q: Improve Inventory Productivity And Reduce Lost Sales

SKU/Store forecasting leveraging machine learning taking into account demand-drivers such as promotions, special dates, and weather changes ensures a more accurate version of the expected demand DC Replenishment integrated with Store Replenishment ensures DC-purchase orders always consider store needs Integration with ERP system enables automated PO creation with faster execution Demand-driven inventory optimization of competing goals – inventory cost and lost sales

Q: Boost Agility And Scalability

Highly and quickly scalable and adaptable for business growth, supporting new categories, new channels, and new store locations Short implementation cycles of cloud-native single planning platform Solvoyo Cognitive Learning for new product introduction and store openings Single data model and analytics engine for end-to-end SC platform all easily accessible through a configurable user interface

Optimally replenish your stores and distribution centers (DCs) in a demand-driven model, optimizing inventory levels to meet service level targets while minimizing inventory costs

Delight your customers with
better availability

Store replenishment is one of the core operational processes for retailers. The trade-off between availability and excess stock is one of the main daily challenges the planning teams face. Companies need to expect what, when, and how much customers will purchase at each channel and location and replenish accordingly to prevent lost sales, stock-outs, and customer disappointments. Especially for retailers managing large SKUs, determining each sales location’s optimal inventory targets can be challenging and time-consuming. An automated and demand-driven replenishment planning solution that tracks inventory forecasts store demand provides executable SKU level replenishment recommendations subject to operational constraints, improves availability, and minimizes lost sales.

Solvoyo Store Replenishment helps automate dynamic inventory target setting and daily replenishment decisions using demand-driven models and minimizing the possibility of lost sales. Solvoyo Demand Forecasting considers different demand drivers such as weather conditions, special events for a more accurate view of expected demand. Prescriptive analytics working with operational and business constraints such as packing requirements, store capacity, and replenishment frequency give recommendations that can be executed immediately without manual intervention. Through automated diagnostics and KPI tracking, users can quickly focus on items requiring attention, approve actions, and send work orders directly to the WMS systems.

Erkan Ceritoglu

Managing Director
A101

"Using demand-driven replenishment planning gave us the agility and scalability we needed in times of market disruptions. We replaced our manual methods with automated recommendations for 10,000 stores in different locations. Thanks to Solvoyo’s daily replenishment recommendations, we gained a competitive edge by reducing stock-outs and increasing availability."

 5/5

What can you achieve with Solvoyo
Store Replenishment Solution?

Automate Inventory Management Process

Improve Inventory Productivity And Reduce Lost Sales

SKU/Store forecasting leveraging machine learning taking into account demand-drivers such as promotions, special dates, and weather changes ensures a more accurate version of the expected demand
DC Replenishment integrated with Store Replenishment ensures DC-purchase orders always consider store needs
Integration with ERP system enables automated PO creation with faster execution
Demand-driven inventory optimization of competing goals – inventory cost and lost sales

Boost Agility And Scalability

Highly and quickly scalable and adaptable for business growth, supporting new categories, new channels, and new store locations
Short implementation cycles of cloud-native single planning platform
Solvoyo Cognitive Learning for new product introduction and store openings
Single data model and analytics engine for end-to-end SC platform all easily accessible through a configurable user interface

Minimize Lost Sales

Improve Inventory Productivity

Demand-driven Replenishment, DC Purchasing

A101 – World’s 5th Fastest-Growing Retailer
A101 achieved digital transformation of manual planning process through a single platform supporting collaboration and visibility

Read →

In-season Inventory Management

DeFacto – Multinational Apparel Retailer
DeFacto reached a 100% automated initial allocation & replenishment processes’ accepting 90% of 150+ weekly recommendations

Read →

In-season Inventory Management

Penti – Apparel Retailer
With smarter replenishment decisions, Penti balanced inventory across the chain enabled 25% revenue growth with only 2% increase in stock

Read →

Detect the recent demand pattern and response to special events and promotions

Safety stock targets based on demand-drivers like promotions, special days and weather into account

Provide optimal replenishment quantities to minimize lost sales and prevent excess stock

Safety stock targets based on demand-drivers like promotions, special days and weather into account

Provide optimal replenishment quantities to minimize lost sales and prevent excess stock

Exception-Based Management for Store Replenishment

SKU/Store Recommendations

Daily SKU specific replenishment recommendations based on demand forecast and operational constraints
‍Planned promotions, price changes and special days are taken into account to provide a more accurate view of the demand and inventory projections
‍Specify triggers for automated PO review & approval, exception management and automated decision filters

Stockout Diagnostics

Automated diagnostics, users can quickly focus on items requiring attention such as root cause analysis for stock-outs
‍All relevant information on one single page; including vendor and DC performance, inventory and approval rates
‍Historical view of SKU specific KPIs and DC breakdown of zero-stock stores
Root cause analysis for stock-out and excess stock management

Recommendations Summary

Summary dashboard allows users to monitor recommendations based on different locations and product categories
Easily track the status of recommendations and get drilled down information like inventory, buyer group, season, and forecast

Advanced Retail Analytics

Demand-Driven Replenishment

Predictive Analytics with AI/ML for SKU/Store forecasts using seasonality and key product & store attributes

Prescriptive Analytics with automated replenishment recommendations

Process Automation

Solvoyo Cognitive Learning for new product introduction and store openings
‍
Integrated with warehouse management systems for no-touch execution

Automated Diagnostics & Alerts

Automated diagnostics and exception management for SKUs needing attention

Root cause analysis for stock-out and excess stock management

Start your journey now

Digital transformation with Solvoyo

GLOBAL HQ

77 Franklin Street
Boston, MA 02110
+1 617 642 1338

INNOVATION LABS & OFFICES

Istanbul Technical University
ARI2 Teknokent
B1-3, 34467
Maslak, Istanbul
+90 212 286 6061
–
Kolektif House 1071 Ankara
Çankaya, Ankara
–
Logothetidi 34, 11524
Attiki, Athens

Store Replenishment