List of Symphony GOLD Demand Planning Customers
Palo Alto, 94304, CA,
United States
Since 2010, our global team of researchers has been studying Symphony GOLD Demand Planning customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Symphony GOLD Demand Planning for Retail Management from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Symphony GOLD Demand Planning for Retail Management include: Intermarche, a France based Retail organisation with 100000 employees and revenues of $41.79 billion, Dollar General, a United States based Retail organisation with 194200 employees and revenues of $40.60 billion, The Save Mart Companies, a United States based Retail organisation with 12000 employees and revenues of $4.60 billion, REMA 1000, a Norway based Retail organisation with 20252 employees and revenues of $2.81 billion and many others.
Contact us if you need a completed and verified list of companies using Symphony GOLD Demand Planning, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Symphony GOLD Demand Planning customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
Apply Filters For Customers
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight | Insight Source |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
|
Dollar General | Retail | 194200 | $40.6B | United States | SymphonyAI | Symphony GOLD Demand Planning | Retail Management | 2010 | n/a | In 2010, Dollar General implemented Symphony GOLD Demand Planning within its Retail Management portfolio, configuring demand forecasting and automated replenishment to support store ordering workflows. The Symphony GOLD Demand Planning deployment emphasized Computer Generated Ordering and was provisioned to accept assortment data from existing planning systems for automated store replenishment and ordering. The implementation embodied core modules and capabilities for statistical forecasting, store assortments and replenishment, assortment modeling for buying teams, exception based reporting for shrink management, and space planning output generation. Development work included requirements and technical design documentation, detailed QA test cases, SQL tuning for performance optimization, and creation of application support documentation to sustain operational use. Integrations and technical architecture leveraged Oracle and Java based stacks with PLSQL and UNIX AIX elements noted in the environment, and the solution was designed to interface assortment outputs into the Intactix Space Planning system from JDA. Audit and reporting flows were aligned with Auditworks and downstream exports that feed external systems such as Lawson, Island Pacific, RSL and ReconNet, and the implementation accounted for state and local retail rules such as beer and wine transaction handling where required. Operational rollout was structured to enable phased vendor activation, allowing individual vendors to be enabled in Symphony GOLD Demand Planning while corresponding upstream processes remained available, supporting side by side comparison of new and existing flows. Governance practices documented in the program included formal requirement documents, technical design documents, unit and system test plans, and operational support procedures to guide the buying organization, field end users and space planning operations, with targeted enhancements to comply with regional display regulations. | |
|
|
Intermarche | Retail | 100000 | $41.8B | France | SymphonyAI | Symphony GOLD Demand Planning | Retail Management | 2020 | n/a | In 2020 Intermarché deployed Symphony GOLD Demand Planning, a Retail Management application, to establish centralized demand forecasting for its French supply chain. The initial rollout focused on embedding Symphony GOLD Demand Planning within distribution center planning to drive inventory optimization and automated replenishment across the Intermarché network. Implementation configured core forecasting and replenishment capabilities, including AI-driven demand forecasting models, inventory optimization rules, and replenishment planning workflows aligned with retailer assortment and promotional calendars. Symphony GOLD Demand Planning was used to operationalize forecasting outputs into replenishment and distribution center shipment planning, supporting merchandising and operations planning processes. Operational coverage targeted Intermarché distribution centers across France and extended to merchandising and operations stakeholders as the program matured. A 2025 extension built on the 2020 deployment and expanded AI-driven forecasting use cases beyond supply chain into merchandising and store operations, increasing cross-functional governance over forecast inputs and deployment cadence. The deployment positioned Symphony GOLD Demand Planning as the focal application for Retail Management demand forecasting within Intermarché, delivering measurable improvements in forecasting-driven operations and supporting ongoing expansion of AI across merchandising and operations. Governance changes included formalized forecast ownership between supply chain and merchandising teams and a staged rollout across distribution centers to standardize replenishment processes. | |
|
|
REMA 1000 | Retail | 20252 | $2.8B | Norway | SymphonyAI | Symphony GOLD Demand Planning | Retail Management | 2015 | n/a | In 2015, REMA 1000 implemented Symphony GOLD Demand Planning as part of its Retail Management stack. The deployment targeted demand forecasting, store operations orchestration, and automated space and planogram processes across REMA 1000's Norwegian stores. Symphony GOLD Demand Planning was configured to deliver AI based demand forecasting and forecast driven replenishment workflows, and to feed automated planogram and space management capabilities. Functional modules implemented included demand forecasting, automated space and planogram processes, and store operations management and scheduling, aligning application behavior with category planning and inventory control workflows. These capabilities were operationalized across REMA 1000's Norwegian store network, supporting supply chain planning and in store operations through integrated forecast outputs and planning data. In 2023 REMA migrated these capabilities to SymphonyAI's cloud hosted platform to gain scalability and lower maintenance while continuing to rely on AI based demand forecasting for supply chain and store operations. The implementation is positioned within the Retail Management category, with governance organized around forecast driven replenishment and category planning workflows that involve supply chain and store operations teams. Vendor disclosures cite improved on shelf availability and reduced waste across stores as outcomes of the Symphony GOLD Demand Planning deployment. | |
|
|
|
Retail | 12000 | $4.6B | United States | SymphonyAI | Symphony GOLD Demand Planning | Retail Management | 2024 | n/a |
|
|
Buyer Intent: Companies Evaluating Symphony GOLD Demand Planning
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
|---|---|---|---|---|---|---|---|---|
| No data found | ||||||||