1~28 item / All 28 items
Displayed results
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationContact this company
Contact Us Online1~28 item / All 28 items
We would like to introduce a case study on the implementation of "o9 Digital Brain" for our client in the food and beverage industry. The company faced challenges with low demand forecasting accuracy and was unable to utilize timely indicators. After implementation, they applied o9's highly differentiated machine learning (ML) forecasting capabilities to both internal and external demand drivers, resulting in improved forecasting accuracy, reduced bias, and effective information provision to the sales team. 【Case Overview】 ■Challenges - They were unable to quickly consider supply and demand scenarios. - Major scenarios were created using spreadsheet software, making appropriate decision-making difficult. ■Results - They became able to execute advanced supply and demand matching algorithms while considering constraints (such as expiration dates, campaigns, logistics, and storage capacity). *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study of the implementation of "o9 Digital Brain" at a customer company in the electronics industry. At this company, many planning systems were operating in a siloed environment, making it impossible to achieve true end-to-end visibility across the entire supply chain. After implementation, they integrated various planning functions across the organization and market areas, shortening the entire end-to-end planning cycle and improving visibility and efficiency. [Case Overview] ■Challenges - Frequent occurrences of inventory shortages and surpluses, with only 10% of SKUs having healthy inventory across the entire network. ■Results - Significantly improved inventory management by calculating statistical and supply-based safety stock. - Streamlined supply planning across the entire supply chain, including the creation of purchase orders and transfer instructions. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study on the implementation of "o9 Digital Brain" for our client in the capital goods industry. In this company, delays in the supply of critical components necessitated a time-consuming replanning process, resulting in significant delays of several days. After the implementation, they were able to verify supplier constraints, enabling rapid replanning of critical components using interactive scenario modeling and supplier collaboration features. 【Case Overview】 ■Challenges - Lack of transparency regarding disruptions in the supply chain of primary and secondary suppliers. ■Results - The enterprise knowledge graph (EKG) modeled primary and secondary suppliers, allowing real-time visualization of disruptions occurring at the suppliers. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study on the implementation of "o9 Digital Brain" for our manufacturing client. The company lacked appropriate forecasting capabilities, and the final confirmed orders were almost the sole basis for decision-making. With the introduction of o9, the client was able to gain an overview of all data and information related to demand planning, and share that information with internal and external stakeholders to enhance collaboration. 【Case Overview】 ■Challenges - The financial team did not have sufficient tools or capabilities to check the status of orders or plan future sales. ■Results - By utilizing o9's features, the client was able to convert demand planning in quantity units into monetary values and reflect various contract conditions, such as lease periods by order. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study on the implementation of "o9 Digital Brain" at a customer company in the machinery industry. This company struggled to plan across their globally interconnected network to respond to international distribution orders from manufacturing plants (with a lead time of one day), subsidiaries, and third-party manufacturers. After the implementation, they were able to create network plans that considered various conditions, enabling rapid inventory movement and calendar adjustments between customers and suppliers. [Case Overview] ■ Challenges - Matching demand and supply required many resources, leading to a reliance on manual processes. ■ Results - They were able to develop supply plans while frequently updating information on available inventory, expected arrivals, and shipping details, effectively responding to customer demand. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study on the implementation of "o9 Digital Brain" at an American industrial aluminum company. In this company, the production process involves multiple stages and includes both internal and external operations. To maximize uptime, sequencing is necessary, and traditionally, planning was done using Excel. After the implementation, by visualizing the process, they were able to improve the demand fulfillment rate and proactively identify solutions to anomalies that affect performance. [Case Overview] ■ Challenges - The existing IT environment was complex, and all planning tasks were conducted on Excel. ■ Results - By integrating the planning process into an open cloud-native platform, they achieved smoother and more integrated data collaboration between internal and external operations. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study on the implementation of "o9 Digital Brain" at a multinational technology company in the high-tech electronics industry. The company had established a very complex and challenging process to create plans for servers and network equipment used in their global data centers. After the implementation, seamless integration and workflows between different processes (demand forecasting, materials planning, capacity planning) were established, resulting in a user-friendly planning process. [Case Overview] ■Challenges - Needed a framework and technology for planning processes to support significant business growth. ■Results - Was able to design a unique and detailed supply chain network for planning. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study on the implementation of "o9 Digital Brain" at a customer company in the chemical industry. The company faced challenges with low forecasting accuracy and was lagging about two months behind industry standards in timing. There was a strong demand for improvements in signals related to demand in order to properly adjust capacity. After implementation, they utilized the consensus forecasting planning process and enhanced the tracking function for forecast deviations. This led to improved forecasting accuracy and better timing. [Case Overview] ■ Challenges - Unable to see capacity load 3 to 5 months ahead, leading to business constraints regarding raw materials and capacity. ■ Results - Achieved complete visibility of the supply chain on a single integrated cloud-native platform. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study on the implementation of "o9 Digital Brain" at a biopharmaceutical (biosimilar) company. The company primarily focused on financial data, but there was no established system for generating and managing supply chain-related data such as Bill of Materials (BOM), Bill of Distribution (BOD), planning items, and inventory visibility. After the implementation, the integration of the digital twin of the supply chain with ERP (SAP) was achieved, enabling end-to-end visibility of supply chain data. [Case Overview] ■ Challenges - Planners managed supply chain-related data, while the marketing team managed related data, each using siloed Excel sheets, leading to a lack of consistency. ■ Results - A single integrated platform was used for master planning, reducing manual work and ensuring consistency. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study on the implementation of "o9 Digital Brain" for a client company in the office supply industry. In this company, the accuracy of order and sales planning was low, primarily using outdated metrics. After implementation, by consolidating onto a cloud platform and utilizing forecasts powered by Facebook's "Prophet," they were able to improve accuracy. [Case Overview] ■Challenges - The loading plans for trucks were done manually, which was very labor-intensive. ■Results - By automatically creating loading plans that consider truck loading rates and the number of pallets, they were able to accurately estimate the number of trucks needed. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study on the implementation of "o9 Digital Brain" at a multinational paint company in the Indian chemical industry. The company required a lot of manual work to modify purchase requisitions every day. After the implementation, they created a purchasing support tool that automated the entire process of monitoring raw material procurement rates, creating purchase orders, and approvals. [Case Overview] ■Challenges - To match demand with raw materials, the schedule for raw material deliveries needed to be linked to the factory's inventory levels. ■Results - By efficiently utilizing a heuristic solver, they were able to match demand, supply, and inventory, creating an efficient schedule. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study on the implementation of "o9 Digital Brain" at a multinational company that provides products for manufacturing and process automation. In this company, various planning systems were operated in a siloed environment, making it impossible to visualize the entire supply chain. A true digital twin of the supply chain has been established, allowing for the integration of various demand and supply planning functions across the organization. [Case Overview] ■Challenges - The planning team spent a significant amount of time on numerical calculations such as data validation, collection, manipulation, and report creation. ■Results - The most time-consuming manual tasks were automated. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study of the implementation of "o9 Digital Brain" at a multinational company that supplies reliable green power, such as hydropower and solar energy. At this company, there was a lack of visibility regarding constraints and costs from capacity planning of molds to installation at customer sites. After implementation, they were able to acquire a digital twin that visualizes project-based demand, blade manufacturing and transportation, as well as mold manufacturing capacity and costs. [Case Overview] ■ Challenges - Fragmentation and siloing of business processes and the supporting systems prevented planners from collaborating across multiple departments. ■ Results - They were able to gain a unique capability to connect all functions and all planning processes on a single integrated platform. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study on the implementation of "o9 Digital Brain" at a tire and rubber production company. The existing S&OP process lacked sufficient visibility regarding supply risks and prioritization of capacity, making it difficult to make executable decisions based on financial analysis efficiently. After the implementation, the company was able to quickly detect planning discrepancies and respond to changes in the market environment by understanding and leveraging various demand drivers. [Case Overview] ■Challenges - Frequent occurrences of excess inventory and stockouts led to potential obsolete inventory, sometimes necessitating additional price promotions. ■Results - Demand drivers were utilized in performance analysis and were used by the sales team to make assortment proposals to dealers. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study on the implementation of "o9 Digital Brain" at a customer company in the tire industry. At this company, strategic planning (for the past 5-7 years) was conducted on Excel without utilizing key market trends or macroeconomic trends. After the implementation, they were able to establish long-term demand plans by incorporating leading indicators of demand and key market trends, allowing for an accurate understanding of market size and market share trends. [Case Overview] ■Challenges - Most of the constraints were stored only as information on Excel or individual knowledge, making it impossible to create long-term capacity plans. ■Results - By executing various scenarios, they were able to accurately assess profitability, expenses, capital costs, and inventory through long-term demand-supply matching. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationHere is an introduction to a case study on the implementation of "o9 Digital Brain" at a steel wire manufacturer. The manufacturer faced issues with inaccurate raw material planning, which prevented them from considering detailed BOM composition, lead times, and alternative sources in their supply model, leading them to rely on Excel for their analyses. After the implementation, they were able to create a master plan that included detailed BOM, materials, capacity constraints, and lead times, significantly improving the accuracy of their raw material planning. [Case Overview] ■Challenges - Lacked appropriate capacity planning, making accurate inventory allocation difficult. ■Results - Utilized scenario-based capacity planning integrated with demand planning, enabling accurate budget assessments for each sales representative. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study on the implementation of "o9 Digital Brain" at a global technology company in the semiconductor industry. The company was managing forecasts through manual processes, relying on disparate spreadsheets, the Adexa system, and email, resulting in an inconvenient setup. After the implementation, they were able to seamlessly create forecasts across all time frames—weekly, monthly, quarterly, and annually—allowing them to respond effectively in terms of both quantity and value. [Case Overview] ■Challenges - Managing wafer inventory was difficult, and the high dependence on manual planning often led to overestimations in inventory accuracy. ■Results - It became possible to improve the planning processes for both buffer and wafer plans, enabling more efficient and agile inventory management and a reduction in wafer inventory. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study on the implementation of "o9 Digital Brain" at a customer company in the telecommunications industry. The company faced challenges related to the demand and inventory planning of mobile base stations in connection with the rollout of 5G, coverage strategies, and recent mergers. After implementation, they were able to link each process, accurately forecast demand, and plan appropriate inventory in the right locations. 【Case Overview】 ■Challenges - The transition from 3G and 4G to 5G required advanced phase-in and phase-out planning. ■Results - Excellent analytical results regarding phase-in and phase-out planning were obtained, leading to the resolution of upgrade issues, reduction of risks associated with the retrieval of old items, and efficient management. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study on the implementation of "o9 Digital Brain" at an international oil and gas company. The company heavily relied on manual processes and primarily used Excel, which led to data-related issues and a lack of visibility into inventory. After implementation, they established a single integrated data source that fully visualizes sales, inventory, and supply chain planning. [Case Overview] ■Challenges - Due to reliance on manual processes and the use of only lagging indicators for forecasting, demand forecasting accuracy was low, leading to a tendency for high inventory levels. ■Results - By incorporating internal and external demand drivers into the ML (machine learning) forecasting functionality, they achieved optimization and reduction of inventory levels. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study on the implementation of "o9 Digital Brain" in a publicly listed company in the oil and gas industry. In this company, most of the planning processes were done manually using Excel, which led to data issues and made it difficult to understand the inventory situation. After the implementation, they were able to visualize sales, inventory, supply chain planning, and more in an end-to-end manner on the cloud-native integrated platform of o9, enabling better collaboration. [Case Overview] ■Challenges - Due to issues with the data structure and lack of integration, it was impossible to have an overview of all data and processes. ■Results - By incorporating internal and external demand forecasts into o9's unique ML (machine learning) capabilities, they achieved optimization and reduction of inventory levels. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study of the implementation of o9 at one of Canada's largest retail companies. The company faced various challenges, such as difficulties in inventory planning considering store capacity constraints and low visibility of store inventory, which hindered replenishment according to store demand. After implementation, they achieved prioritized allocation considering the constraints of each store. Additionally, it brought about various benefits, including improved productivity for planners. 【Implementation Effects】 ■ Improved accuracy of AI/ML-based forecasts ■ Achieved prioritized allocation considering constraints for each store ■ Realized prioritized allocation considering store constraints ■ Enabled rapid decision-making through collaboration between merchandising, supply chain, and store operations ■ Increased productivity for planners *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study of the implementation of o9 at a major global dairy manufacturer. This manufacturer faced various challenges, including significant variability in forecasting accuracy and quality, as well as managing the forecasting process using Excel while utilizing SAP APO as the execution layer. After the implementation, bias was improved in almost every week. Additionally, by incorporating detailed promotional information, it became possible to forecast the uplift from promotions globally, resulting in a variety of benefits. 【Main Implementation Details and Scope】 ■ Automation of past anomaly corrections and segmentation of the product portfolio ■ Best-fit forecasting including a machine learning driver-based model using internal and external drivers such as promotions, holidays, and weather ■ Decomposition of weekly forecasts of past shipment performance into daily forecasts using smart AI analytics *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study of the implementation of o9 at a major global healthcare product supplier. This supplier faced various challenges, including reliance on manual processes for many operations and difficulties in tracking changes in forecasting and related assumptions over cycles. After implementation, the accuracy of sell-in forecasts improved by an average of 2-5%, and sell-out forecast accuracy improved by over 10%. Additionally, it brought about various benefits such as visualization of effects and improved forecasting accuracy. 【Main Implementation Details and Scope】 ■ Created sell-in and sell-out forecasts using multiple internal and external metrics. ■ Integrated forecasting data through a collaborative workflow with an integrated demand planning platform, enabling cross-departmental collaboration. ■ Utilized o9's open architecture to optimize forecasts with industry-leading approaches and algorithms. *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationHere is a case study of the implementation of o9 at a major global automotive parts supplier. This supplier faced various challenges, including significant variability in the quality and accuracy of forecasts from OEMs, demand forecasting and capacity verification being conducted in Excel with scattered data. After implementation, planner productivity improved by about 15-25%. Additionally, it brought various effects such as an increase in task automation rates. **Implementation Effects** - Demand forecast accuracy improved by 10 percentage points, reaching the 80% range. - Planner productivity increased by about 15-25%. - Task automation rates improved (estimated at 30% based on initial baseline). - Decision-making cycles accelerated from monthly to weekly levels. *For more details, please download the PDF or feel free to contact us.*
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationWe would like to introduce a case study of the implementation of o9 at a major global food manufacturer. This manufacturer faced various challenges, including low forecast accuracy based on long lead time metrics, and the creation of demand forecasts, financial forecasts, and commercial forecasts based on different datasets and assumptions. After implementation, the machine learning capabilities significantly improved forecast accuracy and successfully reduced bias. Additionally, it achieved an average improvement in forecast accuracy of 5 to 8 percentage points, resulting in various benefits. [Background of Implementation] - Low forecast accuracy based on long lead time metrics - A majority of the demand planner's working hours were spent on Excel-based planning, leaving little time to focus on critical tasks - Demand forecasts, financial forecasts, and commercial forecasts were created based on different datasets and assumptions - Considering migration from SAP APO and Blue Yonder *For more details, please download the PDF or feel free to contact us.*
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationThe modern supply chain is being buffeted by the turbulent waves of change. What consumers are seeking is rapid delivery, diverse shipping options, and above all, the ability to purchase affordable and high-quality products. Amid uncertainty, complexity, and instability, o9 Digital Brain supports companies in actively and boldly challenging the times. With o9 Digital Brain's powerful automation and analytical capabilities, insights reflecting current and future market forecasts can be provided to various related departments, along with corporate strategies and constraints. [Overview] ■ The customer is always right: Consumer behavior is changing ■ Utilizing leading indicators for forecasts ■ Supporting business challenges with o9 Digital Brain ■ Features of o9 Digital Brain *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationThe "new normal" has arrived in the automotive industry due to various changes. How can automotive manufacturers build a robust supply chain in response to many challenges? We will introduce ways to utilize technology for problem-solving. [Main contents of the white paper] ■ Transformation of the ecosystem ■ Planning for problem-solving ■ Effects brought by the SCM platform "Digital Brain" *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registrationChallenges of supplier collaboration and risk management in the supply chain faced by many companies. Based on our experience in implementing solutions for various customers, we will introduce how o9 Digital Brain provides benefits and solves these challenges. Please feel free to contact us when you need assistance. 【Main contents of the white paper】 ■ Reasons why supplier collaboration is difficult ■ Scope of o9 Digital Brain's response ■ Examples of o9 Digital Brain's implementation *For more details, please download the PDF or feel free to contact us.
Added to bookmarks
Bookmarks listBookmark has been removed
Bookmarks listYou can't add any more bookmarks
By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.
Free membership registration