Manage your business better with supply chain planning. Increase profitability by enhancing and improving supply chain processes to track and align supply and demand, ensuring availability while reducing inventory costs. Monitor and anticipate evolving customer needs, and create innovative revenue growth strategies and execute plans to fulfill them.
At the same time, identify root causes to respond to supply chain concerns quickly and successfully. Forestall issues with effective demand management, supply planning, and sales and operations planning.
Cloud updates ensure that your planning software remains state-of-the-art.
Coalesce customer-facing processes with sourcing and fulfillment of orders to maximize the bottom line. Consistently meet customer request dates and quantities to enhance customer satisfaction. Integrate with your extended supply chain network to ensure full utilization of resources. Manage the process from receiving orders to fulfillment to post-sales service. In-context analytics keep you updated and poised to control exceptions including order changes.
Streamline the source-to-pay process to reduce costs, manage supplier risk, and enhance profitability. Manage spending to be informed of spending and saving opportunities and to maximize negotiated savings. Improve shopping experience for employees. Integrate processes for speed and effectivity. Work with suppliers through document sharing to ensure strategic decision-making with accurate and updated information and analytics.
Product Lifecycle Management
Enhance product lifecycle and value chain with solutions to improve product development functions. Improve cost reduction, enhance build time and product quality and time-to-market. Employ analytics for design, product readiness, and technical and business requirements. Refine product concept to achieve product excellence and conformity to standards and customer requirements.
Streamline manufacturing processes and execution for closed-loop quality management to maximize resources and minimize costs. Satisfy customer demand for products while meeting standards and ensuring compliance. Integrate scanning, quality collections, Internet of Things, and shop floor analytics into an all-in system that enables visual imaging of the production processes, control of manufacturing costs, effective batch and discrete production, and tracking of requirements and compliance.
Improve operational efficiency by monitoring downtime and maintenance needs. Reduce the need for downtime with comprehensive and logical scheduling of maintenance. Create models to provide real-time views of asset performance. Increase uptime and productivity and maximize operational efficiency of machines and other physical assets. Leverage data-driven decision making to reduce operation costs and risks. Use on-board analytics to determine best strategies for asset performance monitoring and cost control.
Enhance business processes across the value chain using SaaS-based blockchain development applications to improve traceability, security, and consensus. Monitor and improve product quality and delivery for customer delight with simplified and ready-to-use applications. Quickly provide solutions to common business issues such as fraud, recalls, disputes, and regulatory compliance using root-cause analysis and end-to-end traceability throughout the supply chain. Integrate with existing systems or use as stand-alone. Save time and effort with built-in workflows with standard business documents such as purchase orders, work orders, and shipment notices. Easily onboard partners to create a business network. Use built-in dashboards to make strategic decisions using real-time results and analytics.
Internet of Things Applications
Deploy IoT solutions for business advantage to monitor workers, assets, production, and fleet using real-time information. Drive down costs and comply with requirements for supply-chain logistics. Connect system end-to-end to efficiently monitor and utilize resources and processes, from manufacturing to maintenance to order capture and fulfillment. Monitor and locate assets, detect faults, diagnose root causes of incidents, prevent theft.
In-Memory Cost Management
Improve profitability by utilizing embedded analytics to determine in real time the most profitable product mix and break-even point. Perform simulations for cost changes related to cost of materials, parts, ingredients, and resources to assess gross margins and profits. Compare costs across organizations and spread cost savings across the entire business. Perform cost-volume-profit analyses to determine optimum cost structures.
Product Master Data Management
Integrate master data and allow trading partners to take ownership of their product data, use flexible data mapping from various source formats for your product data model, and import data for monitoring to a centralized graphical user interface. Correct and verify errors before updating and publishing master data. Work with large volumes of data to create product records, quickly access product information through parametric search, and receive real-time analysis for decision making.
Supply Chain Collaboration and Visibility
Work with people within your enterprise and with key trading partners to detect, analyze, and resolve disruptions for a more efficient supply chain. Manage end-to-end partner-related processes, allowing suppliers to access order forecasts and you to review changes, negotiate commitments with suppliers, and monitor commitment dates and cycle times. Ensure inventory control by working with suppliers on required replenishment quantities, while tracking with them purchase orders, shipments, and invoices.
Machine Learning and AI Applications
Use embedded analytics to surface key patterns and correlations related to operational inefficiencies. Track information related to resources and managements to perform root-cause analysis. Minimize risks related to products, processes, suppliers, and customers by calculating the probability of critical events and taking the appropriate measures. Manage, prepare, and contextualize data to create descriptive and predictive models to analyze key performance indicators in manufacturing such as yield, cycle time, scrap, rework, and costs.