Sales and Operations Planning using AI/ML
Sales and Operations Planning using AI/ML
Sales forecasting model per cell, per part number for visibility of volume of work, revenues, better workflow management and sales targeting
Refers to the application of artificial intelligence (AI) and machine learning (ML) techniques to enhance and optimize the sales and operations planning process within an organization
Is a process that aligns sales, production, and other functions to create a cohesive plan that balances supply and demand
Automation
Adaptability
Decision Making
Enhanced Predictive Capabilities
Improved Forecasting
Efficiency Gains
Features
Identify gap-to-fill
Insights into monthly revenues and volumes per cell
Predictive trending in components to proactively management capacity and training
Reduced admin to produce revenue budgeting
Provides account managers with foresight of customer volumes to better support and ensure CSAT
Facing any of these Challenges?
Pain Points
Reactive Customer Account Management:
MRO account managers struggle with inadequate foresight regarding customer volumes, limiting their ability to provide proactive support, ensure optimal customer satisfaction and fill revenue gaps.
Delayed Purchase Order Placement Impact on Workflow Efficiency:
MROs often face challenges related to delayed purchase order placement, due to the process of ordering piece parts after a unit is already in the shop and completed testing and inspection. This practice can lead to extended lead times and introduce unnecessary delays, ultimately affecting workflow efficiency. These delays increase turnaround times for customers, impacting their satisfaction and the MRO's overall operational performance.
Inability to Forecast Inventory Requirements:
MROs' inability to forecast incoming work volumes impede their capacity to predict piece parts requirements based on volume of work and replacement factors per work scope. This lack of insight results in uncertainty regarding inventory investments required to meet demand.
Fragmented Sales Pipeline and Operations Planning:
MROs often do not have a mechanism to enable Sales and Operations Planning (S&OP), resulting in a disconnect between the sales pipeline and capacity utilization. This fragmentation leads to inefficiencies matching demand with available manpower, affecting overall operational efficiencies, customer satisfaction and revenue optimization.
Solutions
Implement an integrated Sales and Operations Planning (S&OP) system that connects sales forecasting with production capacity planning. Use historical data and predictive modeling to forecast customer volumes and maintenance needs by measuring cycles in removal rates based on flight hours and landings. Assign dedicated account managers to closely monitor and support customer accounts proactively with analytics that forecast repair work required, identifying opportunities for upselling and ensuring high customer satisfaction.
Implement an integrated Sales and Operations Planning (S&OP) system that connects sales forecasting with production capacity planning, enabling a proactive procurement strategy that involves the early placement of purchase orders based on forecasted needs and historical demand patterns, ensuring that required piece parts are readily available when a unit enters the shop, thus reducing lead times and improving workflow efficiency.
Forecasting work volume and inventory requirements through Sales and Operations planning and Predictive Maintenance models would enable more effective customer delivery and recovery planning, offering visibility into vendor roadblocks and their impact on workflow. Implement demand forecasting solutions and predictive analytics to accurately estimate inventory needs based on incoming work volumes and replacement factors.
Implement an integrated Sales and Operations Planning (S&OP) that connects sales forecasting with production capacity planning. Use advanced analytics and demand forecasting tools to align sales and operations effectively. This system should provide real-time visibility into demand, capacity, and resource allocation, by using sales forecast as a mechanism to backwards-engineer the manpower and supply chain requirements.