Inventory and Demand Planning: Guest Posts
Data Driven Planning, Demand forecasting and inventory optimization
Data verification and validation are essential to the success of the implementation of software that performs statistical analysis of data, like Smart IP&O. This article describes the issue and serves as a practical guide to doing the job right, especially for the user of the new application.
Utilities in the electrical, natural gas, urban water, and telecommunications fields are all asset-intensive and reliant on physical infrastructure that must be properly maintained, updated, and upgraded over time. Maximizing asset uptime and the reliability of physical infrastructure demands effective inventory management, spare parts forecasting, and supplier management. A utility that executes these processes effectively will outperform its peers, provide better returns for its investors and higher service levels for its customers, while reducing its environmental impact.
Smart Inventory Planning & Optimization (Smart IP&O) can help with inventory ordering functionality in Epicor P21, reduce inventory, minimize stockouts and restore your organization’s trust by providing robust predictive analytics, consensus-based forecasting, and what-if scenario planning.
The supply chain has become the blame game for almost any industrial or retail problem. Shortages on lead time variability, bad forecasts, and problems with bad data are facts of life, yet inventory-carrying organizations are often caught by surprise when any of these difficulties arise. So, again, who is to blame for the supply chain chaos? Keep reading this blog and we will try to show you how to prevent product shortages and overstocking.
Just-In-Time (JIT) ensures that a manufacturer produces only the necessary amount, and many companies ignore the risks inherent in reducing inventories. Combined with increased globalization and new risks of supply interruption, stock-outs have abounded. So how can you execute a real-world plan for JIT inventory amidst all this risk and uncertainty? The foundation of your response is your corporate data. Uncertainty has two sources: supply and demand. You need the facts for both.
In a perfect world, Just in Time (JIT) would be the appropriate solution for inventory management. But as the saying goes “everyone has a plan until they get punched in the mouth.” One enormous punch in the mouth for the global supply chain was Suez Canal Blockage that held up $9.6B in trade costing an estimated $6.7M per minute.
Keeping inventory investments in check while maintaining high customer service levels is a constant balancing act. Without proper controls, excess inventory grows throughout your supply chain, locking up vital working capital that constrains your company’s growth. Every day, the ERP system makes purchase order suggestions and manufacturing orders based on planning drivers such as safety stock, reorder points, and Min/Max levels. Ensuring that these inputs are understood and continually optimized will generate substantially better returns on your inventory assets. Unfortunately, many organizations rely on rule of thumb logic, institutional knowledge, and “one-size-fits all” forecasting logic that assigns all items within a particular group the same service level target. These approaches yield suboptimal policies that cause inventory costs to balloon and service performance to suffer. Compounding the problem is the sheer volume of data – thousands of items stocked at multiple locations means planners don’t have the bandwidth to proactively review these inventory drivers on a regular basis. This results in outdated reorder points, safety stocks, order quantities, and Min/Max settings that further contribute to the problem.
Smart Inventory Optimization (SIO™) is available on Smart’s Inventory Planning and Optimization Platform, Smart IP&O. It delivers inventory policy decision support and the means to share, collaborate, and track the impact of your inventory planning policy. This can help realize millions in savings by improving customer service and reducing excess stock. You can forecast metrics such as service level, fill rate, holding costs, ordering costs, and stock out costs. Users can identify overstocks and understocks, adjust stocking policies when demand changes, share proposed policies with other stakeholders, collect feedback, and establish a consensus inventory plan. And unlike traditional inventory planning systems that rely on rule of thumb approaches or require the user to arbitrarily set suboptimal service level targets, Smart Inventory Optimization prescribes the optimal service levels for you. Users can optionally assign service level constraints to ensure the optimization engine respects business rules. SIO provides the required inventory planning parameters for a variety of replenishment policies such as Reorder Point/Order Quantity, Min/Max, Safety Stock Planning, and Order Up to levels.
Register to Watch the Demo
With Smart Inventory Optimization you can:
- Identify where you are overstocked and understocked.
- Modify planning parameters based on your business rules, service targets, and inventory budget.
- Leverage the optimization logic in SIO to prescribe planning parameters and service levels for you.
- Compare proposed policies to the benchmark.
- Collaborate and develop a consensus inventory plan.
- Automatically generate revised planning parameters as demand and other inputs change.