Inventory managers have the problem of handling tens or even hundreds of thousands of products, each with unique properties, demanding sophisticated and time-consuming calculations. The proactive management of big inventories becomes unfeasible in the absence of a systematic approach and effective analytic tools.
Without inventory optimization, businesses run the risk of overpaying and underperforming. Manufacturers, distributors, and MRO inventory managers frequently err on the side of caution when setting stocking levels to prevent expensive shortages. Establishing the ideal stock levels for manufacturers, distributors, and MRO should be a science, not an art.
Learn industry best practices on how to optimize inventory to save on costs, meet demand, and streamline your supply chain below.
Maximize Machine Uptime with Probabilistic Modeling
If you both make and sell things, you own two inventory problems. Companies that sell things must focus relentlessly on having enough product inventory to meet customer demand. Manufacturers and asset intensive industries such as power generation, public transportation, mining, and refining, have an additional inventory concern: having enough spare parts to keep their machines running.
This technical brief reviews the basics of two probabilistic models of machine breakdown. It also relates machine uptime to the adequacy of spare parts inventory.
What is the difference between Demand planning and Inventory optimization ?
The Smart Demand Planning app (SDP) provides demand forecasts. The SDP forecasting engine is also the core of the Smart Inventory Optimization app (SIO), which stress-tests various inventory policies using a number of demand scenarios to find optimal inventory policy settings.
Want to Optimize Inventory? Follow These 4 Steps
Service Level Driven Planning (SLDP) is an approach to inventory planning based on exposing the tradeoffs between SKU availability and inventory cost that are at the root of all wise inventory decisions. When organizations understand these tradeoffs, they can make better decisions and have greater variability into the risk of stockouts. SLDP unfolds in four steps: Benchmark, Collaborate, Plan, and Track.
Four Ways to Optimize Inventory
Inventory optimization has become an even higher priority in recent months for many of our customers. Some are finding their products in vastly greater demand; more have the opposite problem. In either case, events like the Covid19 pandemic are forcing a reexamination of standard operating conditions, such as choices of reorder points and order quantities.
TOP 3 COMMON INVENTORY POLICIES
In this Video Dr. Thomas Willemain, co–Founder and SVP Research, defines and compares the three most used inventory control policies. These policies are divided into two groups, periodic review and continuous review. There is also a fourth policy called MRP logic or forecast based inventory planning which is the subject of a separate video blog that you can see here. These videos explain each policy, how they are used in practice and the pros and cons of each approach.
Backing into Safety Stock is the Safe Play
Safety stock is a critical component in any system of inventory management. Indeed, some inventory software treats safety stock as the key decision variable in the quest to balance inventory cost against item availability. Unfortunately, that approach is not the best way to strike the balance.
Problem
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.
Solution
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.
Smart Inventory Optimization
Optimal Inventory Levels
Reduce excess stock
Improve service levels
Minimize buyer transactions
Maximize return on assets
Organizational Consensus
Balance service levels
Identify stockout risk
Identify overstocks
No finger-pointing
Operational Connectivity
Align process with strategic objectives
Empower team to “make it so”
Optimize as conditions change
Pass results to ERP
Who is Inventory Optimization for?
Smart Inventory Optimization is for executives and business savvy planners who seek to:
- Yield maximum returns from inventory assets.
- Address the problem of highly variable or intermittent demand.
- Broker the service vs. cost tradeoffs between different departments.
- Develop a repeatable and efficient inventory planning process.
- Empower the team to ensure operational plan is aligned with strategic plan.
What questions can Inventory Optimization answer?
- What is the best service level achievable with the inventory budget?
- What service levels will yield the maximum return?
- If lead times increased, what would it cost to maintain service?
- If I reduce inventory, what will the impact on service be?
- If order quantity increases, what will the impact on service and costs be?
- What is the order quantity that balances holding and ordering costs?
Inventory forecasting for the inventory executive
Smart Inventory Optimization empowers you to:
- Predict service performance and inventory costs.
- Assess business impact of “what-if” inventory policies.
- Align inventory policy with corporate strategy.
- Establish an operational framework that guides the planning team.
- Reduce inventory and improve service.