ImpressArt Helps Entrepreneurs Create Beautiful Jewelry – aided by Smart IP&O
Jeff Wolter, CEO of ImpressArt, explains why forecasting is so important, how he came to select Smart Inventory Planning and Optimization as Impress Art’s forecasting and demand planning system, and how better forecasts are helping their business.
Electric Utility Goes Live in 90 Days with Smart IP&O and saves $9,000,000
Smart Software today disclosed its selection by a large US Electric Power Utility along with initial operating results. Smart implemented its software in just 90 days and has been credited for reducing inventory by $9 million within its first six months of operation.
Field Service Parts Optimization at Seneca Companies
Seneca Companies, an industry leader in automotive petroleum services, adopted Smart Software to model customer demand, inventory performance, and to drive Service Parts Optimization.
Engineering to Order at Kratos Space – Making Parts Availability a Strategic Advantage
The Kratos Space group within National Security technology innovator Kratos Defense & Security Solutions, Inc., produces COTS s software and component products for space communications – Making Parts Availability a Strategic Advantage
Optimizing Parts Management at BC Transit
BC Transit values its newfound ability to forecast the financial impact of stocking decisions. They are able to balance capacity against criticality and the cost of inventory.
Draped in Success – Inventory Planning at Rose Brand
Rose Brand selected demand and inventory planning software from Smart Software as the foundation for a methodical planning process. Rose Brand is North America’s largest provider of theatrical fabrics, fabrications and production supplies for the entertainment, event and display industries.
Recent Posts
Fifteen questions that reveal how forecasts are computed in your companyIn a recent LinkedIn post, I detailed four questions that, when answered, will reveal how forecasts are being used in your business. In this article, we’ve listed questions you can ask that will reveal how forecasts are created. […]
The top 3 reasons why your spreadsheet won’t work for optimizing reorder points on spare partsWe often encounter Excel-based reorder point planning methods. In this post, we’ve detailed an approach that a customer used prior to proceeding with Smart. We describe how their spreadsheet worked, the statistical approaches it relied on, the steps planners went through each planning cycle, and their stated motivations for using (and really liking) this internally developed spreadsheet. […]
How to interpret and manipulate forecast results with different forecast methodsThis blog explains how each forecasting model works using time plots of historical and forecast data. It outlines how to go about choosing which model to use. The examples below show the same history, in red, forecasted with each method, in dark green, compared to the Smart-chosen winning method, in light green. […]
Why Spare Parts Tradeoff Curves are Mission-Critical for Parts PlanningWhen managing service parts, you don’t know what will break and when because part failures are random and sudden. As a result, demand patterns are most often extremely intermittent and lack significant trend or seasonal structure. The number of part-by-location combinations is often in the hundreds of thousands, so it’s not feasible to manually review demand for individual parts. Nevertheless, it is much more straightforward to implement a planning and forecasting system to support spare parts planning than you might think. […]
What to do when a statistical forecast doesn’t make senseSometimes a statistical forecast just doesn’t make sense. Every forecaster has been there. They may double-check that the data was input correctly or review the model settings but are still left scratching their head over why the forecast looks very unlike the demand history. When the occasional forecast doesn’t make sense, it can erode confidence in the entire statistical forecasting process. […]
Inventory Optimization for Manufacturers, Distributors, and MRO
- The top 3 reasons why your spreadsheet won’t work for optimizing reorder points on spare partsWe often encounter Excel-based reorder point planning methods. In this post, we’ve detailed an approach that a customer used prior to proceeding with Smart. We describe how their spreadsheet worked, the statistical approaches it relied on, the steps planners went through each planning cycle, and their stated motivations for using (and really liking) this internally developed spreadsheet. […]
- Why Spare Parts Tradeoff Curves are Mission-Critical for Parts PlanningWhen managing service parts, you don’t know what will break and when because part failures are random and sudden. As a result, demand patterns are most often extremely intermittent and lack significant trend or seasonal structure. The number of part-by-location combinations is often in the hundreds of thousands, so it’s not feasible to manually review demand for individual parts. Nevertheless, it is much more straightforward to implement a planning and forecasting system to support spare parts planning than you might think. […]
Spare Parts Planning Isn’t as Hard as You ThinkWhen managing service parts, you don’t know what will break and when because part failures are random and sudden. As a result, demand patterns are most often extremely intermittent and lack significant trend or seasonal structure. The number of part-by-location combinations is often in the hundreds of thousands, so it’s not feasible to manually review demand for individual parts. Nevertheless, it is much more straightforward to implement a planning and forecasting system to support spare parts planning than you might think. […]
Service-Level-Driven Planning for Service Parts BusinessesService-Level-Driven Service Parts Planning is a four-step process that extends beyond simplified forecasting and rule-of-thumb safety stocks. It provides service parts planners with data-driven, risk-adjusted decision support. […]
Smart IP&O, a Digital Supply Chain Platform
Cloud Native Platform
A single, secure, and scalable native cloud platform with multiple end user Apps that helps you predict accurately, protect against uncertainty, and plan efficiently.
Intermittent Demand Planning
Engineered for intermittent demand, Smart’s field proven methods succeed on even the hardest to forecast, anything but normal, unplannable items.
Automate Supply Chain Decisions
You’ll build automated, exception based plans that adapt and respond to frequently changing business conditions while doing away with time intensive manual planning.
Collaborative Planning
Share collaborative “what if” demand forecasts, inventory policies and develop an authorized consensus plan aligned to achieve business objectives.
Probabilistic Forecasting
Predict a range of outcomes and the probability for each possibility to accurately prescribe risk adjusted stocking policies that optimally balance service levels and cost.
Smart ERP Integrations
Seamlessly integrate with your system of record with an automated bi-directional data exchange that ensures alignment between planning policies and execution.
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.