The Smart Forecaster

Pursuing best practices in demand planning,

forecasting and inventory optimization

6 Observations About Successful Demand Forecasting Processes

6 Observations About Successful Demand Forecasting Processes

Forecasting is both an art and a science, requiring a balance between professional judgment and objective statistical analysis. In this blog, we will explore how to generate accurate predictions by leveraging statistical methods, incorporating business knowledge, and enhancing credibility through refinement and graphical representation. Learn about aligning techniques with data nature and integrating them with other business processes, creating a comprehensive planning approach that acknowledges margin of error and forecast bias. Gain the principles and techniques for successful demand forecasting, empowering informed decision-making and optimized planning.

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Don’t Blame Excess Stock on “Bad” Sales / Customer Forecasts

Don’t Blame Excess Stock on “Bad” Sales / Customer Forecasts

Sales forecasts are often inaccurate simply because the sales team is forced to give a number even though they don’t really know what their customer demand is going to be. Let the sales teams sell. Don’t bother playing the game of feigning acceptance of these forecasts when both sides (sales and supply chain) know it is often nothing more than a WAG.

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What makes a probabilistic forecast?

What makes a probabilistic forecast?

What’s all the hoopla around the term “probabilistic forecasting?” Is it just a more recent marketing term some software vendors and consultants have coined to feign innovation? Is there any real tangible difference compared to predecessor “best fit” techniques? Aren’t all forecasts probabilistic anyway?

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A Practical Guide to Growing a Professional Forecasting Process

A Practical Guide to Growing a Professional Forecasting Process

Many companies looking to improve their forecasting process don’t know where to start. It can be confusing to contend with learning new statistical methods, making sure data is properly structured and updated, agreeing on who “owns” the forecast, defining what ownership means, and measuring accuracy. Having seen this over forty-plus years of practice, we wrote this blog to outline the core focus and to encourage you to keep it simple early on.

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Prepare your spare parts planning for unexpected shocks

Prepare your spare parts planning for unexpected shocks

In today’s unpredictable business climate, we do have to worry about supply chain disruptions, long lead times, rising interest rates, and volatile demand. With all these challenges, it’s never been more vital for organizations to accurately forecast parts usage, stocking levels, and to optimize replenishment policies such as reorder points, safety stocks, and order quantities. In this blog, we’ll explore how companies can leverage innovative solutions like inventory optimization and parts forecasting software that utilize machine learning algorithms, probabilistic forecasting, and analytics to stay ahead of the curve and protect their supply chains from unexpected shocks.

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Why Spare Parts Tradeoff Curves are Mission-Critical for Parts Planning

Why Spare Parts Tradeoff Curves are Mission-Critical for Parts Planning

When 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.

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Electric Utilities’ Problems with Spare Parts

Electric Utilities’ Problems with Spare Parts

Every organization that runs equipment needs spare parts. All of them must cope with issues that are generic no matter what their business. Some of the problems, however, are industry specific. This post discusses one universal problem that manifested in a nuclear plant and one that is especially acute for any electric utility.

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What data is needed to support Demand Planning Software Implementations

What data is needed to support Demand Planning Software Implementations

We recently met with the IT team at one of our customers to discuss data requirements and installation of our API based integration that would pull data from their on-premises installation of their ERP system. The IT manager and analyst both expressed significant concern about providing this data and seriously questioned why it needed to be provided at all.

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Types of forecasting problems we help solve

Types of forecasting problems we help solve

Generating accurate statistical forecasts isn’t an easy task. Planners need to keep historical data continually up to date, build and manage a database of forecasting models, know which forecast methods to use, keep track of forecast overrides, and report on forecast accuracy. Here are examples of forecasting problems that SmartForecasts can solve, along with the kinds of business data representative of each.

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How to Forecast Spare Parts with Low Usage

How to Forecast Spare Parts with Low Usage

What do you do when you are forecasting an intermittently demanded item, such as a spare part, with an average demand of less than one unit per month? Most of the time, the demand is zero, but the part is significant in a business sense; it can’t be ignored and must be forecasted to be sure you have adequate stock.

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Recent Posts

  • Managing Spare Parts Inventory: Best PracticesManaging Spare Parts Inventory: Best Practices
    In this blog, we’ll explore several effective strategies for managing spare parts inventory, emphasizing the importance of optimizing stock levels, maintaining service levels, and using smart tools to aid in decision-making. Managing spare parts inventory is a critical component for businesses that depend on equipment uptime and service reliability. Unlike regular inventory items, spare parts often have unpredictable demand patterns, making them more challenging to manage effectively. An efficient spare parts inventory management system helps prevent stockouts that can lead to operational downtime and costly delays while also avoiding overstocking that unnecessarily ties up capital and increases holding costs. […]
  • 5 Ways to Improve Supply Chain Decision Speed5 Ways to Improve Supply Chain Decision Speed
    The promise of a digital supply chain has transformed how businesses operate. At its core, it can make rapid, data-driven decisions while ensuring quality and efficiency throughout operations. However, it's not just about having access to more data. Organizations need the right tools and platforms to turn that data into actionable insights. This is where decision-making becomes critical, especially in a landscape where new digital supply chain solutions and AI-driven platforms can support you in streamlining many processes within the decision matrix. […]
  • Two employees checking inventory in temporary storage in a distribution warehouse.12 Causes of Overstocking and Practical Solutions
    Managing inventory effectively is critical for maintaining a healthy balance sheet and ensuring that resources are optimally allocated. Here is an in-depth exploration of the main causes of overstocking, their implications, and possible solutions. […]
  • FAQ Mastering Smart IP&O for Better Inventory ManagementFAQ: Mastering Smart IP&O for Better Inventory Management.
    Effective supply chain and inventory management are essential for achieving operational efficiency and customer satisfaction. This blog provides clear and concise answers to some basic and other common questions from our Smart IP&O customers, offering practical insights to overcome typical challenges and enhance your inventory management practices. Focusing on these key areas, we help you transform complex inventory issues into strategic, manageable actions that reduce costs and improve overall performance with Smart IP&O. […]
  • 7 Key Demand Planning Trends Shaping the Future7 Key Demand Planning Trends Shaping the Future
    Demand planning goes beyond simply forecasting product needs; it's about ensuring your business meets customer demands with precision, efficiency, and cost-effectiveness. Latest demand planning technology addresses key challenges like forecast accuracy, inventory management, and market responsiveness. In this blog, we will introduce critical demand planning trends, including data-driven insights, probabilistic forecasting, consensus planning, predictive analytics, scenario modeling, real-time visibility, and multilevel forecasting. These trends will help you stay ahead of the curve, optimize your supply chain, reduce costs, and enhance customer satisfaction, positioning your business for long-term success. […]

    Inventory Optimization for Manufacturers, Distributors, and MRO

    • Managing Spare Parts Inventory: Best PracticesManaging Spare Parts Inventory: Best Practices
      In this blog, we’ll explore several effective strategies for managing spare parts inventory, emphasizing the importance of optimizing stock levels, maintaining service levels, and using smart tools to aid in decision-making. Managing spare parts inventory is a critical component for businesses that depend on equipment uptime and service reliability. Unlike regular inventory items, spare parts often have unpredictable demand patterns, making them more challenging to manage effectively. An efficient spare parts inventory management system helps prevent stockouts that can lead to operational downtime and costly delays while also avoiding overstocking that unnecessarily ties up capital and increases holding costs. […]
    • Innovating the OEM Aftermarket with AI-Driven Inventory Optimization XLInnovating the OEM Aftermarket with AI-Driven Inventory Optimization
      The aftermarket sector provides OEMs with a decisive advantage by offering a steady revenue stream and fostering customer loyalty through the reliable and timely delivery of service parts. However, managing inventory and forecasting demand in the aftermarket is fraught with challenges, including unpredictable demand patterns, vast product ranges, and the necessity for quick turnarounds. Traditional methods often fall short due to the complexity and variability of demand in the aftermarket. The latest technologies can analyze large datasets to predict future demand more accurately and optimize inventory levels, leading to better service and lower costs. […]
    • Future-Proofing Utilities. Advanced Analytics for Supply Chain OptimizationFuture-Proofing Utilities: Advanced Analytics for Supply Chain Optimization
      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. […]
    • Centering Act Spare Parts Timing Pricing and ReliabilityCentering Act: Spare Parts Timing, Pricing, and Reliability
      In this article, we'll walk you through the process of crafting a spare parts inventory plan that prioritizes availability metrics such as service levels and fill rates while ensuring cost efficiency. We'll focus on an approach to inventory planning called Service Level-Driven Inventory Optimization. Next, we'll discuss how to determine what parts you should include in your inventory and those that might not be necessary. Lastly, we'll explore ways to enhance your service-level-driven inventory plan consistently. […]