Statistical Forecasting Blog

Optimize Inventory planning parameters,improve service levels and increase revenue

Forecasting is a fully developed business process that most organizations still struggle with today. Almost everyone’s top priority is probably to be able to consistently and accurately forecast Sales, Demand, Costs, Inventory, etc.  The inability to obtain a good forecast frequently has a significant business impact. Inaccurate forecasting leads to overstocking or running out, resulting in high costs and excess, impacting the bottom line and the success of the company.

A good forecast should give you enough confidence to make sound business decisions. For a more efficient forecast, consider these best practices:

  • What are the most common forecasting methods, and why do they produce inaccurate results.
  • How to achieve better ROI and optimal processes through scale, granularity, and agility
  • How to improve forecasting accuracy
  • How to use simple machine learning and artificial intelligence tools to get accurate and scalable forecasts
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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Recent Posts

  • professional technician engineer planning spare parts in industrial manufacturing factory,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. […]
  • Uncover data facts and improve inventory performanceUncover data facts and improve inventory performance
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  • Electricity problems. Repairman is working indoors with Software for spare partsElectric 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. […]
  • Correlation vs Causation Relevant to your demand planning businessCorrelation vs Causation: Is This Relevant to Your Job?
    Outside of work, you may have heard the famous dictum “Correlation is not causation.” It may sound like a piece of theoretical fluff that, though involved in a recent Noble Prize in economics, isn’t relevant to your work as a demand planner. Is so, you may be only partially correct. […]
  • Downtown Miami skyline panorama and with software guided lights on at duskSmart Software Customer, Arizona Public Service to Present at USMA 2023
    Smart Software CEO and APS Inventory & Logistics Manager to present USMA 2023 Session on APS supply chain transformation project and the role of inventory optimization technology in their new process. […]

    Inventory Optimization for Manufacturers, Distributors, and MRO

    • professional technician engineer planning spare parts in industrial manufacturing factory,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. […]
    • Electricity problems. Repairman is working indoors with Software for spare partsElectric 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. […]
    • Worker maintenance industrial machine robotic Forecasting Spare PartsHow 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. […]
    • Spare Parts, Replacement Parts, Rotables, and Aftermarket PartsSpare Parts, Replacement Parts, Rotables, and Aftermarket Parts
      Those new to the parts planning game are often confused by the many variations in the names of parts. This blog points out distinctions that do or do not have operational significance for someone managing a fleet of spare parts and how those differences impact inventory planning. […]

    Problem

    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. These steps are typically managed in a cumbersome spreadsheet that is often error-prone, slow, and difficult to share with the rest of the business. Forecasts tend to rely on one-sized fits all methods that require seasonality and trend to be added manually resulting in inaccurate predictions of what comes next

    Solution

    SmartForecasts™ Cloud is a statistical forecasting solution available on Smart’s Inventory Planning and Optimization Platform, Smart IP&O. It provides a statistically sound, objective foundation for your sales and operations planning process (S&OP). SmartForecasts automatically selects the most accurate forecasting method, allows users to fine-tune statistical and user-defined models, enables forecast and historical overrides, and automatically measures forecast error and bias. Forecast overrides are tracked and historical data is automatically updated eliminating the manual effort accompanying spreadsheet-based solutions. Coupled with Smart’s ERP connectors, results can be pushed to your ERP system of choice automatically. The result is more efficient sales planning, budgeting, production scheduling, ordering, and inventory planning process.

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      SmartForecasts ® Cloud

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      Accurate Demand Forecasts

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      Best Forecasting Methods

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      Imports Historical Data

      What can you do with SmartForecasts?
      • Run a forecasting tournament that selects the right forecasting method for each item.
      • Hand-craft forecasts using several time-series forecasting methods and non-statistical methods.
      • Automatically predict trends, seasonality, and cyclical patterns.
      • Imports demand data from files
      • Leverage ERP connectors to automatically import demand data and return forecast results
      Who is SmartForecasts for?

      • Demand Planners.
      • Forecast Analysts.
      • Material & Inventory Planners.
      • Operational Research Professionals.
      • Sales Analysts.
      • Statistcally Minded Executives.

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