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
A Primer on Probabilistic Forecasting
If you keep up with the news about supply chain analytics, you are more frequently encountering the phrase “probabilistic forecasting.” Probabilistic forecasts have the ability to simulate future values that aren’t anchored to the past. If this phrase is puzzling, read on.
Improve Forecast Accuracy by Managing Error
In this video, Dr. Thomas Willemain, co-Founder and SVP Research, talks about improving Forecast Accuracy by Managing Error. This video is the first in our series on effective methods to Improve Forecast Accuracy. We begin by looking at how forecast error causes pain and the consequential cost related to it. Then we will explain the three most common mistakes to avoid that can help us increase revenue and prevent excess inventory.
Probabilistic vs. Deterministic Order Planning
Consider the problem of replenishing inventory. To be specific, suppose the inventory item in question is a spare part. Both you and your supplier will want some sense of how much you will be ordering and when. And your ERP system may be insisting that you let it in on the secret too.
Four Useful Ways to Measure Forecast Error
In this video, Dr. Thomas Willemain, co-Founder and SVP Research, talks about improving Forecast Accuracy by measuring Forecast Error. We begin by overviewing the various types of Error Metrics: Scale-dependent error, Percentage error, Relative error, and Scale-free error Metrics. While some error is inevitable, there are ways to reduce it, and forecast metrics are necessary aids for monitoring and improving forecast accuracy. Then we will explain the special problem of intermittent demand and divide-by-zero problems. Tom concludes by explaining how to assess forecasts of multiple items and how it often makes sense to use weighted averages, weighting items differently by volume or revenue.
Automatic Forecasting for Time Series Demand Projections
In this video tutorial Dr. Thomas Willemain, co–Founder and SVP Research at Smart Software, presents Automatic Forecasting for Time Series Demand Projections, a specialized algorithmic tournament to determine an appropriate time series model and estimate the parameters to compute the best forecasts methods.
Forecast Using Leading Indicators – Regression Analysis:
In this Video Tutorials Dr. Thomas Willemain, co–Founder and SVP Research, presents Regression Analysis, a specialized statistical modeling technique to improve the accuracy of the forecasts. These videos explain with examples how to use Regression Analysis and the various scenarios where this technique makes a good choice.
Recent Posts
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5 Ways to Improve Supply Chain Decision SpeedThe 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. […]
12 Causes of Overstocking and Practical SolutionsManaging 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 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 FutureDemand 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 PracticesIn 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 OptimizationThe 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 OptimizationUtilities 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 ReliabilityIn 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. […]
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
Accurate Demand Forecasts
Best Forecasting Methods
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.
A Reliable and Secure Platform
