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
5 Demand Planning Tips for Calculating Forecast Uncertainty
Those who produce forecasts owe it to those who consume forecasts, and to themselves, to be aware of the uncertainty in their forecasts. This note is about how to estimate forecast uncertainty and use the estimates in your demand planning process. We focus on forecasts made in support of demand planning as well as forecasts inherent in optimizing inventory policies involving reorder points, safety stocks, and min/max levels.
Forecasting Techniques for a more profitable business
Compares the most useful Forecasting Techniques: Exponential Smoothing, Single Exponential Smoothing, Holt’s Method and Winter’s Method. These videos explain the basic thinking under each technique as well as the math behind them, how they are used in practice and the tradeoff of each method.
Managing the Inventory of Promoted Items
In a previous post, I discussed one of the thornier problems demand planners sometimes face: working with product demand data characterized by what statisticians call skewness—a situation that can necessitate costly inventory investments. This sort of problematic data is found in several different scenarios. In at least one, the combination of intermittent demand and very effective sales promotions, the problem lends itself to an effective solution.
Managing Demand Variability
Anybody doing the job knows that managing inventory can be stressful. Common stressors include: Customers with “special” requests, IT departments with other priorities, balky ERP systems running on inaccurate data, raw material shortages, suppliers with long lead times in far-away countries where production often stops for various reasons and more. This note will address one particular and ever-present source of stress: demand variability.
Reveal Your Real Inventory Planning and Forecasting Policy by Answering These 10 Questions
In this blog, we review 10 specific questions you can ask to uncover what’s really happening with the inventory planning and demand forecasting policy at your company. We detail the typical answers provided when a forecasting/inventory planning policy doesn’t really exist, explain how to interpret these answers, and offer some clear advice on what to do about it.
Riding the Tradeoff Curve
In the supply chain planning world, the most fundamental decision is how to balance item availability against the cost of maintaining that availability (service levels and fill rates). At one extreme, you can grossly overstock and never run out until you go broke and have to close up shop from sinking all your cash into inventory that doesn’t sell.
Recent Posts
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. […]
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
