Supply chain management involves planning and implementation. Demand planning, based on a statistical projection, evaluates inventory, marketing, and demand-influencing factors and defines where to distribute products to fulfill the anticipated demand. Usually kicks off the planning side of SCM.
To increase the precision of the demand forecasts utilized in the supply chain, companies invest a lot of time and money in forecasting activities. The objectives of a precise demand plan and a lean supply chain process may be hampered by a bad process design.
Learn industry best practices on how to improve demand planning and create supply chain efficiencies.
You Need to Team up with the Algorithms
This article is about the real power that comes from the collaboration between you and our software that happens at your fingertips. We often write about the software itself and what goes on “under the hood”. This time, the subject is how you should best team up with the software.
A Rough Map of Forecasting-Related Terms
People new to the jobs of “demand planner” or “supply planner” are likely to have questions about the various forecasting terms and methods used in their jobs. This note may help by explaining these terms and showing how they relate.
Six Demand Planning Best Practices You Should Think Twice About
Every field, including forecasting, accumulates folk wisdom that eventually starts masquerading as “best practices.” These best practices are often wise, at least in part, but they often lack context and may not be appropriate for certain customers, industries, or business situations. There is often a catch, a “Yes, but”. This note is about six usually true forecasting precepts that nevertheless do have their caveats.
Correlation 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.
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.
Elephants and Kangaroos ERP vs. Best of Breed Demand Planning
The largest ERP companies can’t develop high quality best-of-breed like solutions. They never had to, so they never evolved to innovate outside their core focus. However, as ERP systems have become commoditized, gaps in their functionality have become impossible to ignore.
Recent Posts
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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
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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
An accurate forecast is a critical supply chain driver, but many organizations have a limited view of what comes next. Forecasts developed by sales teams or customers are often inaccurate and biased toward sales goals or budgets. Forecasts are often provided only at aggregate levels leaving unspecified which items will be at which locations. Planning teams are left to interpret sales figures and convert them into actionable forecasts of the item mix. Incorporating sales feedback, determining which decades old forecast model to use, managing the consensus forecast process, and tracking forecast accuracy are manual processes. They are often managed in complex spreadsheets that are difficult to use, share and scale, and don’t account important features of demand such as seasonality and trend.
Solution
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Accurate Demand Forecasts
Capture trend and seasonality
Predict range of future demand
Flag exceptions
Cleanse historical data
Operational Consensus
Collaborate with key stakeholders
Review at any level of hierarchy
Apply overrides and achieve consensus
Consistent Repeatable Process
Common system
No spreadsheets
Embed and reuse forecast rules
Monitor accuracy and fine-tune
Who is Smart Demand Planner for?
- Demand Planners.
- Forecast Analysts.
- Material & Inventory Planners.
- Operational Research Professionals.
- Sales Analysts.
- Statistcally Minded Executives.
What questions can Smart Demand Planner answer?
- What is my short and long term demand most likely to be?
- Which areas of the business and products are trending?
- What is the forecast at different levels of my hierarchy (customer, item, family)?
- What is the likely range of future demand?
- Which forecasts need to be reviewed (exception reporting)?
- What is our forecast error (accuracy) for each item, group, overall?
- Are forecast overrides adding value to the process?
What can Smart Demand Planner do?
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Accurately forecast demand for thousands of items in any unit of measure, powered by the SmartForecasts® engine.
- Capture trends, seasonal, and cyclical patterns at any level.
- Outlier detection and correction to enhance the quality of historical data.
- Identifies “causal” factors such as price and economic data and models their impact on demand.
- Patented Intermittent Demand Planning via APICS award winning “Bootstrapping” technology.
- Create forecasts at any level of the hierarchy – customer, item, product groups, regions.
- Share forecasts with internal and external stakeholders such as sales and suppliers.
- Apply, document, and track forecast overrides.
- Quantify the impact that promotions will have on future demand.
- Apply user defined forecasting methods and rules.