Demand Planning Best Practices
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.
For some of our customers, weather has a significant influence on demand. Extreme short-term weather events like fires, droughts, hot spells, and so forth can have a significant near-term influence on demand. There are two ways to factor weather into a demand forecast: indirectly and directly. The indirect route is easier using the scenario-based approach of Smart Demand Planner. The direct approach requires a tailored special project requiring additional data and hand-crafted modeling.
In a highly configurable manufacturing environment, forecasting finished goods can become a complex and daunting task. The number of possible finished products will skyrocket when many components are interchangeable. A traditional MRP would force us to forecast every single finished product which can be unrealistic or even impossible. Several leading ERP solutions introduce the concept of the “Planning BOM”, which allows the use of forecasts at a higher level in the manufacturing process. In this article, we will discuss this functionality in ERP, and how you can take advantage of it with Smart Inventory Planning and Optimization (Smart IP&O) to get ahead of your demand in the face of this complexity.
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.
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.
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.
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.
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.
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Accurate Demand Forecasts
Capture trend and seasonality
Predict range of future demand
Cleanse historical data
Collaborate with key stakeholders
Review at any level of hierarchy
Apply overrides and achieve consensus
Consistent Repeatable Process
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?
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.