Demand Planning Best Practices

Smart Software

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.

Scenario-based Forecasting vs. Equations

Scenario-based Forecasting vs. Equations

Traditionally, software has served as a delivery vehicle for equations. This is fine, as far as it goes. But we at Smart Software think you would do better by trading in your equations for scenarios. Learn why Scenario-based planning helps planners better manage risk and create better outcomes.

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Managing Inventory amid Regime Change

Managing Inventory amid Regime Change

If you hear the phrase “regime change” on the news, you immediately think of some fraught geopolitical event. Statisticians use the phrase differently, in a way that has high relevance for demand planning and inventory optimization. This blog is about “regime change” in the statistical sense, meaning a major change in the character of the demand for an inventory item.

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Blanket Orders

Blanket Orders

Our customers are great teachers who have always helped us bridge the gap between textbook theory and practical application. A prime example happened over twenty years ago, when we were introduced to the phenomenon of intermittent demand, which is common among spare parts but rare among the finished goods managed by our original customers working in sales and marketing. This revelation soon led to our preeminent position as vendors of software for managing inventories of spare parts. Our latest bit of schooling concerns “blanket orders.”

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Coping with Surging Demand During the Rebound

Coping with Surging Demand During the Rebound

Many of our customers that saw demand dry up during the pandemic are now seeing a significant demand surge. Other customers in critical industries like plastics, biotech, semiconductors and electronics saw demand surges starting as far back as last April. For suggestions about how to cope with these situations, please read on.

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Six Steps Up the Learning Curve for New Planners

Six Steps Up the Learning Curve for New Planners

If you are a new professional in the field of inventory management, you face a very steep learning curve. There are many moving parts in the system you manage, and much of the movement is random. You may find it helpful to take a step back from the day-to-day flow to think about what it takes to be successful. Here are six suggestions that you may find useful; they are distilled from working over thirty five years with some very smart practitioners.

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    Traditionally, software has served as a delivery vehicle for equations. This is fine, as far as it goes. But we at Smart Software think you would do better by trading in your equations for scenarios. Learn why Scenario-based planning helps planners better manage risk and create better outcomes. […]

    Inventory Optimization for Manufacturers, Distributors, and MRO

    • Blanket Orders Smart Software Demand and Inventory Planning HDBlanket Orders
      Our customers are great teachers who have always helped us bridge the gap between textbook theory and practical application. A prime example happened over twenty years ago, when we were introduced to the phenomenon of intermittent demand, which is common among spare parts but rare among the finished goods managed by our original customers working in sales and marketing. This revelation soon led to our preeminent position as vendors of software for managing inventories of spare parts. Our latest bit of schooling concerns “blanket orders.” […]
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      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. […]

      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

      Smart Demand Planner™ is a consensus demand planning and statistical forecasting solution available on Smart’s Inventory Planning and Optimization Platform, Smart IP&O. Smart Demand Planner, powered by the SmartForecasts® Engine, aligns strategic business forecasting at any level of your product hierarchy with granular forecasts of the item mix to improve forecast accuracy. It provides a statistically sound, objective foundation for your sales and operations planning process (S&OP).  Smart Demand Planner’s collaborative workbench enables forecast overrides to be applied, imported, reviewed, and approved by authorized users driving the consensus plan. Forecast accuracy is measured, helping ensure that the best possible forecast is delivered to the business at both the aggregate and item mix levels. The result is more efficient sales planning, budgeting, production scheduling, ordering, and inventory planning.

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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?
        • 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.

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