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.
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.
Is your demand planning and forecasting process a black box?
There’s one thing I’m reminded of almost every day at Smart Software that puzzle me: most companies do not understand how forecasts are created, and stocking policies are determined. It’s an organizational black box. Here is an example from a recent sales call:
The Role of Trust in the Demand Forecasting Process Part 2: What do you Trust
Regardless of how much effort is poured into training forecasters and developing elaborate forecast support systems, decision-makers will either modify or discard the predictions if they do not trust them.”
The Role of Trust in the Demand Forecasting Process Part 1: Who do you Trust
Trust is always a two-way street, but let’s stay on the demand forecaster’s side. What characteristics of and actions by forecasters and demand planners build trust in their work? Key to building trust among the users of forecasts are perceptions of forecaster and demand planner competence and objectivity.
Recent Posts
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The Cost of Spreadsheet PlanningCompanies that depend on spreadsheets for demand planning, forecasting, and inventory management are often constrained by the spreadsheet’s inherent limitations. This post examines the drawbacks of traditional inventory management approaches caused by spreadsheets and their associated costs, contrasting these with the significant benefits gained from embracing state-of-the-art planning technologies. […]
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The Forecast Matters, but Maybe Not the Way You ThinkTrue or false: The forecast doesn't matter to spare parts inventory management. At first glance, this statement seems obviously false. After all, forecasts are crucial for planning stock levels, right? It depends on what you mean by a “forecast”. If you mean an old-school single-number forecast (“demand for item CX218b will be 3 units next week and 6 units the week after”), then no. If you broaden the meaning of forecast to include a probability distribution taking account of uncertainties in both demand and supply, then yes. […]
Why MRO Businesses Should Care About Excess InventoryDo MRO companies genuinely prioritize reducing excess spare parts inventory? From an organizational standpoint, our experience suggests not necessarily. Boardroom discussions typically revolve around expanding fleets, acquiring new customers, meeting service level agreements (SLAs), modernizing infrastructure, and maximizing uptime. In industries where assets supported by spare parts cost hundreds of millions or generate significant revenue (e.g., mining or oil & gas), the value of the inventory just doesn’t raise any eyebrows, and organizations tend to overlook massive amounts of excessive inventory. […]
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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.