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Week 5 Demand Management - Coggle Diagram

- - - - demand for any finished product
      - data used to forecast demand is collected form retailers' POS data
    - - demand for the raw materials, parts and components used to manufacture a product
      - material requirements planning(MRP)
    - - Input for forecasting/demand and inventory planning
      - Input for supply plan
      - Output of demand stream analysis
      - Input/output of S&OP (Sales and operations planning/manufacturing)
  - - - General Factors
        
        Price of the product
        
        Taste and Preference
        
        Income
        
        Prices of the related goods
        
        Trends(fashion)
        
        Seasonal activities
      - Additional Factors: (Luxury Goods & Durables)
        
        Consumer’s Expectation of future price.
        
        Consumer’s Expectation of future income.
    - - forecast cycles plan weekly or monthly demand at various aggregated levels
      - sales and operations planning process don't address SKU by location accuracy
      - advanced: demand driven, demand sensing and shaping techniques occur outside daily operations
      - network and inventory optimization initiatives don't address on-going variability
  - - - customers----order entry&promising, link
      - demand planning/fcst
      - sales&marketing
      - distribution replenishment
      - interplant demand
      - new product development
    - - Forecasting is a decision-making tool used by many businesses to help in budgeting, planning, and estimating future growth. In the simplest terms, forecasting is the attempt to predict future outcomes based on past events and management insight.
      - We forecast many business values like sales, expenses, HR, manufacturing qtys, investment needs...
      - Demand forecasting
        
        Is comprised of techniques for estimation of probable demand for a product or service in the future.
        
        It is based on the analysis of past demand for that product or service in the present market condition. Demand forecasting should be done on a scientific basis and facts and events related to forecasting should be considered.
        
        After gathering information about various aspect of the market and demand based on the past we use techniques to predict the future demand.
        
        We try to predict the future by looking back at the past
        
        We should also consider
        
        Trends
        
        Seasonality
        
        Cyclical elements
        
        Autocorrelation
        
        Random variation
      - Forecasting techniques
        
        Qualitative methods
        
        Rely on subjective opinions from one or more experts.
        
        Grass Roots: deriving future demand by asking the person closest to the customer.
        
        Market Research: trying to identify customer habits; new product ideas.
        
        Panel Consensus: deriving future estimations from the synergy of a panel of experts in the area.
        
        Historical Analogy: identifying another similar market.
        
        Delphi Method: similar to the panel consensus but with concealed identities.
        
        Quantitative methods
        
        Rely on data and analytical techniques.
        
        Time Series: models that predict future demand based on past history trends
        
        Causal Relationship: models that use statistical techniques to establish relationships between various items and demand
        
        Simulation: models that can incorporate some randomness and non-linear effects
        
        How should we pick our forecasting model?
        
        Data availability
        
        Time horizon for the forecast
        
        Required accuracy
        
        Required Resources
        
        Facts about Demand Forecasting
        
        Dynamic in Nature
        
        Considers Uncertainty
        
        Relies on Information collected from market as well as past data
        
        Applied to various time horizons
        
        short term
        
        medium term forecasts
        
        long term forecasts
        
        Steps in the Forecasting Process
        
        Determine the Use of the Forecast
        
        Select the Items to be Forecasted
        
        Determine a Suitable Time Horizon
        
        Select an appropriate Set of Forecasting Models
        
        Gather Relevant Data
        
        Conduct the Analysis
        
        Validate the Model - Assess its Accuracy
        
        Make the Forecast
        
        Implement the Results
        
        Some general characteristics of forecasts
        
        Forecasts are rarely correct !!
        
        Forecasts are more accurate for groups or families of items
        
        Forecasts are more accurate for shorter time periods
        
        Every forecast should include an error estimate
        
        Forecasts are no substitute for calculated demand.
        
        Choosing a forecasting technique
        
        No single technique works best in every situation
        
        The forecast horizon
        
        Forecasting frequency
        
        Forecasting is not for free
        
        Consider cost and accuracy
        
        Weigh cost-accuracy trade-offs carefully
        
        Forecast detail, part / product level?
        
        Availability of
        
        historical data
        
        computers
        
        able users / decision makers
        
        A method of segmenting products to determine appropriate forecasting approach
        
        high demand volume, high demand uncertainty------Scenario driven forecasts
        
        high/low demand volume, low demand uncertainty-----data driven forecasts
        
        low demand volume, high demand uncertainty------make-to-order environment
        
        Data forforecastingprocess(S&Mview) , required
        
        Sales committment for the period
        
        ABC of SKU’s or family
        
        Direct sales or through distribution
        
        24 months sales history in value & units
        
        Planned or anticipated activities
        
        Other...
        
        Weather
        
        Effects of movies, TV series
        
        Fashion leaders’ choices
        
        Expected events (games, exhibitions etc.)
        
        ABC of SKU’S
        
        24 months sales history in units & COGS
        
        Total supply chain lead time (with same trp method)
        
        Historical OTIF data vs target
        
        Backorders
        
        Marketing input re planned activities
        
        Supplier input
        
        Purchase price
        
        Landing cost factor
        
        Packaging information (size)
- - - - statistical
      - forecasting
      - market intelligence
      - seasonality
      - lost sales
      - supersessions
      - promotion planning
    - - strategic inventory
      - management
      - ABC stratification
      - Scenario Analysis
      - Time-phased
      - Optimization
    - - recommended PO's, WO's and Transfer Orders
      - Constrained Orders
      - Alerts/Exceptions(Potential Stock Outs, Excess, Defers, Cancels, Expedites, etc)
      - Opportunity Buying
- - - - Is performed at least monthly
      - Brings together all functional plans
      - Reconciles supply, demand and new product plans
  - - - outlooks/budgets
      - sales/marketing plans
      - Gross Profit Forecast
    - - Plant loadings
      - inventory levels
      - raw material forecasts
    - - DAYS1-7 Create unconstrained demand plan
      - DAYS7-9 develop supply plan proposals
      - DAY10-12 approved supply plan
      - DAY13 partnership meeting
      - DAY15 Executive Meeting
      - Approved plan
- - - - product review
        
        interface to NPD process
      - demand planning
        
        create(statistica) forecast
        
        sales input
        
        review unconstrained demand plan
        
        sales approval
    - - supply planning
        
        review critical resources&assess scalability
        
        develop initial supply chain plan
        
        identify demand gaps&supply issues
      - inventory planning
        
        review service level agreements
        
        review target stock
    - - balancing&decisions
        
        analyse scenarios, incl, financial impact
        
        prepare decision proposal
        
        pre-meeting based on reconciliation
        
        executive decision meeting
        
        update revenue&cost estimate
    - - execution
        
        handover from decision meetings
        
        update of latest estimate(quarterly)
        
        communication&decision execution
    - - Collaborative Planning, Forecasting, and Replenishment (CPFR), an initiative of the Voluntary Intra-Industry Collaboration Society (VICS)
        
        buyer and supplier share inventory-status, forecast, and event-oriented information and collaboratively make replenishment decisions
        
        pilot program between Wal-Mart and Warner-Lambert, called CFAR: (www.cpfr.org)
      - Challenges to CPFR
        
        fear that competitively-sensitive “private information” will be compromised
        
        Necessary to protect “sensitive” forecast information such as sales promotions from “leaking”
      - CPFR overview
        
        plan your extended supply chain
        
        share forecasts and supply commits with customers and suppliers
        
        get visibility to supplier capacity
        
        reallocate key components
        
        make alternate sourcing decisions
        
        manage inventory cost and improve fulfillment
        
        suppliers manage your inventory
        
        manage your customers inventory
        
        react quickly to supply chain exceptions
        
        waterfall analysis
        
        user-configurable exceptions
        
        automated exception handling via workflow