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  • Use this as an ice breaker session: Get flipchart and ask them for their thoughts on why forecasting should happen. Then show the slide and see what they have added extra.

Demand forecast Demand forecast Presentation Transcript

  • Forecast Demand
  • Learning ObjectivesTo understand the fundamental of Demand Forecasting.To help plan own Sales Budgets
  • Contents Forecasting What is a forecast? Why forecast? Putting it Together Forecast Types How to Forecast- Forecast Definition - Total forecast components- Forecast uses - Statistical forecasts - Judgmental forecasts- Benefits of doing forecasts OUTPUT:- Consequences of not Volume: Evaluate TOTAL forecast- Statistical Methods Value: link to volume forecasts- Creating Judgmental forecasts Evaluating the Forecast
  • What is a Forecast ? • Definition: A forecast is an estimate of volume or value – for a given SKU (or group of SKUs) – for a given period of time. e.g. • How much Ventolin Inhaler 200 dose will we sell in February? • How much will a case of Augmentin 100 mg cost in November? • What % of Panadol sales will we spend on Television Advertising in 2002?
  • What is a Forecast used for? • Budgeting / Business Planning • Input to the PMI process – Inventory Planning – Distribution Requirements Planning – Inventory Management A Forecast is an ESTIMATE of future sales It will always be wrong to some extent, but will always be BETTER than NO information
  • Why forecast….? • Develop forward view of business • Allow more informed decision taking • Highlight gaps vs. budgets – volume & financial • Communicate through the supply chain • Aim for lower costs – inventory – write-offs • PLAN don’t REACT
  • Consequences of not Forecasting• Always reacting to surprises – fire-fighting vs. value adding – no communication through supply chain• Stock unlikely to absorb abnormal demand – high stock (wrong stock) – poor customer service – unstable NR’s and poor supply• Forrester Effect – demand spikes are amplified • caused by over-reaction to surprises
  • Developing a forecast- Roles • Marketing – Long Term Forecast • Sales – Short Term Forecast • Finance – Prices & Cost forecasting • Senior Management – Sign Off • Demand – Process champions – customer of the forecast A forecast should be reached by CONSENSUS
  • Monthly Planning Cycle Forecast Review Meeting Fr Mo Wk. 2 Wk. 1 Th Tu Finalise WeDownload and We Forecast KPIReview Actuals REPORTING Sales & Tu DEADLINE Th Marketing Meeting Transmit Monthly Mo Demand Meeting Agreed Fr Supply Plan Planning Financial Transmit Mo Month Close Cycle Fr Net Req’s Rough Cut Capacity Negotiate Planning Supply Tu Exceptions Th Review Global Meeting Demand We We Meeting Tu Th Global Mo Fr SupplyWk. 4 Meeting Wk. 3
  • Developing a Forecast- Forecast types• Forecasts consist of two types of information – Statistical forecasts • based on historical data & patterns – Judgmental forecasts • based on judgement, research, consensus, assumptions
  • Developing a Forecast- Forecast typesStatistical Judgmental• Base volume • Adjustments – seasonality – changing market conditions – repetitive orders – seasonal pattern changes • yearly tenders – sales promotions • samples • (with no historical data) – promotions – random tenders • (with historical data) • New Products• Any situation where historical information is available and • Any situation where no historic data reliable. exists or is NOT VALID
  • Developing a ForecastForecast Types - SA Investigator• In SA various volume facts exist to develop the TOTAL VOLUME FORECAST – Base Volume • Statistical – Adjustment Volume • Judgmental/Statistical – Samples Volume • Judgmental/Statistical – Free Goods Volume • Judgmental – Tenders Volume • Judgmental – TOTAL VOLUME • CALCULATED
  • Developing a Forecast- Process• What are the processes that create the different types of forecasting? – Statistical • Base volume forecast – Judgmental • adjustments etc.
  • Statistical Forecasting- Process• Capture actuals – from Sales Order Processing (SOP) system• Filter history – to remove abnormal demand – to remove stock outs – to adjust for step changes • one off task - when conditions change• Run forecasting “algorithm” • tournament, regression etc.• Evaluate results against assumptions
  • Statistical Forecasting Process- Capture Actuals • Actuals from SOP system – provides historical data to use for statistical method • essential to drive forecast in future – will be invoiced sales - therefore : • all sales will be included – including promotions volumes • stock problems will be reflected in lower figures – requires maintenance to be effective • initial one off job when first building forecast • ongoing task is to maintain last month only
  • Statistical Forecasting Process -Actuals being used as History • Projects historical sales patterns into future forecasts – shape will be ‘smoothed’ to varying degree 160 140 120 100 80 60 40 History Forecast 20 0 16 19 25 28 43 1 4 7 10 13 22 31 34 37 40 46
  • Statistical Forecasting- Uses of History• Trends 250 200 150 100 50 Trending 0 Jul Jul Jul Jul Jan Jan Jan Jan Apr Apr Apr Apr Oct Oct Oct Oct History Forecast Linear (History)
  • Statistical Forecasting- Uses of History• Seasonality 180 160 140 120 100 80 60 40 20 Seasonality 0 1 4 7 13 16 19 22 25 28 31 34 37 40 43 46 10 History Forecast Linear (History)
  • Statistical Forecasting Process- Filtering (modify) History • Why Filter – large abnormal patterns will wrongly influence future 300 Total Vol FC Sales Vol FC Sales Vol 250 200 150 100 50 0 Jan Jan Jan Oct Oct Oct Oct Jan Jul Jul Jul Jul Apr Apr Apr Apr • Things to look for in History to filter – stock outs (zeros) & promotions (spikes)
  • Statistical Forecasting Process -Filtering (modify) History • Results of filtering – smoother pattern is projected into future 300 Total Vol FC Adjstmt FC Sales Vol Md / Fc 250 Sales Vol FC Sales Vol 200 150 100 50 0 Apr Apr Apr Apr Oct Oct Oct Oct Jan Jan Jan Jan Jul Jul Jul Jul
  • Business Forecasting Process Capture Sales/Marketing Historic Data Responsibility Modify History Generate Forecasts Review Commercial Plans Review Exceptional Demand Demand Review Meeting Sign off Feed toDemand Planning Process Consensus Forecast
  • Developing a Forecast- Judgmental Forecasting• When Statistics won’t work…. – Where there is no reliable history • New SKUs – For future events that have no past information • range changes • changing market conditions • promotions• Solution……. – Use Judgmental forecasts • to create forecasts where no statistical can exist • to adjust statistical volume (as per last slide)
  • Judgmental Forecasting• Used to add future events to the forecast – can be positive or negative – adjustments made to the statistical base • if one exists (e.g. New SKUs)• Require assumptions to base judgement on – research – market information – brand plans – consensus forecasts (Demand Review Meeting)
  • Judgmental Forecasting • Adjustments should NOT overwrite base volume – should be complementary to the statistical numbers • statistical Base added to judgement adjustments • get the Correct TOTAL VOLUME – in SA use different Fact for adjustments • allows analysis & visibility • comments database can be used to store assumptions
  • Judgmental Forecasting 300 250 200 150 100 50 0 Jan Feb Apr M ay Jul Aug Sep Nov Dec Feb M ar M ay Jun Jul Sep Oct Dec Adjstmt Vol 0 0 0 0 33 104 5 0 0 10 20 80 50 40 40 40 40 Sales Vol FC 100 123 131 144 122 80 110 85 112 123 108 144 122 122 110 130 112 Total Forecast 100 123 131 144 155 184 115 85 112 133 128 224 172 162 150 170 152
  • Putting the Forecast together… -Effort of Forecasting • Focus Forecasting Effort – Statistical forecast alone will often achieve sufficient level of accuracy (especially Cat B/C) – not always the best solution alone • Build judgmental adjustments in where necessary – Complex Demand or High Value (Cat A) Products • Together powerful tool to deliver TOTAL forecast • Statistical - deliver base, trends & seasonality • Judgmental - promotions, ranges changes, abnormal scenarios
  • Putting the Forecast together… -Effort of Forecasting Value A Judgmental Forecasts B Statistical C Forecasting Complexity
  • Putting the Forecast together…- The bigger picture 300 Sales Vol FC Adjstmt Vol Sales Vol Total Forecast Sales Vol MD 250 200 150 100 50 0 Jan Jan Jan Jan Jul Jul Jul Jul Apr Apr Apr Apr Oct Oct Oct Oct
  • Putting the Forecast together…- The Volume - Value link• Value Forecasts driven by volume – Volume x Average Price = Sales Value • both volume and price require forecasting• Volume - Value link will deliver the 24 month rolling business forecast – new products will need to be forecast earlier to get full business picture• Financial forecasting was deployed in 2000 – will allow forecasting for profit and contribution• ONE SET of NUMBERS drives the business
  • Putting the Forecast together…- Points to remember…. • Always remember…. – the forecast from the system may be correct – the initial assumptions may be wrong • changing market conditions • unexpected seasonal conditions • Work out if adjustments are – required, realistic and reasonable to make – if they are - don’t overtype the base volume • use judgmental facts (i.e. Adjustment vol.)