Project Sales Or Production Levels Using The Rolling Average Principles of Cost Analysis and Management © Dale R Geiger 2011 What if? You planned for 10 but… © Dale R Geiger 2011 Terminal Learning Objective • • Task: Project Sales Or Production Levels Using The Rolling Average • Standard: with at least 80% accuracy Condition: You are a cost advisor technician with access to all regulations/course handouts, and awareness of Operational Environment (OE)/Contemporary Operational Environment (COE) variables and actors • Demonstrate understanding of Trend Projection concepts © Dale R Geiger 2011 Importance of Demand • We have seen how demand drives cost • • Assumptions about probabilities may not yield useful information • • Flexible forecasting “Precisely wrong” Examining trends gives another perspective on demand © Dale R Geiger 2011 Predicting the Future • • • Take your M77 Crystal Ball and predict the number of burgers needed Would your prediction change if you knew the last six cookouts needed • • 10 ? Or 16 15 14 13 12 11 ? If yes, then you are recognizing that the past can help us make better decisions about the future © Dale R Geiger 2011 What is Trend Projection? • • • Uses historical data about past demand to make estimates of future demand Relies on systematic methodologies and assumptions Cannot predict the future or anticipate catastrophic events © Dale R Geiger 2011 Three Methods • Regression • Rolling average • Planning factors • • • Represents a straight line with the least squared error from actual Uses average of prior period demand to predict future period demand Assumes a relationship between a current value and future demand © Dale R Geiger 2011 Regression Analysis • • Plots a linear relationship between multiple data points Minimizes the “squared errors” • • Square difference between mean and actual to eliminate negative values Uses the format y = mx + b where: m = b = n(Σxy) - (Σx)( Σy) 2 n(Σx ) - (Σx) (Σy)( Σx ) (Σx)( Σxy) 2 n(Σx ) - (Σx) © Dale R Geiger 2011 Regression Results • Very predictable • • The ascending series is y = x + and we can predict that the th period would need 11 burgers The descending series is y = -x + 17 and we can predict that the th period would need 10 © Dale R Geiger 2011 Regression Exercise • th th th Use spreadsheet to predict the , , and 10 event burger demand if the first six demands were: • 10 12 13 15 © Dale R Geiger 2011 10 Graph of Rolling Average Actual 3-mo avg 1 10 11 12 This is a time series X-axis represents sequential time periods © Dale R Geiger 2011 25 Graph of Rolling Average Actual 3-mo avg 1 10 11 12 This is a time series X-axis represents sequential time periods © Dale R Geiger 2011 26 Rolling Average vs Regression Actual Linear (Actual) 3-mo avg 1 10 11 12 This is a time series X-axis represents sequential time periods © Dale R Geiger 2011 27 Using Rolling Average to Project Future Demand • • Assume that the previous rolling average will be maintained Period 10 11 12 Our forecast for period 13 will assume a rolling average of 5, same as period 12 Value 3mo Avg X X 6.0 5.0 4.7 5.0 6.0 6.3 5.7 5.7 4.3 5.0 (Per11 + Per12 + Per13)/3 = © Dale R Geiger 2011 28 Using Rolling Average to Project Future Demand • Plug in the known values and solve the equation: (Per11 + Per12 + Per13)/3 = (4 + + Per13)/3 = * (4 + + Per13)/3 = * + Per13 = 15 Per13 = © Dale R Geiger 2011 29 Using Rolling Average to Project Future Demand • Plug in the known values and solve the equation: (Per11 + Per12 + Per13)/3 = (4 + + Per13)/3 = * (4 + + Per13)/3 = * + Per13 = 15 What would regression analysis project? Per13 = Which is “right”? © Dale R Geiger 2011 30 Rolling Average vs Regression month rolling average suggests an inflection point has changed the trend Regression picks up the long term downward trend, predicting another decrease 1 10 11 12 This is a time series X-axis represents sequential time periods © Dale R Geiger 2011 31 13 Rolling Average Strengths and Weaknesses • • • Can be calculated very precisely • But may be precisely wrong Simple to calculate The main strength of rolling averages is that they dampen the effect of short term changes • • • This helps decision makers avoid knee jerk responses to changes in demand that may not be significant Decision makers are often looking for inflection points An inflection point in a six month rolling average carries a lot of weight © Dale R Geiger 2011 32 Check on Learning • • What would be the equation for a six-month rolling average calculation? What is the primary assumption when using rolling average to project future demand? © Dale R Geiger 2011 33 Planning Factors • • Assume some cause and effect relationship If we suspect that demand for education counseling decreases when a unit deploys • • • We could study the history of that relationship and determine a planning factor (or ratio) of sessions per soldier as “a” We could then use that factor to plan for the drop in session demand when X soldiers deploy as New demand = a*X © Dale R Geiger 2011 34 Planning Factor Example • Given the recent history determine the planning factor relating sessions and soldiers • Use that factor to predict sessions as population goes to • • • 8000 Counseling Sessions Soldiers on Post 327 10856 369 10012 285 10255 301 10566 349 10467 363 10200 7000 6000 © Dale R Geiger 2011 35 Planning Factor Example • Given the recent history determine the planning factor relating sessions and soldiers • Use that factor to predict sessions as population goes to • • • 8000 * 032 = 256 Counseling Sessions Soldiers on Post 327 10856 369 10012 285 10255 301 10566 349 10467 363 10200 7000 * 032 = 224 6000 * 032 = 192 Total = 1994 62365 1994/62365 = 032 or 3.2% © Dale R Geiger 2011 36 Leading Indicators • Leading indicators are similar to planning factors with a couple differences • Leading indicators often have a weaker cause and effect relationship • Changes in consumer confidence index may foreshadow an increase in sales at the post exchange • There is a period of time before the effect is seen (i.e that’s why they are called leading indicators) © Dale R Geiger 2011 37 Check on Learning • • What are planning factors? How are planning factors generally expressed? © Dale R Geiger 2011 38 Practical Exercise © Dale R Geiger 2011 39 ...What if? You planned for 10 but… © Dale R Geiger 2011 Terminal Learning Objective • • Task: Project Sales Or Production Levels Using The Rolling Average • Standard: with... Trend Projection concepts © Dale R Geiger 2011 Importance of Demand • We have seen how demand drives cost • • Assumptions about probabilities may not yield useful information • • Flexible forecasting... a cost advisor technician with access to all regulations/course handouts, and awareness of Operational Environment (OE)/Contemporary Operational Environment (COE) variables and actors • Demonstrate