2. Budgeting

3. Given expected sales forecasts, sales price, and cash collections policies, be able to prepare a sales budeget. Given expected sales and inventory policies, be able to prepare a production, materials, and direct labor cost budgets. Given a budget and actual cost figures, be able to compute and interpret budget to cost variances.

4. Set Objectives Bottom Up vs Top Down Sales Forecast Historical Data Non-Financial Parameters Responsibility Accounting

5. Profit Increased market share Return on Investment Cost Reduction Revenue increases

6. Iterative Process You cannot ask a manager at any level to accept responsibility for living within budgets that he or she had no hand in setting.

7. Operating Budget Sales Production Direct Materials/Labor Factory Overhead Pro-forma income Financial Budget Cash Pro-forma balance sheet

8. Prepare sales forecast Determine aggregate production Estimate manufacturing costs & operating exp. Determine cash flow Formulate project financial statements

9. Sales Budget Production Budget Direct Material Factory Overhead Direct Labor Cost of Good Sold Budget Selling Expense Admin Expense Budgeted Income Budgeted Balance Desired Ending Inventory Capital BudgetCash Budget

13. u CMA u FMA FtFt = 3 A t-3 + A t-2 + A t-1 FtFt = 3 A t-1 + A t + A t+1

16. Forecast Exponential Smoothing Short Term Bias, forecast lags demand Simple Exponential Smoothing.2 < <.5 Double Exponential Smoothing Short Term Trends Holt Winters Trends with Seasonal adjustment 

17. Model A t = a +  t Recursion F t =  A t + (1-  )F t-1 Forecast F t+  = a t = F t

20. Recursion F t =  A t + (1-  )F t-1 Alternate F t+1 =  A t + (1-  )F t

24.           000010 101000 1 1 1 1...... FAF F F FAF A ttt t ttt t

25. Optimal  ?

26. Tendency is to choose lowest RSE Min {RSE} when  = 1.0 Fit Past History very well

27. Tendency is to choose lowest RSE Min {RSE} when  = 1.0 Fit Past History very well Divide data into two sets {t=1:60}, {t=61:101}

31. FAF ttsts  where slengthofseasonalcycle    ()1 FAF ttt    ()1 1 or

32. FAF ttsts  where slengthofseasonalcycle    ()1 FAF ttt    ()1 1 or

34. Model A t = a + bt +  t Forecast F t+  = a t + b t  Recursion 1. 4. F t =  A t + (1-  )F t-1 2. F t =  F t + (1-  )F t-1 ^^ 3. a t = 2F t - F t ^ b t = (F t - F t ) ^  1- 

37. where S t = Seasonal Factor for time period t Recursion 1. Compute Seasonal factors S t 2. Deseasonalize data 3. Double smooth on deasonalized data Forecast F t+  = (a t + b t  )S t+  Model A t = (a + bt)S t t 

52. De-emphasizes the use of historical data as the basis for budgeting Justify each dollar spent, not solely the budget increment

53. De-emphasizes the use of historical data as the basis for budgeting Justify each dollar spent, not solely the budget increment

54. Number of new customers Process yield Sales calls per day per salesperson % late deliveries rate of turnover rate of absenteeism

55. Cost Centers Manager responsible for develop a realistic budget and controls expenditures to that budget Profit Centers Manager accountable for both revenue generation and expense control Investment Centers Manager has authority to commit investment resources

57. Positive (favorable) Variances Negative (unfavorable) Variances

58. Deterministic Expenses Discretionary Expenses

59. Materiality of the Variance

60. Timeliness Date: 12-07-98

61. a.Develop a variance report by expense b.Which expenses are important (Mngmt by exception)? c.Which variances are significant (materiality)?