IT S ALL ABOUT THE CUSTOMER FORECASTING 101

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1 IT S ALL ABOUT THE CUSTOMER FORECASTING 101 Ed White CPIM, CIRM, CSCP, CPF, LSSBB Chief Value Officer Jade Trillium Consulting April 01, 2015

2 Biography Ed White CPIM CIRM CSCP CPF LSSBB is the founder of Jade Trillium Consulting. Over the course of his career he has worked in several industries ranging from food and pharmaceutical to chemicals and plastics. He has held positions at many different management levels and been responsible for numerous projects in Supply Chain, cost saving, education and value enhancement, Ed is an active member of APICS as an instructor and Chapter Board member. In addition Ed is a published author and sought after speaker on various Supply Chain topics. He has spoken at several international conferences for APICS, IBF & SAPICS. Making Organizations More Effective!

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4 FORECASTING IS LIKE BREATHING, EVERYONE DOES IT AND YOU ALMOST NEVER THINK ABOUT IT

5 How long will it take to get to work? What time do you have to leave Based on history, modified by weather conditions, current road construction and traffic conditions Will I run out of money before I run out of month? Decide whether to go see a movie with family Based on outstanding bills, modified by current cash situation and understanding of potential new bills

6 There are two types of forecasts: INFORMAL: No defined process Everyone making their best guess as to what will be needed in their own areas FORMAL: Defined process and procedures Used by everyone in the defined group THIS IS WHAT YOU WANT!!!

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8 Because we want to: to keep our customers happy and profitable so we can stay happy and profitable and employed

9 Main functions of Materials Management is: to ensure material is available for sale at an acceptable customer service level while maintaining stock levels at a financial level that is acceptable to the company. 9

10 Purpose of MRP is to recommend changes to material stock levels that will; To ensure material is: in the right place at the right time in the right quantity at the right cost 10

11 Forecasting is the prelude to planning Little planning can be done without some form of estimation Forecasts are at best an informed guess Forecast is NOT the budget divided by 12 Forecast is related to the LE not the budget

12 Are almost always wrong If they are right it s a mistake Should include an estimate of error

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14 Are almost always wrong If they are right it s a mistake Should include an estimate of error Are more accurate for groups of products Are more accurate for nearer periods of time

15 There are two types of formal forecasts: Qualitative Someone s best guess Quantitative Calculated based on someone s past sales data You should be doing both

16 The problem with only using a calculated forecast is that it is like driving using only the rear view mirror. You re OK until the first curve in the road and then you re in the ditch.

17 Efficient production sequencing which will lead to more available capacity. Less rework Better run size distribution Reduced Dead and Slow Inventory due to a more accurate product mix in the inventories and greater inventory turnover Improved product quality Improved customer confidence Cost containment through improved freight logistics Optimized inventories More accurate raw material planning

18 Inventory carrying cost on Dead and Slow Moving Stock Dead and Slow Write-Downs Extra warehousing costs for ineffective inventory Lost production due to rush inserts Reworked inventory

19 Short answer everyone that has information on future demand. System can generate a calculated forecast based on history Sales must modify based on Cust. knowledge Only sales knows Cust. long term plans. SALES & OPERATIONS PLANNING (S&OP) process is used to arrive at a consensus forecast

20 Trend General movement upwards or downwards Seasonal repeating pattern over a period of time Bias artificially introduced trend Outlier data point that is significantly different than the norm

21 General business and economic conditions Competitive factors Market trends such as changing demands in the marketplace Firm s own plans pricing product changes Regulatory compliance

22 Jan 100 Feb 90 Mar 110 Apr 105 May 95 Jun 90 July 90 Aug 120 Sept? Simplistic Last month sales repeated This is the simplest form of formal forecast available. Only useable if sales very steady Since Aug sales was 120 units the forecast for Sept is 120 To allow for planning lead time you could always offset by one or more months. For example a one month offset would use July sales of 90 units as the forecast for Sept.

23 Jan 100 Feb 90 Mar 110 Apr 105 May 95 Jun 90 July 90 Aug 120 Sept? Simplistic Last month sales repeated (Forecast =120) Average Average preceding 12 months sales Ignores seasonality and variability In this example we only have 8 months of data so an 8 month average would be ( )/8 = 800/8 = 100

24 Jan 100 Feb 90 Mar 110 Apr 105 May 95 Jun 90 July 90 Aug 120 Sept? Simplistic Last month sales repeated (Forecast =120) Average Average preceding 12 months sales (Forecast = 100) Moving 3 month Average Average only previous 3 month sales Captures seasonality but not trends Previous three months (Jun, July and Aug) give an average of ( )/3 = 300/3 = 100

25 Jan 100 Feb 90 Mar 110 Apr 105 May 95 Jun 90 July 90 Aug 120 Sept? Simplistic Last month sales repeated (Forecast =120) Average Average preceding 12 months sales (Forecast = 100) Moving 3 month Average Average only previous 3 month sales (Forecast = 100) Winters, Student T, Multiple Linear Regression, etc Potentially more accurate but requires statistical background to set up and interpret Definitely more expensive

26 1. You want the formula and process that gives you at least the lowest acceptable accuracy 2. This should be balanced against the cost of the process. If you are spending more than you are saving, find a simpler process. 3. Should always compare your accuracy against the accuracy of simplistic formula. If no major improvement, why use the more complicated formula / methodology.

27 1. Are there any one time events like shutdowns planned by the customer? 2. Are there any anticipated increases in demand? 3. Are there any anticipated decreases in demand? 4. Is there any chance of an existing product / size being replaced by a new combination? 5. Is there any chance of a change to customer / location / etc?

28 No more than 3 hours a month Critical customers first Critical materials second Low f/c accuracy combinations before high accuracy combinations If you must guess - guess high

29 Forecasts are always wrong We don t care if they are wrong The important point is how wrong are they! By monitoring the forecast accuracy report we can track which material / customer combinations or other groups of forecasts have the most opportunity for improvement.

30 REMEMBER: FORECASTS ARE MORE ACCURATE FOR LARGER GROUPS Therefore more accurate at material level rather than at material / Cust. Level IN THE NEAR FUTURE RATHER THAN THE DISTANT FUTURE 3 months out more accurate than 12 months out, but 12 months still important for tentative capacity planning FOR A CUMULATIVE TIME FRAME RATHER THAN A SINGLE TIME FRAME By reporting sales over rolling 3 months rather than each month individually we eliminate the issue of sales that fall just over the line into another month

31 1. Formula: Forecast Accuracy (%) = Sales - Sales- Forecast x 100 Sales Month Jan Forecast from Dec Actual Sales Sales - Forecast 200 (absolute variance) 1st Step: Calculation of absolute forecast error with respect to forecast lowest level ONLY If Forecast = 0 and Actual 0, then Forecast Accuracy = 0% If Actual = 0 and Forecast = 0, then Forecast Accuracy = 100% If Forecast 0 and Actual = 0, then Forecast Accuracy = 0% Forecast Accuracy (%) = x 100) = ,9% Aggregation of SALES and absolute deviations on all aggregation levels; calculation of forecast accuracy on all aggregation levels Consequence: Deviations grow on every aggregation level (net out effect of positive and negative errors is eliminated) 2nd Step: Examine result for special cases at the article level 3rd Step: Calculation of Forecast Accuracy by using given formula 4th Step: Aggregation according to predefined reporting levels

32 The important factor is not technique, it is process control and management The S&OP process allows everyone to participate in creating a consensus Demand & Supply plan Anyone can forecast but the right person with the right information can significantly increase accuracy Small changes in forecast accuracy can translate to big $ improvement in profitability Bottom line it s all about customer satisfaction

33 FORECASTING IS JUST ANOTHER COMMUNICATIONS PROCESS Remember, IT S ALL ABOUT THE CUSTOMER

34 34

35 For more information or if you have any comments about this presentation please contact me at: Please remember to give your completed feedback form to our room monitor.

36 Ed White CPIM CIRM CSCP CPF LSSBB Value Catalyst Jade Trillium Consulting Supply Chain and Management Consulting Forecasting 101 It s all about the customer Ed ca.linkedin.com/in/edwhitesupplychain/

37 FORECAST PROCESSES Forecast Processes rounded Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Last year sales 9,250 9,100 9,000 9,050 8,950 9,250 9,250 9,400 9,550 9,675 9,900 9, ,225 Simplistic last yr + 10% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total This year f/c 10,175 10,010 9,900 9,955 9,845 10,175 10,175 10,340 10,505 10,643 10,890 10, ,448 rounded Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Last year sales 9,250 9,100 9,000 9,050 8,950 9,250 9,250 9,400 9,550 9,675 9,900 9, ,225 Adjusted Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total This year f/c 10,175 10,010 9,900 9,955 9,845 10,175 10,175 10,340 10,505 10,643 10,890 10, ,448 Sales Adjustment ,100 Final f/c 10,075 9,910 9,900 10,005 9,895 10,175 10,175 10,440 10,705 10,893 11,140 11, ,548 rounded Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Last year sales 9,250 9,100 9,000 9,050 8,950 9,250 9,250 9,400 9,550 9,675 9,900 9, ,225 Tiered This year f/c Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Promotional Holiday Seasonal Internal Service ,200 Base 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10,000 10, ,000 Forecast 10,150 10,050 9,950 9,950 9,900 10,050 10,150 10,250 10,450 10,750 11,050 11, ,750

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