Sales Forecasting in Automotive Companies

Transcription

1 Sales Forecasting in Automotive Companies Presentation GSSI Conference, Aalen Prof. Dr.-Ing. Jobst Görne HTW Aalen Aalen University of Applied Science Prof. Dr. Jobst Görne 1

2 Objectives 1. Importance of Sales Forecasting 2. Sales Forecasting for Tier 1-Companies 3. Sales Forecasting for Tier 2-Companies Aalen University of Applied Science Prof. Dr. Jobst Görne 2

3 1) Importance of Sales Forecasting Planning of the Sales Activities Safeguarding Liquidity Safeguarding Supply Planning and Safeguarding Financial Result of the Company Aalen University of Applied Science Prof. Dr. Jobst Görne 3

4 Basic Model for Sales Forecasting : + = Aalen University of Applied Science Prof. Dr. Jobst Görne 4

5 Sales Controlling Parameter of the Control Loop: Reliability and Precision of the Data Frequency of Updating Market Response Time MRT The Parameters are set by the industry type Aalen University of Applied Science Prof. Dr. Jobst Görne 5

6 Saels Volume Action Definition Market Response Time (MRT) t MRT = Time from Start of a Sales Action until measurable Feedback from the Market in Form of Sales Volume t MRT Time Aalen University of Applied Science Prof. Dr. Jobst Görne 6

7 Serial Supply Structure Automotive Tier3 Often material suppliers needed to produce parts Big, Powerful International Companies Tier2 Manufacturer of parts like stampings or castings used for the components SME, often national, technology driven Tier1 Manufacturer of complex components, such as diesel injection pumps, axles Big, Powerful International companies OEM Car Manufacturer Big, Powerful Global Companies Aalen University of Applied Science Prof. Dr. Jobst Görne 7

8 Characterization of Tier 1 Companies Small number of customers Supply small number of parts, but with a high value Very good relations to the OEM Sales forecasting short term (up to 6 months) is based on their customers call offs Middle and long term forecasting can be based upon OEM s sales forecasting Aalen University of Applied Science Prof. Dr. Jobst Görne 8

9 Facts Forecasting Tier 1 Gaining business contracts at the OEM is highly competitive The loss of a contract to a competitor during a model period is very unlikely This has as consequence that to gain business during a model period is unlikely, too. New and additional sales volume can only be acquired when a new car model is put on the market The car life cycle duration is up to 7 years Aalen University of Applied Science Prof. Dr. Jobst Görne 9

10 Example Tier 1 Sales Forecasting Running Orders Product Custo mer Sales Forecast TIER 1 Petrol Pump Department Sales Value /Car (EUR) Car Sales (OEM) Predicted Sales Volume ( ) Car Sales (OEM) Predicted Sales Volume ( ) Car Sales (OEM) Predicted Sales Volume ( ) Car Sales (OEM) Predicted Sales Volume ( ) Diesel Pump XZ OEM Fuel Pump FP OEM Diesel Pump M OEM OEM Total Sales: Aalen University of Applied Science Prof. Dr. Jobst Görne 10

11 Sales Volume Chart Running Business Tier Sales Volume Development for Running Business over next Years based upon OEM Sales Forecast Aalen University of Applied Science Prof. Dr. Jobst Görne 11

12 Acquiring New Business: Time Components of MRT: Tier 1 Duration (Months) Action definition 1 Contact potential customers 3 Waiting for the appropriate time slot Project definition 3 12 Quotation and negotiation 3 12 Getting production ready 6 12 Submit PPAP 1 Homologation 1-6 Wait for SOP 6 Payment terms 1,5 Total: approx. 3-6 Years Aalen University of Applied Science Prof. Dr. Jobst Görne 12

13 Forecasting Probable New Business, Tier 1 Sales Forecast TIER1 "New Projects" Product Custo mer Sales Value /Car (EUR) Proba bility of success (%) Car Sales (OEM) Pre dicted Sales Volume ( ) Car Sales (OEM) Predicted Sales Volume ( ) Car Sales (OEM) Predicted Sales Volume ( ) Car Sales (OEM) Predicted Sales Volume ( ) Diesel Pump XN OEM Fuel Pump FP OEM Dies. Pump XB OEM Total Sales: Aalen University of Applied Science Prof. Dr. Jobst Görne 13

14 Consolidated Sales Volume Development Tier EUR Running Business plus probable new Business Running Business Aalen University of Applied Science Prof. Dr. Jobst Görne 14

15 Consequences of Forecasting Process Tier 1: Reliable sales figures can be derived from OEM car sales forecasting up to 4-5 years Low sales figures cannot be raised within short term The long MRT require long sighted sales plans: it is too late to act when Sales Volume shows downwards figures Early indicators need to be established Aalen University of Applied Science Prof. Dr. Jobst Görne 15

16 Extended Sales Control Loop Markets with long MRT require the use of extended control loops. Early business indicators are needed Otherwise the reaction to market movements will be too late Aalen University of Applied Science Prof. Dr. Jobst Görne 16

17 Tier 2 Characterization of Tier 2: Tier 2 often have many customers (typically 100) They supply multiple parts to each customer (often10-50) The supplied parts have high volumes, but a relatively low value The parts are often used in many projects so it is difficult to make the relationship between parts consumption and car model sales Tier 2 supply often different markets Aalen University of Applied Science Prof. Dr. Jobst Görne 17

18 Time Components New Business Tier2 Duration (Months) Planning 0,5 Contact 0,5 Waiting for appropriate time slot 2 Quotation and negotiation 1 Getting production ready 3 Submit PPAP 1 Homologation 2 Wait for SOP 3 Payment terms 1,5 Total: approx 1 1,5 years Aalen University of Applied Science Prof. Dr. Jobst Görne 18

19 Sales ForecastingTier2 Short term sales forecasts are based upon customers call offs The big number of customers and parts does not allow sales forecasting based upon car model sales for mid- and long term Proposal for Forecasting: Use the phenomenon of Loss Of Orders (LOO) to predict remaining life of projects The LOO approach is based upon typical project life times. If a company monitors its New Acquired Business (NAB) on a continuous basis, the end of the projects is continuous, too Example: the company supplies 100 different parts to it s customers with a part life of 10 years. If the contracts have been acquired evenly in the past, each year about 10% of the contracts will end This means, that for keeping the Sales Volume constant, at least 10% of the Sales Volume needs to be acquired freshly year by year. Loss of orders = 10% per year Aalen University of Applied Science Prof. Dr. Jobst Görne 19

20 Average Contract Life Average Loss of Orders Different types of industry show different contract lifes: automotive: 6 years truck: 10 years Computer and IT: 2 years Gardening equipment: 3 years Loss of orders LOO can be formulated as: LOO = Turnover (average contract life) EUR/Year Aalen University of Applied Science Prof. Dr. Jobst Görne 20

21 Orders Orders Sales View of Orders Time Time Orders Arranged According to End of Life Aalen University of Applied Science Prof. Dr. Jobst Görne 21

22 Consequences of Loss Of Orders Due to the loss-of-order effect the Sales Volume will decrease continuously, if no new business is acquired The Loss of Orders LOO needs to be (at least) compensated by new acquired business NAB So the sales manager can easily predict the future business development in looking at the balance of LOO and NAB + = Aalen University of Applied Science Prof. Dr. Jobst Görne 22

23 Continous Check of the New Acquired Business NAB can be monitored each month to show deviations from plan New Acquired Business Cumulative Jan-Okt Parts Target Line Jan Feb Mär Apr Mai Jun Jul Aug Sep Okt Nov Dez Tools Aalen University of Applied Science Prof. Dr. Jobst Görne 23

24 More Early Indicators for Business Development Before order acquisition, there is a negotiation period for the different projects The commercial volume of the negotiated projects can be monitored This is only a very rough indication. A high project volume will not necessarily lead to a high order income. But a very low project volume cannot lead to high orders Projects Jan Feb Mär Apr Mai Jun Jul Aug Sep Okt Nov Dez Aalen University of Applied Science Prof. Dr. Jobst Görne 24

25 Fazit Sales planning is an important task with severe consequences Tier 1 companies can rely on good data obtained from their customers. Very long MRT s require additional use of early indicators to deal with the market movements. Tier 2 companies show much shorter MRT s, but the quality of the planning data is considerably worse Tier 2 companies can make use of average loss of order figures which have to be balanced by new acquired business Using these forecast methods, forecast deviations can be less than 10% Aalen University of Applied Science Prof. Dr. Jobst Görne 25

26 References Backhaus, Klaus; Voeth, Markus (2007): Industriegütermarketing. 8., vollst. neu bearb. Aufl. Vahlen (Vahlens Handbücher der Wirtschafts- und Sozialwissenschaften). München Cravens, Ingram, LaForge, Young (1993): Behavior-based and Outcome-based Salesforce Control Systems, Journal of Marketing, Vol. 57, Oct. 93, Diederich Hinrichsen and Anthony J. Pritchard (2005): Mathematical Systems Theory I - Modelling, State Space Analysis, Stability and Robustness Springer-Verlag, Heidelberg, Germany Franklin et al. (2002): Feedback Control of Dynamic Systems (4 ed.). New Jersey: Prentice Hall Keuper und Hogenschurz, 2007: Sales & Service: Management, Marketing, Promotion und Performance, Gabler-Verlag, Wiesbaden, Germany Kilian (2005): Modern Control Technology. Thompson Delmar Learning Kraft (1999): An empirical investigation of the antecedents of sales force control systems Journal of Marketing, Vol 63, pp VDA (2007): Beschäftigte in der deutschen Automobilindustrie, Wallace and Stahl (2002): Sales Forecasting: A New Approach Apics Bookstore Wilkinson, (2009): Toward a comprehensive framework of sales management within business-to- business marketing organizations, the marketing review, vol9, no.1, pp79-95 Aalen University of Applied Science Prof. Dr. Jobst Görne 26