Economics for Engineering Prof. Andrea Sianesi academical year 2008/2009

1. Economics for Engineering Prof. Andrea Sianesiacademical year 2008/2009 Performance Measurement

2. Performance measurement objective • To take the right decisions: • Perceive the signals regarding results, company status, environmental variables and customer requirements; • Improve the quality and the timeliness of decisions; • To learn: • To understand what is wrong is NECESSARY to know what has been done; • To motivate: • Share the actual results; • Measure the result of everyone; • Incentive / discourage employees (e.g. MBO) • WE CAN NOT IMPROVE WHAT WE CAN NOT MEASURE

3. The “distinctions” • Distinguish between performances and operative conditions: • Performances are the result (measured against a multi-dimensional scale) of the logistic and productive process; • Operative conditions are the external and internal “context” in which this result is obtained. • They should be both taken into account, but they should not be mixed up. • Examples: • Internal operative condition: machines obsolescence; • External operative condition: exchange rate instability.

4. Synthetically: • External performances = performances directly measurable from outside the production system (e.g. by client) • Internal performances = performances whose measurement is of specific interest of the company, but not of the client. • Operative condition = way of working or state of a process that can influence a certain performance

5. Example Percentage of waste intercepted by quality control = internal performance of interest for the firm Production System Level of machines obsolescence = operative condition Delivery lead time to produce a product with a quality ok = external performance that can be measured by the client

6. The “distinctions” • The level of analysis: • The same concept to measure a certain performance must be specified keeping in mind the level you need to measure SUPPLIERS FIRM CLIENTS ComponentsProduction Assembly Finish Worker A Worker B Worker C

7. Performance measurement system design • The “Uncertainty principle”. • By measuring any dimension inside a complex system like the organization of a company, the measurement process changes the real value of that dimension. • Direct effect. Connected to motivation. • Example: to measure punctuality: • Average delay = many jobs late but of few days; • Number of delays = few jobs that are late but of many days; • Indirect effect. Connected to expectation. • Example: to measure workforce productivity. • Eager behavior; • Distrustful behavior.

8. Performance measurement system design • Performance measurement system requirements: static properties… • Timeliness: • It is the capability to return the information with a short delay, and so this information can be used in the right moment; • Completeness: • It is the capability to measure all the determinants that contribute to the creation of value in a firm; • Oriented to the long period: • It is the capability to offer the right temporal perspective for the evaluation; • Focus on specific responsibilities: • It is the capability to spot the results that could be univocally assigned to a single element.

9. Performance measurement system design • Performance measurement system requirements : • Precision: • It is the capability to discern little changes in the performances and to translate them in little changes in the performance indicator; • Measurability: • It is the capability of an indicator to be measured quantatively and objectively; • … and dynamical properties. • Maintainability: • It is the capability to be adapted to small or big variations of the objective or the measurement methodology. • Cheapness: • It is the capability to have a low cost in terms of primitive data gathering, and their elaboration.

10. Performance framework • The fundamental objective is to evaluate at the same time: EFFECTIVENESS in serving the “client” EFFICIENCY in using the resources To manage industrial production effectively, we need the capability to measure and control the performances of the logistic-production system, as this is the way to reach a high profitability.

11. Performance framework Quality External performances or EFFECTIVENESS Internal Performances or EFFICIENCY Service Cost (Productivity) The framework of the performances of logistic and production systems is well-artculated, multi-obiectives and multi-dimensional.

12. Performance framework More that “Performances” it is fundamental to measure the “components” (or the “determinants”) The general framework SERVICE Effectiveness Area Punctuality pre-sales Assistance Availability post-sales Accuracy FLEXIBILITY Timeliness Customization Project quality Plans flexibility Product flexibility Compliance in field Availability Mix flexibility In house compliance (waste) Volume flexibility (elasticity) QUALITY Materials (direct, indirect) Capital (fixed, circulanting) Workforce (direct, indirect) Machines Efficiency Area PRODUCTIVITY

13. Efficiency (or productivity) performances Workforce Productivity of production resources Plants Materials Productivity Availability and potentiality Stock turnover and covering Warehouses productivity ABC-ABC analysis

14. Productivity measures • Productivity measurements are, generally, expressed by indicators of efficiency such as: • P = Output / Input • These can be measured with reference to a single machine or to a group of machines, to stages of the production process or to the entire production system.

15. Internal performances • The states of a plant (a machine or in general a produtive resource) • T opening time (potentially productive) • TPb time of good production • TPs time of waste production • TS time of setup • TPr time for tests • TG idle time due to breakdown • TM idle time due to maintenance • TMo idle time due to lack of orders • TMm idle time due to lack of materials • TSc strikes • TO organizational causes

16. The reference framework for internal performances time Organizationalcauses (plantcould produce) Ts Total timeperiod Opening calendartime (1) Plantoperating Time POT Realutilizationtime(3) Actual production time (4) Net production time (5) Quality-ok production time (6) T Managerialcauses (plantcould produce) TSc TO Technologicalcauses (plant can’t produce) TMo Notproductiveperiods (producing) TMm TM TG TPr TS TPs TPb

17. Availability • It measures the impact of breakdowns and stoppages on the time when a machine is THEORETICALLY available to be used • Availability can be measure as well with reference to the ACTUAL time of use by subtracting at the numerator the time spent in doing production tests

18. Production potentiality • Ideal production conditions: only one product and standard condition of production rate Theoretical Pt Potentiality Real conditions: mix of many products, different production rates depending on the product that is produced Mix Pmix

19. The potentialities • PT = Specified Potentiality (or nominal) • Pt = Theoretical Potentiality • In multi product situations it is useful to use the “Mix Potentiality” (ratio between the quantities of the different codes that have been produced and the time that is needed to produce them including the setup time)

20. Mix Potentiality • Withreferenceto a specific mix ofproducts, itisdefinedas the averagenumberofunitsthat can beproduced per timeunit. • Pmix = quantityproduced / timerequired

21. Mix potentiality RSi = standard production rate of the generic item i k = reference item (equivalent units base) NP = number of units that it’s possible to produce Pb / Ps = Quality-ok / scrap units produced NP = i [ (RSk/RSi) x (Pbi + Psi) ]

22. If mix potentiality and plant opening time T are known, it is possible to estimate, for a future period, the Stadard Available Capacity (based on the hypothesis that in the future the impact of strikes, tests and other organizational causes is equal to the present one) Standard availablecapacity

23. Productivity measures • To make a diagnosis is, generally, not so useful to aggregate the productivity measures; more useful indications derives from the decomposition of productivity measurements (P) in use (U) and yield () of productive factors. • The output of the process is always the good production that is stocked measured against “standard hours” (i.e. the hours that according to the standard are necessary to produce a specific object, including the setup time) • The input changes according to the productive factors considered (machine or workforce)

24. Productivity measures Production volume (expressed in a certain unit of measurement) Level of use of a certain production factor Productivity= Material Productivity Machine productivity Workforce productivity

25. Productivity measures ACTUAL PRODUCTION TIME USE (U) = OPENING CALENDAR TIME • Machine use

26. Productivity measures ACTUAL PRODUCTION TIME USE (U) = PAID HOURS • Workforce usage

27. Productivitymeasures STD H. “STOCKED” h = • Yield Actual Production in std. hours h = ACTUAL PRODUCTION TIME ACTUAL PRODUCTION TIME Theconceptof standard time is fundamental.

28. Productivity measures

29. O.E.E. – OverallEquipmentEffectiveness OEE = A x P x Q A = Availability

30. O.E.E. – OverallEquipmentEffectiveness OEE = A x P x Q P= Performance

31. O.E.E. – OverallEquipmentEffectiveness OEE = A x P x Q Q = Quality

32. O.E.E. – OverallEquipmentEffectiveness OEE = A x P x Q

33. Service performance measurement – General framework Availability Systems working “to Stock” (MTS) Stock-out persistency Delivery Accuracy and Completeness Service Timeliness Systemsworking “toorder” (MTO, ATO….) Punctuality

34. Service performance measurement – General framework • The aim of service performance measurement is to evaluate the “immaterial” performances connected to clients’ needs and desires satisfaction. Examples: • Timeliness in fulfilling orders • Punctuality of the delivery • Accuracy of the delivery • Post-sales assistance • …

35. Why service is important: example Suppliers OEM Post-salesassist. Product variety Time-to-Market Timeliness Punctuality Flexibility Cost Quality 0 1 2 3 For a sample of firms in the household appliance sector, service performances are as much important as quality and price.

36. General considerations • In a firm service performances measurements should be defined accordingly to what is assumed to be the “service for the client”: • A complete Order or a single Order Line • Acceptable time delays Order xy Client aa Delay in week 38 Order yy Client aa Article 123, 500 pieces Article 123, 500 pieces Week 37 Article 321, 100 pieces Article 321, 100 pieces Week 38

37. The structure of an order ROSSO BIANCHI S.p.A Milan, 25-11-2004 Dear GIALLO VERDI s.r.l. Order n. 548/zz Article aaaa…………….n°3 pieces Article bbbb………. …..n°7 pieces Article cccc ……… …. .n°9 pieces Terms for delivery: . . . . . . . . . . Place of delivery:……………….. Payments terms: . . . . . . . ORDER ROWS or ORDER LINES

38. Service measurements – Accuracy (or Precision) • It evaluates the quality of the process of order preparation. The following indicators are used: • Physical: • N° mistakes in the delivery / N° Orders (Order lines) managed; • N° returns due to delivery mistakes; • Economical: • Cost of the penalty for inaccurate delivery; • Cost of management and accounting activities duplication. • The delivery mistakes can be of packaging, articles, batches, etc…

39. Service measurements – Completeness • It evaluates the reduction in the level of service perceived by customers in terms of splitting of order fulfillment. The following indicators are used: • Physical: • N° of order rows fulfilled with the first delivery / N° total rows; • Average N° of deliveries for each order; • Economical: • Value of order rows fulfilled with the first delivery / Total value of rows; • Cost of fractioned deliveries.

40. Service measurements MTS - Availability • It takes into account, in make to stock systems, the phenomenon of the stock out. • Indicators: • Physical: • N° items in stock-out / N° total items; • N° order filled / N° total orders; • N° order lines filled / N° total order lines; • N° codes filled / N° codes requested; • Economical: • Cost of the lost sale due to the stock out; • Cost of the penalty for delayed delivery.

41. Service measurements – Stock out persistency ( productunavailability) • It measures the “going on of the inefficiency” • Physical: • Average time of delivery of the orders delivered not “off-the-shelf”; • N° periods in stock-out / N° total periods. • We should evaluate both the “actual” stock out and the “potential” stock out, especially in those situations in which it is actually difficult to control the real stock out occurence (e.g. the good is not available on the shelf)

42. The “potential” orders REQUEST FOR SUPPLY (ORDER FOR N ARTICLES) FULLFILLED COMPLETELY FULFILLED IN PART (rows in stockout) “MISSED” ORDER FULLFILLED ORDER COMPLETE ORDER EMISSION ORDER EMITTED FOR THE PART FULLFILLED WITH STOCK • “POTENTIAL” ORDER (FOR WHAT IS LEFT) • n<N “POTENTIAL” ORDER ROWS “NON-RELIABLE” CLIENTS “RELIABLE” CLIENTS • “POTENTIAL” ORDER • N “POTENTIAL” ORDER LINES • “POTENTIAL” ORDER = PART OF THE ORDER EQUAL TO MARKET SHARE (MS) • “POTENTIAL” ORDER LINES=MS*N

43. Service measurements – The concept of lead time • LTI = it is the time that is necessary to perform all the activities inside the factory from the customer order arrival to the moment in which the material is ready to be delivered. Credit Confirmation, Release of Production Order & Acquisition Order Inspectionand finalcontrol Production time • Externalwait: • Queue at the machine • Waitformaterials Storage lead-time

44. Service measurements – The concept of lead time • Also the “production time” isnotentirely “productive”. setup manufacturing wait for lot control

45. Service measures – punctualityand timeliness (DD - DP) Production Lead Time (DD - DP) Non planned delay Date of the order Date of production start Requested date Planned date Actual delivery date TIME (DD - DO) Total Lead Time (DR - DO) Requested Delivery L.T. (DD - DR) Delay TIMELINESS PUNCTUALITY (DP - DR) Planned delay

46. The measure of timeliness • Itmeasures the reactivity of the system, byobserving the distancebetween the date of the emission of the order and the date of the shipment / delivery of the goodsto the client. • Fisici: •  ( Delivery Date – Order date) / N° tot orders •  (Date of full delivery – Oreder date) / N° tot orders • N°ordersfilledwithin x days / N° total orders • N°linesfilledwithin x days / N° total lines

47. The measure of punctuality • It is the distance from the date requested or agreed (depending on the client perspective) • Physical: • Number of orders / number of late order lines (absolute, relative); • Average delay (measured for all the orders, only for those that are late); • Economical: • Penalty cost; • Cost of double administrative and management activities.

48. Delivery punctuality • Taking as reference base the orders whose delivery has been promised in the reference period: ORDERS TO BE DELIVERED in ΔT: ORDERS DELIVERED (and NOT) in ΔT: Delivered in advance 100 Delivered late Not delivered Delivered “on time”

49. Delivery punctualityperformances calculated with respect to the orders to deliver in a certain period # orders delivered “on time” * 100 % orders delivered “on time” = Tot orders to deliver in the period # orders delivered late * 100 % orders delivered late = Tot orders to deliver in the period # orders delivered in advance * 100 % orders delivered in advance = Tot orders to deliver in the period # orders not delivered * 100 % orders not delivered = Tot orders to deliver in the period

50. Delivery punctualityperformances calculated with respect to the orders to deliver in a certain period (# ordersdelivered lateof iunits of time ) * i Σi Average delay of the orders delivered late = # orders delivered late (# orders delivered in advanceof i units of time ) * i Σi Average advance of the orders delivered in advance = # orders delivered in advance