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Service productivity measures / evaluation techniques/ measurement challenges

Service productivity measures / evaluation techniques/ measurement challenges. :CASE OF SOFTWARE INDUSTRY. Abide COŞKUN Murat Umut İZER Sarp KOHEN. Outline. Introduction Service Productivity Software Productivity Conclusion. What is Productivity?.

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Service productivity measures / evaluation techniques/ measurement challenges

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  1. Service productivity measures / evaluation techniques/ measurement challenges :CASE OF SOFTWARE INDUSTRY Abide COŞKUN Murat Umut İZER Sarp KOHEN

  2. Outline • Introduction • Service Productivity • Software Productivity • Conclusion

  3. What is Productivity? • Productivity shows whether the activity of an organization is efficient and effective. • But simply it is defined as Output over Input Output Input Productivity =

  4. What is Productivity? • Productivity measures express relationships between the outcomes or outputs of service processes and the resources or inputs required to operate them (McLaughlin and Coffey, 1990). • Input Resources spent to generate the output (ex. Effort) • Output The Value delivered

  5. What is Productivity? • There are many different productivity measures. • The choice between them depends on the purpose of productivity measurement and on the availability of input and output

  6. What is Productivity?

  7. Productivity Measurement • Nordhaus explained the sectors that can have well-measured outputs as: • Agriculture, forestry, and fishing • Mining • Manufacturing • Transportation and PublicUtilities • Wholesale trade • Retail trade

  8. Productivity Measurement • Productivity measurement is difficult in some sectors because outputs and inputs are typically quite diverse and are often themselves difficult to measure (Nordhaus, 2001). • Construction • Real estate • Finance • Government • Services

  9. Service and Software Productivity • Productivity in the service sector was not analyzed before the end of the twentieth century, while productivity in manufacturing has been analyzed for more than two hundred years (Rutkauskas, Paulavicien, 2005). • Since input and output of service sector productivity consist not only of quantitative elements but also qualitative, measuring service productivity is difficult.

  10. Service and Software Productivity • Anselmo and Ledgard (2002) state that software is the most important industry among others. • Whileit is noticed that software productivity is declining more rapidly than other industries (Groth, 2004).

  11. PRODUCTIVITY IN SERVICE SECTOR

  12. The U.S.Bureau of Labor Statistics (BLS) • 173 - industry titles • 39 - the broad service, or nongoods, sector

  13. ProductivityRatio Output Input Productivity =

  14. Service ProductivityRatio Service Productivity = Quantity and Quality of Output Quantity and Quality Input

  15. Quantityaspects of service productivity Inputs • Labor • Capital • Rawmaterial Output • Service volume

  16. Qualityaspects of service productivity Inputs • Tangibleelements • Intangibleelements Output • Customerperceivedquality

  17. Measurereflection • changes in technology • scale of production • educational levels of workers • managerial techniques

  18. Challenges Whatmakesmeasuring service productivityso hard? thenature of service

  19. IHIP-criteria • Intangibility - incapable of being perceived • Heterogeneity - non-standardized • Inseparability - consumed at the point of production • Perishability – transitory nature

  20. Measurement Outputs for Service Industries Transportation • the movement of goods • passengers over distance • labor input – ex. trucking, air transportation, and bus carriers Trade • gross sales • labor cost • employee hour Communication • number of calls (or call minutes) • number of access (main) lines • revenues • labor hours • number of pieces of mail Retail banking • numbers of transactions and deposit • loan accounts revenues

  21. Measurement Outputs for Service Industries Real Estate • realestate loans. the number of residential mortgage loans the number of construction loans the number of commercial mortgage loans Business and personal services • number of calls (or call minutes) • number of access (main) lines • revenues • labor hours • number of pieces of mail

  22. Brinkerhoff & Dressler’s 7 Steps of Measurement 1. Mission Statement Write a mission statement for the unit that identifies the major goals and customer of the unit.

  23. Brinkerhoff & Dressler’s 7 Steps of Measurement 2. Expectations Expectation must be clearly identified and explaining quality needs.

  24. Brinkerhoff & Dressler’s 7 Steps of Measurement 3. KeyOutputs Identify outputs that are important to the unit’s mission.

  25. Brinkerhoff & Dressler’s 7 Steps of Measurement 4. Major Functions Identify and describe the major functions of the unit.

  26. Brinkerhoff & Dressler’s 7 Steps of Measurement 5. Output Measurement Selection Construct measurement techniques for one or more key outputs.

  27. Brinkerhoff & Dressler’s 7 Steps of Measurement 6. Input Measurement Selection Construct measurement techniques for one or more key inputs.

  28. Brinkerhoff & Dressler’s 7 Steps of Measurement 7. Index Construction Construct one or more productivity measures to incorporate the output and input measures.

  29. PRODUCTIVITY IN SOFTWARE INDUSTRY

  30. The Software Industry • Introduction of the computer technology from the 1960s • Software industry consists of theactivities: • Development, • Maintenance, • Production • Softwareservices (documentation, support and training)

  31. The Software Industry • Personalcomputersbecamewidespread in themid 1970s • Theneedforoperatingsystemsand software • MS-DOS • Introduction of workstationsandservers • Theneedforenterprise software • Size andcomplexity of software projectsincreasedrapidly (Groth, 2003)

  32. Productivity of the Software IndustryAmongOthers Annualproductivitygrowthratesforindustryfrom 1998 to 2003 (Groth, 2003)

  33. WhytoMeasure Software Productivity? • Tocontrolandimprovetheperformance of software development • Benchmarks • Time to market andspeed of delivery is moreimportanteconomically • Reliableandconsistentmeasurement • Trade-offswithspeed of deliveryandquality (Petersen, 2011) (Symons, 2010)

  34. ChainLinkingMeasurement (Symons, 2010)

  35. Challenges of Software Productivity • Problemsdeterminingthe software productivity: • Poordefinition of measures • Unclearroot-causeeffectforfunctionpoints • Lack of combiningmanagerialandtechnicalaspects • Whatrepresentsqualityfortheuser? • Whatrepresentsqualityforthedeveloper? (Scacchi, 1991) (WongandJeffery, 2002)

  36. Challenges of Software Productivity • Why software productivity is a complexprocess? • It is difficulttomeasureregardingtothetraditionaldefinition • It is affectedbylots of factors, some of themaredifficulttomeasure • Interactionbetweenthesefactors • (It is easierto be productivewhiledisregardingquality) (Premraj et al., 2005)

  37. Challenges of Software Productivity Two different programs with exactly the same functionality (Premraj et al., 2005)

  38. Challenges of Software Productivity • Metrics don’t work properly increasing complexity of the software • No trend data forproductivity • Thereason of decliningproductivity: • No industrywidestandarddefinition • Increasingcompexity of software applications • Needformoreformalizedprocesses (Symons, 2010) (Groth, 2004)

  39. LowProductivity (Jeet et al., 2011)

  40. Challenges of Software Evaluation • No consensus on generic software evaluation criteria • A framework must be developed to help decision makers • Selectionandtheevalutation of software packagesbeingmorecomplex • Largenumber of software packages • Incompabilitiesbetween hardware and software packages • Lack of technicalskills of decisionmakers • Ongoingimprovements in IT (Jadhav et al., 2008) (Jadhav et al., 2011)

  41. Modelsfor Software Evaluation (Petersen, 2011)

  42. Modelsfor Software Evaluation (Hernandez-Lopez et al., 2010)

  43. Decisions of Software Evaluation • Keep or change, • Make or buy, • Commercial product evaluation, • Tender evaluation, • Software certification, • Software process evaluation, • Software system design selection (Stamelos et al., 2003)

  44. Software EvaluationCriteria (Jadhav et al., 2011)

  45. DecisionHierarchyfor Software Evaluation (Jadhav et al., 2011)

  46. Software MeasurementProcess (Farooq et al., 2011)

  47. In Conclusion • The improvement in software productivity cannot be predicted without measuring it likewise the service sector • The measures of a software product such as functionality, complexity or quality differ from service sector in terms of intangibility, heterogeneity, inseparability and perishability.

  48. Thank You For Listening =)

  49. MIS 518 SELECTED TOPICS Abide COŞKUN Murat Umut İZER Sarp M. KOHEN

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