¹Universidad de Valparaíso, School of Nutrition and Dietetics, Chile. Associate Professor. Email: fernando.rojas@uv.cl
²Universidad Adolfo Ibáñez, Faculty of Engineering and Sciences, Chile. Universidad de Valparaíso, Institute of Statistics, Chile. Professor. Email: victorleivasanchez@gmail.com
³Universidade Federal de Rio de Janeiro, School of Business, Brazil. Associate Professor. Email: peter@coppead.ufrj.br
⁴Universidad de Valparaíso, Institute of Statistics, Chile. Universidade Federal de Pernambuco, Department of Statistics, Brazil. Assistant Professor. Email: carolina.marchant.fuentes@gmail.com

We propose a methodology useful for food services, allowing contribution margins to be optimized. This is based on statistical tools, inventory models and financial indicators. To reduce the gap between theory and practice, we apply this methodology to the case study of a Chilean company to show its potential. We conduct a real-world demand data analysis for perishable and non-perishable products in the companys inventory assortment. Then, we use suitable inventory models to optimize the associated costs. We compare the proposed optimized system with the non-optimized system currently employed by the company, using financial indicators.

Key words: Data Analysis, Demand, Distributions, Inventory.

Proponemos una metodología útil para servicios de alimentación, la que permite optimizar sus márgenes de contribución. Ésta se basa en herramientas estadísticas, modelos de inventario e indicadores financieros. Para reducir la brecha entre la teoría y la práctica, la aplicamos a un estudio de casos de una empresa chilena para mostrar su potencial. Realizamos un análisis de datos de demanda del mundo real para productos perecederos y no perecederos del surtido de inventario de esta empresa. Entonces, utilizamos modelos de inventarios adecuados para optimizar los costos asociados. Comparamos el sistema optimizado propuesto y el sistema no optimizado, que es actualmente empleado por la empresa, a través de indicadores financieros.

Palabras clave: análisis de datos, demanda, distribuciones, inventario.

Texto completo disponible en PDF

References

1. Agrawal, M. & Cohen, M. (2001), 'Optimal material control and performance evaluation in an assembly environment with component commonality', Naval Research Logistics 48, 409-429.         [ Links ]

2. Ahmed, S., Castro-Kuriss, C., Flores, E., Leiva, V. & Sanhueza, A. (2010), 'A truncated version of the Birnbaum-Saunders distribution with an application in financial risk', Pakistan Journal of Statistics 26, 293-311.         [ Links ]

3. Barros, M., Leiva, V., Ospina, R. & Tsuyuguchi, A. (2014), 'Goodness-of-fit tests for the Birnbaum-Saunders distribution with censored reliability data', IEEE Transactions on Reliability 63, 543-554.         [ Links ]

4. Barros, M., Paula, G. & Leiva, V. (2009), 'An R implementation for generalized Birnbaum-Saunders distributions', Computational Statistics and Data Analysis 53, 1511-1528.         [ Links ]

5. Ben-Daya, M. & Raouf, A. (1994), 'Inventory models involving lead time as a decision variable', Journal of the Operational Research Society 45, 579-582.         [ Links ]

6. Bhatti, C. (2010), 'The Birnbaum-Saunders autoregressive conditional duration model', Mathematics and Computers in Simulation 80, 2062-2078.         [ Links ]

7. Blankley, A., Khouja, M. & Wiggins, C. (2008), 'An investigation into the effect of full-scale supply chain management software adoptions on inventory balances and turns', Journal of Business Logistics 29, 201-224.         [ Links ]

8. Botter, R. & Fortuin, L. (2000), 'Stocking strategy for service parts: A case study', International Journal of Operations and Production Management 20, 656-674.         [ Links ]

9. Braglia, M., Eaves, A. & Kingsman, B. (2004), 'Forecasting for the ordering and stock-holding of spare parts', Journal of the Operational Research Society 55, 431-437.         [ Links ]

10. Braglia, M., Grassi, A. & Montanari, R. (2004), 'Multi-attribute classification method for spare parts inventory management', Journal of Quality in Maintenance Engineering 10, 55-65.         [ Links ]

11. Burgin, T. (1975), 'The Gamma distribution in inventory control', Operations Research Quarterly 26, 507-525.         [ Links ]

12. Carter, P., Carter, J., Monczka, R., Slaight, T. & Swan, A. (2000), 'The future of purchasing and supply: A ten-year forecast', Journal of Supply Chain Management 36, 14-26.         [ Links ]

13. Castro-Kuriss, C., Kelmansky, D., Leiva, V. & Martinez, E. (2009), 'A new goodness-of-fit test for censored data with an application in monitoring processes', Communications in Statistics: Simulation and Computation 38, 1161-1177.         [ Links ]

14. Castro-Kuriss, C., Kelmansky, D., Leiva, V. & Martinez, E. (2010), 'On a goodness-of-fit test for normality with unknown parameters and type-II censored data', Journal of Applied Statistics 37, 1193-1211.         [ Links ]

15. Castro-Kuriss, C., Leiva, V. & Athayde, E. (2014), 'Graphical tools to assess goodness-of-fit in non-location-scale distributions', Revista Colombiana de Estadística 37, 341-365.         [ Links ]

16. Chiu, Y. (2010), 'Mathematical modelling for determining economic batch size and optimal number of deliveries for EOQ model with quality assurance', Mathematical and Computer Modelling of Dynamical Systems 16, 373-388.         [ Links ]

17. Cobb, B., Rumí, R. & Salmerón, A. (2013), 'Inventory management with lognormal demand per unit time', Computers and Operations Research 40, 1842-1851.         [ Links ]

18. Ferreira, M., Gomes, M. & Leiva, V. (2012), 'On an extreme value version of the Birnbaum-Saunders distribution', REVSTAT - Statistical Journal 10, 181-210.         [ Links ]

19. Fox, E., Gavish, B. & Semple, J. (2012), 'A general approximation to the distribution of count data with applications to inventory modeling', Working Paper 10, 181-210.         [ Links ]

20. Grant, D., Karagianni, C. & Li, M. (2006), 'Forecasting and stock obsolescence in whisky production', International Journal of Logistics Research and Application 9, 319-334.         [ Links ]

21. Harvey, W. (2002), 'And then there were none', Operations Research 50, 217-226.         [ Links ]

22. Hernández-González, C. (2011), 'Methodological proposal for the management of the refulling in the company Astilleros del Oriente', Yearbook of the Faculty of Ecomomical and Business Sciences 2, 53-60.         [ Links ]

23. Hillier, F. & Lieberman, G. (2005), Introduction to Operational Research, McGraw Hill, New York.         [ Links ]

24. Jin, X. & Kawczak, J. (2003), 'Birnbaum-Saunders and lognormal kernel estimators for modelling durations in high frequency financial data', Annals of Economics and Finance 4, 103-124.         [ Links ]

25. Johnson, N., Kotz, S. & Balakrishnan, N. (1994), Continuous Univariate Distributions, Vol. I-II, New York, Wiley.         [ Links ]

26. Keaton, M. (1995), 'Using the gamma distribution to model demand when lead time is random', Journal of Business Logistics 16, 107-131.         [ Links ]

27. Kogan, K. & Tell, H. (2009), 'Production smoothing by balancing capacity utilization and advance orders', Journal of Business Logistics 41, 223-231.         [ Links ]

28. Lau, H. (1989), 'Toward an inventory control system under non-normal demand and lead time uncertainty', Journal of Business Logistics 10, 88-103.         [ Links ]

29. Leiva, V., Athayde, E., Azevedo, C. & Marchant, C. (2011), 'Modeling wind energy flux by a birnbaum-saunders distribution with unknown shift parameter', Journal of Applied Statistics 38, 2819-2838.         [ Links ]

30. Leiva, V., Hernandez, H. & Sanhueza, A. (2008), 'An R package for a general class of inverse Gaussian distributions', Journal of Statistical Software 26, 1-16.         [ Links ]

31. Leiva, V., Marchant, C., Saulo, H., Aslam, M. & Rojas, F. (2014), 'Capability indices for Birnbaum-Saunders processes applied to electronic and food industries', Journal of Applied Statistics 41, 1881-1902.         [ Links ]

32. Leiva, V., Ponce, M., Marchant, C. & Bustos, O. (2012), 'Fatigue statistical distributions useful for modeling diameter and mortality of trees', Revista Colombiana de Estadística 35, 349-367.         [ Links ]

33. Leiva, V., Rojas, E., Galea, M. & Sanhueza, A. (2014), 'Diagnostics in Birnbaum-Saunders accelerated life models with an application to fatigue data', Applied Stochastic Models in Business and Industry 30, 15-131.         [ Links ]

34. Leiva, V., Santos-Neto, M., Cysneiros, F. & Barros, M. (2014), 'Birnbaum-Saunders regression model: a new approach', Statistical Modelling 14, 21-48.         [ Links ]

35. Leiva, V., Saulo, E., Leao, J. & Marchant, C. (2014), 'A family of autoregressive conditional duration models applied to financial data', Computational Statistics and Data Analysis 79, 175-191.         [ Links ]

36. Leiva, V., Soto, G., Cabrera, E. & Cabrera, G. (2011), 'New control charts based on the Birnbaum-Saunders distribution and their implementation', Revista Colombiana de Estadística 34, 147-176.         [ Links ]

37. Lu, Y. & Song, J-S. (2005), 'Order-based cost optimization in assemble to-order systems', Operations Research 53, 151-169.         [ Links ]

38. MINSAL, (2004), Agreement Hygienic for Food Services, Ministry of Health, Santiago, Chile.         [ Links ]

39. Marambio, M., Parker, M. & Benavides, X. (2005), Food and Nutrition Service: Technical Guidelin, Ministry of Health, Santiago, Chile.         [ Links ]

40. Marchant, C., Bertin, K., Leiva, V. & Saulo, G. (2013), 'Generalized Birnbaum-Saunders kernel density estimators and an analysis of financial data', Computational Statistics and Data Analysis 63, 1-15.         [ Links ]

41. Mentzer, J. & Krishnan, R. (1988), 'The effect of the assumption of normality on inventory control/customer service', Journal of Business Logistics 6, 101-120.         [ Links ]

42. Moors, J. & Strijbosch, L. (2002), 'Exact fill rates for (R; s; S) inventory control with gamma distributed demand', Journal of the Operational Research Society 53, 1268-1274.         [ Links ]

43. Morillo, M. (2009), 'Service costs for food and beverage in hostels', Visión Gerencial 2, 304-327.         [ Links ]

44. Nahmias, S. (2001), Production and Operations Analysis, McGraw Hill, New York.         [ Links ]

45. Nicolau, J. (2005), 'Leveraging profit from the fixed-variable cost ratio: The case of new hotels in Spain', Tour Manager 26, 105-111.         [ Links ]

46. Paula, G., Leiva, V., Barros, M. & Liu, S. (2012), 'Robust statistical modeling using the Birnbaum-Saunders-t distribution applied to insurance', Applied Stochastic Models in Business and Industry 28, 16-34.         [ Links ]

47. Ramanathan, R. (2006), 'ABC inventory classification with multiple-criteria using weighted linear optimization', Computers and Operations Research 33, 695-700.         [ Links ]

48. Ramirez, A. (2013), 'A multi-stage almost ideal demand system: The case of beef demand in Colombia', Revista Colombiana de Estadística 36, 23-42.         [ Links ]

49. Sanhueza, A., Leiva, V. & López-Kleine, L. (2011), 'On the Student-t mixture inverse Gaussian model with an application to protein production', Revista Colombiana de Estadística 34, 177-195.         [ Links ]

50. Silver, E., Pyke, D. & Peterson, R. (1998), Inventory Management and Production Planning and Scheduling, Wiley, New York.         [ Links ]

51. Soman, C. (2006), 'Combined make-to-order make-to-stock in a food production system', RInternational Journal of Production Economics 90, 223-235.         [ Links ]

52. Speh, T. & Wagenheim, G. (1978), 'Demand and lead-time uncertainty: The impacts on physical distribution performance and management', Journal of Business Logistics 1, 95-113.         [ Links ]

53. Stasinopoulos, D. & Rigby, R. (2007), 'Generalized additive models for location, scale and shape (GAMLSS)', Journal of Statistical Software 23(7).         [ Links ]

54. Tadikamalla, P. (1981), 'The inverse Gaussian approximation to the lead time demand in inventory control', International Journal of Production Research 19, 213-219.         [ Links ]

55. Vilca, F., Sanhueza, A., Leiva, V. & Christakos, G. (2010), 'An extended Birnbaum-Saunders model and its application in the study of environmental quality in Santiago, Chile', Stochastic Environmental Research and Risk Assessment 24, 771-782.         [ Links ]

56. Villegas, C., Paula, G. & Leiva, V. (2011), 'Birnbaum-Saunders mixed models for censored reliability data analysis', IEEE Transactions on Reliability 60, 748-758.         [ Links ]

57. Wagner, S. & Lindemann, E. (2008), 'A case study-based analysis of spare parts management in the engineering industry', Production Planning and Control 19, 397-407.         [ Links ]

58. Wanke, P. (2008), 'The uniform distribution as a first practical approach to new product inventory management', International Journal of Production Economics 114, 811-819.         [ Links ]

59. Wanke, P. (2009), 'Consolidation effects and inventory portfolios', Transportation Research Part E: Logistics and Transportation Review 45, 107-124.         [ Links ]

60. Wanke, P. (2011), Inventory Management in Supply Chain: Decisions and Quantitative Models, Atlas, Brazil.         [ Links ]

61. Wanke, P. (2012), 'Product, operation, and demand relationships between manufacturers and retailers', Transportation Research Part E: Logistics and Transportation Review 48, 340-354.         [ Links ]

62. Wanke, P., Arkader, R. & Rodrigues, A. (2008), 'A study into the impacts on retail operations performance of key strategic supply chain decisions', International Journal of Simulation and Process Modelling 4, 106-118.         [ Links ]

63. Yajiong, X. (2005), 'ERP implementation failures in China: Case studies with implication for ERP vendors', International Journal of Production Economics 97, 279-295.         [ Links ]

64. Zipkin, P. (2010), Foundation of Inventory Management, McGraw-Hill, New York.         [ Links ]

Este artículo se puede citar en LaTeX utilizando la siguiente referencia bibliográfica de BibTeX: