Skip to main content

Demand Management Model Based on Quantitative Forecasting Methods and Continuous Improvement to Increase Production Planning Efficiencies of SMEs Bakeries

  • Conference paper
  • First Online:
Intelligent Human Systems Integration 2020 (IHSI 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1131))

Included in the following conference series:

  • 4704 Accesses

Abstract

In the last quarter of 2018, the manufacturing sector grew 11.4%, of which 19.6% was accounted for by the food industry. However, one of the main problems faced by micro and small companies is poor management, since many of these businesses plan based on experience. In addition, inaccurate demand forecasting generates losses for these organizations due to overproduction or understocking. While the former triggers losses from elevated operating costs, the latter leads to loss of revenue and unsatisfied customers and compromises future demand rates. Therefore, a demand management model was designed to provide accurate and relevant information, which may improve production planning based on the continuous improvement approach. The model increased the planning from 91.2% to 96.2% in a micro business dedicated to the production and sale of bread.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Mohamed, A.B., Mohd, T.T., Mustafa, O.: Developing cash waqf model as an alternative source of financing for micro enterprises in Malaysia. J. Isl. Acc. Bus. Res. 7, 254–256 (2016)

    Article  Google Scholar 

  2. Avolio, B.: Factors constraining growth in micro and small peruvian businesses. J. PUCP 22, 70–80 (2011)

    Google Scholar 

  3. Huber, J., Gossmann, A., Stuckenschmidt, H.: Cluster-based hierarchical demand forecasting for perishable goods. Exp. Syst. Appl. 76, 140–151 (2017)

    Article  Google Scholar 

  4. Abdul, K.: Demand forecasting for strategic resource planning. In: Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management, USA, pp. 23–25 (2016)

    Google Scholar 

  5. Ren, S.: A comparative study on fashion demand forecasting models with multiple sources of uncertainty. Ann. Oper. Res. 257, 335–355 (2017)

    Article  MathSciNet  Google Scholar 

  6. Rexhausen, D., Pibernik, R.: Customerfacing supply chain practices: the impact of demand and distribution management on supply chain success. J. Oper. Manag 30, 269–281 (2012)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Carlos Raymundo-Ibañez .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Contreras-Choccata, D., Sotelo-Raffo, J., Raymundo-Ibañez, C., Rivera, L. (2020). Demand Management Model Based on Quantitative Forecasting Methods and Continuous Improvement to Increase Production Planning Efficiencies of SMEs Bakeries. In: Ahram, T., Karwowski, W., Vergnano, A., Leali, F., Taiar, R. (eds) Intelligent Human Systems Integration 2020. IHSI 2020. Advances in Intelligent Systems and Computing, vol 1131. Springer, Cham. https://doi.org/10.1007/978-3-030-39512-4_116

Download citation

Publish with us

Policies and ethics