On the Development of Theory-Informed Operationalised Definitions of Demand Patterns
Lead Research Organisation:
University of Salford
Department Name: Man and Man Sciences Res Institute
Abstract
Different Stock Keeping Units (SKUs) are associated with different demand patterns, which in turn require different methods for forecasting and stock control. Consequently, we need to categorise the various SKUs and apply the most appropriate methods for each particular category. The way we are going to perform this task has obviously tremendous implications in terms of stock and customer satisfaction and, as such, the relevant rules constitute a vital element of every inventory management system. To deal with this problem people tend to classify, rather arbitrarily, the demand patterns (using rules that, based on experience, work well) and then select the forecasting and stock control methods that perform best in each category. Nevertheless, the choice of the most appropriate forecasting and inventory control methods is the very purpose of conducting any categorisation exercise. Therefore, it is more logical to first compare alternative estimation procedures and stock control models for the purpose of identifying their regions of superior performance and then, based on the results, categorise the demand patterns, rather than working the other way around. A procedure like this one is obviously expected to offer better results. In research conducted with John Boylan and John Croston we developed a theoretically coherent categorisation scheme, along the lines discussed above, for forecasting purposes only. However, stock control issues were not addressed and this is what I would like to do in this proposed research. This research area has attracted very limited academic attention over the years. A reason for that may well be the considerable associated complexity. That is, forecasting and stock control have to be viewed as interrelated functions (as they are in practice) rather than stand-alone modules of a wider solution, and this obviously increases the theoretical complexity of the problem. Although some early work has been done on the interaction between forecasting and stock control, a theoretically coherent approach is still required and this is the first proposal to provide it.The main objective of this research is to produce theoretically sound demand categorisation rules for both forecasting and stock control purposes. To conduct such a project, the input from industry practitioners is very important. In this regard, two companies have been selected as project partners. This collaboration will also ensure that the empirical data required for the purposes of this research becomes available. My philosophical stand-point is positivistic in the sense that universally applicable categorisation solutions are sought to be developed. However, due to the complexity of the problem, the research strategy employed cannot be purely deductive. An iterative procedure between theory and data is to be introduced and such an approach will ensure that all important factors are identified.In summary, the proposed research deals with an issue that is worth investigating from both a theoretical and practitioner perspective. Very little work has been conducted in the area of demand categorisation and, from the research to date, it is not clear how managers should classify demand patterns for forecasting and stock control purposes. The importance of this issue has been reported on numerous occasions, and what is agreed upon in the relevant literature is the immediate need to further advance knowledge in this area and empirically assess the relevant issues. The proposed research therefore constitutes a very timely project. The results of such a project will find application in all forecasting and stock control software package manufacturers. Indeed, there is also a natural application to any industrial setting where an in-house developed or bought-in demand classification computerised solution is in place to facilitate inventory management.
People |
ORCID iD |
Argyrios Syntetos (Principal Investigator) |
Publications
Teunter R
(2010)
Determining order-up-to levels under periodic review for compound binomial (intermittent) demand
in European Journal of Operational Research
Lengu D
(2014)
Spare parts management: Linking distributional assumptions to demand classification
in European Journal of Operational Research
Teunter R
(2011)
Intermittent demand: Linking forecasting to inventory obsolescence
in European Journal of Operational Research
Syntetos A
(2009)
Demand categorisation in a European spare parts logistics network
in International Journal of Operations & Production Management
Syntetos A
(2010)
On the variance of intermittent demand estimates
in International Journal of Production Economics
Syntetos A
(2010)
Forecasting and stock control: A study in a wholesaling context
in International Journal of Production Economics
Babaï M
(2009)
Dynamic re-order point inventory control with lead-time uncertainty: analysis and empirical investigation
in International Journal of Production Research
Babaï M
(2009)
Dynamic re-order point inventory control with lead-time uncertainty: analysis and empirical investigation
in International Journal of Production Research
Syntetos A
(2015)
Forecasting intermittent inventory demands: simple parametric methods vs. bootstrapping
in Journal of Business Research
Syntetos A
(2017)
Periodic control of intermittent demand items: theory and empirical analysis
in Journal of the Operational Research Society
Description | This research resulted in new theory informed fully operationalised rules for demand classification in an inventory context. It demonstrated the very tangible benefits that may be achieved (in terms of inventory costs reductions and service level improvements) through the implementation of new robust categorisation algorithms. |
Exploitation Route | Amendments of forecasting, inventory and supply chain software when it comes to slow / intermittent demand items. |
Sectors | Aerospace Defence and Marine Electronics Manufacturing including Industrial Biotechology Retail |
URL | http://www.salford.ac.uk/business-school/research/operations-and-global-logistics-management/on-the-development-of-theory-informed-operationalised-definitions-of-demand-patterns |
Description | The findings of this project have influenced some major changes into the way forecasting and srock control are conducted in an intermittent demand context in real world practices and have motivated a tremendous amount of further scientific research into this area. |
First Year Of Impact | 2008 |
Sector | Aerospace, Defence and Marine,Digital/Communication/Information Technologies (including Software),Manufacturing, including Industrial Biotechology,Retail |
Impact Types | Economic Policy & public services |
Description | Forecasting and Inventory Management: Bridging the Gap |
Amount | £50,000 (GBP) |
Funding ID | EP/F012632/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 08/2007 |
End | 08/2008 |
Description | Brother International Europe Limited |
Organisation | Brother Industries |
Department | Brother International Europe |
Country | United Kingdom |
Sector | Private |
PI Contribution | Enabling the participating organisation to obtain insights into (and amend their solution on): i) demand classification for logistics purposes, ii) forecasting of service parts requirements; iii) the way judgement interacts with statistical decision making in inventory and supply chain management. |
Collaborator Contribution | Data provision, participation in focus group meetings, informal discussions on the development of solutions. |
Impact | A major joint publication in the International Journal of Operations and Production Management. Details are provided under the outputs of this project. |
Start Year | 2006 |
Description | CSC Computer Sciences Ltd |
Organisation | Computer Sciences Corporation (CSC) |
Country | United States |
Sector | Private |
PI Contribution | Offering insights to them into how there may be an improvement in service parts forecasting and stock control. |
Collaborator Contribution | Data provision and insights into how things operate in practice. |
Impact | Although the collaboration with the particular organisation did not continue, the collaboration with the company representative to the project is still active and has been extremely successful. The company representative subsequently moved to BAE and then Tata Consultancy Services ans is one of my close Industry Collaborators to date. |
Start Year | 2006 |