During the execution of some steps of this research, not always the optimal approach was chosen due to scoping of the research and also due to e.g. lack of certain data. Therefore, some limitations along with further recommendations are been formulated for both the scientific and the business world. After this, a reflection on the research project is presented.
7.1 Limitations
Some limitations were observed while conducting this research:
The decision of investigating six different IRIS fluctuating from 1 day to 2 months was a decision based on the author’s estimation that interesting results will accrue if the IRIs were selected in a way that they grow exponentially. Hence, this research’s scope is limited until what happens for IRIs of 1 day to 2 months. Hence, the limitation here is that we don't know how bigger IRIs would influence the supply chain performance of company X. Moreover, the main conclusion was that the IRIs do not have that much of influence on the KPIs: When the IRIs are short (IRIs< 21 days), the influence is not that important. If the inventory is not reviewed for one month or two, (21 days or 42 days) then the KPIs start to decrease faster. Hence, it is still unknown what happens if the IRI is 80 days. On the other hand, bigger IRIs do not seem realistic enough, because for IRIs over which the demand is higher than the target inventories we know for sure stock outs will occur.
Another limitation was encountered while validating the model, when it was realized that some data were missing because not all the inventory management data were reliable. The validation process showed that and it was explained how the problem was encountered and how the validation process changed in order to validate the model with the other data that were available, without using the unreliable data.
An additional limitation lies on the fact that this model does not take into account the various costs, the way that is modeled so far and depending on the inputs that it can have now.
Moreover, the fact that in the current policy there is too much inventory makes it difficult to have strong results regarding the impact of the IRI on supply chain performance. As it has been mentioned, as long as you are in a month the IRIs do not really matter: it is not that important how often the review of the inventory will take place. If the IRIs get longer in relation to what is happening, then the KPIs start to drop quickly. For example, it may be too long to close your eyes and not review the inventory for 2 months. However, in case of too much inventory, it is shown that not many differences can be observed. Hence, a limitation is that too much inventory on the current policy does not allow seeing much of the influence of the IRIs on supply chain metrics.
Another limitation lies on the difference between the inventories scales in the two inventory
replenishment policies. This in practice makes more difficult to compare the inventory KPIs because of the significant difference in the inventory scales. This is not a problem for the service level KPI as it is expressed in percentage. As it has already been stated, the inventory levels in the current policy are significantly higher than those in the Min/Max policy. Hence, we cannot know what would happen if the current policy was used with just less inventory instead of switching to the Min/Max policy.
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7.2 Recommendations for future research
In recommendations for future research, a clear distinction is being made between recommendations for future research from a business perspective, for company X or for other businesses and also from an academic perspective.
7.2.1 Future research from a business perspective
The results of the simulation show that as long as the IRI is less than a month, the KPIs do not decrease significantly. It is after an IRI of one month where service levels and inventory KPIs show a quicker decrease. From a business perspective, this is an important implication since Accenture will implement the “real time” Min/Max policy. The results of this research show that for company X, that is ready to abandon the current policy and implement the Min/Max policy with the help of Accenture, it does not matter when the inventory is being reviewed, as long as we are in a period of one month. If the time interval get bigger than a month, then it matters more as the IRIs seem to influence supply chain performance if they are higher than one month.
Hence, from the perspective of company X, a recommendation would be to estimate if the Min/Max policy that is proposed to be “a real time” policy is indeed beneficial: Based on the results of this research, it could be stated that the Min/Max policy works efficiently with the low levels of inventory that are kept, but still, the review interval of the inventory does not seem to influence the service level and the inventory KPI. Thus, paying for the real time policy implementation, from the IRIs perspective does not seem beneficial enough since during one month period it is not needed to have a real time observation on what is happening to the inventories. The results showed that the influence of the IRIs is not important if the IRIs are less than one month.
Moreover, an additional recommendation would be to manage better the inventories towards the optimal ones using the current policy. Since the “real time” proposition is not that important according to these results, from the IRIs perspective, company X could fix the inventory management processes to first try the implementation of the current (s,S) policy with lower inventories and see how the service levels and the inventory KPIs behave. Thus, the recommendation would be to try the implementation of the current policy but with fewer inventory levels.
7.2.2 Future research from an academic perspective
From an academic perspective, a knowledge gap was tackled as there was not much literature found regarding the impact of the IRIs on supply chain performance. Hence, using the case study that scoped the research on company X’s boundaries, a conceptual model was developed and then was implemented into a simulation model. Therefore, from an academic perspective one of the deliverables of this research is a functioning simulation model. As it has been already discussed, future research could be conducted to expand the model for other supply chains that use the same inventory replenishment policies, even if it regards different kind of companies with different product characteristics. The model is made in a way that the inputs could be altered and has the same research conducted for another company. The dynamics of the model results would be the same as long as the (s,S) and the Min/Max policy are followed by other companies.
Furthermore, one could investigate what happens for other replenishment systems as well. Using the same model it is possible to change some inputs or parts by writing some pieces of code in C# or adapting existent ones. This way, one could conduct experiments using a different inventory replenishment policy.
Moreover, the same model could be used for further research with few alterations: It would be interesting to investigate how higher IRIs influences the supply chain performance. From the
115 simulation results it is shown that IRIs that is less than one month do not influence that much the supply chain metrics. This research investigated IRIs from one day to 2 months. Hence, it would be interesting to see how 80 days IRI would influence the supply chain metric for the two policies that were reviewed.
Additionally, from an academic perspective, it would be interesting to investigate the current policy with fewer inventories, hence to optimize the inventory management of the current policy and change the scales of inventories in this policy. It would be interesting to see how the KPIs behave in this case and how different their behavior would be from the real time “Min/Max” policy.
To conclude, this research was scoped for a specific company; company X, in order to answer to the research question “What are the effects of review intervals on the supply chain performance of company X?” From a scientific perspective, it was not clear how supply chain performance could be influenced by different IRIs. Hence, the author selected a case in order to narrow down the scope of the research. However, after the limitations that were also presented and discussed in the previous subchapter, someone in the future could perform another case study to test this model for another company with different supply chain. Nevertheless, one could go further and perform a more fundamental study and not take just one case of company, but perform a more controlled experiment in which he is going to turn all the variables that have been thoroughly discussed during the implementation of the experiments.
7.3 Reflection
Simulation projects can consume much more time than typically presumed. In fact it has been observed that many simulation projects take at least twice as long as originally estimated (Benneyan, 1994). That also holds for this research that was initiated as a six month MoT graduation project. In the end, the total span of this project turned out to be a little less than a year. In this section the author reflects on the causes of this delay and the lessons learnt throughout the long process.
Moreover, the author realized how complex it is to validate a model. Few interesting challenges occurred during the model validation. The author learned that simulation in a real world context imposes larger challenges than in an educational context. The availability of a large amount of data does not necessarily make it possible to quantify all parameters or does not imply that data are always reliable. In the end, the plan for the validation process was reconsidered and the validation was performed without using the inventory management data that were found to be unreliable. Furthermore, this was the first time for me to execute a project of this size and that planning the obligatory meetings with the graduation committee caused some delay due to agenda issues. After all, in the process of writing my thesis I understood how important time management is and how one can avoid delays when managing his time efficiently.
Looking back, I am satisfied with the choice I made to perform my thesis project within a company instead of at the university. The internship at Accenture and Macomi taught me and gave me a good insight in how a company and an office works, both content wise and socially. Getting the responsibility to deliver results and also getting the freedom to do this in the way and time I preferred, contributed to a great and informative internship.
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