For the last 10 weeks, I have actively been engaged in testing and evaluating the SCM Globe Simulation tool. The experience at SCM Globe simulation has been immensely vast as it encompassed the major workings of the simulating tool in supply chain management. I was able to have an in-depth analysis of the various features of the SCM Globe Simulator, the simulation outcomes & comprehension, user-friendliness, challenges, benefits, drawbacks and others aspects of the SCM Globe simulation . The outcome of the testing and evaluation results for the ten weeks will be discussed in this paper with a view to providing the recommendations on the SCM Globe simulation tool. As a professional tools evaluator, being at the SCM Globe simulation tool was an experience to reckon with as it required utmost zeal and meticulousness .In this respect, I had to be vigilant in the evaluation to ensure that I never missed any aspect of it. Nevertheless, the staff ensured an enabling environment for carrying out the evaluation and was willing to answer all the questions that I asked. They also guided me through the SCM Globe Simulation tool which proved vital to the evaluation.
Below is a List of the weekly testing and evaluation at SCM Globe:
Week 1: Overview of the tool, Summarize Initial Thoughts
Week 2: Begin testing and evaluation of the tool, Summarize Thoughts
Week 3: Outline the features
Week 4: Evaluate user-friendliness
Week 5: Simulation outcomes & comprehension
Week 6: Challenges
Week 8: Benefits
Week 9: Drawbacks
Week 10: Recommendations- Enterprise-wide implementation of the tool
Big companies often utilize sophisticated supply chains where up to hundreds of distributors could be involved, the factories could be in tens or in hundreds, the same for warehouses and transporters while the suppliers could be up to thousands. With such massive transactions, it is practically impossible for mind of a human being to have a full comprehension of the system and make predictions regarding such a sophisticated system. At this point, the simulation tool such as the SCM Globe Simulation tool comes in to offer the way out in incorporating all the data and the changing aspects in a sophisticated supply chain into a model generated from a computer to inform the management decisions.
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The SCM Globe simulation tool uses the Google Maps to present a real world experience in depicting the supply chain. The model has four entities namely; products, facilities, vehicles and routes through which any supply chain can be simulated. The tool enables the creation of a supply chain that delivers the desired outcome through making changes in the elements contained in the entities to ensure optimization. Outlining the tool in week two resulted in establishing the optimization feature in the SCM Globe simulation tool. The optimization feature entails finding the ideal guidelines of operation that ensure the realization of the optimal results of an objective. I established the interplay of minimizing risks and costs to yield maximum profits. Similarly, I established that other conditions in operating the supply chain could be optimized such as the level of inventory, maintenance expenditure as well as the location and distribution of warehouses. All these operating conditions proved crucial in determining the desired outcome.
The decision analysis feature came in handy to present a quantitative view of making a certain decision such as building a new facility of production or changing the location of the new facility geographically. The tool depicted the implications of such decisions on the entire supply chain (Terzi & Cavalieri, 2004). The other feature was diagnostic evaluation which was conducted to determine the efficiency of the tool in establishing the cause of a certain problem in the supply chain. In my case, I used the problem of having the inventory running out of stock and conducted a simulation to establish the cause. The tool gave a graphical representation of the various factors that were causing the running out of inventory. The other feature was the risk management feature that enables corporations to prepare mitigation measures for negative uncertainties such as worker strikes, disasters resulting in destruction of crucial facilities, political unrest in a nation supplying the essential raw materials among others. With this feature, companies can design mitigation strategies to reduce the impact of such occurrences. The last feature is the project planning feature. This feature seeks to establish the best way of implementing a project, providing cost minimization, scheduling and decreasing the potential risks.
User-Friendliness
Establishing the features took me to week 4 objectives which were evaluating user-friendliness of the SCM Globe simulation tool. User friendliness entails the ease of using the tool for its intended purpose. From my evaluation, I deemed it user friendly as outlined below:
My interaction with the tool made me to look at some of its aspects regarding usability. After launching the tool, there was documentation on how to go about the process of simulating supply chain management. The documentation was written in clear language that every user can understand. Moreover, the documentation includes all the aspects of the tool from the entities to the navigation of the process to allow an accurate and easy process of modelling and simulating the supply chain of choice. The documentation is in electronic form with videos and electronic documents that contain all the tutorials for a newbie in using the tool.
The tool does not require the user to keep clicking as the features are easily accessible after making a few clicks. As such, it avoids the monotony of keeping on clicking to progress with the simulation process. It avoids the repetition of many confirmation windows and thus enables an expeditious process. In fact, I enjoyed the efficiency of the tool in modelling and simulating various supply chains that I wanted to test. The search interface of the SCM Globe simulation tool is simplified as only four entities are present for the manipulation of the user.
The other aspect regarding the user friendliness of the SCM Globe simulation tool is its aspect of entering data, editing or voiding data. After selecting one of the entities in the supply chain, say products, the tool enabled me to create a product of my own design. After entering the required data, the tool requires selection of the update option to progress. I made my product and later edited the specifications of the product which proved easy even for a newbie. Removing a given product from the supply chain was also easy and fast. However, editing the data in one entity affects the other entities as would apply in real time experience.
In my navigation in the tool’s process flow, I established that the arrangement of the windows, tabs and menus are aligned with the process of supply chain management. This arrangement proved essential in ensuring an easy navigation of the system. Moreover, the arrangement can be customized as per the user’s need. For instance, when I was working on the vehicles, I put them on the first menu to ensure that it flowed with my work flow. Progressively, I found it easy to customize other aspects depending on the stage if the process. From this perspective the tool could be customized for use by any corporation as it easily integrates into the business dynamics.
The aspect of functionality is well worked out to ensure that the major functions of the tool are well presented. From my observation, the employees at the SCM Globe simulation have tailored the tool to ensure that the functions are easily accessible to the user. The menu is less stringent to allow quick navigation and rapid switching between various entities. Similarly, the accessibility is guaranteed after activating or opening a new account in the SCM Globe simulation tool.
Simulation outcomes and comprehension
The major goal set for week five was establishing the simulation outcomes and comprehension. A major aspect of the SCM Globe simulation is that an understanding of the system makes it provide meaningful results. It is essential to recognize that any model will not deliver worthwhile results if it lacks comprehension regarding the system being modelled. As a result, structuring a conceptual model outlining the system proves to be a valuable aspect of the entire process of simulation (Terzi & Cavalieri, 2004). The SCM Globe simulation tool is designed with a superior comprehension of the key factors that determine the performance of the system, to ensure consistently useful results. At the SCM Globe Simulator, the analysis phase is well laid out showing the various interconnected subsystems that outline the key constituents of the system, the interactions between these constituents, and all pertinent mechanism for feedback. I practically went through the conceptual model that guides the workings of the SCM Globe simulation tool and I found it to accurately depict the outcomes.
After simulating my supply chain, the total costs for running each facility came up in the data display window. The names of the facilities appeared with the operation costs indicated on the right side of the facility name in bold. Additionally, the amount of products held at the facility as well as the display of the products held by the facility on a day to day basis appeared on the same tab (SCM Globe, 2016). The same case applied for the products, the vehicles and the console tab. Specifically, the products tab presents the names of the facilities, the names of the products, the quantities of products held in the facilities as well as the value of the products held in the facilities. On the other hand, the vehicles tab presented the names assigned to various vehicles, the total costs of operation cumulatively presented, the carbon emissions from the vehicles in the cumulative, the destination of the various vehicles and the route through which the vehicles traversed (SCM Globe, 2016). The console tab presents a breakdown of the data for every product and every facility. Since I needed further analysis of the data, I utilized the export function that occurred after stopping the simulation to have the data in Excel format.
From the aforementioned tabs, the outcomes of the simulation were deduced. From the simulation of my supply chain model, I was able to see the movement of inventory across the various facilities. I could identify the facilities that had a buildup of inventory as well as the facilities that run out of inventory. Moreover, the capacity of the storage facilities such as warehouses was brought out and I could see the facilities that needed an enhancement in their storage capacity and the facilities that could perform optimally with a reduction in their storage capacity. On the other hand, the outcomes of the vehicles showed the variation of transportation costs that depended on the frequency if deliveries and the vehicles used to make the deliveries. By clicking in the display tab, I had both the numeric and graphic presentations of the data from the simulation.
In comprehension of the outcomes, I paid close attention to certain aspects of the graphical presentations on the simulation data. From the various simulations carried out, I understood that graphical representations of lines sloping downwards indicate that the supply of the product is meeting the demand at the facility level. The opposite held if the lines were sloping upwards which indicated that the product being delivered or produced exceeded the demand on facility. A different display was that of lines in the form of saw teeth that indicated that deliveries happened for every few days. An in-depth analysis of these lines indicates that once the deliveries are made, the supply shoots upwards but the daily demand at the facility level depletes the supply resulting in a decline. Further, a display of patterns similar to the stair steps indicates the pattern of deliveries and their impact in the safety stock ( Sivanandam et al., 2005) . In this regard, the downward slope on the pattern indicates the deliveries missed on occasional basis eventually decreasing the tock kept for safety purposes. On the contrary, the upward slope on the pattern indicates the additional deliveries that cause too much increment on the safety stock.
On the other hand, a graphical representation of data showing a relatively flat line or a completely flat line indicates a match in the delivered product and the demand for the product. Hence, as the line becomes more flat, the interpretation was a better match between supply and demand (SCM Globe, 2016). In this respect, I tried to ensure that the product held in each of the facilities was minimized, resulting in a flat line. To ensure that enough inventory was available to meet the days when deliveries were missed, the line representing the product and the line representing the level of inventory were moved downwards. This was crucial in avoiding massive inventory in facilities as well as in preventing stock from running out.
Challenges
In week 6, my main goal was to establish the major challenges associated with the SCM Global simulation tool. Despite the various user friendly features presented in the SCM Globe simulation tool, some challenges presented in my evaluation which was my week six goal. As I evaluated the challenges I found that the first requirement of the SCM Globe simulation tool is the user’s data. As a user, the accuracy of the data that I entered determined the usefulness of the results (Terzi & Cavalieri, 2004). Although the model is well outlined, the data used is often of the user’s own making hence the inferences from it cannot be used for development of new concepts. Nevertheless, with accurate data, the results of the simulation emphasize the outcomes that a corporation is likely to realize.
I also established challenges with optimization where varying factors that affected demand limited the extent of optimization. Although the user can make alterations to the demand profile, I found that the situation is quite different in real world. As such, a more dynamic approach with a manual review is needed to verify the demand trends especially on a daily basis.
A different challenge encountered is that the system does not provide the means of arriving to the results of optimization. It only accepts the data and the figures and does the rest of the calculations without involving the user. In my case, all the system did was providing the results and possible solutions but the actual process of arriving at the solution remains a mystery. Due to the complexity of the system, the operator remains in dark regarding the calculations as the entire system works as a single unit. However, the operator is still able to see the effects of varying the various factors of production as well as other variables in the supply chain. Again, this effectiveness depends on the accuracy of the data entered by the operator. The other challenge established is regarding the predictability of risks, especially natural disasters. For instance, the system has no way of predicting that floods are likely to occur and result in destruction of facilities and other factors of production. Moreover, it cannot predict when the technology used will be obsolete or policies that can result in the closure of the business operations.
Benefits
After outlining the challenges, I identified the benefits of the SCM Globe simulation tool through my real time evaluation as my week eight goal. To begin with, I saw the simplicity of integrating an entire supply chain into the system and simply simulating. With the correct data, any company can take advantage of the simplified approach to forecast their operations. Additionally, it is well known that for companies to conduct physical experimentations massive costs are involved but still technical challenges affect the experimentations. For the various simulations that I conducted, the results proved realistic and applicable to real world experience. I consider companies in this era quite lucky to have such a tool that models large scale supply chains with an in-depth analysis. Progressively, I evaluated the results obtained by various companies after agreeing to share and they were convincing. They all agreed that simulation appears to be the only remedy to making models and analyzing the performance in large businesses for which experimentation would be too expensive (Terzi & Cavalieri, 2004). From their own opinions, the simulation enabled the accomplishment of dual purposes. From the one hand, companies could make designs of their supply chains and model them followed by simulation that gave the likely outcomes. On the other hand, the assessment of the management of the supply chain prior to execution enabled the system to implement a what-if analysis to inform the best course of action or the most beneficial decision for the management to make.
Working with the SCM Globe simulation tool the classification of the decisions by management fell into two categories; the operational decisions for short term objectives and structural decisions for the long-term objectives. Due to the multifaceted simulation of the flow of materials was done with due considerations taken on random occurrences that may affect operations. I obtained the optimal level of performance in various sophisticated supply environments and the multi-agent systems (MAS) proved useful. Through the multi-agent systems, I managed to model various agents in a company’s supply chain network who occupied significant positions in the entire company. The reason for this move was that at times, the management may independently make decisions affecting the entire system, hence the need to incorporate the multi-agent systems. I ensured that various agents represented diverse objects presenting along the supply chain network of the company. For instance, the distributions supply chain worked well with multi-agent systems to guide the context of manufacturing control.
The SCM Globe simulation tool allowed for modifications on the assumptions made in the operations subject to impending conditions. It depicted the correct practice where managers in the supply chain make decisions for the future with the basis on the available information. As I simulated a supply chain model, the costs of transportations seemed high and had an inclination to significantly increase in the future. One of the ways that the tool provided in solving the problem was in seeking suppliers within the geographical location of the facilities. Typically, this would be practical in the real world as transportation costs have a direct link with the distance from the facilities to the suppliers ( Mahendrawathi & Pujawan, 2007) . Thus, the simulation tool specified the possible responses that managers make to the indefinite aspects of the supply chain as well as the implications of these changes to the overall system afterwards. Thus, the simulation provided the mechanism to make predictions on the complete range of likely future outcomes, provided an analysis of the results to inform the next step in the way forward.
The sales and inventory were controllable in the simulation tool but various uncertainties presented along the course. For a fact, the uncertainties are a common feature in every sophisticated supply chain system. I practically engaged some uncertainties such as the variations in demand given different sets of circumstances. In this case, I reduced the budgets for sales and promotions to project the possible effects of such a move on demand. The results proved that product awareness remained constant, with negligible gains and declines. However, the accessibility to the product reduced as the sales budget was reduced. Other uncertainties looked into were the changes in the costs of transportation, changes in the distribution line with a significant proportion of the distributors opting to leave the business as well as the effects of changes in currency due to inflation.
I also looked into various uncertainties along the intervals of production and supply activities, the consequences of scaling up the duration of such operations and other pertinent uncertainties in the supply chain. From this, the SCM Globe simulation tool enabled the incorporation of various uncertainties concerning the overall impacts of undertaking various activities as well as the occurrence of unprecedented events such as the exit of major distributors from the business. These simulations provided important alerts to the individual planning the supply chain regarding various weaknesses in the plan and offered relevant guidance towards enhancing the supply chain strategy.
The simulation provided direct insights that present in the real world experience. The system is well structured to ensure that uncertainties cannot be eliminated including reduction in the prices of the products. Therefore, the SCM Globe simulation tool enabled me to interact with various uncertainties and establish relevant information. For instance, I had the insight that if the uncertainties are unambiguously well-thought out during the planning phase of the supply chain, the company is in a position to lay down strategies and mechanisms as contingency plans that will reduce the negative impacts of the identified uncertainties in case they occur.
Draw backs
As with every system, drawbacks are inevitable in the SCM Globe simulation tool which was the major focus of my week nine goal. From my interaction with the staff at SCM Globe Simulator, I established that it costs them much time in computing to ensure continuous progress in the system. Every company willing to utilize the tool must have well prepared staff to spend time in the SCM Globe simulation tool. On the other hand, the tool provides the various ways of dealing with hurdles along the supply chain but does not provide the actual solutions ( Sivanandam et al., 2005). At such a point, I used various ways presented by the tool to try and solve some of the problems along the supply chain. Interestingly, some of the ways of solving the problem worked while other created even more problems. Therefore, I had to be prudent in evaluating the likely outcome of each proposed method of solving the problem in the supply chain.
On trying out the various solutions presented, I found out that the system is to an extent based on trial and error method. In other words, the ways of solving the problems have no guarantee to work in the desired manner. I fact, making repeated simulations showed different solutions each time which makes it difficult to ensure the level of precision in the SCM Globe simulation tool. Similarly, the process required continuous editing of the values to come up with the optimal values in the products, the facilities and the vehicles. In my case, one of the facilities had losses and I had to review different values in other parameters to optimize the entire system. I had to analyze the reports generated from the supply chain model to determine the various values that needed changes to realize the optimal results. As a result, I progressively made changes to the facilities, the vehicles and the routes and made simulations to see if the desired improvements were realized. Since changing the entities created other problems, I conducted several simulations before arriving at the desired result.
Recommendations
The recommendations regarding the implementation of the SCM Globe simulation tool was the week ten goal where I had to review the important aspects of the tool. Firstly, the tool demonstrated the capability to openly integrate variations and uncertainties into its analysis reports. Notably, the presence of uncertainties and variations affect the process of simulating the behavior of the supply chain system in the future such as variations of demand on seasonal basis, changes in prices of raw materials and so on. As such, the Simulation tool demonstrated the capacity to make representations of the uncertainties in the system dynamics which yielded simulations addressing the potential uncertainties.
Similarly, the simulation tool showed the unplanned distinct events in a way that accounted for the probability of happening, how sever the event would be as well as the potential consequences of such events. This capability proved critical in projecting the robustness, the flexibility and the general performance of the supply chain. Additionally, mitigation plans are only set and evaluated after the risks have been determined and their likelihood of occurrence in the future. With these capabilities, the SCM Globe simulation tool proved useful for evaluating the supply chain and making the right decisions to ensure optimization. Thus, my recommendation is that the management should fund enterprise-wide implementation of the tool. Other industries are increasingly adopting the tool for its real world simulation in guiding decision making on the operational decisions for short term objectives and structural decisions for the long-term objectives. The drawbacks were few and can only be improved as time goes by and hence should not be a limiting factor to implementing the tool. Evidently, the tool costs much time in computing to ensure continuous progress in the system. Like every other company willing to utilize the tool, ACME Industries has well prepared staff to spend time in the SCM Globe simulation tool to ensure its implementation.
References;
Mahendrawathi, E., & Pujawan, I. N. (2007). Principles of Simulation Modelling for International Supply Networks.
SCM Globe. (2016). Analyzing simulation data . Retrieved on august 4, 2017 http://blog.scmglobe.com/?page_id=972
Sivanandam, S. P., Srinivasan, R., & Karimi, I. A. (2005). A novel framework and tool for dynamic simulation of Supply Chains .
Terzi, S., & Cavalieri, S. (2004). Simulation in the supply chain context: a survey. Computers in industry , 53 (1), 3-16.
