Operation management critical thinking

Introduction

Demand forecasting is one of the most important aspects of the planning process in a firm’s supply chain. The market environment is highly competitive and dynamic and therefore the demand for goods and services keeps on fluctuating. Therefore, business organizations need to find ways of estimating demand to survive the growing levels of competition (Li et al. 2017). There are different methods of demand forecasting which have been studied over the years. There are still a lot of arguments on the best approach which are categorized based on short-term planning. Each of the forecast methods used by different organizations has its advantages and disadvantages and hence organizations must choose the best approach. This report will focus on the case of highline financial service which offers different types of products to the customers. The company carries out its operations based on three categories. This paper seeks to analyze the case of the company and carry out demand forecasting of the three categories for the next four quarters and the best forecasting method.

Demand forecasts for the next 4 quarters

According to the case study, the organization mainly operates its business operations on 3 service categories. To forecast the demand for the different service categories, the first step involves checking the demand for the products over the previous years to come up with an appropriate estimate.

After observing the data of the previous 8 quarters, it is evident that for product A, demand increases in each quarter, for product B, the demand decreases in each quarter while product C is highly unstable. Based on this information and also the trend portrayed by the data, the most appropriate demand forecasting approach that can be used for the company to estimate the demand in the next four quarters includes the na?ve method. ?The na?ve forecasting approach is considered to be a simple but widely used approach unlike the moving average approach which uses several most recent data, the na?ve approach uses a single previous value of time series to forecast the demand (Stevenson and Sum, 2014). The advantage of the Na?ve approach is that it can be used for stable series, with seasonal variations or trends and variations around average.

?The above graph reveals that the demand for category A will increase in the next 4 quarters although it will not be very high. For category B, the demand will decrease over the next 4 quarters whereby the decrease will be much higher while that of category C will fluctuate. A comparison of the three categories shows that the demand will be highest for category C while the demand for A constantly grows. Therefore, the company needs to care of the category B and C.

The forecasting method that was used and why

The na?ve forecast approach was used for all the different categories given that it is the best approach for stable series that might be affected by trends or seasonal variations like in the case of Highline financial companies. Additionally, the na?ve approach would be cost-effective for the company as it is recognized among the most cost-effective demand forecasting approaches and it is also an important basic which is used to develop the more complex demand forecasting approaches (Dweiri et al. 2015). Given that the market environment is highly volatile and characterized by a lot of risks, it is recommended that the company employs demand forecasting approaches that are less expensive and also approaches that will be consistent with the base period. Therefore, the na?ve approach is simpler to apply and also gives the simplest forecast that can be easily understood by the management.? Additionally, by using the na?ve approach, the management of Highline financial services can easily trace back the forecast to the previous year’s outcome which gives ample room for adjustment when estimating the next forecast.

Why only one approach was used for the different products

Na?ve approach was chosen for all the products of the company. This is essential as it would help in coming up with a more constant value to be used as the basis of demand forecasting. Using one approach is preferred because it enables the researcher to easily identify a common structure that can be used for demand forecasting and hence making it easy for the organization to understand and interpret and most importantly make informed decisions (Li et al. 2017). It is also faster and effective which allows the organization to save on cost and also human resources. Additionally, the simple nature of the na?ve approach reduces additional errors which might be obtained from other approaches and also it helps the researcher to easily compare between the margin errors which increases the reliability of the method.

Benefits of a formalized demand forecasting approach

Demand forecasting is a method used to predict the expected demand for an organization’s product shortly or in the long run. Organizations need to use the best demand forecasting method for more accuracy which is crucial for their success and sustainability. If the forecast is more accurate and reliable, then organizations can be able to avoid future losses and also be ready to plan ahead and avoid issues such as inventory problems. For bigger and more complex forecasting issues, economists and researchers propose that organizations should invest more in formalized approaches where a complex set of data is involved (Dweiri et al. 2015).

One of the benefits of using a more formalized approach is that the use of computers can be easier for the management and also quantifying the information. This helps to avoid the case of an individual using personal intuition as it is common in a less formalized approach which tends to interfere with the accuracy and reliability of the information (Stevenson and Sum, 2014).? For example, when an organization has to deal with small forecasting issues, personal bias may be a major hindering factor which may influence the forecast.? As organizations grow larger and also their market share increase, they have to deal with large sets of data and hence it becomes difficult to only rely on less formalized methods because it is hard for an individual to process large amounts of data.

A formalized demand forecasting approach is also essential as it allows organizations e.g. manufacturers to better equip themselves when ordering raw materials and decide whether or not to add shift labour, plan the levels of inventory, and increase or decrease levels of production (Aneiros et al. 2016). Additionally, it helps organizations to accurately determine the profits and costs due to increasing costs of raw materials, taxes and other factors that affect the cost of shifting and cost of raw materials.

When an organization uses a formalized forecasting approach, it is also able to help in trending of the seasonal operations of the firm e.g. whether they should ramp up the production levels to stock inventory or reduce the levels of production due to the dynamic nature of the industry.? More importantly, the formalized approach helps the organization with long-range plans and also makes decisions on new product development.

Another benefit of demand forecasting is that it allows an organization to better track its overall performance. This means that the firm can identify where it went right or wrong and provides the organization with a basis to compare the actual demand in the market against the expectations of the management (Stevenson and Sum, 2014).? In this case, through a formalized approach, a firm can develop charts or graphs that help it identify how far its forecast is from the actual demand and come up with the most appropriate adjustments.

Conclusion

The evaluation of Highline financial services data shows that the company should adopt a na?ve forecast approach which is simple and also more cost effective for the company. The report reveals that with all the available actual data, the company can accurately forecast the outcomes of the coming year but for more accuracy, it would be more vital to have more information and data of the previous years.? However, the na?ve approach also has some drawbacks which the management should take into consideration. For example, it might not produce highly accurate forecasts and it mainly replicates the actual organization’s data. ?The forecast has revealed that category C will have a higher demand compared to others while that of B will be below and A will grow constantly. It is clear that a formalized demand forecasting approach is crucial for the company as it will help the company in decision-making on how to improve on the product will low demand and where to invest its resources.

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References

Aneiros, G., Vilar, J., & Ra?a, P. (2016). Short-term forecast of daily curves of electricity demand and price. International Journal of Electrical Power & Energy Systems, 80, 96-108.

Dweiri, F., Khan, S. A., & Jain, V. (2015). Production planning forecasting method selection in a supply chain: a case study. International Journal of Applied Management Science, 7(1), 38-58.

Li, X., Pan, B., Law, R., & Huang, X. (2017). Forecasting tourism demand with composite search index. Tourism management, 59, 57-66.

Stevenson, W. J., & Sum, C. C. (2014). Operations management. McGraw-Hill Education.