Development of recommendations for improving logistics processes at the enterprise in an unstable period

​РАЗРАБОТКА РЕКОМЕНДАЦИЙ ПО ПОВЫШЕНИЮ ЭФФЕКТИВНОСТИ ЛОГИСТИКИ ПРЕДПРИЯТИЯ В НЕСТАБИЛЬНЫЙ ПЕРИОД

Кожинова Анастасия Константиновна

студент, департамент логистики и управления цепями поставок, Научно-исследовательский университет «Высшая школа экономики»,

РФ, г. Санкт-Петербург

Маевский Александр Генрихович

научный руководитель, канд. экон. наук, доц., Научно-исследовательский университет «Высшая школа экономики»

РФ, г. Санкт-Петербург

АННОТАЦИЯ

В данной статье был проведен анализ рынка на примере компании X по производству косметики. На основе анализа в пик COVID-19 (2021-2022 гг.) были предложены рекомендации по повышению эффективности логистики, подробно расписано решение задачи, связанной со снабжением. COVID-19 – как один из катализаторов в поиске новых решений предприятием. Аналогично анализ можно провести, взяв за основу иные временные периоды, другие вводные данные.

ABSTRACT

In this article, a market analysis was conducted using the example of cosmetics company X. Based on the analysis at the peak of COVID-19 (2021-2022), recommendations were proposed to improve logistics efficiency, and the solution of the supply-related problem was described in detail. COVID-19 is one of the catalysts in the company's search for new solutions. Similarly, the analysis can be carried out using other time periods and other input data as a basis.

Ключевые слова: период неопределенности; логистика; рынок косметики; менеджмент; производственная логистика; логистика снабжения; эффективность; выбор поставщика; функциональная область; рекомендации.

Keywords: period of uncertainty; logistics; cosmetics market; management; production logistics; supply logistics; efficiency; supplier selection; functional area; recommendations.

Modern times are changing quickly, and businesses need to adjust fast to stay competitive. Each organization should choose a development strategy and create a work plan for the activity in order to adapt on time. Using the instance of a manufacturing cosmetics company X, the article explores the use of logistic procedures during the time following an immense COVID outbreak. The condition of COVID-19 itself is one of the initiators of potential issues.

Prior to thinking about logistical solutions, it is important to pinpoint the enterprise's weak points. EU and US sanctions, the crisis between Russia and Ukraine, and pandemic restrictions have made the cosmetics business unstable. Sales rose 5% between 2011 and 2016, but fell 2.6% between 2018 and 2022. Sales increased to 3.69 billion units in 2021 following the epidemic, but because of the Russian crisis in 2022, volumes fell 7.9% to 3.40 billion units [4]. This resulted from both market saturation and the decline in the nation's population. Following the pandemic and its accompanying limitations, people started to return to their previous lifestyles, old behavioral patterns reappeared, and levels of activity rose. Sales in 2021 totaled 3.69 billion units, the most in the previous five years. Nonetheless, the crisis caused a 7.9% decline in cosmetics sales in Russia as early as 2022, bringing the number down to 3.40 billion units.

Figure 1. Russian cosmetics sales from 2018 until 2022

The production business X discussed in the article made the decision to expand the current plant and construct a new facility in 2020 in an effort to lower the amount of goods imported and to respond more swiftly and nimbly to shifts in market demands. Predictions that the supply of shampoos would rise by an average of 2.9% annually starting in 2018 led to making the choice to invest in upgraded cosmetics production [7].

In fact, according to the GidMarket research [6], in 2018, there was a decrease in the shampoo market volume to 41.9 billion rubles (growth rate 97.7%). In 2019, the volume of the industry amounted to 39.9 billion rubles, a decrease of 2.6% compared to the previous year. 96.3% is the growth rate of the shampoo market in 2020. By the end of 2021, having played back a three-year decline, the market volume amounted to 45.7 billion rubles (growth rate of 119.0%).

Figure 2. Dynamics of the hair shampoo market volume, 2017-2021

The demand for cosmetics made with natural ingredients rose by 31% between April and May of 2022 compared to the same period the previous year. The geopolitical situation had an impact on this, resulting in a reduction in the raw material supply, and organic cosmetics emerged as a key factor in the import substitution trend [5]. Thus, in order to open its first in-house R&D laboratory, the company X committed roughly €1.5 million.

RSHB analysts highlight organic cosmetics as the most popular among consumers, willing to pay more for natural, non-toxic ingredients. Therefore, the company X organization's factory in issue was concentrated on producing organic hair colors, shampoos, balms, deodorants, and shower gels.

The behavior of Russian customers has changed due to the departure of several major international companies, which has shifted demand for indigenous products, particularly organics. The long-term procurement of raw materials and challenges with suppliers as a result of an unsystematic approach might be noted in addition to the price increase that has taken place. The majority of the overall costs are accounted for by logistics expenses. The facts presented leads one to the conclusion that developing a cooperative relationship with suppliers is critical to ensuring the smooth operation of the business.

It is noteworthy that the corporation makes use of a third-party warehouse's capabilities while discussing the problem of storing finished goods. Trucks are used to transport finished goods to this facility. There are 1,400 pallets at a third-party place. At its own disposal, company X has a warehouse of raw materials for the production of cosmetics and a warehouse of components. By applying the chronological average approach [2] it is possible to determine the average stock level over the 2019–2022 period.

,                                                                         (1)

 — average stock level for the entire period j;

 — the rest of the stock for the first period period j;

 — the remaining stock for the last period period j;

 — index of a single accounting period (interval);

 — number of gaps;

   — the rest of the stock for the i-th period period j.

For example, the average stock level for 2019 will be:

Data for all years are presented in Table 1.

Table 1.

Average stock levels for 2019, 2020, 2021 and 2022

According to the table, the average stock level is increasing at a rate of 19%. The company X expanded its revenue and concentrated on producing organic goods.

The dynamics of the stock level's rise and its ratio to the palletomest standard indicator are illustrated in Figure 3.

Figure 3. Stock level in the third-party warehouse

The graph illustrates that the third-party warehouse was nearly full in 2022.

Using a linear development model, Figure 4 shows the expected rise in pallet places in the warehouse.

Figure 4. The forecast for the growth of the number of pallets

By 2024, the average amount of pallet space in the situation under examination is 1,467, meaning that a third-party warehouse will not have enough production capacity to fulfill demand while maintaining the current development pattern.

A summary of the primary tasks to be accomplished and the anticipated outcomes are provided in Table 2.

Table 2.

Tasks to improve the efficiency of the enterprise

Hence, by completing the tasks, the company will optimize the logistical functional areas, lower total costs, and boost profits [3].

Supply is the functional domain of logistics. The first task for the business is to develop a procurement logistics strategy in order to lower supplier expenses. The production of organic products was the main focus of the company's factory in question. A local supplier with consistent raw material supplies was required for the new production line. Reliable enterprises are chosen for evaluation.

Further, the compiled list of suitable suppliers can be analyzed according to the following criteria: reliable supply, order execution time, product quality, reputation in the chosen industry, willingness to negotiate tariffs. Using the chosen parameters, the table distributes information about suppliers. When assessing suppliers, logistics experts are involved.

Table 3.

Information about suppliers according to criteria

For the purpose of selecting the dependence on which the weighting coefficients are computed, the given criteria need to be prioritized. Among the strategies for ranking is the paired comparison method [1]. This method fills in the Ikj matrix (see to Table 4). The following is a definition of the matrix elements:

,                                                                 (2)

Table 4.

The matrix of paired comparisons

It can be seen from Table 4 that the amounts of points that meet the criteria are evenly distributed (7, 6, 5, 4, 3), therefore, the weight coefficients are calculated using the formula:

,                                                                            (3)

 — the number of indicators to be taken into account.

So, for the indicator "reliable supply " (rank 4), the weight is considered:

The weight coefficients for the remaining indicators are calculated in an identical way and presented in Table 5.

Table 5.

Weight coefficients of the criteria depending on the rank

Next, quantitative estimates are calculated in accordance with the principles of qualimetry for the criteria "reliable supply" and "order execution time", see Table 3. When choosing a supplier, a higher level of reliability is preferred, therefore, the value Aij Max, which is the reference, corresponds to a maximum reliability of 0.88 – supplier reliability S4. Having chosen the largest Wimax as the reference value, we will divide the supplier indicators by it and multiply, respectively, by the already calculated weight. Considering the "order execution time" criterion, we select the smallest Aimin as the reference value, the preferred number of delivery days is 3. We divide the Aimin standard by the necessary supplier indicators and multiply by weight, ωi. We add the quantitative estimates obtained by columns. The calculation results are shown in Table 6.

Table 6.

Calculation of quantitative estimates

To determine qualitative estimates, there is a desirability function, the values of which are calculated using the formula:

,                                                      (4)

 — the value of the desirability function;

 — the value of the i-th parameter on the coded scale.

The  value on the coded scale is positioned symmetrically relative to 0. Table 7 shows the boundary and average values of the desirability function.

Table 7.

Evaluation of quality and standard scores on the desirability scale that correspond with it

For example, the S1 supplier's "product quality" indicator was rated by experts as "very good". According to Table 7, this estimate corresponds to an average value of 0.9124. Taking into account the weight, the qualitative estimate is 0.9124×0.2 = 0.1825. The other qualitative estimates are calculated in the same way, Table 8.

Table 8.

Calculation of qualitative estimates

In order to focus on the best supplier with whom it will be possible to conclude a contract, it remains to add up quantitative and qualitative estimates. The highest integral score belongs to S5, Table 9.

Table 9.

Calculation of integral estimates

It was thus demonstrated how to apply analysis in an uncertain situation to go forward with activities that could improve the scenario using the example of one of the functional areas of logistics, specifically supply.

As part of the development of production measures, as noted in Table 2, it is possible to analyze the demand for products within the desired year. In an unstable period, the number of pallets will also decrease and increase. It is possible to determine how many permanent employees are required, whom to keep on staff, and who is better to use only during peak periods. In addition to uncertainty, the cosmetics market is also affected by seasonality, its patterns can already be established.

Turning to the functionality of the distribution area, one of the key decisions that a company faces in the field of warehousing is the choice of an organizational structure for managing its warehouse. The company must determine whether it will have its own warehouse or use the services of a shared warehouse, renting the necessary space. The presented choice between organizing own warehouse and using a common one to place stocks is a typical "make or buy" decision. Moreover, even when the decision to "make or buy" is made, the company needs to continue the analysis, having calculated all the risks, for example:

• rental expenses might be decreased by employing its own warehouse to hold finished goods (+);
• the company will have more control over the management of warehouse operations, company X will have direct access to its goods (+);
• using own warehouse will provide more reliable protection of business and customer data (+);
• the company may incur considerable additional costs, it depends on the calculated payback period (-);
• managing own warehouse will require a lot of time and effort (-);
• there may be a need for quality control, safety and other aspects, which may present technical and operational difficulties (-).

References:

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3. Christopher, M. Logistics and supply chain management. - 2004. - 325 p.
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