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Activity-based costing or ABC model in logistics

The Activity-based Costing (ABC) model is one of the many approaches to estimate logistics costs. The term was coined in the late 1980s by Robert Cooper and Robert Kaplan in their article titled, “Measure Costs Right: Make the Right Decisions.” ABC model is defined as a management accounting technique which allocates costs to different activities that consume organizational resources thereby identifying the costs per product or service or customer (Themido et al., 2000). Conventionally, logistics costs were determined as a gross figure, but later on, it was realized that such measures usually present a fallacious account of the logistics costs. This is because logistics functions take place in a dynamic environment.

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Understanding the value of logistical cost in a business

Often the efficiency of the logistics function of a business is estimated in terms of value. But there is no concrete definition of the term ‘value’ in logistics (Francis et al., 2014). The need for defining value did not arise in the past because earlier, logistics was considered to be a cost. Since two decades emphasis over recognizing logistics as a value-adding function was made (Rutner and Langley, 2000; Kilibarda, Andrejić and Popović, 2013). Value is created in the logistics when the capabilities of the elements of the supply chain are combined in a way that it leads to the improvement of competitive advantage of all parties (Hammervoll, 2009). Conventionally value in logistics denoted cost efficiency but now variables like mutual learning, customer satisfaction and agility in the supply chain have also gained significance.

Different methods of value measurement in logistics

Measuring logistics performance implies quantification of the current state of logistics and identifying the improvement potentials (Dörnhöfer, Schröder and Günthner, 2016). Like the concept of value, there exist several financial and non-financial value measurement metrics in logistics. Some authors relate value to the timeliness of logistics operations and calculate it by taking the total time taken to complete the logistics process.

Another common value measurement metric in logistics is Customer Value Added (CVA) which denotes the customers’ perception of value-added from logistics. It is measured as the comparison of total costs in relation to the perceived benefits of the customer. Furthermore, the logistics value can also be measured as total revenue generated, profitability, and shareholder value (Kilibarda, Andrejić and Popović, 2013). The selection of a specific performance measurement indicator depends upon multiple factors such as the:

  • type of industry,
  • overall organizational goal and
  • organizational goal of the organization (Dörnhöfer, Schröder and Günthner, 2016).

However, there is no precise value measure in logistics. While financial measures overlook other aspects of value, the measures relating to customer satisfaction and customer value-added are inconsistent in nature because the notion of value may keep changing for the customers over time (Lambert, 2014).

Value metrics Advantages Disadvantages
Customer satisfaction Improves revenues, logistics costs, market share, and customer experience. Too much reliance on customers for making logistics-related decisions, in spite of high costs.
Customer value-added Also leads to higher revenues, profit margins and shareholder value Fails to measure the financial impact of focusing on customer value-added.
Total cost analysis Focus is on costs. Makes it easy for managers to reduce logistics costs. It is more time-consuming as each customer’s evaluation has to be assessed. Does not study logistics costs in a standalone manner. It is also expensive to obtain information from every customer.
Strategic profit model Measures net profit, return on assets and return on net worth. Helps managers make better investment decisions. Does not take into consideration the timing of cash flows.
Shareholder value Values money in terms of time. Considers the risk of investment. It is challenging to implement in areas such as discount rates, projected cash flows, planning etc. due to a missing link between business strategy and shareholder value. Moreover, it is time-consuming, expensive and requires a vast amount of data.

Figure 1: Comparative advantages and disadvantages of value metrics in logistics (Lambert, 2014)

An example of time value in logistics

In February 2018, almost two-thirds of the UK outlets of the renowned global fast-food chain KFC had to close their operations for a day because of their new logistics partner, DHL had delayed the supply of raw material. As the company sells perishable food items, timeliness represents the value in KFC’s logistics system. This not only caused financial damage to the company but also a reputational setback for the brand KFC (Pooley, 2018).

An example of cost-efficiency in logistics

IKEA, the world’s largest retailer of home furnishing operates in over 29 nations. Its reputation precedes with not only its high-quality products but also the affordability. A massive share of this success has been contributed by the company’s well-designed logistics. IKEA focuses on reducing the costs so that its products can be afforded by the masses. To that purpose, IKEA manufactures most of its products from recycled products and uses comparatively lesser material in the production. This not only reduces the inventory of raw materials but also the transportation costs. Furthermore, the integrated supplier network and the selling of unassembled products saves costs. This way IKEA creates value in logistics through cost-cutting.

An overview of different logistical costs

The essence of calculating logistical costs lies in the fact that logistics while creating value is also a cost incurring function. The estimation of costs incurred for the logistics functions is important to enabling better decision-making. But, logistics involves several processes hence the assessment of logistical costs is usually complicated as they are fragmented around several processes (Halinen, 2015). The logistical costs can be fixed and variable or planned and unplanned.

For example; warehouse costs are a planned cost but, due to adverse weather conditions, the business might maintain excess inventory. The additional warehousing and inventory management costs are unplanned costs.

Similarly, the costs incurred on wastages can be divided by:

  • their nature,
  • cost centre,
  • the relationship with other processes and
  • on the basis of volatility (Stępień et al., 2016).

Another recent approach to classify logistics costs includes categorizing the costs on the basis of functional areas of the business processes. This has been depicted through the below diagram (Chukurna, 2016).

Classification of logistical costs by functional areas

Figure 2: Classification of logistical costs by functional areas. (Chukurna, 2016)
Classification of logistical costs by business processes

Figure 3: Classification of logistical costs by business processes (Chukarna, 2016)

Why it is important to balance logistical costs and value?

Businesses need to have a clear perspective on how they define value and what methods to use to estimate the logistical costs. The logistics function can create value for the customers and the business. This can be explained through the example of Tesla Incorporation which is known for its innovative electric cars. Tesla cars are embedded with Artificial Intelligence (AI) and thus considered as a premium name in the technologically-driven car market. In fact, with its high paced innovation ability, Tesla often threatens its competitors to become obsolete soon. But, the company struggles to satiate its target audience due to its:

  • poor logistics functions,
  • poor quality control,
  • the timelines are missed and,
  • the supplier network is narrow and insufficient.

The outcome is that the company often delivers cars with defects thus inviting a refund or exchange. Tesla also misses the production and delivery schedules and ultimately faces customer dissatisfaction (Lambert, 2017; Boudette, 2018; Jurvetson, 2018). Tesla is probably unclear about what value it wants to achieve through its logistics function and is letting its endeavours go in vain.

References

  • Boudette, N. (2018) What Tesla’s ‘Delivery Logistics Hell’ Is Like for Model 3 Buyers, The New York Times.
  • Chukurna, O. P. (2016) ‘NEW APPROACHES TO THE CLASSIFICATION OF LOGISTICS COSTS OF INDUSTRIAL ENTERPRISES IN THE CONDITIONS OF GLOBALIZATION’, Economics: time realities, 3(25), pp. 105–112.
  • Dörnhöfer, M., Schröder, F. and Günthner, W. A. (2016) ‘Logistics performance measurement system for the automotive industry’, Logistics Research. Springer Berlin Heidelberg, 9(1), p. 11. doi: 10.1007/s12159-016-0138-7.
  • Francis, M. et al. (2014) ‘The meaning of “value” in purchasing, logistics and operations management’, International Journal of Production Research, 52(22), pp. 6576–6589. doi: 10.1080/00207543.2014.903349.
  • Halinen, H.-M. (2015) Understanding the Concept of Logistics Cost in Manufacturing.
  • Hammervoll, T. (2009) ‘Value-Creation Logic in Supply Chain Relationships’, Journal of Business-to-Business Marketing.  Taylor & Francis Group , 16(3), pp. 220–241. doi: 10.1080/10517120802484577.
  • Jurvetson, S. (2018) Case study: How Tesla changed the auto industry, Supply Chain Dive.
  • Kilibarda, M. J., Andrejić, M. M. and Popović, V. J. (2013) ‘CREATING AND MEASURING LOGISTICS VALUE’, in 1st Logistics International Conference. Belgrade: LOGIC, pp. 197–202.
  • Lambert, D. M. (2014) ‘Measuring and Selling the Value of Logistics’, The International Journal of Logistics Management, 11(1), pp. 1–17. doi: 10.1108/09574090010806038.
  • Lambert, F. (2017) Tesla’s over-the-air software updates make other vehicles ‘highly vulnerable to obsolescence’, says analyst, Electrek.
  • Pooley, C. R. (2018) KFC runs out of chicken in logistics fiasco, Financial Times.
  • Rutner, S. M. and Langley, C. J. (2000) ‘Logistics Value: Definition, Process and Measurement’, The International Journal of Logistics Management. MCB UP Ltd, 11(2), pp. 73–82. doi: 10.1108/09574090010806173.
  • Stępień, M. et al. (2016) ‘Identification and Measurement of Logistics Cost Parameters in the Company’, Transportation Research Procedia, 16, pp. 490–497. doi: 10.1016/j.trpro.2016.11.046.

The challenges of using forecasting techniques in logistics

Quantitative forecasting techniques refers to the approaches of forecasting used for examining the future trends by analysing the historical data. These forecasting techniques are applied through static methods like time series forecasting and casual forecasting (Spedding & Chan, 2010). The casual forecasting is conducted using simple or multiple regression models. On the other hand, casual forecasting is executed through the use of autoregressive moving average models. In logistics, time series forecasting focuses on analyzing the change in business strategies over a period of time. This forecasting is done using moving average and exponential smoothing which uses mathematical formulas to identify the forthcoming claim of the consumers addressed (Dombi, et al., 2018).

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Maslow’s hierarchy of needs to understand the social characteristics of online customers

Maslow’s hierarchy of needs focuses on the basic requirement and demand for the individuals utilized by the marketers to identify the customer buying pattern (Yan, et al., 2016). The components of the theory or basic needs of the human being comprise:

  • psychological needs,
  • safety and security needs,
  • love and belonging need,
  • self-esteem and,
  • self-actualization needs.
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Supply chain costs management models

Supply chain cost management is the task of controlling the operational cost in order to enhance the profit margin of a business. It involves all activities of logistics and supply chain such as stocking, distribution, processing, packaging, procurement, and handling (Silva, Gonçalves, & Leite, 2014). Supply chain cost management has become very crucial for businesses due to the intensifying market competition (Lai & Cheng, 2016).

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Quantitative and qualitative forecasting techniques in logistics management

Demand forecasting is defined as an approach used for analyzing future demand in comparison to the previous ones. The purpose of demand forecasting is to apply future planning and decision in the domain of finance, logistics, operation and sales. Companies use a qualitative method of forecasting to analyse and evaluate the opinion of experienced staff rather than focusing on numerical values (Dwyer, et al., 2012). These methods are used for predicting any short term or internal forecasting on the basis of summative feedback of departmental heads. On the other hand, quantitative forecasting technique deals with numerical data focus on projection of trends on the basis of historical figures of the business. This method of forecasting is consistent and useful for long term scenario planning of the company.

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A decision framework to mitigate the challenges of international logistics

International logistics requires many different options and requirements to be met in order for a business to operate internationally (Wood, 2012). International logistics is the design and management of a system that controls the flow of materials, through, and out of the international business unit. By taking a systems approach, the firm explicitly recognizes the linkages among the traditionally separate logistics components within and outside the corporation (David, 2003).

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Managing defected product returns in reverse logistics

Reverse logistics is often known as aftermarket logistics or aftermarket supply chain. It is described as the activities that are carried out to recapture the value after the product has been sold (Dekker, et al., 2013). The logistics process of delivering a product from the point of manufacturing to the point of consumption is reversed in reverse logistics.

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