Amortization Practices in the Bidding Models of the Human Resources: A Case of the Strategic Cost Management

Shivakumar Upavasi

Guest Faculty, Dept of PG Studies in Commerce, Skng Govt First Grade College, Gangavathi -583227.

*Corresponding Author E-mail: supavasi12345@gmail.com

ABSTRACT:

The most precious intangible asset in the world is the human resource that can be valued at any cost as per the required services. Nowadays bidding for the skilled human resource is one of the most emerging trends among the Corporate and the Government sectors for recruiting the task force. The IPL cricket players and the Government doctors of Karnataka bidding events added significance for skilled capabilities in deciding the value of human resources. The following article aims to discuss about the amortization practices that can be introduced to depreciate the human asset as the agreement is for a stipulated period of time. Further the applications of the mentioned approach duly support in quoting the price of the human asset after depreciating the proposed value that shall be helpful for the bidding agencies. In view of supporting this approach empirically, “The Learning Curve Theory” of Strategic Cost Management applications is utilized to meet out the assigned objectives.

KEYWORDS: amortization, learning curve, efficiency, intangible asset, player.

INTRODUCTION:

T.P. Wright of Curtiss Buffelo, USA, introduced the theory of learning curve.

When the production quantity of a given item is doubled the cost of that item decreases at a constant rate. Theory of learning curve has been formulated on the basis of this formula.

[The Institute of Chartered Accountants of India]. The applications of the learning curve are commonly used in cost accounting for anticipating costs and the same has been used to introduce amortization practices in the bidding of the human resources. As the concept is new, the objectives are duly supported by the quantitative methods to generate the empirical evidences. Let us first understand the term ‘amortization.

Amortization is the systematic allocation of the depreciable amount of an intangible asset over its useful life.

A) Depreciable amount is the cost of an asset less its residual value

B) Useful life is either: (a) the period of time over which an asset is expected to be used by the enterprise; or (b) the number of production or similar units expected to be obtained from the asset by the enterprise. (Accounting Standard (AS) 26 notes)

OBJECTIVES:

a) To introduce amortization practices in bidding of human assets.

b) To generate empirical evidences in the proposed model by applying the applications of the learning curve.

c) To represent the task graphically in order to pursue the efficiency.

METHODOLOGY:

In the proposed model, an IPL player for ten matches is selected by XYZ agency. For every two matches the remuneration is doubled and the learning curve ratio is seventy five percent decreasing proportionately. The applications of the learning curve are applied to generate empirical evidences. Other than this academic journal, notes and books are referred as the secondary data.

Assumptions of the proposed model:

a) For 10 matches the player selected by the IPL agency XYZ is an all rounder and his efficiency will decrease equally at a rate 75% of the learning curve ratio after every two matches.

b) The remuneration will be doubled after every two matches.

c) The amortization is calculated by multiplying the remuneration paid by the decreasing ratio and cumulative amortization represents the total amount to be subtracted before quoting the value of the bid.

Hypothesis:

As the remuneration increases the efficiency of the player decreases and the cumulative amortization amount represents the total amount to be deducted before quoting the bid value of the player.

Table 1.1 Calculation of the amortization amount

Sl. No of matches after every two consecutive matches	Remuneration doubled after every Two matches	75% decreasing learning curve ratio(efficiency)	Amortization amount	Cumulative amortized amount
Match1 &2	100000	1 (100% X 100%)	100000	-----------
Match 3&4	200000	0.75(100% X75%)	150000	50000
Match 5&6	400000	0.56 (75% X75% )	224000	74000
Match7&8	800000	0.42 ( 56% X 75%)	336000	112000
Match 9&10	1600000	0.32 (42%X 75% )	512000	176000

Findings:

a) The total cumulative amortized amount is the amount to be amortized for the bid value.

(16, 00,000-4, 12,000= 11, 88,000)

b) Now the bid value is 11, 88,000 and the bidder saves 4, 12,000

c) After every two consecutive matches the increase in the remuneration is propionate to decrease in the efficiency.

Limitations:

a) The efficiency of the player cannot be determined and there is no convincing proof either it increases or decreases after every two matches.

b) Standards in units are not established to determine human efficiency.

c) The scope of the research supports the pertaining case only.

The steady state phases of the learning curve effect shows that the efficiency of the player can be utilized until the learning curve effect is zero.

Calculate the amortization amount for 11^th and 12^th match using the learning curve ratio 75%

DISCUSSION:

In the proposed model the depreciation of human assets is introduced but there are no absolute measures that can fix the efficiency rate. As human resource is an intangible asset and profession wise the efficiency may increase or decrease and every case is different from each other. The total bid value is a contract and this is fixed on the previous records of the player. Still it is to better to adopt such practices so that the bidder can save his money. If efficiency decreases the remuneration increases and this helps to calculate the amortizing cumulative value of the asset.

CONCLUSION:

Even though human efficiency cannot be decreased or increased subject to certain influences it may vary .So, until there are measures to measure efficiency the prior performance of an individual will be the only ground to decide the future services.

Scope for further research:

Fix standards to measure the human efficiency in units.