A Mathematical Approach for Resources Managements

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International Journal On Advanced Computer Theory And Engineering (IJACTE)

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ISSN (Print): 2319-2526, Volume -6, Issue -2_3, 2017 10

A Mathematical Approach for Resources Managements

1Sayar Ahmad Kuchy, ²Syed K Ahmed Khadri

1,2Lead Consultant, ITC Infotech, Bangalore, India

Abstract- In this research work, we are trying to focus the need of retaining the successful resources in our organizations.

Usually when we see the number of employees and the number of actual time or efforts spent on the productive work; it is not looking like a balanced boat. By taking into consideration of the variables of different aspects like their productive time, nonproductive time efforts etc.

Keywords- Mathematical model, Resources Managements, Logical Regression

I. INTRODUCTION

Mathematical model as all know it is a way of collection of ideas, behavior or structures of an existing or a new proposed system by using mathematical knowledge. Below are the advantages obtained when we use mathematical model in any organization. It helps in determining the future ahead ways of how we can enable our existing staff and make them more productive. An organization will have a better approach towards the resource utilization once there is a clear and accurate prediction. Output of the organization will get increased in multiple folds once it is predetermined that how our approach towards a new implementation of an idea or new constructive model will work. As it is possible by using mathematical model to get an abstract output of a newly proposed model before it is implemented in actual. Lot of risk management aspects will get an accurate result by using a mathematical model.

Hence it will an absolute correct way of predetermining how an approach towards a risk will get avoided and what are the outcomes – prior to that any risk management approach is applied in actual. It will help in determining which engineering model will suit to an organization. Like the facilities to be provided for the employees, seating arrangements, eco-friendly campuses, employee’s health insurances schemes, catering maintenance etc. Logical regression is defined as how we are differentiating or classifying the variables (Dependent variables) and finding a relationship between them; to get a maximum or an accurate outcome. This regression helps us in determining the way of how these dependent variables are behaving

when one of them is getting changed. This way we can find a new set of predictions that determine the future outcomes of any model.

II. MOTIVATION OF WORK

The moto of doing this work is to high light the need of retaining the successful resources in our organizations.

Usually when we see the number of employees and the number of actual time or efforts spent on the productive work; it is not looking like a balanced boat. It has been calculated that approximately 95% of the employees are spending just 5% of their actual punch in time into the productivity tasks. This way we start a research on how to minimize the wastage of resources and how to propose a system/algorithm which will help an organization to avoid huge loss on to the occupancy of non-usable bulk nonproductive employees.

III. SCENARIO

Based on the data of punch in and punch out time entries of an organization. We calculate that as an average an employee provides a productive time efforts of 20 to 25mins per day – compared to his actual 8 hours of daily available productive time. An organization of 200 employees having an expertise level ranging from 2 to 10 years of resources. Based on the individual resources time spent on relaxing activities Like tea, lunch, breakfast, dinner, talks, internet social media etc. This time is calculated as approximately 3 hours per day. Remaining time is 4hours and 30mins. Which an organization is wasting daily while having those resources on board. Now as per our proposed algorithm it’s observed that reducing just one hour of that wastage of time either from the employee relaxing time or from non-productive time. We can release 25% of the employees without affecting the organizations revenue/profit scale.

IV. ALGORITHM

1. start

2. Read N

3. If (x <= t)

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4. Write : release employees 5. Else if( x1 < np)

6. Write : No change 7. Else

8. Set x1 = np

9. End

V. PARAMETER OF MATHEMATICAL MODEL

Before:

X: time spent on productive tasks (t = 20 mins) Y: Experience in years (m <= 10yrs.)

Z: Number of employees (n = 200) X1: Non-Productive hours (np = 3hrs) P: Profit in lakhs (p1 = 20L)

After:

X: Time Spent on productive tasks (t = 180 mins) Y: Experience in Years (m <= 10yrs.)

Z: Number of employees

Es: Employees can be released (m1 = 50) X1: Non-productive hours (np = 2hrs) P: Profit in Lakhs

VI. PROPOSED ALGORITHM

Step1: Start

Step2: read number of employees

Step3: if “time spent on productive tasks(x)” is less than or equal to (t) min

release employee

Step4: else if “non productive hours (x1)” is less that (np) hours

no change Step5: else

Step6: set “non productive hours (x1)” to (np) hours.

Step7: End.

VII. ADVANTAGES OF PROPOSED ALGORITHM

There are multiple advantages of our proposed algorithm.

Some of them are listed as;

1. Reduce the number of employees.

2. Organization resources will be reduced which in turn will help in reduction of expenditures. Hence addition to the organization profit.

3. Appreciation to the employees will be an easy to determine process. As the target resources are well known now.

4. It will help us in analyzing the need of whether we need these many number of resources or not.

VIII. FLOW OF WORK

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