Boğaziçi UniversityDepartment of Management Information Systems

MIS 463 Decision Support Systems for Business

PROJECT FINAL REPORT

A DSS FOR RESOURCE ALLOCATION

Project Team No: 02

Gökdal AlıcıBurcu Balım

Mehmet Nuri CanMustafa Yörük

Instructor : Aslı Sencer Erdem

İstanbul – 21 December, 2008

Table of Content

Table of Content................................................................................................................2

I. INTRODUCTION..........................................................................................................3I.1 The Decision Environment......................................................................................3I.2 Mission of Project....................................................................................................4I.3 Scope of Project.......................................................................................................4I.4 Methodology............................................................................................................4

II. LITERATURE SURVEY.............................................................................................5III. DEVELOPMENT OF THE DSS................................................................................6

III.1. DSS Architecture..................................................................................................6III.2 Technical Issues.....................................................................................................6III.3. Model and Algorithms..........................................................................................7

Resource Allocation................................................................................................11III.4. Data Source and Flow Mechanisms...................................................................12

III.4.1 Steps of a CRM Project in Cynda Company and Their Related Skills........12III.4.2. Emloyees’ Knowledge of Skills..................................................................15

III.5. User Interface and Reports.................................................................................20III.5.1. Main Page of the system..............................................................................20III.5.2. New Project Page........................................................................................21III.5.3. Add Skill......................................................................................................22III.5.4. DSS is Ready to Run...................................................................................23III.5.5. Output Page.................................................................................................24III.5.6. Output Graph...............................................................................................26III.5.7. Available Projects........................................................................................27III.5.8. Employees...................................................................................................29III.5.9. Tasks............................................................................................................31

IV. ASSESSMENT.........................................................................................................34V. CONCLUSION..........................................................................................................35REFERENCES................................................................................................................36

Bibliography................................................................................................................36

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I. INTRODUCTIONAs a group 02, we developed a Decision Support System Model in order to solve recourse allocation problem of Cynda Company. Cynda is IT Consultancy Company and cannot effectively tap into its employees and resources to its current projects. Therefore; it loses potential incomes.

To improve the effective and efficient work system we are developing a DSS for Human Resource Allocation. With this DSS Model, project managers will choose the best-fitted employees for the current and forthcoming projects.

I.1 The Decision Environment

Cynda is a company which provides IT consultancy services to its customers in different areas of technology. CRM software consultancy is one of its core areas. The Cynda is a certified gold partner of Microsoft and it is marketing Microsoft CRM product.

There is a CRM team which comprises 21 members and 1 team manager in the Cynda company. Most of the members are developers; however there are 3 analysts and one sales director in that team.

Nowadays CRM is a very popular issue and several companies want to buy a CRM software package under the effect of this trend. Moreover, the Cynda has a positive reputation in its sector. Because of those reasons, there are many potential and existing CRM customers for the Cynda Company. Nevertheless, the Cynda has some efficiency problems. Although there are many potential and existing customers as mentioned above, profit level of the projects is not satisfactory.

According to the company managers, there are two main reasons of this problem. First one is nonefficient project management. The Cynda is working on a software project management methodology and wants to adopt it to the CRM projects. Second reason is about employee, in other words resource allocation.

Resource allocotion in CRM team is done by classical methods. Whenever a new project starts, members are asked if they are available for the time. If there are enough available members, no problem occurs. However, most of the time all 21 members are busy with on-going projects and it is not possible to start a new project immediately. Moreover, exact available times of employees are not clear, and to determine this information repetitively is a loss of time and energy.

Another critical problem in resource allocation is about specialities of CRM team members. Each of 21 members has different capabilities and excellence. However, specialization level of members is not measured in a meaningful way. Of course, there is an impression for the speciality of each member in the head of the team manager, but this is strongly a subjective measurement. That situation causes some difficulties to anticipate the duration of the projects. A project which can be completed in 30 days by 2 experienced members can be completed in, for example, 60 days by 2 inexperienced members or in 45 days by 1 experienced and 1 inexperienced member, but it is not possible to determine those numbers without using an objective measurement

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methodology. This uncertainity can cause a negative difference between planned and actual time of the projects and that means a profit loss for the Cynda Company.

I.2 Mission of Project

This project aims at desiging and developing a decision support system for resource allocation problem in the Cynda Company. Developing a rule to determine the level of specialization in CRM team is one of the important steps of the project. To be able to track exact avaliable times of employees is another critical step.

After completion of this project, the Cynda plans to find a useful solution to its resource allocation problem and not to loose more time or energy to do this job.

I.3 Scope of Project

Basically, this project is a part of the steps to improve the employee efficiency of the Cynda Company, but it is not the only step. There are complementary parts of reaching this goal. In other words, “A DSS for Resource Allocation” solely contains the subjects which affect resource allocation in CRM projects. In other words, the project is applied to the Cynda’s consltancy department and its members who are responsible for CRM projects. The Improvement in project management methodology or other solutions of increasing efficiency are not in the scope of this project.

I.4 Methodology

The main problem of the Cynda Company stems from using labour resources in an unefficient methodology and here we try to put work distribution in a right order. We aim to optimize using of labour resources of company and operation researh tecniques is the right solution for us. The trigger of the system is a new project registration. A project basically has some parameters such as complexity, importance, required man hour to develop, expected finish time and so on. We must determine these values for all projects with a measurable number interval. Constraints of system come from situation of employees and complexity of the project. Work intensity, seniority and skills are main constraints. All these constraints must have quantitative values to be distinguished effectively.

All of these parameters must be used in decision phase to reach an optimum role distribution. End of the process, we must get an output of allocation with the information of project team leader, project members and project time.

During our literature survey, we have found and red many benefical articals. One of them called “A systematic approach for resource allocation in software projects” was really helpful to adopt a model to our case. The problem described in that paper have lots of similarities with the situation of Cynda Company. So, we decided to apply this allocation method to our model by changing some of its parts which we have to do because of case specific issues those will be explained in the development of DSS part.The model mentioned in this article is called Best-Fitted Resource and it is derived by using linear programming.

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II. LITERATURE SURVEYCopmleting a software project within given time and budget is one of the main problems for the Software Companies.Lingberg states that, Only about 16% of software projects are on time and within budget.(Lingberg, 1999)

Software development projects are continually be set with serious and persistent problems, such as significant overruns in cost and schedule, poor reliability,and user dissatisfaction with the product. Increasingly, effective project management is an important prerequisite for the successful delivery of software systems on budget and on schedule. (Sengupta, Abdel-Hamid, & Bosley, 1999) One of the most critical factors driving the cost of software projects: the staffing decision. (Jeffery, 1987)

Brooks described the difficulty that managers have in making staffing decisions. (]F.Brooks, 1975) As projects slipped behind schedule, managers would attempt to increase the staff at fairly late stages in order to speed up the project. However, employing more people would result in higher communication and training overheads, thereby affecting adversely the productivity of the existing staff, and setting the project back even further. (Sengupta, Abdel-Hamid, & Bosley, 1999)

To assign right person to the right project is a complicated decision. Major contributors to the outcome of software projects are personnel assignment decisions. (Abdel-Hamid, 1989)

Productivity and efficiency of projects are strongly related to task durations. An expected benefit from improving resource allocation processes is decreased tasks’ durations, which will allow companies to be more productive. (Kolisch, 1999)

Despite all the research and advances in the field, managing software personnel remains a very complicated endeavor. A major contributor to this complexity is the increased demand for specialized individual skills in the workforce, which results from high turnover rates and the fast pace at which new technologies and techniques are being developed. As a result of higher demands, candidates with exact required skills to work tasks are usually not available. Due to the lack of proper methods to assess personnel capabilities, decision makers are forced to assign resources to tasks based on subjective measures only. This results in excess training times that significantly affect the schedule of projects. Therefore, further studies of processes and techniques for personnel management are necessary to provide better solutions in terms of quality, cost, and schedule. (Otero, 2008)

Training time of employees is another critical issue in software projects and this subject is a factor of duration of the projects. One specific characteristic in software projects is that tasks are usually not expedited by adding extra resources (Plekhanova, 1999), since there is significant overhead training and communication time required for resources to get familiarized with tasks (Abdel-Hamid, 1989). Another specific characteristic in software projects is that estimates of tasks’ durations are very imprecise, since they depend on a set of factors that are hard to estimate such as capabilities of developers. (Plekhanova, 1999)

Because a resource allocation methodology in software projects is not common and well-determined, most managers make allocation decisions in a highly subjective

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mannet. According to Acuna et al. software managers typically make assignments based on ‘‘their experience, heuristic knowledge, subjective perception, and instinct" (Acuna, Juristo, & Moreno, 2006)

III. DEVELOPMENT OF THE DSS

III.1. DSS Architecture

Our DSS model is based on the Best-Fitted Resource methodology. It is a new allocation model developed in United States by Luis Daniel Otero et al. We will made some changes to adopt this model to the resource allocation problem of Cynda.

Our inputs will be produced by determination of core skills and related skills for a CRM project. Defining tasks of a CRM software project is another major part to clearly list the inputs.

Details of our model will be explained in the models and algorithms part.

III.2 Technical Issues

Determining the right technical environment for managing and developing a software project plays a crucial role to accomplish a solution that exactly suits the business requirements. So, we concluded the following technical issues that we should handle with appropriately:

establishing the range of decision making requirements needed;

specification of the prototype DSS - architecture, standards, interface, data extraction and transfer methods;

Definition of standard or compatible models of data collection.

The project team undertook the following phases to handle the technical issues:

A research phase which developed baseline requirements and assessed the use made of DSS.

Specification and development of the prototype, undertaken jointly by two employees working for the Cynda Company. An iterative rapid prototyping methodology was followed, instead of the original plan of detailed user specification and subsequent development.

Field-testing in real-time decision making and management environments in the Cynda Company.

Finalization of the prototype and definition of standard models of data collection, extraction, interpretation and presentation for DSS.

These phases enable the project team to have some control over adaptability and use of DSS software by choosing appropriate software tools and hardware that are useful enough to provide the desired facilities. Therefore, DSS project team decided to develop software on following technical environment.

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Platform: Windows XP professional Tool : MS Office Excel 2003

Languages: MS Visual Basic and VBscript

III.3. Model and Algorithms

As it is mentioned before, we will use a base methodolgy called Best-Fitted Resource(BFR) which is developed by Luis Daniel Otero et al. However we will make a minor change in that methodology to adopt it into our case.

Basically BFR was developed to solve resource allocation problem in software projects. It assumes that there can be diversified projects in a software company. Task and abilities needed can change according to the nature of the specific project. So, this model is designed to be implemented in software projects which have different tasks and needs different skills.

However the Cynda case is a little bit different from that assumption. Cynda CRM team has several projects, their contents are not totaly the same, but most of the content in other words tasks and skills needed are the same. The steps of a CRM project are clearly known which means all tasks are already determined. Skills needed for a CRM project are also known very well, and they are not varying too much. So, we decided to fix our tasks and assume that there will not be any different task in a CRM project. If there becomes, the model which we offer can be updated for the new task. Briefly we use BFR methodolgy on task basis, not on project basis, and we assume that our tasks are not changeable.

In this method, the definition of skills needed for a project is very important. Possible skills needed for a CRM project are;

C# knowledge Analysis ability SQL knowledge Reporting Services knowledge Presentation Skills SQL Server knowledge Java Script knowledge VB Script Knowledge MS CRM knowledge

Those skills can be enhanced or narrowed.

Clearly defining tasks is another critical point of our method. We divided a CRM project to 5 steps for the moment. They are;

Analysis & Basic Customizations Installation & Configuration Development & Implementation Documentation

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Training

BFR also asseses related skills to our core skills. For example C# knowledge is a must for implementation task. Let’s say one of Cynda’s resources does not know C# very well, but he has a perfect Java knowlegde. Those coding languages are very similar, and we can assume that this employee can easily use C# because of his excellence in Java. Listing all available skills which exist in Cynda CRM team is another prerequisite for our model.

So, we aim to evaluate employee skills in Cynda CRM team according to the project tasks. After this evaluation employees will be assigned to the tasks of projects if they are available.

BFR methodolgy defines many inputs and allocate the resources to the projects by using linear programming. The summary of these inputs and related outputs are listed below. The details are available in the following pages.

H set of all skillsH (t) set of required skills for task tejt expected use of skill j on task t. Assigned values range from 0

to 11 = highly u s e d0 = not used

cjt complexity of skill j on task t. Assigned values range from 0to 11 = high level of complexity on the task for this skill0 = no complexity

sjt significance of skill j on task t = cjp ejp. Calculated values range from 0 to 11 = critically important0 = not important

rjk relationship between the level of knowledge of known skill j and the level of knowledge for required skill k. Assigned values range from 0 to 11 = strong relationship0 = no relationshipif j = k and the level of knowledge of both j and k are equal, then rjj = 1

lyj level of knowledge of resource y for skill j. Assigned valuesrange from 0 to 11 = expert0 = no knowledge

byj relationship between resource y and its known skills and skill j calculated values range from 0 to 11 = strong relationship; resource y is an expert in the skill or a highly r e l a t e d skill0 = no knowledge in the skill or in a related skill

fyt fit of resource y to task t. Calculated values range from 0 to 11 = strong fit

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0 = resource is a bad fit for the task

There are 5 steps to describe those inputs and to find outputs;

1. Task Required Skills(TSR) – TSR Table2. Skill Relationships(SR) – SR Table3. Resources’ Skill Set(RSS) – RSS Table4. Best-Fitted Resource(BFR) – BFR Table5. Resource Allocation to Multiple Tasks (RA)

Graphical representation of these steps has been showed below.

The Steps of Best-Fitted Resource Methodology

Note: Most of the following part which describes the model eleborately is taken from “A systematic approach for resource allocation” paper.

The first step of the process is to define levels of skills required for a task. Each skill level is specified in terms of its expected use (ejt) and complexity (cjt). For s impl ic i ty and flexibility, both ejt and cjt are defined subjectively by decision makers with discrete values ranging from 0 to 1. Default levels for e j t and cjt are as follows:

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For ejt, default values are:

Little use = 0.3Significant use = 0.7Extensive use = 1.0

For cjt, default values are:

Simple = 0.2Complex = 0.5Very challenging = 1.0

The significance of each required skill for a task, represented as sjt, is calculated as the product of the expected use index times the complexity index.

The objective of the SR Table is to show the learning curve rela t ionships (rjk) between known and unknown skills. Decision makers subjectively define learning curve relationships with discrete values ranging from 0 to 1. Default values for rjk values are as follows:

No relationship = 0Weak = 0.2Intermediate = 0.5Strong = 1.0

The third step of the process is to prepare a tabular representation of the knowledge of available resources with discrete values ranging from 0 to 1. These values are also subjectively defined by decision makers. Default values are as follows:

No knowledge = 0Low = 0.2Intermediate = 0.5High = 1

The fourth step of the process is to set up a BFR table to determine the suitability of available resources with the skills required for a task. The most suitable resource will most likely take the least amount of training time. For a required skill k, there are two factors considered for each resource y. The first factor is the level of knowledge of resource y in the required skill, denoted by lyk. The second factor is the level of knowledge of resource y in all other possible skills and their relationship to the desired skill, obtained by multiplying lyh*rhk, where hEH. The capability of a resource in a required skill, which is an indicator of the expected training time, is defined as:

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Byk = MaxhEH * [lyh*rhk] The suitability of resource y with task t with skill set H(t) is determined by the sum of the products of the significance of skill j for task t times the capability of resource y in skill j as

Resource Allocation

After the completion of BFR table, allocation of resources can be realized.

The first step is to determine the suitability of resource y with each task t using t h e following equation:

The next step is to formulate the problem as a linear p rog ramm ing model ba sed on values of fyt. It is assumed that the number of available resources is greater than or equal to the number of tasks. The constraints are that a resource can be assigned to at most one task and each task must be assigned to a resource.

The decision variable is defined as

The corresponding objective function is;

Since fy t describes how suitable is resource y to work task t, the objective function states that the best assignment policy is the one that maximizes the sum of the fyt coefficients. The first cons t ra in t states that a resource may be assigned to at most one task.

The second constraint states that each task must be assigned to a resource.

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III.4. Data Source and Flow Mechanisms

To test our model with the relevant data, we collected information from Cynda company1. The information is about tasks, skills, and employees’ knowlodge of skills.First, we have determined the tasks which Cynda company performs in a CRM software projects. We have defined 5 tasks, then their related skills have been described to prepare a skill relations set for each task. After determination of tasks and related skills, empoyees’ knowledge of those skills have been identifed for each task.Because one of our team members (Mehmet Nuri CAN) works in Cynda CRM team for 2 years, collection of real data was quite easy with the support of Cynda CRM department. In the following part, you can find “Steps of a CRM Project in Cynda Company and Their Related Skills” and “Emloyees’ Knowledge of Skills”.

III.4.1 Steps of a CRM Project in Cynda Company and Their Related Skills

Task 1: Analysis and Basic CustomizationsSkills of this task are;

Presentability Communication Skills MS Office Visio CRM Application CRM Customization

The relationship between those skills are defined on the table below. Abbrevations mean;S: Strong, I: Intermediate, W: W, NR: No Relation

Presentability Communication MS Office Visio Application Customization

Presentability S I NR NR NR

Communication I S NR NR NR

MS Office Visio NR NR S NR NR

Application NR NR NR S W

Customization NR NR NR I S

Task 2: Installation & Configuration

1 This part was before “Models and Algorithms” part in the final report format. However, we think it is superior to give this data after the explanation of “Models and Algorithms” to comment “Data Source and Flow Mechanisms” better.

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Skills of this task are; SQL Server CRM Installation Share Point Server Performance Point Server

The relationship between those skills are defined on the table below. Abbrevations mean;S: Strong, I: Intermediate, W: W, NR: No Relation

SQL Server CRM Installation Share Point Perf. Point

SQL Server S W NR W

CRM Installation W S NR NR

Share Point I NR S I

Perf. Point W NR I S

Task 3: Development and ImplementationSkills of this task are;

C # VB SQL Java Script SQL Server Reporting Services XML MS CRM Platform Language CRM Application CRM Customization Java PHP

The relationship between those skills are defined on the table below. Abbrevations mean;

C# VB

SQL

Java Script

Rep. Serv.

XML

Plat. Lang.

Applic.

Cust.

Java

PHP

C # S W NR W NR NR I NR NR S WVB W S NR W W NR W NR NR W WSQL N

RNR

S NR I NR W NR NR NR NR

Java Script W W NR S NR NR W NR NR W WRep. Serv. N

RW I NR S NR NR NR NR NR NR

XML NR

NR

NR S NR S NR NR NR NR NR

Plat. Lang. S I I W NR W S NR NR I WApplication N

RNR

NR NR NR NR NR S I NR NR

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Customization

NR

NR

NR NR NR NR NR I S NR NR

Java S W W I NR NR I NR NR S WPHP W W W W NR NR W NR NR I S

S: Strong, I: Intermediate, W: W, NR: No Relation

Task 4: DocumentationSkills of this task are;

Office Word Office Visio Writing Skills English

The relationship between those skills are defined on the table below. Abbrevations mean;S: Strong, I: Intermediate, W: W, NR: No Relation

Word Visio Writing EnglishWord S W NR NRVisio W S NR NRWriting W NR S NREnglish NR NR NR S

Task 5: TrainingSkills of this task are;

Presentability Communication Skills CRM Application

The relationship between those skills are defined on the table below. Abbrevations mean;S: Strong, I: Intermediate, W: W, NR: No Relation

Presentability Communication Application

Presentability S I NR

Communication I S NR

Application NR NR S

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III.4.2. Emloyees’ Knowledge of Skills

Empoyee’s knowledge of skills for each task in Cynda CRM team are summarized on the tables below. For privacy issues, we have not used real names, but the data is strongly valid and correct. Abbrevations mean;NK: No Knowlege, L: Low, M: Medium, I: Intermediate, UI: Upper-Intermediate, A:Advanced

Employee Skills of Task 1: Analysis and Basic CustomizationsPresentability Communi

cationMS Office Visio

Application Customization

Mehmet Çetin UI UI A A I

Ebru Çakır UI A L I I

Halil Dikmen I UI I UI UI

Aysel Tunacı I I NK L I

Göktan Eloğlu UI UI L I I

Sinan Candan I I I I I

Önder Yolcu A A UI A A

Gül Özer I I I UI UI

Fatoş Güzel L L I L I

Serkan Dilli L I I I UI

Sercan Tunç I UI I I UI

Barış İlke I I I L L

Ömer Ak L L I I L

Kayhan Öz L I I I UI

Engin Altın UI UI I UI UI

Rıdvan Tenli L L L L L

Coşkun Günlü L L I I A

Rıfkı Şahin I I UI I A

Bekir Sevi L L L L I

Cem Saltık I UI I I A

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Employee Skills of Task 2: Installation & ConfigurationSQL Server Installation Share Point

ServerPerf. Pt. Ser.

Mehmet Çetin UI L L L

Ebru Çakır L NK L NK

Halil Dikmen I A I I

Aysel Tunacı L L NK NK

Göktan Eloğlu UI UI UI L

Sinan Candan I L NK NK

Önder Yolcu UI A I L

Gül Özer I UI L L

Fatoş Güzel L L L L

Serkan Dilli I L L NK

Sercan Tunç UI I L L

Barış İlke A L L I

Ömer Ak L L NK NK

Kayhan Öz UI I L L

Engin Altın UI UI L NK

Rıdvan Tenli L NK NK NK

Coşkun Günlü I I L L

Rıfkı Şahin UI UI I L

Bekir Sevi L L L NK

Cem Saltık UI UI UI L

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Employee Skills of Task 3: Development and ImplementationC# V

BSQL

Java Script

Rep. Serv.

XML

Plat. Lang.

Applic.

Cust.

Java

PHP

Mehmet Çetin I L A L UI L L UI I L L

Ebru Çakır I L M M M M M M M M NK

Halil Dikmen NK

NK

L NK NK L NK UI A NK NK

Aysel Tunacı L L L L L L L L M NK NK

Göktan Eloğlu M L I UI I I I UI UI L L

Sinan Candan UI L I I I I I I I L NK

Önder Yolcu I UI UI M UI UI UI A A L NK

Gül Özer UI UI UI I UI M UI I UI L NK

Fatoş Güzel I L L L L L L M I L NK

Serkan Dilli UI I I I I I I M UI L NK

Sercan Tunç UI UI UI UI I M UI UI UI NK NK

Barış İlke A A A UI I UI NK L L L I

Ömer Ak L UI I I L L NK L I L NK

Kayhan Öz A A A UI UI I I I UI UI L

Engin Altın UI UI UI UI L UI UI UI A L NK

Rıdvan Tenli NK

I UI L L L NK L L NK NK

Coşkun Günlü A UI UI A L UI UI UI UI I L

Rıfkı Şahin A A A A A A A UI UI L L

Bekir Sevi I I I I M I NK L M I NK

Cem Saltık A UI A A A A A I UI L L

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Employee Skills of Task 4: DocumentationOffice Word Office Visio Writing Skills English

Mehmet Çetin A A A A

Ebru Çakır I I I A

Halil Dikmen A I UI I

Aysel Tunacı I L I UI

Göktan Eloğlu UI I I UI

Sinan Candan UI L I UI

Önder Yolcu A UI UI I

Gül Özer I I I UI

Fatoş Güzel I L I L

Serkan Dilli I I I UI

Sercan Tunç I L I UI

Barış İlke L L M I

Ömer Ak L L L M

Kayhan Öz I I I L

Engin Altın UI I UI UI

Rıdvan Tenli I L L I

Coşkun Günlü I I I I

Rıfkı Şahin UI UI I UI

Bekir Sevi I I I I

Cem Saltık I I UI UI

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Employee Skills of Task 5: TrainingPresentability Communication CRM Application

Mehmet Çetin UI UI A

Ebru Çakır UI I M

Halil Dikmen I UI UI

Aysel Tunacı I I I

Göktan Eloğlu UI UI A

Sinan Candan I I I

Önder Yolcu A A A

Gül Özer I I UI

Fatoş Güzel L L L

Serkan Dilli L L I

Sercan Tunç UI I UI

Barış İlke I I L

Ömer Ak L L L

Kayhan Öz I I I

Engin Altın A A UI

Rıdvan Tenli L L L

Coşkun Günlü M L UI

Rıfkı Şahin I I UI

Bekir Sevi L L M

Cem Saltık UI M UI

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III.5. User Interface and Reports

III.5.1. Main Page of the system

Figure 1 – Main page of the system

Main page of the system (Figure 1) has simple design. In the header part of the page, user can navigate between pages with the help of menu bar. If an item selected, this selected item will have a thicker font in order to differentiate it from other menu items. In the footer, there is small group info and communication info of the system.

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III.5.2. New Project Page

Figure 2 – New project registration and adding tasks

New project pages consists new project registration and updating available project requirements. Record function is executed step by step. Firstly, user enters a project name. After recording name of the project, step 2 is visible in order to add required tasks in the project. There is a task list in the step2, this list shows the added tasks. Every task must be consist skills. To add a skill to task, user must click to “Add skill” in the required row. Also user can delete a task in the project by clicking the delete item at the end of the task row. Page can be viewed in Figure 2.

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III.5.3. Add Skill

Figure 3 – Adding skills and selecting skill levels

If user clicks one of the tasks in order to add skills and determine skill levels, user is redirected to task specifications (Figure 3). User adds skills in the step 3 tab. In step 4, user selects expected use and complexity levels for the selected skills. Every action is validated and at the end of every action, user is informed. In addition to these, user can delete all skill level selections and also skills.

After completition of adding skills and selecting skill levels, user clicks to “BACK” button to view project main page (Figure 4). In this process, all user input is validated whether it is ready to offer an allocation or not. If it is required, error messages is shown users to inform him/her which inputs is incomplete when clicking the “Offer Allocation >>” button.

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Figure 4 – New project page validated all input

III.5.4. DSS is Ready to Run

Figure 5 – DSS is ready to run

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User is informed with a small note when input data is appropriate to run DSS model. Then User clicks the “Offer Allocation>>” button to view results.

III.5.5. Output Page

Figure 6 – Project output

In our example, we have selected five tasks in the project. Output page shows these five tasks and suggested first five employee in terms of the coherence. There are two coherence value in the output table, first one is real value of employee, second one is disregards that employee is busy or idle.There is a “MORE>>” button in the every task output table. This button opens a new detail page to list all employees in a order. For example, user clicks for the “Instalation & Configuration” task, output detail is shown(Figure 7) below. All employees are listed in this detail page with regard of their coherence ratio.

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Figure 7 – Task output detail

In addition to these, there is a graphical version of output data. User can click the “Click fo Graphical Version >>” button to view a graph(Figure 8). Button is at the end of table.

Figure 8 – Graphical Version

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III.5.6. Output Graph

Figure 9 – Graphical Version of Output

Output is shown in a bar graph for the first five employees regarding its coherence to task requirements. In addition to bar graph representation, pie chart of the first five employees are shown when you click for the pie chart version>>.

Figure 10 – Graphical Version of Output

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III.5.7. Available Projects

All entered projects are recorded to the system and can be viewed in “Available Projects” page. User clicks to the project to view output. Also project requirements can be updated. In addition to these, user can delete projects. Page can be viewed in Figure 11. If user clicks one of the project names, user is redirected to output page (Figure 6). Then user can continue to the detail and graph pages in turn.

Figure 11 – Available Projects

If user clicks the project requirements icon, a detail page is shown(Figure 12). User can update selected project requirements by clicking the “Update Project Requirements” button.

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Figure 12 – Project Requirements

III.5.8. Employees

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Employee page lists all employees with their availability value. If an employee is idle, he/she appears available. Employees can be updated and deleted with the icons that are at the end of every row. Also a employee info can be viewed by clicking name or surname. Header part of the page, there is a form to save a new employee. Employee is saved and knowledge level values are selected by clicking his/her name in the list. Employee table can be viewed in Figure 13.

Figure 13 – Employee list & Record a new employee

If user clicks name, surname or edit icon for an employee, user is redirected to a detail page (Figure 14). This page enables user to update user’s skill knowledge levels for all skills in the system.

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Figure 14 – Employee Detail

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III.5.9. Tasks

Tasks in the system are managed in this page. Page lists all tasks and also enables user to create a new task. Task list and record page can be viewed in Figure 15.

Figure 15 – Tasks in the system

If user clicks one of the tasks, user is redirected to a detail page. In this page, skills of task are shown. User can add or delete a skill for the selected task. This data is important because DSS system uses skills to determine a coherence ratio for a task. Task detail page can be viewed in Figure 16. In the sample screen, “Development & Implementation” task is selected.

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Figure 16 – Skills in the tasks

Another important process is determining skill relations with other skills in the task. When user clicks a skill name, system redirects user to a skill relation page to determine skill relations. User evaluates skill and selects a relation level in the select list. After the action, result of action is shown to user. Skill relation page can be viewed in Figure 17. In the sample, “C#” skill is selected to determine its skill relations in their task.

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Figure 17 – Skill relations with other skills in the task

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IV. ASSESSMENTDSS evaluation is difficult because of their dynamic nature. However, we specified user requirements clearly at the outset and designed our DSS application to support well-structured tasks (decisions). We consider a DSS as a part of a complex decision making system which consists of tasks, users, the organization, and the DSS itself. In other words, we think that our DSS application is a decision aid designed to support various tasks for management, and ultimately, designed to support organizational objectives. As a result, we assessed our system (A DSS for Resource Allocation) from the perspective of following features:

Support for DSS evolution Align DSS with organizational objectives Support for multiple evaluators/users Provision of DSS flexibility

It is well known that a complete set of system requirements cannot be identified at the outset of the DSS development process. Therefore, we received constant feedback and adaptation from the Cynda Company. This enabled us to develop our DSS continuously through an adaptive process of developer learning. As a result, we received a good support from the company during DSS evolution. So, we wholeheartedly can say that the system is well-structured for IT companies that have encountered problems for assigning right person to right task. Also, the evaluation way of the system allowed us to put organizational objectives and plans into the desired functions and features of the DSS. Thus, the matches between DSS functions and organizational are provided.Our system is developed for person who held a management position in a IT company because they have charge of resource allocation. So, we will get managers to evaluate our system after we release the beta version of the system. The business environment is increasingly volatile, changing quickly due to new business opportunities, problems and government regulations. To keep our DSS application effective, we provided users with opportunities to change the system settings so that they can adapt the DSS application to new user knowledge, technology, and other internal or external company environmental factors. Therefore, our DSS application is fully flexible to support changing problem domains and changing problem solving environments.

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V. CONCLUSIONIn this study, we have shown a different way to develop a system that goes beyond DSS methods thought in the course in which students learn a few methods and base their project solution on them. We have used Best-Fitted Resource methodology that is defined in a journal published by Elsevier. The system briefly develops a solution to IT companies that have difficulties in assigning employees to appropriately matching tasks. Person who is responsible for assignment of employees to tasks will get useful recommendation from the DSS application. For instance, managers can easily observe changes in assignment when inputting a different skill value of employee to the system. Also, we added a graphical representation to the system so that the managers can make a quick inference from the system recommendation. Thus, the DSS application helps managers in making right decision on resource allocation. We strongly believe that the system provide good solutions to the assignment problem in an IT company. With this course, we learnt that limitation on imagination means going round in circle. In addition to enlargement of our views, the course and the project undoubtedly have a great value to team members due to their approach to practical problem solution.

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