Konstantinos Kirytopoulos

Risk management for SMEs: Tools to use and how

Business endeavours have transformed to project based efforts for many years now. Most companies usually operate more than one project. Day by day risk management is earning ‘credits of appreciation’ even in the very competitive, project-based operating environment. The aim of this paper is to attempt a presentation of basic risk management tools along with their key features. Although other qualitative risk analysis tools exist, this paper presents only those with explicit quantitative analysis capabilities. Sixteen software tools have been indicated and ranked in terms of the features available. Indicative results of one of those tools are presented using a short case study. The study demonstrates that the use of appropriate software tools may enhance project-related operations and reduce costs, especially when the user is an SME.

Multiple sourcing strategies and order allocation: an ANP‐AUGMECON meta‐model

Purpose – The strategic importance of sourcing is inherent in the positioning of the purchasing operation in a supply chain and supplier evaluation – a crucial step in sourcing – is a complex multicriteria decision making (MCDM) problem. The purpose of this paper is to provide a meta‐model for supplier evaluation and order quantity allocation, based on a MCDM method, namely the Analytic Network Process (ANP) and a multiobjective mathematical programming method (MOMP), the AUGMECON.Design/methodology/approach – The proposed approach consists of two parts. The former develops and applies the ANP method in order to evaluate the suppliers in qualitative terms. The latter implements the AUGMECON method in order to find the Pareto optimal solutions for the allocation of order quantities in a multiple sourcing environment. The integrated meta‐model is exposed through an illustrative case concerning the parapharmaceutical enterprise cluster in Greece.Findings – The proposed meta‐model constitutes an efficient met...

Risk management: a competitive advantage in the purchasing function

This paper aims to explore the purchasing function on behalf of the provider, when the purchasing takes the form of a request for proposals (RfP) from the client. A methodology for handling the bidding process is presented, illustrated by a case study from the IT sector. The proposed methodology places risk as a factor for the selection of the best and final offer of the provider in addition to the traditional decision factors: delivery time, product cost and performance. The method is supported by a structured corporate memory and a decision support system based on the analytical hierarchy process.

Incorporating uncertainty in optimal investment decisions

Investment decisions are now more crucial than ever. The investors are in need of sound arguments, which will be able to shape the investment specifications and appraise their uncertain nature. This paper proposes an innovative approach that merges optimisation and risk analysis in one single method. The two-step investment appraisal approach reaches an optimum through a Genetic Algorithm optimisation and then assesses the environments risk through a Monte Carlo simulation. The approach, thus, offers the best investment characteristics, as well as information about its implied risk. The use of the method is illustrated through an extensive Case Study.

Risk management as a strategic issue for the implementation of ERP systems: a case study from the oil industry

The introduction of complicated and expensive Enterprise Resource Planning Systems (ERP) in companies operating in the process industry has become a strategic issue. The success of Information Technology (IT) implementation projects is dependent upon technological issues (software and hardware), the design of new efficient processes and the utilisation of human resources that will participate in new processes using the new IT solution. Risk management can be an important component of strategy helping in the identification and control of project-related risks. The methodology presented in this paper proposes a structured risk management approach for the successful implementation of ERP systems. The application of the proposed methodology is demonstrated within a case study concerning a European company operating in the petroleum sector. The conclusion drawn by the study is that the risk management strategic approach is of significant importance when the best outcome from the implementation of an ERP project in industry needs to be obtained.

An analytic network process approach for sales forecasting

New product sales forecast is a difficult but essential task for companies, as it drives a variety of multifunctional decisions. Most new product forecasting literature presents sophisticated statistical techniques and complex methodologies with little or no thought given to ease of implementation. As a result, there is a significant gap between what forecast academics create and what forecast models professionals really seek. This study proposes a new product sales forecast model based on an Analytic Network Process framework. The analytic network process (ANP) is a multicriteria decision analysis technique that takes into account both tangible and intangible criteria with interdependencies and feedback among them. It is argued that the proposed framework is more flexible and is more comprehensive than traditional methods and previously developed models. The ANP model is illustrated through a real example concerning the sales forecast of a new edition (book).

PERT vs. Monte Carlo Simulation along with the suitable distribution effect

Project schedule development is an iterative process that determines the planned start and finish dates for project activities. Within this process the anticipated project duration is also determined. The primary aim of this paper is to stress the importance of historical information as well as the right distribution selection in activity duration estimating, by comparing the different outcomes of scenarios when historical information is or is not used. The scenarios were implemented on 20 small- and medium-sized construction projects. Both the Programme Evaluation and Review Technique (PERT) and Monte Carlo Simulation (MCS) are used and the results produced under four different scenarios are compared. The first scenario uses standard PERT, while the three remaining scenarios are simulation approaches differentiated in the use of the right distribution or not and in the use of historical information or not. The findings validate that MCS is superior to PERT and moreover expose the difference in the results when the suitable distributions are selected based on accurate historical information compared to when historical information is not available.

Project termination analysis in SMEs: making the right call

Abandoning a project is difficult as it engages an enormous psychological load for project managers and team members and increases personal and professional insecurities. Organisations not only delay this kind of decisions, but also escalate their commitment into a failing project. Terminating a failing project with least of problems, releasing valuable resources and investing in higher potential projects are crucial for organisations prosperity. The aim of this study is to support the decision making when project termination is of question, help project managers and executives understand the problem context and revise their belief about terminating projects. The paper proposes a framework, based on the analytic network process. The study reveals the criteria that have to be taken into consideration in project termination decisions and provides a structured approach in order to help managers make decisions. The paper includes a case study of a troubled ERP implementation project in a SME.

Hybrid nature-inspired intelligence for the resource leveling problem

The paper deals with a class of problems often met in modern project management under the term “resource leveling optimization problems”. The problems of this kind refer to the optimal allocation of available resources in a candidate project and have emerged, as the result of the even increasing needs of project managers in facing project complexity, controlling related budgeting and finances and managing the construction production line. For the effective resolution of resource leveling optimization problems, the use of nature inspired intelligent methodologies is proposed. Traditional approaches, such as exhaustive or greedy search methodologies, often fail to provide near-optimum solutions in a short amount of time, whereas the proposed intelligent approaches manage to timely achieve high quality near-optimal solutions. In the paper, extensive experimental results are presented, based on available data collections existing in literature for a number of known benchmark project management problems. The comparative analysis of three different intelligent metaheuristics, shows that a hybrid nature inspired intelligent approach, combining ant colony optimization and genetic algorithms, proves to be the most effective approach in the majority of benchmark problems and special decision making settings tested.

Project management educational software (ProMES)

ProMES (ProMES software is freely provided for academic purposes and can be downloaded from: simor.mech.ntua.gr/Kirytopoulos/promes.asp) fills the gap of educational software in training on basic tools of project management. It offers aid to trainees in project management positions or courses to understand how CPM, PERT, and RACI are used and enhances conditions for the acquisition of the required knowledge based on pedagogical approaches.