Decision support system for multi-project cash-flow management.

Kramarenko, Sergei ; Shevtshenko, Eduard

1. INTRODUCTION

The delivery of projects as a means for strategic goals achievement has gained prominence. As a result, changes in (construction, R&D, software) project procurement and implementation have shifted from single project to multi-project delivery. The problem we highlight in this paper is a necessity of accounting the complexity and dynamics in the multi-project environment, especially for resources allocation (cash flow management). We follow the idea of integrated decision support system, which is capable to support managers in the multi-project enterprises. In the construction industry, various forms of integrated decision support systems are established to support project management, price and bid decision making, cash flow management and site selection (Kenley, 2003; Borgonovo & Peccati, 2005; Khosrowshahi & Kaka, 2007).

2. IDSS IN PROJECT MANAGEMENT

Mostly every contemporary company has an enterprise resource planning (ERP) system to conduct different production and service operations. It includes modules for finance management, warehouse management, marketing management, sales and purchase management. Although data can be shared extensively through ERP systems, it still does not directly support the decision making. Thus, IDSS integrated with ERP systems is used by decision makers for enterprise project portfolio/multi-projects performing. In our previous IDSS related research was proposed manufacturing projects management model (Kramarenko et al., 2008).

In manufacturing companies with multi-project/project portfolio management, the problem of optimal resource allocation is important due to the necessity of limited resources distribution among the different projects. It demands a constant attention from the managers who have to deal with re-allocation of resource during short term planning process. Particularly, lack of data required for reliable cash flow analysis needs to be resolved. Before IDSS could be used for cash flow management purposes we need to receive the reliable data from ERP system. Due to the lack of useful data, a common practice is to collect data manually from suppliers, which is time-consuming process and depends on how well suppliers' behaviors are known.

We propose the cash-flow management model that covers the real process starting from budget to the real-time cash-flow tracking. As shown in Figure 1, the model of cash-flow planning and tracking is used in calculation of ENPV for all possible solutions (e.g., Sol. 1, Sol. 2, Sol. 3, Sol. n).

[FIGURE 1 OMITTED]

3. PROJECT PORTFOLIO AND COMPLEXITY

Turner and Speiser (1992) contend that by far the greatest proportion of project related activities takes place within portfolios, or programmes. Payne (1995) estimates that up to 90% of all projects value is carried out in a multi-project context of some sort. In a study of construction client typologies, Blismass et al. (2004) found that despite the widespread multi-project nature of many construction clients, single project management strategies were usually adopted for managing programmes and portfolios but this resulted in only limited success.

About two decades ago emerged issue of multi-project/portfolio organizations which are complex and dynamic environments. Complexity theory is concerned with the behavior of dynamic systems (the systems are able to change in time). Some systems, though they are constantly changing, do so in a completely regular manner whereas others lack stability. Unstable systems move further and further away from starting conditions until/unless they are altered by some over-riding constraint. Stable and unstable behavior as concepts is part of the traditional repertoire of the physical sciences (Smith et al., 2008). In the review of the concept of project complexity, Baccarini (1996) argues that projects and project management are often associated with the concept of complexity. However, Lewin (1999) observes that both practitioners and academics have difficulties accepting and treating projects as complex. Phelan (2001) states, whilst there are many definitions of the broad field of complexity, there are some commonalities that are core in the different concepts of complexity. From a management perspective there seems to be an agreement that complexity theory offers an opportunity to re-examine reductionist and mechanistic thinking thereby providing a more holistic view.

3.1 The description of the dynamic cash-flow principle

Here we propose a novel way to manage project cash flow dynamics using the Bernoulli principle of fluid dynamics. The idea of modelling financial cash flows through fluid alike motion recently attracted attentions. It was applied in studying financial markets, where the financial turbulence is described by laws from fluid dynamics. Los (2001) reformulated the classical laws of fluid mechanics for cash flow mechanics in order to measure and simulate various degrees of financial liquidity/illiquidity.

The Bernoulli's principle is equivalent to the principle of conservation of energy, which states that the total amount of energy in an isolated system remains constant. The consequence of this law is that energy cannot be created or destroyed (Munson et al., 1998). In our case, the cash flows of the constituent projects have the same total effect on the whole portfolio, as the result of the principle of conservation of value (energy). Bernoulli equation has a form as:

p + 1/2[rho][v.sup.2] = P. (1)

This equation implies that the sum of static (p) and dynamic ([rho][v.sup.2]/2) pressures is constant and equals the total pressure (P). Below we explain the implication of the idea. Under total pressure we understand the total measure of a project cash-flow dynamics ([CF.sub.dyn]). Static pressure presents an amount that is invested in the project at [t.sub.0]. Dynamic pressure consists of the density and velocity. We mean that density is a double difference (in order to get rid of multiplier 1/2 in the equation) in the sum of investments and returns, respectively, at time t1. Velocity represents a rate of return on the investments (%ROI) made by time [t.sub.1]. Therefore, a new form of the equation (1) could be defined:

Investment x (%[ROI.sup.2] - %[ROI.sup.3]) = [CF.sub.dyn] (2)

The result of calculations (Figure 2) shows that the project cash-flow dynamics is a non-monotonic convex function with a maximum point (about 66%).

[FIGURE 2 OMITTED]

It means project dynamics is a changing measure, so that it could be taken into account modeling and managing project portfolio (multi-projects). The effectiveness of project portfolio management is a matter of its dynamics i.e., as higher the dynamics as efficient the portfolio is. Moreover, the dynamics need to be considered in the questions like resource allocation and projects' prioritization in the portfolio. These results provide us with further development of IDSS for cash-flow management in case of dynamics.

4. CONCLUSION

In this paper we presented the idea of project portfolio cash flow management supported by IDSS systems. The IDSS is able to assist decision makers in major capital investments such as the introduction of new products, which requires cash flow information over the life of the project. The investment profitability estimation depends on cash flow estimations, which are generally uncertain. Many cash flow elements (such as demand) are subject to substantial uncertainties. The proposed solution enables real time tracking of project cash flows. It makes the ENPV calculation for alternative assessments. Then, an idea of complexity and dynamics was applied to project portfolio management. The novel method based on Bernoulli principle is presented. It has an importance for dealing with complexities in multi-project environment and facilitates in resource allocation (cash management).

Our future research will go on with the development of decision support which could solve issues of complexity and dynamics in project portfolio. We will proceed with calculations for case studies that will justify our hypothesis.

5. ACKNOWLEDGEMENT

Hereby we would like to thank the Estonian Ministry of Education and Research for targeted financing scheme SF0140113Bs08 that enabled us to carry out this work.

6. REFERENCES

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