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Impact of Outsourcing Strategy on Mobile Operators’ Profitability

Table of Contents

2. Literature Review
2.1 Introduction
2.2 Outsourcing in the Mobile Telecommunications Business – A Worldwide View
2.3 Overview of  the Mobile Telecommunications Business in Egypt
2.4 Outsourcing From Two Perspectives: Operator & Supplier views
2.4.1 Supplier’s View of Outsourcing Network Operation Services
2.4.2 Operators View of Outsourcing Network Operations Services
3. Theoretical Foundations of The Proposed Work
3.1 The Resource Based View (RBV) theory:
3.2 Transaction costs economics (TCE) theory:
3.3 Agency Theory:
3.4 Integrated Framework
3.5 System Thinking
3.5.1 Perception
3.6 Decision support Systems
3.7 System Dynamics
3.7.1 History
3.7.2 System dynamics components
Stock & flow model
Equations in discrete time
Equations in constant time

  1. Literature Review
  1.        Introduction

We have discussed how the telecommunication operators are struggling to find a way to face the challenges of rapidly extending their network, services and technology. We mentioned the outsourcing as a possible way to reach such goal, but is it really a proven concept?
In the practical world, the rapid rise of multi-vendor outsourcing has made ‘Outsourcing’ fashionable and a much-discussed term among the large and contentious world of industry analysts who follow the telecoms industry. Much has been written about the various flavors of outsourcing, its definition, when out-tasking becomes outsourcing, whether outsourcing should, or should not, take place, etc.
The main reason for outsourcing is cost reduction ,mainly that supply-side economies of scale reduce costs and hence improve operation model. However, outsourcing can also influence product and service quality and thus affect corporate revenues.
On the academic front, Outsourcing became a strategic decision to be taken or most companies in Europe and the United States and nowadays in Middle East and Africa .
Despite that outsourcing became widely applied business strategy, evidence on performance implications of outsourcing is rare, with the majority of the literature focusing on the governance choice (David and Han 2004). The empirical literature dealing with performance impacts of outsourcing mainly focus on :
-Technological performance (Leiblein et al. 2002, Raassens 2011)
-Perceived performance (Grover et al. 1996, Poppo and Zenger 1998 ,Marcolin and McLellan 1998, Gilley et al. 2004,  Weigelt 2009, Mani et al. 2010).
– Shareholder value (Jiang et al. 2007, Raassens 2011).
To the researcher knowledge, in the analysis of the corporates financial statements and performance only Jiang, Frazier and Prater (2006) analyze it and distinguish cost effects from revenue effects.
A key question in the outsourcing domain: is why companies outsource? It is worth highlighting the difference between why companies have chosen outsourcing as a strategy and why they actually did it (Lonsdale & Cox, 1998). Many factors are behind the choice of outsourcing as a strategy for the firms. Reasons for choosing outsourcing of standards activities are in most cases different than they are for core business activities. In addition, organizations in different business environments and different competition will get different benefits (Kremic et al, 2006). It is worth mentioning that most western companies outsource primarily for short-term cost savings (Kakabadse & Kakabadse).
As a conclusion;it is not the type or the flavors of “sourcing Strategy” that pre-occupies us in this research – rather it is the impact that these investments create and what it does to an operator’s business and its bottom line.

  1.        Outsourcing in the Mobile Telecommunications Business – A Worldwide View

In 2008, the total telecom services market is estimated in the $70 billion range and managed service is about 28.5% of this market, around $20 billion. Network-related managed services account for approximately 30% of revenue while IT-related managed services account for 70% or $14.2 billion. ABI Research calculates the global OPEX for 2008 at over $330 billion. This means that there is a lot of room to expand outsourcing as operators focus on increasing revenue and reducing costs. Figure (1) shows the OPEX vs. the managed service revenue projection. (ABI Research, Managed Services for Mobile Wireless Operators, 2009).

Figure (1): Global Operators’ OPEX compared to Managed Services Revenue ($ Billions)
In emerging markets, outsourcing is used either to meet time-to-market demands or to reduce cost and increase profitability in highly competitive markets such as Egypt and Algeria.
The recent global recession forced operators to reduce their Operational Expenses (OPEX), which if carried out carelessly will impact the customer experience. On the Capital Expenditure (CAPEX) front, the fact that there still are billions of unconnected people in the world along with advances in new technology which necessitates continual network modernization, means that the trend is for continued increase.
Despite the above challenges, the past decade has been a time of great success for the leading mobile operators in the Middle East and Africa. Growing revenues and strong cash flow in domestic markets have generated significant demand as well as competition. The leading operators have used their cash and the ready availability of private capital to build regional mobile empires. Today, there are seven powerful multinational operators: Etisalat, Orascom, Qtel, STC, Zain in the Middle East, and MTN and Millicom in Africa. Between them, they have more than 300 million subscribers.
Figure (2) shows the subscribers’ numbers forecast till 2020.

Figure (2): Subscriber Numbers by Region, World Market, Forecast 2007 to 2020
Despite the realities for the current mobile market leaders in the Middle East and Africa, these regions continue to represent the world’s last major growth play for traditional voice and text services. The evidence is apparent in Bharti and Reliance’s interest in Africa’s MTN, in Essar’s buyout of the Warid properties in Uganda, in Vodafone’s steady increase in control at Vodacom, in Vivendi and others’ reported interest in Zain, and in Orange’s desire to boosted its presence in Africa and mainly in Cairo by acquiring Mobinil fully and re-branding it to Orange-Egypt, among many other moves in the market.
The largest Middle Eastern and African groups in this environment have a choice to make. They can continue with their expansion strategies to try to build a truly multinational or global presence—or they can join forces with the largest global players. These deci­sions will have to be made soon.
In Europe, the main driver is the need to reduce OPEX to remain competitive and improve the bottom line. In several European countries, mobile penetration exceeds 100%. As a result, operators have to transform from bit pipe providers to personalized services providers to remain competitive. These operators need networks that enable the development, testing, and deployment of new low cost services quickly and efficiently. These services must leverage higher data rates and low latency of next-generation networks to improve the customer experience and IT capabilities to personalize those services.
In Latin America and North America, managed services are used primarily to deploy complex technical solutions such as IP Multimedia Subsystems (IMS), support legacy networks, and for deployment in new frequency bands or markets where companies have few or no employees. Operators and MVNOs, who want to test new services without a lot of capital investment, turn to hosted services that enable shared utilization of infrastructure without major capital outlay. Managed hosting also enables operators to add and change services with minimal investment, which is also a key driver for this segment.
Service providers benefit through lower operational costs, improved network performance, and increased service offerings. Service providers who leverage managed services can shift their focus to generating revenue, knowing that their networks are in good hands. The network operations employees working on the managed portion of the network are usually transferred to the Original Equipment Manufacturer (OEM). This provides opportunities to increase skills and knowledge, flexibility in work locations, and job security.

  1.        Overview of  the Mobile Telecommunications Business in Egypt

Egypt’s mobile subscriber base had risen to 105.5 million from 83.121 million at the end of December 2015 (Table 1). The telecommunication industry of Egypt is one of the fastest developing sectors in the country, by 2017; it is believed that the market will have around 110.9mn subscriptions and penetration rate of 125.2%. Since the establishment of the Ministry of Communications and Information Technology in 1999, the Egyptian telecom industry has been ushered into an era of liberalized policies and new regulatory laws. In recent times, there has been a significant growth in low-income customer segment owing to stiff competition between various mobile operators, which has led to tariff reductions.
Egypt’s mobile market is among the most competitive in the Middle East and North Africa region, playing host to three major international players: The Vodafone Group-backed Vodafone Egypt, Orange-backed Orange-Egypt (Mobinil) and Etisalat-backed Etisalat Misr plus the new awarded Telecom Egypt – see Table (2).
Business environment became more competitive, especially with market saturation , the introduction of fourth operator , the Mobile-Fixed Convergence and the implementation of new regulatory policies such as mobile number portability. We expect competition to become even more intense in the next few years following the proposed introduction of MVNO, FVNO and 4G services.
Table (1): Mobile Market Overview

Clearly, the political situation in Egypt has had a positive effect on mobile subscriber growth contrary to previous expectations. However, the effect on operators’ financial indicators is less encouraging as Mobinil and Vodafone reported a sharp decline in ARPUs and, consequently, net profits during past years (figure 3).
Table (2): Competitive Landscape

Source: BMI Egypt Infrastructure Report Q4 2016, Publish By: Business Monitor international 2016
There are still a number of negative characteristics of Egypt’s telecoms sector. These include a mobile market that is highly skewed towards prepaid users and falling mobile ARPUs. In addition, price competition has been aggressive since the introduction of compulsory SIM registration in May 2010. Although Egypt’s operators have reported sequential increases in ARPU, the overall trend in the market remains downwards as strong competition continues to give consumers large amounts of choice and forces prices down.

Figure (3): Industry Forecast – ARPU 2011-2018, BMI Forecast, Source BMI

  1.        Outsourcing From Two Perspectives: Operator & Supplier views

The above state of affairs of the Mobile Industry is pushing operators to look for new paradigms to manage their OPEX and CAPEX more efficiently.
One of these paradigms is outsourcing. Network operation in telecommunication industry has jumped on the top list of the operators outsourcing activities. Network operation refers to the daily management of all Mobile network activities including and not limited to field maintenance, sites integration, optimization, incident management and spare parts management, of the mobile network base stations. It also include supervising the mobile network, capacity management, fault management as well as resolving software problems. The term also could cover capacity planning and overall network quality controlling (Friedrich et al. 2009). The issue that such activity requires huge number of resources to cover all the mobile network extended across the countries. In addition to high training and skills.

  1. Supplier’s View of Outsourcing Network Operation Services

Typically the firms’ best positioned to offer network operations service by definition, they have the deepest knowledge of the equipment are the mobile telecommunications equipment manufacturers themselves, since being serviced. However, given that a mobile operator’s network is typically based on a multi-vendor environment, The vendors now have back to back agreements together in order to offer the outsourcing and managed service not only to the operations related to their own products but as well can cover other vendor products.Such agreements have simplified the operation processes,as the operstors instead of having multiple outsourcing agreements with different vendors can now have a single agreement with a big vendors .This big vendors will have the others working as third parties behind him, transparent to the customer , here the network operator.
Those big network operations services providers run Global Network Operation Centers (GNOCs) that could cover even several operators in different countries.For example in November 2016 The Giant telecommunication operator Orange inaugurated Abidjan’s GNOC with the Big Vendor HUAWEI in Cote d’Ivoire  Responsible of the management and supervision of the facilities network in nine countries (Cameroon, Ivory Coast, Guinea, Guinea Bissau, Mali, Central African Republic, Niger, Congo, and Senegal). The aim is to achieve a more efficient organization, for an excellent customer experience, satisfying their needs in terms of quality of service and getting rid of the costs burdens.

  1. Operators View of Outsourcing Network Operations Services

Many of the mobile network operators were established in the era of 2G mobile technologies. Most of them were not able to cope with the rapid changes in technologies up to 4G and 5G and fell down with limited experienced resources to satisfy the needs of their customers from service quality. Beside the high churn of experienced employees seeking better career opportunities mostly in the network equipment’s/Software manufacturers/developers.
Most mobile operators view their physical network as a main differentiator vis-a-vis other mobile network operators, including virtual ones as well. Accordingly, many consider their network an important strategic asset (Friedrich et al. 2009). As a result, while mobile operators are vigorously undertaking the outsourcing of network operations services, many choose to continue to claim legal ownership of the underlying assets and choose to continue owning the responsibility for the associated strategic decisions (Anderson and Williams 2004).
Normally, mobile operators start by outsourcing less critical functions like network maintenance and rollout. If proven a success, they extend the agreement to include a larger scale of network operations functions (Friedrich. et al. 2009). Moving up even to reach the GNOC model explained before to achieve better results.
Finally, in an effort to continue to squeeze the operational costs, some operators are exploring sharing their physical infrastructure with other operators to create one common network infrastructure, which can be managed by one external provider. If this trend takes hold, it will make the case for outsourcing network operations services even more compelling.

  1. Theoretical Foundations of The Proposed Work

In this section, the researcher will present some of the theoretical ideas that will be used to underpin the development of the conceptual Model.
A number of outsourcing studies in the telecoms industry have employed either Transaction Cost Economics (TCE) as Edoardo Mollona & Alessandro Sposito (2008), Jiang, B., Belohlav, J. Young, S. (2007).   Or Resource-Based View (RBV) as Aron, R., Singh, J.V.(2005) Ellram et al.(2008); Youngdahl and Ramaswamy (2008)  or Agency Theory as Logan, Gorla, Narasimhaiah ; Somers, Toni M.(2014) theoretical frameworks to undertake their analysis. The three aforementioned theories will be used jointly, as a theoretical underpinning for the proposed model, which is possible to accomplish with our System Dynamics approach.
System Dynamics models are computational representations of the causal structure of systems—be they physical, social, or economic—as a set of differential equations using stock and flow variables. The stock and flow variables are arranged in structures called causal loops to eventually form Causal Loop Diagrams or CLDs – A further detailed overview will be presented in Section 3.7.
One of the most important reasons to use system dynamics it its capability to manage soft variables included in our model like ” Resource Capabilities” variable, as far as soft variables are concerned, numerical data are often unavailable or non-existent. Despite this, such variables are known to be critical to decision making and, therefore should be incorporated into system dynamics models.
The stocks and flows constituting each loop in the researcher’s proposed CLD will have its theoretical underpinning tied to one of the three aforementioned theories, for which we present a short overview next.

  1. The Resource Based View (RBV) theory:

One classical definition of a firm is that it is simply an organizational structure that co-ordinates, facilitates, exploits and connects the activities of its resources (Penrose 1959). Throughout the life of a firm, organizational practices specific to the firm are developed, honed and perfected. The successful organization will ingrain these practices into their DNA, becoming inseparable from its identity. A firm whose resources are rare, not substitutable, valuable and imperfectly imitable is well positioned in the marketplace to possess a sustained competitive advantage – that is the Resource Based View (RBV) theory (Barney 1991).
Accordingly, increasing the resource specificity within a firm enriches the common language, knowledge and procedures, which in turn enhances the efficiency of a firm’s operations (Poppo and Zenger 1998).
From an outsourcing perspective, the implications of the RBV theory then are that firms should focus on and nurture their core set of competencies that offer them a competitive advantage in the marketplace. On the other hand, activities that are not directly impacting a firm’s products, services and customers, i.e. non-core, non-strategic activities, should be outsourced (Quinn and Hilmer 1994).

  1. Transaction costs economics (TCE) theory:

Transaction Cost Economics is a theory in the field of Business Strategy. It addresses questions how firms define their boundaries, i.e. which goods and services should be produced by a firm and which ones should be procured from the market. A key factor in deciding the firms’ boundaries are transaction costs (Williamson 1991).
Consider the case whether a firm should or should not outsource software development of an IT application. If a firm elects to develop the application in-house, it’s production costs including development team costs, software tools, etc., while it’s transaction costs include recruiting and assembling the development team. If a firm elects to outsource the development of the application, then the production costs include the price the supplier charges while the transaction costs include the cost of search for, procuring, negotiating and managing with the supplier.
Economies of scale and specialization play a key role in realizing efficiencies for external supplier. This competitive advantage renders the supplier an attractive option to deliver outsourced services (Poppo and Zenger 1998). A firm will then have to compare whether the transaction costs relating to outsourcing an activity along with the outsourcing production costs to internal production costs (Williamson 1991).
An illustrative example from the telecommunications industry is a supplier that builds Global Network Operations Center (GNOC) to serve the networks of many operators. In this case, it is evident that economies of scale achieves great efficiencies as the fixed costs of setting up the centers’ infrastructure as well troubleshooting team is incurred once upfront and then shared  (put in the service of) many customers and ensuring high utilization of these resources with little idle time. That is in contrast with many Network Operating Centers of smaller size (Hecker and Kretschmer 2010).
To a first degree, two factors dominate the transactions costs in the Telecommunications industry, namely, Frequency of the transaction, the nature of the transaction (whether simple an generic, vs. complex and specific) and the unpredictability of the demand.
Frequency of the Transactions: On the commercial front, Network operators typically sign long-term contracts (3 years – 5 years) with external suppliers, thus diluting the impact of the one-time costs related to the search, procurement, and negotiation with the supplier. The only aspect of the transaction cost that is incurred throughout the engagement is that of the management/supervision of the contract.
Nature of the Transaction: The typical external suppliers that offer telecommunications services are the major equipment vendors, who have a strong knowledge and domain expertise not only on the equipment they produce, but also on the other major vendor’s equipment. As a result, the nature of the transaction, while complex and specific, it is not rare and inimitable. Furthermore, given the management interfaces in telecommunications networks are standardized and that all major equipment vendors can manage other’s equipment, an operators can switch suppliers if required, even though there will be an overhead on the transaction cost in this case.
Unpredictability of Demand:
Market demand in the Telecommunications industry is constantly changing, ebbing and flowing (Crandall 2009). With their limited capabilities operators cannot react adequately to such frequent and abrupt changes.
To summarize, the outsourcing in the Telecommunications industry is a viable option according to the Transactions Cost Economics theory as external suppliers are able to realize efficiencies through economies of scale with the transactions costs that are more favorable than in-sourcing.

  1. Agency Theory:

Agency Theory explains situations where a principal delegates work to an agent (Williamson 1985 Williamson, O., E.,(1985) ‘The Economic Institutions of Capitalism’, Free Press New York). Typical examples of a principal are a company’s shareholders, whereas the agents in this case are the company’s managers. The two key issues that the theory addresses are: (1) how to align the interests of both the principal and the agent so that they are not in conflict and (2) how to reconcile the risk tolerances.
In the context of the telecommunications industry and outsourcing, the effects of the agency theory are managed through measuring the performance of the external network operations service providers (agents).  In this case, the performance of the external network operations service providers manifests itself and is measured directly by the quality and reliability of the operator’s network – which is the ultimate measure of the success of an operator.
In the above scenario, If the agent were to act opportunistically to further his interest at the expense of the principal, the network quality indicators would immediately start to suffer and the principal would take corrective actions. This quick feedback mechanism acts to ensure the interest of the principal and the agent are aligned (Poppo and Zenger 1998).

  1. Integrated Framework

The theoretical framework is based on addressing the application of TCE, RBV and Agency theories in an integrative framework to understand if it is profitable for local telecommunication network and service providers to outsource activities to international managed service providers. Specifically, the researcher applies RBV to address the questions related to the strategic importance of those activities, assessing whether they are core competences of the firms or not. By contrast, TCE will assist in assessing whether economic advantages are actually achievable by outsourcing activities. Finally, Agency theory will be used to assess the quality measure.

  1. System Thinking
    1.                  Perception

Information comes to the brain via our senses (sensations); the brain then interprets this information to produce what we term perceptions; this interpretation process is not precise, can be misleading and thus is the cause of many misinterpretations and misunderstandings.
The human brain is often an unreliable machine and it is important to realise this.  There are many recorded cases where:

  1. people genuinely believe things that later can be proved never happened and
  2. things happen but are not perceived by observers.

Kant introduces two terms – the phenomenal world (which is the world as is observed) and the nominal world (which is the world as it is). He posited that it was impossible to know the nominal world. Our perceptions also are the basis of our culture so it is important to examine them. The researcher focused this session around several observations.

  1. It’s easy to see something that isn’t there. This deals with false perceptions. Some problems are impossible to solve if one assumes a restriction that isn’t stated (called an artificial boundary). If the artificial boundary is relaxed then the solution is easy. People are often prevented to solve problems because they assume things that are not actually there!
  2. People perceive things differently.
  3. It is sometimes hard to see what IS there.
  4. How we approach a situation alters our perception of it.

This introduces the idea of analysis. The way we analyse something can give skewed results. The example given is that of cutting an orange where depending which way it is cut gives different views of its inside. The Mind is very easily deceived.
This is covered by showing visual illusions. It also covers how the brain “fills the gaps” i.e. if information seems to fit a pattern, then the brain completes the pattern even though the pattern may not be there.
The conclusion is that the way we perceive is EXTREMELY important and the question then arises “How do we know what is correct”.

  1.                  Types of thinking

By examining the thinking that was needed to administer countries up until the middle of the 20th century; the researcher is trying to show that such a system of governance required a few strategic thinkers but a vast number of people who did not think but just followed orders.  This situation has changed in the last 40 years (greatly influenced by the discovery of computing power and the internet) and many more people are required to think and make strategic decisions.
Now we will examine classical ways of thinking:

  1. Logical Thinking – this is usually expressed as
  • Premise a;
  • Premise b;
  • Conclusion.

This is obviously a very useful way of thinking especially when one is solving a crime (e.g. Sherlock Holmes). However it has its weaknesses when developing strategy because of what has been discussed previously. There could be a mistake in the premises and therefore the conclusion could be wrong. Also the premises might not be independent of each other which also affects the conclusion.
By definition, an expert is expert in a very restricted area and his knowledge outside that area is not reliable .Obtaining knowledge can be compared to digging a hole. Logic is the tool used to dig the hole but if the hole is in the wrong place then no amount of improvement will make it in the right place. It is easier to keep on digging than starting again An expert is an expert because he understands the present hole more than anyone else so he is found at the bottom of the deepest hole.
Concepts of expert thinking have two fallacies:

  1. If you work logically on a situation you will eventually arrive at the right answer (persistence).
  2. The established way of looking at a situation is the only possible way because it is RIGHT (culture, background, education )’

There are many circumstances where these two statements do not occur.

  1. Systematic Thinking

This can be described as thinking in a logical order:

  • First do this;
  • Then this;
  • Then this.

Examples would include the “Toyota Way” – which is used in car manufacturing and most production lines. However, humans cannot be treated as units in a production line and therefore excessive reliance on Systematic thinking is dangerous.

  1.  Reductionist Thinking.

Reductionist Thinking is often known as “analysis.” In this type of thinking one breaks a problem down into small parts and solves each part. Then one put the solutions together to get a complete solution. This is a useful diagnostic tool,but this type of thinking is not applicable when the parts are not independent. If the parts are all interconnected then it is impossible to use this type of thinking. One needs another type of thinking which is can be called Holistic Thinking.

  1.  Holistic Thinking

The important element of this type of thinking is that the sum is greater than its parts. This is especially true when one is forming a team. A good team is more than assembling the best players, This is often seen in football. The example of slicing an orange has already been discussed. I also used the old example of six blind men describing an elephant. Each gave a different description depending on which part they were feeling (see figure 5.1).

Figure 5.1 Multiple Viewpoints

  1.  Creative Thinking

Often to solve problems a third type of thinking (creative thinking) is needed. Examples are given and then I concentrate on a particular type of creative thinking called “thinking outside the box” or Lateral Thinking. Lateral Thinking recognizes dominant polarizing ideas and then looks for alternatives. It does not always use logic and it recognizes the role of chance in any discovery. Extensive use is made here of the books by Edward de Bono who first coined the name “Lateral Thinking”.
The researcher then discussed “Thinking Traps” ; when one find himself in a situation that he has faced before and what is coming to your mind as thinking is the same as before; and you know well it didn’t work. You feel you are stuck in your thinking.
Something that seems normal or inevitable today began with a choice that made sense at a particular time in the past but has survived despite the eclipse of the justification for that choice.
Hebbian Learning
Donald Hebb was a Canadian Neuroscientist who first postulated that thinking is caused by Neurons firing in the Brain. If two neurons repeatedly fire simultaneously then the pathway between them is enhanced. The enhanced pathways form what we call patterns. This is learning by reinforcement. It is the basis of machine learning (sometimes called Pavlovian Learning) and has given birth to neural networks

  1.                  System thinking approach
    1.          Introduction

System Thinking is a discipline that does not focus on the parts alone, but rather the whole picture and specifically how the parts interact with each other.
Today, with the rapid changes in technology, the growth in systems complexity, the cloud and virtualization world and more, systems thinking is needed more than ever!
Systems thinking is a discipline for detecting the structures governing complex situations, and for determining the various changes which lies within.
In many cases, a manager’s intuition is not necessarily underpinned by sound logic; in fact it may appear not very logical. A manager may have a “gut feel” that the obviously rational choice or course of action, while suitable for the short-term, will have a detrimental effect in the long term. The explanation often lies in the fact that in the instances when a manager’s intuition is indeed correct (counter the logical course of action), it is because the manager had a keen sense of the complexity of the systems and the interrelationship between its component parts.
As managers become more comfortable with systems thinking as an alternative framework, they come to find their intuitions explainable.

  1.          Background

The beginnings of System Thinking can be traced to the field of system dynamics, which was founded in 1956 by Professor Jay Forrester of Massachusetts Institute of Technology. He recognized the need for a better way of testing new ideas, and in the same way the ideas can be tested in field of management especially strategic planning. The concept of System thinking helps people in understanding the systems problems and finds a solution to those problems and considering all of them as a whole system, and improve their understanding of planning systems .
According to Hammond, systems theory is the representation of the relationships between  the social, technological, biological, ecological and psychological aspects of our complex lives (Hammond 2010: Book – The Science of Synthesis). Notable scientists in the field of systems thinking include Ludwig von Bertalanffy, Kenneth Boulding, Russell, Ackoff, Stafford, Wiener, Shannon and Weaver, John von Neumann and Laswell.
At the same time, Strategic management as a discipline was getting off the ground in the 1950s and 60s. Key early contributors to Strategic Management include Alfred D. Chandler, Philip Selznick, and Peter Drucker. These contributions include Philip Selznick insight of matching the organization’s internal factors with external environmental circumstances currently known as SWOT analysis, as well as Alfred Chandler’s recognition of the importance of coordinating the various aspects of management under a unifying strategy and coupling it with a long-term perspective (Obliteration et. al, 2010). On the other hand, Peter Drucker was a prolific strategy theorist. He wrote many management books and had a long professional career spanning five decades. He had many contributions, however two contributions stand out. Firstly, he developed the concept of management by objectives and secondly he helped in predicting the importance of intellectual capital (Odiorne, 1965).
System Thinking Approach and Strategic Planning System thinking is a holistic way of thinking, fundamentally different from that of traditional forms of analysis in which the observer considers himself the part of reality as a whole system. System thinking resists the breaking down of problems into its component parts for detailed examination and focuses on how the thing being studied interacts with the other constituents of the system – a set of elements that interact to produce behavior of which it is a part. By examining the links and interrelationships of the whole system, patterns and themes emerge which offer insights and new meaning to the initial problem. This means that instead of taking smaller and smaller parts or view of the system taken for study, it actually works by expanding its view by taking into account larger and larger numbers of views or parts of the system. This procedure sometimes results in strikingly different conclusions than those generated by traditional forms of analysis, especially in those cases which are more complex or are having dependence / feedback from other sources i.e. internal or external(Obliteration et. al, 2010).
The character / nature / approach of systems thinking makes it extremely effective on the most difficult types of problems to solve: those involving complex issues, those that depend a great deal dependence on the past or on the actions of others, and those stemming from ineffective coordination among those involved and some of the examples in which system thinking has proven its value include: Systems thinking is a management discipline that concerns understanding a specific system by assessing the interactions and association between components that encompass the entirety of the system  (Odiorne, 1965).
System thinking is an integration agent of effective enabler for decision making for important and permanent solutions of this complicated world. It has been developed as a significant tool for making important decisions and strategic planning. System thinking concepts usually consider strategic planning by contributing at the initial level of the issues and analysing all the possible reasons for the same going down the various levels of causative factors. An incorporation of system thinking along with strategic planning will incorporate the solution capability by offering effective solutions and planning (Werhane, 2008).
The entire system is a systems thinking view of all the organization in association to its environment. It offers a way of understanding, assessing, and speaking about the design of organization as a complex composition of various interconnected systems that have to work for the whole to be able to function successfully. Whole systems include different units, which include various entities (ex:- policies, practices, and individuals) and could be broken down into additional sub systems (Assaraf & Orion, 2005).
Systems could be thought about as having external boundaries or having open links with the environments. Open systems perception is more common and sensible. Boundaries for the system may be selected and defined at a suitable level for the specific purpose after careful consideration; ex: – the education system and all the school system. Similarly, systems can be selected and defined at various levels and can then operate alongside with each other. An example would be the finance, decision making, and accountability system (Werhane, 2008).
Organizations as entities can also suffer from significant systemic failure. This takes place in the whole or high level system where failure occurs between and among the different system elements that have to work together to ensure success. Systemic failure factors may consist of confused goals, flawed systems, and weak understandings that promote loyalty to various subordinates, instead of super ordinate aims and goals, insufficient feedback, poor cooperation, and a lack in accountability. The success of the whole system needs a performance management system that is in the level of various individual systems and their leadership. The features could consist of group and team level setting of goals, decision-making, development, communication, rewards, and accountability. The goal is to focus on what connects people together and what connect systems together instead of functional performance only (Zoller & Scholz, 2004).
The failure of whole systems may take place next to functional success. The leadership could be successful but not integrated into all the system owing to an inadequacy of systems design and understanding. The whole system can be successful only by managers cooperating across various functional systems. All the systems can fail only when leadership at the degree of the whole system ends up failing, and where various senior managers are included in the process. Therefore, this failure is labelled as a leadership systemic failure (Eilam, 2012).
When systemic failure takes place, individual executives who work at a lower sub system level could be completely free from any responsibility or blame. They could argue that it was a bigger system that ended up failing. They could also claim that specific systems that mix with their own work will end up letting them down. Responsibility and accountability for successful designs and running integrated whole systems will have to rest somewhere (Forrester, 1994).
Anticipating and comprehending how the system works is support to work, is currently working, and how it reacts under pressure, can practically defeat and let down many executives. To prevent censure for this difficult challenge, they usually seek recourse to the hollow mantra of ‘’lessons should be learned’’. Also, they attempt to divert many executives (Forrester, 1994).
The leadership challenge is emphasized by the understanding that for every legitimate and official system, there will be a shadow system. The shadow system is where all the different non rational issues are, such as politics, greed, power struggles, and ambitions. There are some cases where the system can overpowerful and lead to leadership failing. However, leadership can completely fail the system. A big leadership failure within or down a company is called ‘’systemic’’ (Forrester, 1994).
System thinking theory incorporates another level called the chaos theory.  In this case, chaos doesn’t mean confusion but refers to the different system dynamics that apparently have little or no order at all. In these systems, minor changes can lead to complex changes in the system. The chaos theory has also introduced brand new perspectives to examine complicated systems, like biological, weather, and the solar system. In the framework of consulting projects, systematic is mainly about setting goals, collecting, and assessing feedback about achieving goals, and then adjusting different activities to fulfil the goals in a more effective way (Werhane, 2008).

  1. Decision support Systems

A Decision Support System (DSS), is typically a computer-based information system that helps managers in their decision making process. In addition to providing data storage and retrieval, a DSS will support for model reasoning, building and problem solving. Typical application areas of DSSs are management and planning in business, industry, and other areas in which an entity’s management will encounter complex decision-making situations.  Such systems are used to support the strategic decisions of executive management decisions in which the required time for modeling the problem in the long run (Druzdzel & Flynn, 2009).
DSSs are especially valuable in situations in which the amount of available information overwhelms the intuition of an unaided human decision maker and in which precision and optimality are a key objective. Decision support systems have the capabilities of integrating various sources of information and helping the decisions process. They can also provide a mechanism for choosing among set of alternatives, such as the methods of statistics, operations, economics, research, and decision (Druzdzel & Flynn, 2009). The efficient application of decision-making tools gives many firms a competitive advantage to make optimal decisions for their business operations and management as well as  for technological processes and their parameters plus their strategic investments (Druzdzel & Flynn, 2009).

  1. System Dynamics

System dynamics is a concept to comprehending the nonlinear behavior and actions of complex systems using stocks, internal feedback loops, and delays in time. It is also a mathematical modeling method to frame and comprehend complex issues. It was originally developed during the 1950s to assist corporate managers assist their comprehension of industrial processes. It used in the public and private sector as well to assess policies and their design (Radzicki & Taylor, 2008).
Suitable graphical user interface software developed into different user-friendly versions during the 1990s and was applied to systems. System dynamics (SD) solve the issue of simultaneity by updating different factors in small time increments with feedback and time delays which structure control and connections. The most popular SD model is the Limits to Growth model which was introduced during 1972. The model predicts that exponential population growth and capital, with restricted resource sources and perception delays, would result in financial collapse during the 21st century under different growth scenarios (Radzicki & Taylor, 2008). .
System dynamics is also categorized under system theory aspects as a technique to comprehend the dynamic behavior of complex models and systems. The foundation of the technique is the recognition that the system structure, the different circular, time-delayed feedback among its components, is usually essential in determining its behavior as individual components as well(Sterman, 2000).

  1.                  History

Jay Forrester of the Massachusetts Technology Institute first introduced system dynamics during the 1950s. During 1956, he accepted a job in MIT Sloan Management School. His main goal was to figure out how his background and degrees in engineering and science can be used in the most beneficial way, especially when it came to the main issues that lead to success or failure of organizations.
During the 1950s and 1960s, Forrester and a graduate students’ team moved the system dynamics emerging field from stages of hand simulation to form computer modeling. Richard Bennet was able to develop the first SD computer modeling language now called SIMPLE. During 1959, Phyllis Fox wrote the first DYNAMO version along with Alexander Pugh. This was an enhanced version of SIMPLE, and the system dynamics language then became the standard in the industry during the next thirty years (Nelson, 2001).
The second significant SD non-organizational application of system dynamics came quickly after the first. During 1970, Forrester was invited to a meeting in Bern, Switzerland which was conducted by the Club of Rome. The Club was dedicated to solving what its members call ‘’the mankind predicament’. These predicaments included the international crisis that could appear in the future, because of demand being put of the carrying capacity of Earth (its renewable and non-renewable resources and its pollutants disposal) by the world’s significantly increasing population.
At the meeting, he was asked if SD could be effectively used to solve mankind predicaments. His answer was that it effectively could. On his way back home from the meeting, Forrester developed the first system dynamic model draft of the world’s socioeconomic system and called it WORLD (Nelson, 2001).

  1.                  System dynamics components

The different system dynamics elements are feedback, accumulation stocks flows, and delays in time.
Often, if management team can agree on a causal model of the company; many problems could be solved without building any more models.
Causal loops
In the methodology of system dynamics methodology, an issue or system (such as an ecosystem or mechanical system) is represented in the beginning as a casual loop diagram. This is a simple map system with all its different constituents, factors, and interactions. By capturing different interactions and the feedback loops, a causal loop diagram discloses the system structure. By comprehending the system structure, it will then become possible to determine the behaviour of systems over a certain amount of time (Roberts, 1978).
The causal loop model of the new product could look like this:-
The diagram has two feedback loops. The positive reinforcement on the right demonstrates that the more individuals who have adopted the new product, the more powerful the word of mouth effect are going to be. There are going to be more product references, demonstrations, and reviews. This positive feedback will generate sales that continuously grow.
The second feedback loop is negative reinforcement or balancing. Growth is going to be continuous as more individuals adopt. Therefore, there are going to be fewer possible adopters by time.
Both of the feedback loops act in a simultaneous manner, but at various time they could have various strengths. Therefore, one could expect increasing sales in the first years, and then decreasing sales during the later years.
In the dynamic causal loop model:
Step 1: positive green arrows demonstrate that Adoption rate is the purpose of Potential Adopters and Adopters
Step 2: negative red arrows demonstrate that the potential adopters decrease by the rate of adoption.
Step 3: positive blue arrows demonstrate that Adopters increases by the rate of adoption (Minsky, 2014).
Stock & flow model
Causal loop models help in visualizing the structure of systems and their behavior, and assessing the system in a qualitative manner. To perform more detailed quantitative assessment, a casual loop model is transformed to stock & flow diagrams. Stock & flow model assist in studying and assessing the system in a quantitative manner. These models are built and then simulated using software. Stocks are the terms used to describe entities that deplete or accumulate by time. A flow is the change rate in stocks.
A flow is the accumulation rates of stocks. In this example, there are two main stocks: Possible adopters and then Adopters. There is only one flow in the model, which are the new adopters. For every adopter, the stock of possible adopters decreases by one and the adopters’ stock increases by one.
The real system dynamics’ power is utilised by simulation. Even though it’s possible to carry out modelling using spreadsheets, there are different software packages that have been specially optimized for this reason. The steps included in a simulation are:

  • Defining the boundary of the issue.
  • Identifying the most significant stocks along with flows that change the level of stocks.
  • Identifying information sources that affect the flows.
  • Identify the main loops of feedback.
  • Illustrate a casual loop diagram that associates the stocks, flow, and information sources.
  • Write equations that determine the level of flows.
  • Estimate parameters and conditions in the beginning. These can be estimated using different statistical techniques, expert opinion, research data of the market, or other important information sources (Jorgen, 1980)
  • Simulate models and assess results (Minsky, 2014).

In this situation, the equations that change these two stocks using the flow are:

    {displaystyle {mbox{Potential adopters}}=int _{0}^{t}{mbox{-New adopters }},dt}

Equations in discrete time
This includes list of equations in  time, in their execution order in every year, for the first year to year.
Results of dynamic simulation
The results of the dynamic simulation demonstrate that the system behavior would be to have development in adopters that go after a classic s-curve shape.
The increase in adopters is very slow in the beginning, then exponential development for a period, followed by saturation (Minsky, 2014).
Equations in constant time
To get intermediary amounts and accuracy, the model can work in continuous time: the amount of units was multiplied and the values were divided in a proportional way. These values will usually change the levels of stocks.
In this case, the fifteen years are going to be multiplied by four to get sixty trimesters, and the value is then going to be divided of flow by four. Dividing the amount is the easiest with the Euler technique, but other techniques could be utilized instead, like Runge-Kutta techniques. This list of equations is in constant trimesters’ time, which is equal to one to sixty (Minsky, 2014).

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