Decision support systems in small firms: decision making with financial information

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(1)2010:162. BACHELOR THESIS. Decision Support Systems in Small Firms Decision Making with Financial Information. Johan Andersson Jesper Sandlund. Luleå University of Technology Bachelor thesis Business Administration Department of Business Administration and Social Sciences Division of Management Control 2010:162 - ISSN: 1402-1773 - ISRN: LTU-CUPP--10/162--SE.

(2) Decision Support Systems in Small Firms: Decision Making with Financial Information. Luleå University of Technology Bachelor’s thesis Department of Business Administration and Social Sciences Division of Management Control and Accounting. Johan Andersson Jesper Sandlund.

(3) Preface With this preface we kindly want to thank the people who have helped and supported us throughout the writing of this thesis. . We would especially like to thank the CEOs who participated in our research. . We would also like to give our deepest appreciations to our external supervisor Peter Wanger and our internal supervisor Sven Andersson, for their valuable comments and support. . Luleå, Sweden, 26 May 2010. Johan Andersson. Jesper Sandlund. . . .

(4) Abstract The main purpose of financial information is to provide a basis for decision making. One way to gather financial information is to use a Decision Support System (DSS). A DSS supports every phase of the decision making process and can integrate a decision maker’s own insights into the decision support data. The main objective of our thesis was to conduct a pre-study for the development of a piece of software, designed as an application to an existing financial information system. In order to function as a pre-study our thesis had to be able to answer the general research problem: How can decision makers’ decisions in small firms made with the use of financial information from decision support systems be described? In order to study the general research problem mentioned above we divided it into three separate research questions: 1. How can decision makers’ usage of existing DSS be described? 2. How can decision makers’ use of financial information be described? 3. How can decision makers’ decision making with financial information be described? This thesis has been conducted using a qualitative research methodology with an actor perspective. The research approach used is deduction and the research strategy in this thesis consists of five case studies. The results and conclusions show that CEO A, B, D and E consider financial information very useful when making decisions. Financial information is considered being especially useful for decisions that have crucial financial consequences. The results and conclusions further show that CEO A, B, D and E in this study are using Microsoft Excel as a DSS in order to make decisions, and not their financial information systems. Furthermore, neither CEO A, B, C, D nor E used a DSS for decisions concerning the daily running operations. Finally, our thesis shows that a DSS is most useful in a small firm when the decision maker has a lot of time available making the decision. The thesis further indicates that a DSS will be most useful in a small firm where the decision maker is faced with familiar situations or problems and not where he or she faces never before experienced situations or problems.. .

(5) Sammanfattning Det huvudsakliga syftet med finansiell information är att det ska utgöra ett stöd för beslutsfattande. Ett sätt att samla finansiell information är att använda sig av ett beslutsstödssystem. Ett beslutstödssystem stödjer varje fas i beslutsfattandeprocessen och kan integrera en beslutsfattares egna insikter med beslutsstödjande data. Denna uppsats huvudsakliga syfte var att utföra en förstudie för utvecklingen av en mjukvara, som ska bli en applikation till ett befintligt finansiellt informationssystem. För att kunna fungera som en förstudie var vår uppsats tvungen att kunna besvara det generella forskningsproblemet som hittas i denna uppsats: Hur kan företagsledares beslut i små företag gjorda med stöd av finansiell information från beslutsstödssystem beskrivas? För att kunna undersöka och besvara det generella forskningsproblemet som nämns ovan delade vi upp problemet i tre separata forskningsfrågor: 1. Hur kan företagsledares användning av befintliga beslutstödssystem beskrivas? 2. Hur kan företagsledares användning av finansiell information beskrivas? 3. Hur kan företagsledares beslutsfattande med stöd av finansiell information beskrivas? Denna uppsats har utförts genom att använda en kvalitativ forskningsmetodologi med ett aktörssynsätt. Den forskningsansats som har använts är deduktion och forskningsstrategin som har använts i denna uppsats är fem fallstudier. Resultaten och slutsatserna i denna uppsats visar att VD A, B, D och E anser att finansiell information är väldigt användbart som stöd vid beslutsfattande. Finansiell information ses som särskilt användbart vid beslut som kan ha betydande ekonomiska konsekvenser. Resultaten och slutsatserna visar vidare att VD A, B, D och E använder Microsoft Excel som ett beslutsstödssystem för att kunna ta beslut och inte deras finansiella informationssystem. Vidare visar uppsatsen att varken VD A, B, C, D eller E använder ett beslutsstödssystem vid beslut rörande den dagliga verksamheten. Slutligen visar vår uppsats att ett beslutsstödssystem är mest användbart i ett litet företag när beslutsfattaren har mycket tid på sig att ta ett beslut. Uppsatsen visar vidare att ett beslutsstödssystem är mest användbart i ett litet företag när beslutsfattare stöter på bekanta situationer eller problem och inte när beslutsfattaren ställs inför aldrig tidigare upplevda situationer eller problem. . .

(6) Table of Contents 1. Introduction .................................................................................................................. 1 1.1 Background ............................................................................................................. 1 1.2 Research Idea and General Research Problem ...................................................... 2 1.3 Research Objectives and Research Questions ....................................................... 2 1.4 Delimitations .......................................................................................................... 3 1.5 Disposition .............................................................................................................. 4 2. Theory ........................................................................................................................... 5 2.1 Decision Support Systems ...................................................................................... 5 2.1.1 Chosen Definition of a DSS .............................................................................. 6 2.1.2 Usage of a DSS ................................................................................................. 6 2.1.3 Semi‐confusing Information Systems .............................................................. 6 2.2 Financial Information .............................................................................................. 8 2.2.1 Degree of Usefulness of Financial Information ............................................... 9 2.2.2 Financial Key Ratios ......................................................................................... 9 2.3 Decision Making ................................................................................................... 10 2.3.1 Rational Decision Making .............................................................................. 10 2.3.2 Bounded Rationality ...................................................................................... 11 2.3.3 Irrational Decision Making............................................................................. 11 2.3.4 Uncertainty in Decision Making .................................................................... 12 2.3.5 Equivocality in Decision Making .................................................................... 12 3. Frame of Reference .................................................................................................... 14 4. Method ....................................................................................................................... 15 4.1 Qualitative versus Quantitative Research ............................................................ 15 4.2 Research Perspective ............................................................................................ 15 4.3 Research Approach ............................................................................................... 16 4.4 Research Strategy ................................................................................................. 16 4.5 Types of Data and Data Collection Methods ........................................................ 17 4.5.1 Primary, Secondary and Tertiary Data .......................................................... 17 4.5.2 Interviews, Observations and Questionnaires .............................................. 18 4.6 Trustworthiness .................................................................................................... 18 4.7 Selection of Respondents ..................................................................................... 19 4.8 Analysis Method ................................................................................................... 19 5. Empirical Results ......................................................................................................... 20 5.1 Interview with CEO A ............................................................................................ 20 5.1.1 Decision Support Systems ............................................................................. 20 .

(7) 5.1.2 Financial Information .................................................................................... 21 5.1.3 Decision Making ............................................................................................ 22 5.2 Interview with CEO B ............................................................................................ 23 5.2.1 Decision Support Systems ............................................................................. 23 5.2.2 Financial Information .................................................................................... 24 5.2.3 Decision Making ............................................................................................ 24 5.3 Interview with CEO C ............................................................................................ 25 5.3.1 Decision Support Systems ............................................................................. 25 5.3.2 Financial Information .................................................................................... 26 5.3.3 Decision Making ............................................................................................ 26 5.4 Interview with CEO D ............................................................................................ 27 5.4.1 Decision Support Systems ............................................................................. 27 5.4.2 Financial Information .................................................................................... 28 5.4.3 Decision Making ............................................................................................ 28 5.5 Interview with CEO E ............................................................................................ 29 5.5.1 Decision Support Systems ............................................................................. 30 5.5.2 Financial Information .................................................................................... 30 5.5.3 Decision Making ............................................................................................ 31 6. Analysis ....................................................................................................................... 33 6.1 Decision Support Systems .................................................................................... 33 6.2 Financial Information ............................................................................................ 34 6.3 Decision Making ................................................................................................... 35 7. Conclusions ................................................................................................................. 37 8. Discussion and Further Research ............................................................................... 39 8.1 Discussion ............................................................................................................. 39 8.2 Further Research .................................................................................................. 39 References ...................................................................................................................... 40 Appendix A ‐ Interview Questions .................................................................................. 43 . .

(8) 1. Introduction In this chapter the research idea and general research problem concerning our Bachelor’s thesis will be discussed. Furthermore, the research questions along with delimitations and a disposition will be presented. The job initiators of this Bachelor’s thesis are experiencing an unsatisfied demand on the market of decision support systems concerning the assessment of small firms’ use of financial information in their decision making. More precisely there is a lack of availability of decision support systems that visually show the financial information with complementing information, e.g. graphs, which constitutes the foundation for decision making in small firms. The main purpose of the initiators’ idea is to develop a piece of software that can be activated with a mouse click and present relevant information in a maximal user friendly way.. 1.1 Background According to Ax, Johansson and Kullvén (2009) and Thomasson, Arvidson, Lindquist, Larson and Rohlin (2010) a fundamental condition for a firm’s long-term survival is the ability to create profitability. Profitability is the “ability of a firm to generate net income on a consistent basis” (Business dictionary 2010) and ensures, for example, that lenders get paid, employees get job security, shareholders get yield (dividends) (Thomasson et al. 2010). In order to create and sustain profitability a firm can plan and control its operations through a term called management control or financial control (Thomasson et al. 2010). Freely translated from NE.SE (2010), management control is defined as the use of financial information to control a firm with the intent to reach certain financial goals (e.g. profitability). According to Thomasson et al. (2010) and Schuetze (2001) the main purpose of financial information is to provide a basis for decision making. Decisions made with the use of financial information affect a wide range of intercompany areas such as investment decisions, production decisions and pricing (Thomasson et al. 2010). Furthermore, Thorén (1995) argues that decision making can be improved by retrieving financial information in a faster, more frequent and user-friendly way. One way to achieve this could be by using a Decision Support System, henceforth abbreviated DSS. The concept of DSS originates from the early 1970’s and was defined as “interactive computer-based systems, which help decision makers utilize data and models to solve unstructured problems” (Turban, Aronson and Liang 2005). According to Turban et al. (2005) a DSS is a methodology or an approach for supporting decision making and the DSS is able to process large amounts of data on a frequent basis. It uses a Computer Based Information System (CBIS), which is flexible, interactive and adaptable and especially developed to solve a specific non-structured management problem (Turban et al. 2005). Marakas (2003) claims that if firms want to succeed and excel on their markets they have a need for an information system that can provide decision makers with relevant decision supporting information. Furthermore, Turban et al. (2005) argues that a DSS supports every phase of the decision making process and can integrate a decision maker’s own insights into the decision support data.. 1(45) .

(9) 1.2 Research Idea and General Research Problem Marakas (2003) argues that one should take into account that it’s the decision makers, not the DSS, who are directly accountable and responsible for the outcome of a decision. According to Bergström and Lumsden (1993) decision makers in small firms more often have little formal education in interpreting financial information (e.g. financial ratios), compared to medium-sized and large firms. Bergström and Lumsden (1993) further show in their dissertation that these decision makers use relatively little internal and external information, rarely use information systems for support in decisions and instead make their decisions on intuition and business experience. Bergström and Lumsden (1993) argues that one of the reasons for the decision makers’ low use of information systems can be related to the fact that the systems are designed with the designers’ presumptions that the decision making end-user is rational and analytical, rather than intuitive. Rice and Hamilton (1979) and Schuetze (2001) also assert that decision makers in small firms possess a limited capacity and capability to interpret and analyse the value that financial information can provide. The consequence of this is that the decision makers cannot benefit from the added value that financial information can give, because they cannot incorporate it in their management control (Marriot and Marriot 2000). Gustafsson (2004) and Jocumsen (2004) argue that financial information and analysis is mainly used in decision making when the uncertainty is low, while decisions made by intuition are more common when the uncertainty is high. However, Gustafsson (2004) further claims that decision makers in small firms are often inexperienced leaders and use financial information as a decision support independently of the degree of uncertainty. Jocumsen (2004) further state that small firms have a significantly less complicated decision process than large firms and that the less experienced a leader or manager is, the less he will rely on outcomes and experiences from previous decision rather than using financial information as a decision support. This leads us to the general research problem of this thesis: How can decision makers’ decisions in small firms made with the use of financial information from decision support systems be described?. 1.3 Research Objectives and Research Questions The main objective of this thesis is to conduct a pre-study for the development of a piece of software, designed as an application to an existing financial information system. The application is supposed to provide relevant financial information in a maximal user friendly way so that people with little experience in interpretation of financial information can use the application in order to make well undermined decisions based on facts such as financial information. The academic objective of this thesis is to explain how CEOs/decision makers in small firms make decisions with the use of financial information that originates from a DSS. According to Cooper and Schindler (2003) one can use research questions in order to make the stated research problem more structured and these research questions can work as a guideline for research. Answering the research questions should lead to an answer to the given general research problem.. 2(45) .

(10) In order to study how decision makers make decisions with the use of financial information retrieved from decision support systems, this thesis will first and foremost examine to what type of decisions existing DSS are used by decision makers, hence the first research question: . How can decision makers’ usage of existing DSS be described?. The second research question can be seen as a subsequent question to the first research question. When the usage of existing DSS has been described, this thesis aims to determine why decision makers use financial information and what financial information they use. Therefore, the second research question is stated as follows: . How can decision makers’ use of financial information be described?. After determining the results from the above research question, this thesis aims to determine to what type of decisions decision makers use financial information, which leads us to the third research question. . How can decision makers’ decision making with financial information be described?. 1.4 Delimitations Rigorously defining small business has always been difficult, and even controversial (D’Amboise and Muldowney 1988). Small business covers a variety of companies. For the scope of this thesis small firms are defined to have less than 50 employees and an annual turnover equal to, or less than, 10 million EUR1 (European Commission 2010). Firms that are excluded from the study are real estate concerns, government and municipal organisations, foundations and subsidiary companies in large international corporate groups. The focus in this thesis will be on the decision makers’ decision making and how they make decisions with financial information. Therefore, the financial information itself is not as relevant in this thesis. The thesis will also not consider the design of the graphic user interface. Because of our own financial limitations the interviews conducted in this thesis are concentrated to small firms in the county of Norrbotten, Sweden. . 1. 10 million EUR corresponds to approximately 95 million SEK (3 June 2010).. 3(45) .

(11) 1.5 Disposition In order to present a fully suitable approach to the research idea, this research study is divided into eight chapters, each signifying relevant information concerning available knowledge and resources. This first chapter has introduced the main research problem, purpose and objectives. Chapter two will give the reader a profound theoretical base for the research problem. The third chapter will address how each stated research question can be investigated by the use of relevant literature addressed in chapter two. Chapter four will discuss available methodology approaches and address our chosen research design. In chapter five the reader can find the empirical results of this study. In chapter six the reader can find the analysis of the empirical results retrieved from the interviews. In chapter seven the reader can find the conclusions of the empirical results connected to the theory. In the eighth and last chapter the reader can find a final discussion about the study and suggestions about further research. A chapter overview is presented visually in Figure 1.. Figure 1 This thesis’ disposition.. . . 4(45) .

(12) 2. Theory This chapter gives a brief overview of the theoretical areas addressed in this thesis.. 2.1 Decision Support Systems In 2003, Marakas (2003) defined a DSS as “A decision support system is a system under the control of one or more decision makers that assists in the activity of the decision making by providing an organized set of tools intended to impose structure on portions of the decision-making situation and to improve the ultimate effectiveness of the decision outcome.” In 2005, Turban et al. (2005) defined a DSS as “… an approach for supporting decision-making.” In 2008, Morge and Mancarella (2008) defined a DSS as “computer-based systems that support decision making activities including expert systems and multi-criteria decision analysis.” As one can see by looking at the three definitions above it seems like there is no exact consensus on what a DSS really is. Therefore Turban et al. (2005) have put together the key characteristics and capabilities of a DSS, which can be seen in Figure 2.. Figure 2 Key characteristics and capabilities of a DSS, adapted from Turban et al. (2005).. According to Turban et al. (2005) a DSS works as a support for decision makers, mainly in semi-structured and unstructured situations by combining computerized information and human judgement (1) in Figure 2. The DSS also gives support to all decision makers in every managerial level, from executives to line decision makers (2) and for both individuals and groups of people (3). The decisions made in conjunction with a DSS can be made once, several times or be repeated (4) and the DSS gives support during the entire decision making process; intelligence, design, choice and implementation (5) (Turban et al. 2005). Turban et al. (2005) further claim that a DSS can support a diversity of decision making styles and processes (6) and that DSS are adaptable and flexible over time (7). Furthermore, the effectiveness of a DSS can greatly increase with the use of a highly user friendly human computer interface (8). The improvement given by a DSS is in the effectiveness of decision making (timeliness, quality, accuracy) rather than efficiency (cost of making decision) (9) and the aim of a DSS is to support the decision maker, not to replace him or her (10) (Turban et al. 5(45) .

(13) 2005). Turban et al. (2005) also state that a DSS can be developed and modified by its end-users (11) and that the user is able to experiment with different strategies under different configurations because of the DSS’s capability to analyse decision making situations (12). Finally, Turban et al. (2005) state that a DSS provides access to a diversity of data sources, formats and types because a DSS can be employed as standalone tool for one decision maker or it can be distributed throughout an organisation using Web and networking technologies (13 and 14).. 2.1.1 Chosen Definition of a DSS With all this in mind, we have chosen the definition of a DSS made by Marakas (2003): “A decision support system is a system under the control of one or more decision makers that assists in the activity of the decision making by providing an organized set of tools intended to impose structure on portions of the decision-making situation and to improve the ultimate effectiveness of the decision outcome.”. 2.1.2 Usage of a DSS Marakas (2003) states that companies use DSS in order to simplify market-, strategic-, operation- and research planning. By using an information system the decision maker can easier extract the required data in order to understand the market better and compete successfully on quality, lead times, customer service and price (Marakas 1998). According to Turban et al. (2005) a DSS is needed when a decision maker is solving problems that include a combination of both human judgement and standard solution processes (e.g. semi-structured decisions). Turban et al. (2005) further state that a DSS should also be frequently used in management control and in other information-rich environments. Marakas (2003) argues that one should take into account that using a DSS does not guarantee that the benefits from the system will be attainable by all decision makers or in all decision situations. Marakas (2003) further argues that the purpose of a DSS is extending the decision maker’s capacity to process the huge amounts of information that the decision maker encounters while making a decision. A decision process can become more effective and increase the capabilities of the decision maker by using a DSS (Turban et al. 2005). However, because it is the decision maker that controls the decision making process a DSS cannot protect an organisation from decisions that are made by inadequate decision makers. Marakas (2003) therefore states that the decision maker must be able to appreciate to what degree he or she should depend on the information and output obtained by a DSS.. 2.1.3 Semiconfusing Information Systems Hedberg and Jönsson (1978) claim that problems people encounter and solve repeatedly are gradually over time replaced by standardized operations or responses as the person gains experience from acting or making decisions. If the person’s decisions are successful, Hedberg and Jönsson (1978) claim that his or her decision making will grow insensitive to change signals and increasingly rely upon their previous experiences. If a firm and its employees act in stable environments with few discontinuities the decision makers are able to make reasonable decisions based on experiences of the past (ibid.). 6(45) .

(14) However, if they act in a changing environment the mentioned behaviour causes organisational inertia that can threaten the organisation’s survival (ibid.). Hedberg and Jönsson (1978) have characterised their look upon the decision making process as seen in Figure 3.. Figure 3 Characteristics of the decision making process, adapted from Hedberg and Jönsson (1978).. Problems solved by standard operating procedures, i.e. routine decisions, are represented in Box 1 in Figure 3. Box 2 in Figure 3 shows problems that can be easy to recognise, but have a difficult solution process. Because the decision maker in this case is lacking understanding to describe and analyse the situation, this characterised decision is called “judgement”. Box 3 in Figure 3represents varied problems where the solution processes can be divided into sub processes and be analysed. Finally, Box 4 in Figure 3 represents problems where the degree of variation is high and where it is impossible to analyse the solution process. Hedberg and Jönsson (1978) name the decision in Box 4 in “construct” because the decision has ingredients of both induction and synthesis. Hedberg and Jönsson (1978) argue that a decision maker always strives towards increased rationality in his actions. Therefore a decision maker tries to “move” problems towards Box 1in Figure 3, where the manager can make the most efficient decisions. There are three ways of moving problems toward Box 1Cited by Hedberg and Jönsson (1978, p. 9), these ways are: 1. “Increase the degree of control over the environment so as to decrease the variation in problems encountered. 2. Increase differentiation by subdividing problems into smaller parts that can be worked on separately by specialists with economies of scale. 3. Model to extend the set of analyzable problems and increase the area that is subject to planning.” Hedberg and Jönsson (1978) state that a decision maker or organisation needs a lot of counter-evidence to challenge their old behaviours and they further state that additional efforts are needed to unfreeze the decision maker’s behaviours and replace them with new ones. This leads to problems regarding decision support systems and information systems (Hedberg and Jönsson 1978). Hedberg and Jönsson (1978) state that information systems are often concerned as being neutral with their respect to organisational behavioural impact because they represent 7(45) .

(15) information that can assist or aid decision makers. However, Hedberg and Jönsson (1978) argue that information systems influence organisations’ behaviours and decisions. They further claim that modern information systems have made organisations more rigid instead of more flexible to changing environments and that they may grow obsolete as the world changes. Hedberg and Jönsson (1978) argue that access to more decision aids and information does not necessarily mean that decision makers will be better informed or be able to make better decisions. They further argue that experienced decision makers need to unlearn standard decision behaviours if they are to make use of new potential and therefore an information system should be designed to stimulate decision makers to scan decision alternatives more frequently. At the same time, one should take into consideration that if a decision maker puts too much value on information and technologies such as information systems or DSS, the result may be that the decision maker drowns himself in excessive information and therefore becomes unable to make a correct decision (ibid.). Therefore, Hedberg and Jönsson (1978) argue that the designs of information systems should balance the decision maker’s exploitation of previous experience and exploration of unknown futures. Information systems that are designed to encourage decision makers to experimental behaviours constitute an essential part of the decision makers’ learning, unlearning and new structure building (ibid.).. 2.2 Financial Information Financial information differs from financial data in that financial information is useful to the decision makers whereas data are not (Bodnar and Hopwood 2001). Data are only the basic raw materials from which information is produced. If you do not know how to use the financial information then the information is useless. According to Bodnar and Hopwood (2001) the usefulness of financial information comes from its impact on the manager’s beliefs concerning events relevant to the decision process. Bodnar and Hopwood (2001) argue that in regard to planning, financial information is useful if it somehow aids the manager to predict the future outcomes under various different courses of action. Consider for example the problem of planning to modernise a factory and also consider the problem of modernising the equipment within the factory. This type of decision requires a prediction of the firm’s cash flows under two conditions; with or without modernisation of the firm’s equipment. Anything that aids in improving the accuracy of these predictions or increase their certainty will be useful to the manager (ibid.). Financial information’s usefulness can be defined in terms of its ability to assist in prediction and risk assessment for planning. However if you consider information’s usefulness for control purposes instead these concepts are not of primary importance. Financial information for control purpose primarily needs to be accurate and timely in order to be useful (ibid.). According to Bodnar and Hopwood (2001) the information of course needs to be relevant or pertinent to the decision at hand, but this usually is not a problem in a budgetary control system since the actual numbers partly correspond to the budgeted numbers.. 8(45) .

(16) 2.2.1 Degree of Usefulness of Financial Information All information is not equally useful and the timeliness of a report is important for control purposes (Bodnar and Hopwood 2001). Financial information also has properties such as quantifiability, accuracy, conciseness and relevance (ibid.). Quantifiability refers to the degree of difficulty of representing events numerically (ibid.). For example, corporate sustainable reporting, sustainable development reporting and intellectual capital reporting can be difficult to quantify. According to Bodnar and Hopwood (2001) accuracy relates to the degree which given information set measures considering what it intends to measure. It is obvious that a source of inaccuracy is errors in the data used to generate information. For example there are various ways of measuring customer satisfaction. If you measure customer satisfaction as number of complaints this is not a very accurate measure of customer satisfaction since the unsatisfied customers might show their dissatisfaction by doing business with someone else instead. Conciseness relates to the degree of detail in the information (ibid.). According to Bodnar and Hopwood (2001), in general, a concise report will be brief and to the point and the level of aggregation will also be high. Relevance is another property of information which relates to how well the information relates to a given decision problem (ibid.). Financial information derives value from its effect on decisions. However information is obtained at cost and therefore if information does not improve or affect a decision, it has only negative value since it drives costs (Bodnar and Hopwood 2001). It is easy to overvalue information. Bodnar and Hopwood (2001) claim that even if information is highly accurate and timely, has an instantaneous response time and is 100% complete these qualities are not essentially of economic value. Further calculating the value of information requires the construction of alternatives and payoffs. Generally, these can only be approximated and a careful estimation is desirable (ibid.).. 2.2.2 Financial Key Ratios Financial key ratios deal with important financial ratios. According to Sundberg and Alvner (1998) it is important to study financial ratios of a firm and not just the profit of a firm in order to decide how well the firm has performed in the past. In order to visualize what just has been stated a small example is given in Table 1. Table 1 Firm X’s financial development over time.. In Table 1 we follow Firm X during five years and in the second row we can observe profit after financial items. Here we can observe that the profit is best in year five (+710) and worst during the third year (-260). By just looking at the second row in Table 1 we cannot really decide whether Firm X was more efficient during year five than year two. For instance, just because the firm made more money in nominal terms year five than year two it doesn’t necessarily mean that they were more efficient in year five (Sundberg and Alvner 1998). This is because we do not know how much capital the firm used in order to create the profit after financial terms. If we take a closer look at Table 1we can see that despite a better profit in year five than year two the return on equity is better in year two and hence Firm X has utilised the capital more efficiently during year two than year five. 9(45) .

(17) Sundberg and Alvner (1998) claim that the important thing to remember about key ratios is that key ratios take both the amount of resources used in order to produce the profit and the profit itself into consideration.. 2.3 Decision Making According to Ax et al. (2009), NE.SE (2010) and Marakas (2003) decision making deals with making a selection between several alternatives, so called decision alternatives. Simon (1979) claims that conscious analytical decision making is rational decision making and defines intuitive and emotional decision making as irrational decision making. According to Cosgrave (1996) and Harrison (1996) decision making is one of the most important activities that a manager engages in all types of organisations, and at any level, and they also believe that decision making should be seen as a critical management control function in all parts of an organisation. Decisions can be of various nature; difficult, easy, important, routine, long-term and short-term. A manager needs information that expresses the consequences of the decision alternatives in order to make a decision (Thorén 1995). Ax et al. (2009) calls this “striving after decision relevant information”. Skitmore, Stradling and Tuohy (1989), Mellemvik, Monsen and Olson (1988) and Thorén (1995) claim that one way to reduce the uncertainty surrounding decision making is to use financial information. Skitmore et al. (1989) further argue that the knowledge achieved by financial information is of significant importance in decision making because it acts like a support for decision makers to recognize and reduce uncertainty and risk surrounding decision making. Furthermore, Mellemvik et al. (1988) and Hayes (1983) claim that the purpose of accounting and financial information is to serve as a basis for decision making. According to Ekman (1970), decisions can be divided into genuine and routine decisions. Routine decisions are defined as decisions made in familiar situations. Genuine decisions are decisions that an organisation or decision maker faces for the first time (Ekman 1970). Ekman (1970) further claim that whether a decision is genuine or routine mainly depends on the decision maker’s previous experience. A genuine decision will often be more time consuming than a routine decision because the situation is unfamiliar to the decision maker (Ekman 1970). Jocumsen (2004) states that the more inexperienced a manager is, the less he will rely on outcomes and experiences from previous decision rather than using financial information as a decision support; he has to make genuine decisions more frequently. Mankins (2004) states that the quality of a decision and the time it takes to make a decision are two essential parts of decision making. Mankins (2004) further asserts that it’s obvious that bad decisions that are made to hastily will lead to less profitability, but that really good decisions that are not made quickly enough can also worsen a firm’s financial performance. Mankins (2004) also claims that a good decision is a decision that is based on strategic and financial information, has asserted various alternatives and that the decision will have a significant impact on the organisation.. 2.3.1 Rational Decision Making Jocumsen (2004) claims that rationality implies objectiveness, goal maximization, access to complete information, the use of common sense and formal logical principles. According to Roos, von Krogh and Roos (2004) the ability to rationally structure a problem increases the more experienced a decision maker is. Bruzelius and Skärvad 10(45) .

(18) (2004) claim that making rational decisions is an important fundamental ability for any organisation. They characterise rational decisions with the features illustrated in Figure 4.. Figure 4 Rational decision making process, adapted from Bruzelius and Skärvad (2004).. However, Bruzelius and Skärvad (2004) further claim that strict rational decision making is rarely possible. A manager’s ability to identify and assess every possible decision alternative is limited and the manager will therefore, in practice, settle with an alternative that is satisfactory but not always optimal (Bruzelius and Skärvad 2004). Herbert Simon named this type of rationality as “bounded rationality” in the mid-1950s.. 2.3.2 Bounded Rationality Simon (1997) argues that striving to achieve an optimal decision is unrealistic because of human limitations. According to Simon (1997) the term “bounded rationality” describes a rational choice that takes the limitations of knowledge and computational capacity of a decision maker into account. Instead of searching for the optimal decision, a decision maker will chose the first decision alternative that seems reasonable with concern to the circumstances (Tsoukiàs 2008). Tsoukiàs (2008) and Todd (2007) claim that why rational decision making doesn’t work in practice is because the decision maker rarely has a clear appreciation of his problems and that decisions always are limited by available information and resources (time and money). Todd (2007) claims that humans generally are eager to make decisions and that decisions based on inadequately information are common. Todd (2007) further argue that even when a decision maker has access to more detailed information, decisions are often made on fast impressions rather than gathering additional relevant information.. 2.3.3 Irrational Decision Making Miljkovic (2003) states that decisions can’t always be based on a rational foundation since the information used could be manipulated. Brunsson (1991) further states that even if several different decision makers would have access to the same information the analysis of this information would be different, which is against rational decision making. Irrational decisions are best suited when the situation demands enthusiasm and participation in conjunction with a quick decision on important events (Brunsson 1991). Hatch (2002) claims that irrational decision making is characterised by a high degree of uncertainty which is a result of information shortage. Irrational decisions are made with other factors than in the rational decision making, which results in a random decision process (Hatch 2002). Because the irrational decision process is random the decision alternatives may have been based on inadequate or misleading information that doesn’t solve the problem or that decisions are made when there actually isn’t a problem present (ibid.). Opiela (2005) further claims that the massive amount of information that is available today stalls decisions because of the time it takes to filter the information. Therefore decisions are often made by inadequate or irrelevant information, which results in an irrational decision. 11(45) .

(19) 2.3.4 Uncertainty in Decision Making When retrieving financial information from a DSS, a decision maker is faced with situations characterised by uncertainty and equivocality. Galbraith (1973, p. 5) defines uncertainty as “the difference between the amount of information required to perform the task and the amount of information already possessed by the organization.” This means that uncertainty is the relative amount of information that must be acquired in order to make a decision and that uncertainty is relative to the amount of information already possessed and the amount of information required (Galbraith 1973). Furthermore, the greater the uncertainty of the task or problem is the greater amount of information a decision maker has to process (ibid.). If there is a lot of uncertainty surrounding a problem the ability to pre-plan the decision becomes limited (ibid.). Therefore decision makers try to minimise uncertainty in order to make decision more quickly and with less information processing (ibid.).. 2.3.5 Equivocality in Decision Making Daft and Lengel (1986, p.556) defines equivocality as “the existence of multiple and conflicting interpretations about an organisational situation.” According to March and Olsen (1976) the concept equivocality is distinct from that of uncertainty because equivocality is the result of an ambiguity of understanding, rather than a function of information quantity. Equivocality is seen as a lack of clarity, high complexity or a kind of paradox that leads to more than one interpretation of information (Martin 1992). Niell and Rose (2006) claim that the type of decision making that focuses on knowable facts or what is known (existing customers or strategies) are less ambiguous. They further claim that in stable environments firms may maintain a view of consistency and sustained current strategies and still prosper. However, in changing environments the firm needs to promote change and thus needs to open up and permit equivocality to be able to adapt. Niell and Rose (2006) found in their study that for experienced decision makers, equivocality promotes strategic flexibility and that less experienced decision makers see equivocality as an obstacle. Niell and Rose (2006) further claim that reducing equivocality through simplification may promote tunnel vision which makes the organisation less responsive in a changing environment. At the same time, it may be temporarily functional for an organisation with less knowledge to engage in simplification.. 12(45) .

(20) Daft and Lengel (1986) have developed a framework of equivocality and uncertainty which is illustrated in Figure 5.. Figure 5 Framework of Equivocality and Uncertainty, adapted from Daft and Lengel (1986).. Daft and Lengel (1986) claim that under conditions of high uncertainty the decision maker obtains data in order to answer objective questions and solve problems. Under conditions of high equivocality, the decision maker seeks to clarify ambiguities, define problems and reach some kind of agreement by exchanging opinions with other decision makers (Daft and Lengel 1986). In cell 1 a decision maker may encounter situations where he or she does not know what questions to ask or what problems to solve (ibid.). In these types of events the decision maker interprets information by relying on judgement and experience. By exchanging information a common judgement evolves and equivocality is reduced (ibid.). In cell 2 both equivocality and uncertainty are high. According to Daft and Lengel (1986) the cell 2 situation is characterised by rapid changes, unanalysable events and trial and error learning. The situation in cell 2 may occur by rapid technological development or new product launches. The problems in this situation may be solved by obtaining rational data in some cases and in other cases they may be solved by subjective experience, judgement and discussion (ibid.). In the cell 3situation the problems are well understood and therefore extensive discussion is not required to solve them (ibid.). Daft and Lengel (1986) claim that in this type of situation a decision maker would rely on standard procedures and policies and primarily use reports, statistical data or routine schedules. Cell 4 represents situations where uncertainty is high and the decision maker needs additional information about many problems. The decision maker knows what questions to ask and what kind of external data that is needed. The decision maker is motivated to obtain and process data to answer important questions (ibid.). . 13(45) .

(21) 3. Frame of Reference This chapter presents the framework and analysis model within this study and introduces some core concepts that are used in this thesis. With the theory chapter as a base, concepts have been put together to a frame of reference. In the frame of reference, the concepts have been brought up and divided into three theoretical areas. For each and one of the concepts a concise and brief explanation is given and what author that derives to the concept. The leftmost column in Table 2 deals with the general theoretical area that has to do with decision support systems, financial information and decision making. Further the second column deals with main concepts within the theoretical areas. The third column explains the implication of the concepts. The third column deals with questions such as: What is the DSS used for? How does the DSS encourage decision makers? Is the decision maker rational or irrational or does it depend on the situation? What type of financial information and how relevant is financial information for decision making? Table 2 This thesis’ frame of reference, showing theoretical areas, concepts, explanation of the concepts and the authors linked to each concept.. In Figure 6 the relations between the theoretical areas in our frame of reference are illustrated. This figure is considered as our analysis model.. . Figure 6 This thesis’ analysis model, showing the relations between the theoretical areas. . 14(45) .

(22) 4. Method This chapter describes the details concerning how this thesis has been carried out. The chapter is divided into eight subchapters that discuss how the research questions will be answered and how the study has been conducted. Method is a way to work in order to collect empiricism or data about the reality (Jacobsen 2002). The method is in other words an aid in order to describe the so-called reality or empiricism. In order to facilitate the understanding of this thesis’ methodological decisions a “map of research method” has been conducted, see Figure 7, where the reader can observe all major decisions taken in our research regarding methodology.. Figure 7 Map of research method modified and adapted from Jacobsen (2002).. 4.1 Qualitative versus Quantitative Research There are essentially two different research methodologies, quantitative and qualitative, that are available for use and the choice of method is based on what type of research that is going to be conducted (Jacobsen 2002). In general, quantitative research is frequently characterised by overall numerical results. Qualitative research, on the other hand, is characterised by using case studies and profound investigations aiming to create a deep understanding (Bryman, Bell and Nilsson 2005). For the scope of the research of this thesis a qualitative research methodology is of greatest use, since it is important to create an understanding of how decisions are made in practice and also what type of decisions specific information are used for. This requires a context based understanding, deep knowledge and many subjective realities possibly from different interviewees.. 4.2 Research Perspective The concept method contains different methodological perspectives. The different perspectives state different assumptions about the reality, which characteristically differentiates one from the other. Within business and administration you usually distinguish between three different methodological perspectives; analytical-, systemand actor perspective (Arbnor and Bjerke 1977). The analytical perspective rests on the assumption that the entirety differs from the sum of all constituting parts. The system 15(45) .

(23) perspective on the other hand, rests on the opposed analytical perspective. Further the system perspective rests on the assumption that the entirety deviates from the sum of all parts (Arbnor and Bjerke 1977). According to Arbnor and Bjerke (1977) the actor perspective focuses on understanding social entireties rather than taking interest in explaining individual phenomena. The understanding of social entireties is achieved with the individual actors as a take-off point (Arbnor and Bjerke 1977). The actor perspective focuses on mapping the meaning and importance that different actors put into their actions and the surrounding environment. The reality is assumed to be a social construction created by intention at different structural levels of meaning. Arbnor and Bjerke (1977) further argue that by this follows that our common language is given different meanings relative these structural levels of meaning. Entireties and separate parts become ambiguous and reinterprets continuously. In order to understand organisations, shops and firms, system attributes are not relevant, according to the system perspective. Interest should instead focus more on important actions of actors’ in a social context. Organisations in such cannot act; instead it is rather the individual actors within an organisation that performs the actions of the organisation. The research perspective used in this thesis is the actor perspective since it gives the opportunity to see the reality and its associated issues from the individual user’s pointof-view. When using the actor perspective the researcher can take part in actors’ viewpoints and thoughts surrounding a problem. Further on we can use the suggestions and possible solutions suggested by the actor in our research. The interest in this thesis is focused on the users/actors of existing decision support systems.. 4.3 Research Approach There are basically two different research methods while carrying out research. Either you use deduction, which tests existing theory, or you use induction and build up new theory from data. According to Saunders, Lewis and Thornhill (2007) an inductive approach follows data rather than vice versa, vice versa is the case with deduction. There is however a third research approach, which is called abductive research approach. This approach is a combination of deductive and inductive research approaches (Arbnor and Bjerke 1997). For the purpose of this thesis a deductive research approach has been used since the interest in this case focuses on describing how decision makers make decisions with financial information and how they use a DSS and comparing this with existing theories. According to Saunders et al. (2007) a deductive research approach is suitable when you are interested in describing what is happening rather than describing why it is happening. Furthermore Saunders et al. (2007) argue that a pure inductive approach requires quite a lot of time and is more suitable for very experienced researchers and since the time available for this thesis is limited a deductive research approach is appropriate.. 4.4 Research Strategy According to Saunders et al. (2007) the choice of research strategy will be guided by the choice of research questions, objectives, the extent of existing knowledge, the amount of time and resources available as well as the researchers own philosophical 16(45) .

(24) underpinnings. There are a vast amount of research strategies available, however for the scope of this study only some of the very common ones are going to be considered. Experiment studies the causal links between variables, whether a change in one independent variable causes a change in another variable. Survey is another research strategy usually associated with a deductive research approach and it answers questions such as who, what, where, how much and how many. Further on another important research strategy is case study. According to Saunders et al. (2007) a case is defined as a strategy for doing research which involves an empirical investigation of a particular contemporary phenomenon within its real life context. In Table 3 you can observe a comparison between different research strategies. Table 3 Research strategies, adapted from Yin (1984). . . Since the research in this thesis focuses on contemporary events and doesn’t require control over behavioural events, the research strategies experiment and history are not considered. Archival analysis is also not considered since this research strategy makes use of administrative records and documents as the principal source of data (Saunders et al. 2007). Our thesis has used primary data sources since there is very little information available in administrative records and also because the information from the administrative records is out of date. Therefore we have chosen case study as the research strategy for this thesis. According to Saunders et al. (2007) a case study is better to use, compared to a survey, when you have relatively many variables and a small sample size. In our research there are a lot of parameters affecting the decision making process. Further on the sample size will consist of five interviews which is a relatively small sample, which also supports the use of a case study.. 4.5 Types of Data and Data Collection Methods 4.5.1 Primary, Secondary and Tertiary Data According to Saunders et al. (2007) a professional case study is characterised by using several data types and sources that complement each other. While collecting data there are three different types of data possible to collect; namely primary data, secondary data and tertiary data. Primary data is data collected specifically for the research project being undertaken (Saunders et al. 2007). Primary data can be collected using several different methods such as interviews, observations and questionnaires. Collecting primary data has several benefits such as unbiased information, original data collected for your specific purpose, 17(45) .

(25) data collected from the direct population of interest. Another category of data is secondary data, which is characterised as data originally collected for some other purpose (Saunders et al. 2007). The last type of data is tertiary data and it consists of, for example, encyclopaedias, catalogues, dictionaries and annual reports. For the scope of our research primary and secondary data have been used. In order to find out what type of decisions financial information is used for in practice it is best to use primary data. Secondary data has been used for firm specific facts such as annual turnover and number of employees. 4.5.2 Interviews, Observations and Questionnaires According to Saunders et al. (2007) collecting qualitative data can be done in several ways by for example interviews, observations and questionnaires. In this study interview questions have been used. The time frame for this thesis is very limited and therefore we have used primary data. There are three main types of interviews that we will go through in order to reason about the most suitable for our research; structured interviews, semi-structured interviews and unstructured interviews. Structured interviews use questionnaires based on predetermined and standardised or an identical set of questions. With this type of interview you can easily read out each question and then record the response on a standardised schedule (Saunders et al. 2007).When using semi-structured interviews the interviewer has a list of predetermined subjects, themes and questions to be covered but the questions may vary from interview to interview (Saunders et al. 2007). Unstructured interviews are informal and this type of interview is suitable to use when you want to explore a general area in which you are interested in (Saunders et al. 2007). According to Saunders et al. (2007) this is often also referred to as in-depth interviews. In our research face-to-face semi-structured interviews have been used which made it possible for the interviewees to show us what they really meant by further showing us in the decision support system. A face-to-face semi-structured interview further supports the actor perspective (Arbnor and Bjerke 1977). The interview questions found in Appendix A are based on the theories in this thesis and the concepts that can be found in our frame of reference, previously addressed in Table 2. The interviews lasted for 1,5 2 hours.. 4.6 Trustworthiness No matter what method you decide to use in a study the need for critical review is always present in order to create trustworthy studies. In order to increase the reliability of this study the material for the interviews was reviewed by both our internal and our external supervisor. This in order to make sure that the questions focused very precise on the general research questions and the individual research questions. Further all interviews have been conducted in the same way with the same questions. Since we both were present during all interviews correctness and relevance were secured. One of us led the interview and the other took notes and asked follow up questions. The interview subjects that were being brought up during the interview were notified for the interviewees at least two days before the interview. All interview objects were asked if it was ok for the researchers to record the interview and all the interviewees were fine with getting recorded. When using a recorder interviewees can feel prevented from 18(45) .

(26) speaking freely. In order to minimise this effect each interview were started with very broad and general questions in order to loosen up the interviewee.. 4.7 Selection of Respondents When selecting the respondents to our semi-structured interviews the CEO could not have an academic degree in business or economics. The firm he was working for had to have between 10 – 40 million SEK in annual turnover. The CEO had to use a DSS frequently in support to his decision making. Finally, all CEOs had to be working in the county of Norrbotten, Sweden. We tried to get CEOs that had an academic degree (in other areas than business or economics) and CEOs that didn’t have an academic degree in order to get a wide spread of educational background. We also tried to get the largest spread possible in the type of businesses that the CEOs were operating in. Firms that were excluded from the selection were real estate concerns, government and municipal organisations, foundations and subsidiary companies in large international corporate groups. When gathering interview objects we created a list by the criteria mentioned above and then randomly called, by telephone, a total of 20 CEOs and five of them decided to participate in our research. We chose to interview CEOs because they are decision makers.. 4.8 Analysis Method In order to give the reader a better understanding of how we have analysed our collected empirical data we have created an illustration of our analysis method. This illustration can be seen in Figure 8.. . Figure 8 This thesis’ analysis method, showing relations between theoretical areas and how the theoretical areas have been analysed by seeking answers to the above stated questions.. 19(45) .

(27) 5. Empirical Results In this chapter the reader can find a presentation and a summary of the empirical results of the five CEOs that participated in this study.. 5.1 Interview with CEO A The CEO of firm A founded the firm in January 2001 with consulting services mainly within the mobile, tele- and data communication as the main focus. Firm A offers competence in 3GPP systems in the form of GSM, UMTS and LTE and onwards to other future standards. Firm A is based in Luleå, Sweden, although their market place is global. In the early days of Firm A's history the company had no more than four employees but today they have over 30 employees. Firm A have an annual turnover about 45MSEK, a 10% return on equity before taxes. In addition the firm's organisational and corporate culture is characterised very much by informal communication. The firm’s organisation is also very flat with short distance from top to bottom in the organisation. Firm A is operating in the IT consulting business. CEO A is also the founder of the parent company and CEO for both the parent company and the corporate group of the firm. CEO A has a M.Sc. in Industrial Electronics from Luleå University of Technology. When the firm was founded in 2001, today's CEO and his co-workers had to learn trivial concepts within accounting, bookkeeping, balance sheets, consolidated statement of income and non-restricted equity. CEO A has not studied economics at university or college level; on the contrary he has studied single business oriented courses outside the university.. 5.1.1 Decision Support Systems CEO A uses Visma software for bookkeeping, follow up work time and for administrating wages. When CEO A takes important decisions, that have impact on the firm’s economic performance, he usually uses a self-constructed Excel spreadsheet. The spreadsheet is constructed in such a way that it allows CEO A to experiment how different decisions affect the future performances of firm A. Financial information is imported from the financial information system Visma. Within the firm one encounters two types of decision levels, one of them on board level. These types of decision pave the way for the future of the firm. The other decision level refers to daily running operations. Within the firm CEO A states that they do not have any standard type decisions. CEO A declares that many decision making situations are driven by a demand. For instance if the security alarm stops working CEO A simply calls the service company to have it fixed quickly. He does not bother doing any extensive analysing before making the decision. Decisions regarding the market are usually evaluated by using the self-constructed Excel spreadsheet and by experimenting with different hourly rates on the future invoices. If the decision concerns a new customer then CEO A usually uses contribution to margin in order to decide whether to take the offer or not. CEO A also uses the Excel spreadsheet for decisions concerning strategy. The Excel sheet is used as a foundation in order to decide whether to stay in a market or not and to determine if the market is profitable enough or not. For decisions regarding the daily running operation of the firm 20(45) .

(28) the Excel spreadsheet is used in some cases but not in the majority. The spreadsheet is however not used for trivial decisions. CEO A states that the Excel spreadsheet is used extensively, although in a situation where the firm is faced by increasing competition and pressure on prices the spreadsheet might suggest that an offer is not profitable and one should recoil. The spreadsheet does not take into account long-term strategic aspects, which could lead to a different decision than the one suggested by the spreadsheet. CEO A further describes that sometimes focus lies too much on costs and what the spreadsheet says. For example when hiring new staffs CEO A sometimes focuses too much on the candidates salary claim and too little on their unique competence. CEO A does not make any decisions that will have an important economic impact on the firm based only on gut-feeling. CEO A usually supports the decision with financial data. At the same time he also states that the faster the decision is made the greater the chance is of missing important facts for the decision. Furthermore, CEO A describes a situation where it was specifically difficult making a decision. Due to the lack of demand from one market segment firm A had to discard a recently employed member of the firm. This decision was discussed intensively by the board and between the executive officers before they came to a decision. CEO A uses a lot of information from the financial information system that is imported into the Excel spreadsheet. Financial information that is used is for example key performance indicators (KPI), quarterly accounts, time worked per employee, total time worked, invoiced time, employee absence.. 5.1.2 Financial Information Financial information is very important for CEO A. Financial information can be also be used for almost all types of decisions in the firm. Financial information is appropriate for all decision that has economical impact on Firm A. CEO A usually uses return on sales. return on capital employed, equity/asset ratio and liquidity for the purpose of internal control and benchmarking with firms in the same line of business. According to CEO A the self-constructed Excel spreadsheet gives you a lot of redundant information for each specific decision being made. The spreadsheet does not give you just the specified information you need for each type of decision. Sorting out what type of information that is useful is you own job according to CEO A. CEO A states that liquidity over time is his most popular financial key ratio. In a typical situation of decision making when CEO A has a lot of time available he usually produces a lot of supporting documents and information for the decision in question. CEO A thinks that it is necessary to document all the decisions and the reason for the decision. If CEO A on the other hand has little time or very little time to make the decision then he usually does the documentation and research after the decision has been made. Personally CEO A is very enamoured in key performance indicators such as time worked, absence due to illness, invoiced time, and total time in project. This type of key performance indicators are very easy to relate to since they are very hands on and can be directly transferred into cash. Further CEO A states that it is better to focus on a measure that produces money than measures that constitute money. If it were possible CEO A would want information that concerns the future and not just the present value. 21(45) .

(29) CEO A can based on historical values see forecasts on future performance but it is not possible to see when a client is going to expand his business.. 5.1.3 Decision Making When CEO A makes great and important decisions he tries to evaluate all possible decision alternatives in order to make a well undermined and professional decision. If the decision is less important CEO A does not evaluate all alternatives. Decision concerning marketing and selling consulting services to specific clients is made with information from the marketing department as a basis. Further more all decisions concerning the future strategy of the firm are made jointly by the executive board. The board sets up goals for the subsidiary firms but the board lets the subsidiaries reach the goals in their own way in order to facilitate creative thinking and to create better and stronger solutions. CEO A states that decisions requiring extensive market, social and environmental research are more difficult to make. Therefore CEO A usually demands more information than what is available for making these types of decisions, which obstructs the decision making concerning these types of issues. Decisions by CEO A that is able to plan in advance of making the decision include all decisions that concern the economy of the firm. However, CEO A further states that "emergency decisions" are not possible to plan in advance. Typical decisions that take longer time to make than others include decisions that require coordination with other parties. For example when CEO A needs to discuss decisions with external parts such as auditors or labour unions. The reason that these types of decisions take longer time to make is simply because they require booking of meetings and coordination of schedules which simply takes longer time than just walking in to a co-workers office. Situations that according to CEO A are specifically difficult to interpret include situations of selling the firm's consultants to clients. It has happened that CEO A has misinterpreted the potential client’s words. In order to solve these types of issues you need to be very realistic when it comes to interpreting the potential client. When CEO A is faced with a new type problem he usually does a more extensive investigation compared to a routine decision. He does also consult from external advisors in order to make a well-undermined decision. CEO A states that decisions that are similar to previous made decisions are made by routine. In situations when CEO A does not know what factors to take into consideration in order to make a good decision he asks people within his nearest social network for advise and guidance. If this does not help he uses contacts from the bank or auditors for guidance and advice. . 22(45) .

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