Jeroen van Dijk
April 2008Jeroen van Dijk
April 2008
Improving The
Manufacturing Architecture
ABSTRACT
In this research, the current optimality of the manufacturing architecture of Philips DAP Singapore is the central theme. It is considered to be low, due to an inflexible manufacturing set-up. This leads to increasing manufacturing costs. The manufacturing architecture can be improved by improving the integrality of information, and by improving the level of knowledge and skills to use that information. (Engineering) knowledge and skills can improve the manufacturing architecture directly as well. However, in this research that relation will not be considered.
For improving the integrality of information, an information tool needs to be developed. In this research it has been made clear what a successfully implementable information tool had to look like, and which knowledge and skills are needed to work with it.
For measuring whether the information tool can be implemented successfully or not, a measurement tool had to be developed. Based on interviews with employees of DAP Singapore and literature, implementability factors were created that defined implementability. By scaling and weighing those factors, a measurement tool has been created.
User requirements on the information tool were developed by prototyping. Out of these user requirements and the measurement tool, it became clear that a present available information tool, the so-called Virtual Factory, could be used again after being upgraded. Requirements on upgrading are given in this report.
By conducting a literature study, requirements on improving knowledge and skills were created. These requirements can be divided into knowledge and skills needed to work with the information tool, and requirements on the adoption process of new knowledge and skills.
The current situation at DAP Singapore needs to be changed, according to requirements on both the Virtual Factory and on knowledge and skills. In that case, both the integrality of information and the level of knowledge and skills will be increased.
0
Index
0 Index... 4
1 Preface ... 7
2 Introduction ... 8
2.1 Philips Electronics Singapore – DAP... 8
2.2 Problem Area: Manufacturing Architecture ... 9
2.3 Chapter Overview ...10
3 Problem Analysis ... 11
3.1 Multiple Viewpoints On Manufacturing Architecture ...11
3.1.1 Strategic Viewpoint ...11
3.1.2 Financial Viewpoint...12
3.1.3 Organizational Viewpoint...13
3.1.4 Marketing Viewpoint ...15
3.1.5 Logistics and Production Viewpoint ...15
3.1.6 Information Viewpoint ...20
3.1.7 Personnel Viewpoint ...21
3.1.8 Quality Viewpoint ...22
3.2 Conceptual Model ...22
3.2.1 Categorizing Statements ...22
3.2.2 Developing the Conceptual Model...23
3.2.3 Selecting Relevant Problem And Causes ...26
3.3 Summary – Problem Analysis ...28
4 Research Design ... 30 4.1 Research Question ...30 4.2 Sub Questions ...31 4.3 Approach ...33 4.3.1 Sub Question 1 ...33 4.3.2 Sub Question 2 ...34 4.3.3 Sub Question 3 ...35 4.3.4 Sub Question 4 ...35 4.3.5 Research Question ...35
4.4 System and Boundaries ...37
4.5 Chapter Overview ...37
4.6 Summary – Research Design...38
5 Defining Implementability Of The Information Tool ... 39
5.1 Implementability Factors in the Virtual Factory ...39
5.1.2 Stakeholders In The Development Process ...40
5.1.3 Defining Implementability Statements ...41
5.2 Implementability Factors In Literature ...42
5.2.1 Overview Of Selected Literature ...42
5.2.2 Overview Of Selected Implementability Factors...44
5.3 Development Of The Measurement Tool...45
5.3.1 Defining Categories Of Implementability Factors ...45
5.3.2 Relation Between Categories And Implementability Of Information Tool ...46
5.3.3 Categorizing Of Implementability Factors From Literature ...48
5.3.4 Defining And Categorizing Implementability Factors From Virtual Factory...50
5.3.5 Scale Development...51
5.3.6 Defining Weighting Factors...53
5.3.7 Creating The Measurement Tool ...54
5.3.8 Using The Measurement Tool ...57
5.4 Summary – Defining Implementability Of The Information Tool ...60
6 Defining The Information Tool... 62
6.1 User Requirements On Information Tool ...62
6.1.1 Defining Stakeholders...62
6.1.2 Prototyping: Iteration 1 ...63
6.1.3 Prototyping: Iteration 2 ...64
6.1.4 Prototyping: Iteration 3 ...66
6.2 Reusable Information Tool?...68
6.3 Summary – Defining The Information Tool ...69
7 Implementing The (Reusable) Information Tool ... 70
7.1 Measuring Implementability Of Reusable Information Tool ...70
7.1.1 Measuring The Characteristics Of The Reusable Information Tool: Virtual Factory.70 7.1.2 Measuring The Characteristics Of DAP Singapore...72
7.1.3 Measuring The Characteristics Of Employees ...73
7.1.4 Implementability Of Information Tool Defined...75
7.2 Improving Implementability Of Reusable Information Tool ...76
7.2.1 Improving The Characteristics Of Innovation: Information Tool ...76
7.2.2 Improving The Characteristics Of DAP Singapore...78
7.2.3 Improving The Characteristics Of Employees ...79
7.2.4 New Implementability Of Information Tool Defined...80
7.3 Summary – Implementing The (Reusable) Information Tool ...81
8 Required Knowledge And Skills For (Reusable) Information Tool... 83
8.1 Required Knowledge And Skills For Reusable Information Tool...83
8.2 Adoption Process Of New Knowledge And Skills ...84
8.3 Overview Of Requirements On Knowledge And Skills ...85
9 Evaluation Of Approach ... 87
9.1 Deriving Implementability Factors...87
9.2 Creating The Measurement Tool...87
9.3 Prototyping ...88
9.4 Measuring Implementability Of The Reusable Information Tool ...89
9.5 Improving Implementability Factors ...90
9.6 Improving Knowledge And Skills ...90
9.7 Research Put Into A Historical Context...91
10 Conclusion ... 92
10.1 Research Question And Approach...92
10.2 Answering Sub Questions SQ2a, SQ3b and SQ4 ...93
10.3 Answering The Research Question...95
Glossary ... 98
References ... 99
Appendices ... 102
Appendix A.1: CAPEX Overview 2006-2007 ... 102
Appendix A.2: Product Models From 2002-2008 ... 103
Appendix B: Prototype 3 ... 104
Appendix C.1: Questionnaire ... 106
Appendix C.2: Results Of Questionnaire ... 108
1
Preface
To finish the program of Master in Technology Management at the University of Groningen (NL), a so-called master research project has to be performed. Based on this research project, a thesis needs to be written. As creating a diagnosis of a technology related problem and advising the organization with respect to the actions that have to be taken sounded most appealing to me, I have started a Diagnoses Research Project. This research project was performed at the Domestic Appliances and Personal Care (DAP) unit at Philips Electronics Singapore. This thesis or research report is the final result of that research project.
In August 2007, I started the research project, which lasted until November 2007. In the period December 2007 – June 2008 I concluded the project by writing this research report. Before, during and after both the research project and the creation of the thesis I have learned not only a lot about the topic in this project, but about myself as well.
Therefore, I want to thank everyone at DAP Singapore, and Harold Kant and Gan T.B. in particular, for offering me this great experience, and Jeroen Vos for contacting DAP Singapore and for his support during writing my thesis. Last but not least, a big thank you for my Philippine neighbor Jojo Angeles, for sharing her kitchen and diners with me.
Jeroen van Dijk
2
Introduction
This research report will start with a short introduction. In this introduction, first the company Philips Electronics Singapore will be introduced and then the focus will turn to location DAP. After that, manufacturing architecture will be the central theme in the description of the problem area at Philips DAP Singapore. This chapter will conclude with an overview of the upcoming chapters.
2.1 Philips Electronics Singapore – DAP
Royal Philips Electronics N.V. is one of the largest electronics companies in the world. It consists of three sectors: Philips Lighting, Philips Healthcare (formerly known as Philips Medical Systems) and Philips Lifestyle (formerly known as Philips Consumer Electronics and Philips Domestic Appliances and Personal Care or Philips DAP). Philips Electronics Singapore belongs to Philips Lifestyle, with one location focusing on Consumer Electronics and another on Domestic Appliances. Philips Electronics Singapore was established in 1951. At first, Philips Electronics Singapore was a trading office only, but in the late 1960’s production of portable radios started. In the 1970’s, Singapore started setting up a training centre, in the 1980’s the mass production of consumer appliances started. Nowadays, Philips Electronics Singapore comprises four main activity groups1,2:
• Philips Innovation Campus
• Regional Competence Centres
• Sales Organizations
• Industrial Operations and Support
Philips introduced the first electric dry iron in 1956 already, but in 1970 Philips Electronics Singapore started to manufacture irons3 at Domestic Appliances and Personal Care (DAP)
Singapore. Later on, the location in Singapore became the Centre of Competence (CoC), meaning that all knowledge about Philips irons worldwide is centred in Singapore. Today, Philips has become the number one brand name in the world, with respect to irons.
For Philips worldwide, Singapore is not the only location where irons are manufactured. A large part of the assembly of irons from Singapore is done in Batam (Indonesia), an island that lies very close to the Singaporean border. Throughout the years, several other satellite businesses were created. Besides DAP CoC Singapore and Batam, the network consists currently of a location in Suzhou (China)4. Singapore focuses more on designing new irons and producing critical parts, the
two satellites manufacture and assemble the regular items.
As DAP Singapore is part of the iron business unit, it not only produces irons for the external market, but for the internal market as well. The external market consists of retailers and companies throughout the entire world. The internal market consists of the other satellite businesses that use parts that are created at DAP Singapore.
1
Source: Philips People Services (PPS), Toa Payoh, Singapore.
2
Source: Website Philips Electronics Singapore.
3 Source: Public Responsibility Statement (2000). 4
DAP Singapore produces different types of products. On the one hand, parts of products are made, that are used for the internal market. These parts or kits consist of heating elements, soleplates and thermostats, all for different types of irons and all used in Philips irons. On the other hand, complete products are made as well (as given in table 1). These product categories are produced for the external market. A few other categories are produced outside of DAP Singapore, but are not directly related to DAP Singapore.
Name Product Category Products (As Of 2007)
Dry XXX
Low End Systems XXX Basic XXX Complete XXX Superior XXX Systems XXX
Table 1: Product Categories And Product At DAP Singapore Source: Production Data 2007
For a company to survive it is important to gain and maintain a competitive advantage. As Philips has been producing irons since 1956, and has become the number one iron seller in the world, it can be stated that Philips, and DAP Singapore in particular, has a competitive advantage. Gaining a competitive advantage is one thing, maintaining the advantage another. The number one factor associated with loss of competitive advantage is change (Devinney and Davis, 1997). As changes always occur, DAP Singapore has to monitor the environment for change constantly. Devinney and Davis (1997) categorize three types of change: competitor-induced change, environment-induced change and evolutionary or spontaneous change. DAP Singapore tries to respond to these changes by continuously lowering its manufacturing costs, by changing lines and capacities, by changing existing products to better meet customer requirements and by designing new types of irons. All these changes affect the manufacturing architecture of DAP Singapore.
2.2 Problem Area: Manufacturing Architecture
The term manufacturing architecture has seldom been used by practitioners and researchers and not well defined either (Mahadevan, 1998). He says that every organization consists of five layers, together making up the value chain of the company. These five layers are:
• Customer layer: represented by a combination of the ultimate customer and various others in the distribution chain (retailers, dealers).
• Core manufacturing layer: the manufacturing set-up in an organization, including areas as machining, fabrication, assembly and testing.
• Manufacturing support layer: includes supporting areas as marketing, quality, design, planning, costing, maintenance, etc.
• Supplier layer: external to the organization, consisting of a network of suppliers and (sub-)contractors.
Mahadevan (1998) concludes that essentially, manufacturing architecture defines the nature of the relationship between these five layers and addresses issues arising out of structure, systems, procedures and people. In short, manufacturing architecture provides an overall framework in which the various activities, people, and issues that are related to the production and distribution of goods either directly or otherwise are organised (Mahadevan, 1998, 1999). In this research, the core manufacturing layer, the manufacturing support layer and the layer of innovation are considered to form the manufacturing architecture of DAP Singapore.
Among other tasks, the Engineering Department of DAP Singapore tries to improve the manufacturing architecture. This is done by creating a number of possible projects that focus on optimizing the manufacturing set-up or on amending the manufacturing set-up to new products. This means a change in manufacturing architecture in both cases, as (parts of) organizational layers are being changed.
Because the investment budget is limited, decisions have to be made on which projects to accept or to decline. In a perfect world, every variable about the future situation DAP Singapore would be known, and thus a perfect decision could be made. However, as in the real world lots of variables are unknown, the best decision can only be made based on available variables. Currently, a number of variables represented by data and information exist separately across the several departments and organizational layers of DAP Singapore. Since the variables are used separately, instead of together and integrated, potential data and information, which can turn a bad into a ‘best’ decision, is lost. This can lead to a situation in which a decision is made to remove a machine, as it is not used that much, but is needed again in a relatively short time after the decision has been made. This means that another investment has to be made to acquire a new machine. To prevent this from happening, a best decision needs to be made (i.e., using the machine again is foreseen when the decision needs to be made), instead of a bad one (i.e., a machine that is hardly used is removed, but needed again later). As a best decision is unlikely to be made without an integrated overview, there is a need for that.
As there is a difference between the actual situation and the desired one, a problem exists, by definition (De Leeuw, 2000). However, a need for an integration of variables may be part of other problems, briefly mentioned in this subchapter. Therefore, a problem analysis is necessary and will be focused on the problem area as described in the previous paragraph.
2.3 Chapter Overview
3
Problem Analysis
This chapter consists of two parts. In the first part, the problem area, as defined in the previous chapter, will be analyzed further. First, multiple viewpoints on the problem area will be adopted. Next, a number of statements about subjects related to the problem area will be developed by using the viewpoints on the problem area. In the second part, a conceptual model will be created. First, the developed statements will be categorized. Next, relations between the categorized statements will be defined, which will result in a conceptual model. Finally, variables relevant for this research project and report will be selected.
3.1 Multiple Viewpoints On Manufacturing Architecture
In general, a problem does not exist on its own (Ackoff, 1978), and therefore it is likely that a so-called ‘problem mess’ exists (De Leeuw, 2000). To start structuring this problem mess, a number of statements has to be developed that characterize the problem mess. To create the statements, multiple viewpoints on the problem area will be adopted. In this way, statements about characteristics of the problem area that can be somewhat hidden in the organization can become clear. A lot of different sets of viewpoints exist. For example, one of those sets can be a set of stakeholders involved in the problem area. They can all have different ideas about what will be the most relevant issue regarding the problem area. However, as the set of relevant stakeholders is not clear at the moment, another set of viewpoints will be used.
This research will focus on manufacturing architecture and the relevant issues related to it. As all functional areas are involved in the problem area, the problem area will be analyzed using the functional areas as a set of viewpoints. De Leeuw (2000) describes eight common functional areas, which will be used for developing statements. The corresponding viewpoints are strategy, financial, organization, marketing, logistics & production, information, personnel and quality viewpoint.
The statements will be created based on literature, articles, interviews with employees and material available at DAP Singapore5. Statements related to the manufacturing architecture in
general and the investment decision process in particular only will be taken into account. This means that issues not related, but nevertheless considered as problems will not be part of this problem analysis. The statements found in the following subchapters will serve as an input for the creation of the conceptual model.
3.1.1 Strategic Viewpoint
Both Porter (1980) and Treacy and Wiersema (1995) identify three competitive strategies for creation and maintenance of a competitive advantage, but those three share the same characteristics. Porter (1980) identifies cost leadership, differentiation and a focus on a niche market. In the same order, Treacy and Wiersema (1995) diversify operational excellence, product leadership and customer intimacy. DAP Singapore focuses on two of those competitive strategies:
differentiation / product leadership and cost leadership / operational excellence. This is supported by three reasons.
The first reason can be subtracted from the mission statement of DAP Singapore. The mission is “to create breakthroughs exceeding consumers’ expectations by achieving a world class innovation and industrial competence”6. DAP Singapore translates this into maintaining a competitive
advantage by focusing both on differentiation / product leadership and on cost leadership / operational excellence strategies, which is stated in the same mission statement.
The second reason is the division in tasks between the Engineering Department and the Research and Development Department (R&D). Roughly said, the first one focuses on improving parts of the existing manufacturing set-up, the latter one on the creation of new and innovative products.
The third reason can be derived from the overview of capital expenditures (CAPEX) for 2006 and 2007. An overview of the CAPEX for these years is grouped into six categories. ‘New products’ and ‘quality’ are considered to support product leadership, ‘mechanizations and technology’ to support operational excellence. The other three are considered to be not directly related to one of both competitive strategies7. As can be derived from table 2 (based on Appendix A.1), in 2006 the main
focus was on differentiation / product leadership8. In 2007, the focus was shifted to cost leadership
/ operational excellence.
CAPEX in S$’000 / yr (rel. % of selected CAPEX)
Competitive strategy
(CAPEX category)
2006 2007 ∆ 2006-2007
Product Leadership
(new products, quality)
XXX (XX,X%) XXX (XX,X%) -XXX (XX%) Operational Excellence (mechanizations/technology) XXX (XX,X%) XXX (XX,X%) +XXX (XX%)
Table 2: (Relative) CAPEX for each relevant competitive strategy (in 2006 and 2007)
Based on these three reasons, it can be concluded that two out of three competitive strategies are chosen to maintain the competitive advantage of DAP Singapore. This implies that no specific choice on a particular competitive strategy exists.
Statement 1: No specific choice has been made on which competitive strategy to focus.
3.1.2 Financial Viewpoint
As DAP Singapore has two satellites (Suzhou, China and Batam, Indonesia), DAP Singapore not only feels competitive pressure from companies outside Philips, but from its satellites as well. Production allocation will take place based on price and quality. For these reasons, DAP Singapore has a goal to lower manufacturing costs by a certain percentage every year. By employees it was
6
Source: GC Vision n Mission (presentation).
7
These categories are: New products, mechanizations and technology, capacity, quality, replacement and departmental needs. Capacity costs are 36-45% of total CAPEX, replacement costs are 15-16% of total CAPEX, departmental needs are considered to be irrelevant for supporting a competitive strategy.
8 The large CAPEX-difference for new products is caused by implementing 6 new products in one year, on
stated that the average FSP Index shows DAP Singapore reached that goal. However, a breakdown in product types shows differently (table 3). Randomly, five product types have been examined. The FSP changes mentioned for the five different product types are representative for each type belonging to the same product model. Each of them shows an increasing FSP. This is surprisingly considering the FSP Index. Therefore, other product models are expected to have a decreasing FSP to decrease the FSP Index overall. However, this does not become clear from the selected data. Therefore, it can be stated that the manufacturing costs increase, but for some product models only. Product Type FSP 2005 (S$) FSP 2006 (S$) FSP 2007 (S$) ∆2006/2007 (in %) GCXX10 - XXX XXX + X,X% GCXX20 - XXX XXX + X,X% GCXX20 - XXX XXX + X,X% GCXX10 XXX XXX XXX + X,X% GCXX XXX XXX XXX + X,X%
Table 3: FSP changes for several product types
Statement 2: The manufacturing costs increase for some product models across product categories.
3.1.3 Organizational Viewpoint
Production of irons is allocated to DAP Singapore and the satellites, by the management, both inside and outside of DAP Singapore. These production allocations are used for both increasing and decreasing production capacity and for implementing or discarding certain types of products or product groups from one of the factories. Production is allocated based on a number of factors. As in general, producing in Suzhou (China) is considered to be cheaper than in Singapore by the management, production allocation is partly based on costs. This results in a movement in the product portfolio: low end products move to Suzhou (China), the high end products stay in Singapore.
In table 4, for each year in the period 2005-2008, production allocation for complete products from relevant SIP’s and AOP’s are compared9. Production allocation schemes (SIP) are strategic
plans for a four year period, and are made every year. The Annual Operating Plan (AOP), which states the number of products to be made in the next year, is made every year as well and is (partly) based on the SIP. For example, 2005 has been described in SIP04 and SIP05. A comparison of these numbers from both documents results in a percentage, which denotes the relative difference (∆) between both numbers. The difference (∆) has been estimated based on the oldest and the newest document, as the newest document is considered to be the most ‘right’. As only two SIP’s are included, it can be expected that in the early years of this period the differences are small, but will become larger during the later years (numbers for 2008 are derived from a SIP
from a long time ago, and from a brand new AOP08). An addition or deletion of a product category is described with ‘N’.
Three things are noticeable with respect to production allocation:
1. The total production allocation is pretty steady: numbers of previous documents grow slowly to the numbers from the newest document (table 4). For some product categories relative large differences exist, but as only small numbers of capacity are involved, they do not influence the overall result.
2. Even in the ‘easy’ year 2005, two new product categories were added that did not exist during the previous prediction (Economy and Perfective). For 2007, the product category ‘Travel’ was included in SIP04, disappeared in SIP05, but came back in AOP07. Both have been derived from table 4.
3. Production capacity for the Easy Speed kits (not displayed in table 410) was assigned to
DAP Singapore, and new facilities had to be created. However, in 2007, the management decided to allocate approximately half of the estimated 1.4 million kits to be made in Singapore to Suzhou (China). For 2008, this number was reduced even further, which left a large part of the installed facilities at DAP Singapore unused.
Product Category Product #’s Year Document Su p e r io r C o m p le te B a s ic E c o n o m y D r y T r a v e l P e r fe c ti v e L o w E n d S y s te m s M o d e n a T o ta l SIP04 (‘000) 1308 1856 1615 0 1950 172 0 50 0 6951 SIP05 (‘000) 1300 1800 1525 440 1885 130 14 30 0 7124 ∆ (%) -1 -3 -6 N -3 -24 N -40 0 2 2005 SIP04 (‘000) 1277 1868 1561 0 1961 169 0 55 0 6891 SIP05 (‘000) 1300 2050 1726 370 1915 100 0 11 7 7479 ∆ (%) 2 10 11 N -2 -41 0 -80 N 9 2006 SIP04 (‘000) XXX XXX XXX XX XXX XXX XX XXX XXX XXX SIP05 (‘000) XXX XXX XXX XX XXX XXX XX XXX XXX XXX AOP07(‘000) XXX XXX XXX XX XXX XXX XX XXX XXX XXX ∆ (%) XXX XXX XXX XX XXX XXX XX XXX XXX XXX 2007 SIP05 (‘000) XXX XXX XXX XX XXX XXX XX XXX XXX XXX AOP08(‘000) XXX XXX XXX XX XXX XXX XX XXX XXX XXX 2008 ∆ (%) XXX XXX XXX XX XXX XXX XX XXX XXX XXX
Table 4: Predictions from SIP04/SIP05/AOP07/AOP8 compared for 2005-2008
Production allocation can be influenced by both market forecasts and managerial decisions. The market forecasts cause a change in the production allocation and are uncontrollable. These forecasts are not steady, but are predicted quite well, as the production allocation does not change that much. Therefore, it is not a big issue. However, the managerial decisions can change the
10 In table 4, product categories only are displayed, as information about kits was only available from
production allocation a lot, according to remarks 2 and 3. This means that for certain product categories, fluctuations in production allocation occur. For these reasons, it can be stated that for some product categories, no steady numbers on production allocation exist.
Statement 3: No steady numbers on production allocation for some product categories.
3.1.4 Marketing Viewpoint
To discover market trends, the production data from the last few years have been examined. In this research, the historical data from 2002 until 2006, the current actual numbers for 2007 and the predictions for 2008 are taken into account. The full overview has been attached to this research paper as Appendix A.2. For the period 2002-2007, the number of product models is fixed. For 2008, the number is predicted in the AOP 2008 (18), but it is likely to rise. Based on Appendix A.2 and the actual production data for 2007, it can be stated that two product models (Power Life (GC2500/2600) and Easy Speed 1800 (LE GC1800)) are produced in December 2007, but do not appear on the AOP 2008. As there is no particular date for deleting product models from the manufacturing process in general, it is likely that the production of these models will be continued in January 2008 and maybe even further. The same reasoning goes for the Comfort 1500/1600, which has an irregular pattern of months with and without production. Therefore, it is expected that the number of different product models can even rise to 21.
Based on figure 1, it can be stated that the number of different product models that DAP Singapore produces each year increases. From 2002, it rose from 13 to 18-21 in 2008. Based on this period, the number of different product models increased with one each year on average.
# types / year 13 16 15 17 22 18 21 0 5 10 15 20 25 2002 2003 2004 2005 2006 2007 2008
Figure 1: Number Of Different Product Models Each Year
As a rather large period has been taken into account, it is likely that this increase will continue in the coming years.
Statement 4: Number of different product models a year increases.
3.1.5 Logistics and Production Viewpoint
dimensions11. D’Souza and Williams (2000) chose to work with Gerwin’s taxonomy (1993), which is
representative for most of the manufacturing flexibility frameworks, and selected the most important dimensions out of it. These are two externally-driven flexibility dimensions (volume and variety) and two internally-driven (process and material handlings). Each flexibility dimension can again be measured in multiple ways and thus an be defined by a number of different indexes. As these four dimensions are most important, they will be used in this research report. As those indexes currently do not exist in literature previously mentioned, they will be defined based on D’Souza and Williams (2000) and will be adapted to the situation of DAP Singapore.
Volume Flexibility
Volume flexibility represents the ability to change the level of output of a manufacturing process, as defined by D’Souza and Williams (2000). They state that one possible way to measure volume flexibility is to examine the costs to increase or decrease the output. A low flexibility is characterized by (high) costs (D’Souza and Williams, 2000). For DAP Singapore, an index will be developed for defining volume flexibility. Measuring this type of flexibility will be done by examining the planned capacities of and the planned demands for each process group12 for 2007,
as defined by DAP Singapore. In case demand exceeds capacity, costs will be made: costs due to lost sales, or due to increasing capacity. There are two types of capacities, both related to product demand. On the one hand, there is a minimum capacity needed to produce according to demand as estimated in the AOP. On the other hand, there is an increased capacity that is needed to produce according to the AOP + 20%. The actual demand will be likely to be in between those numbers.
Two indexes can be created for measuring volume flexibility. The first index is the relative volume flexibility index (RVFI). This index can be created by measuring the number of months in which planned demand is lower than the planned capacity in 2007, which is presented in formula 1.
Formula 1: Relative Volume Flexibility Index (RVFI) =
∑
= 6 112 g g dwith d as number of months in which demand is below planned capacity, g as process group. For 2007, the RVFI has been calculated based on the Resource Plan 200713, which has been
summarized in table 5. In case demand is according to the AOP 2007, the RVFI is 0.68, for AOP + 20% the RVFI is 0.55.
11
Machine, material handling, operations, automation, labor, process, routing, product, new design, delivery, volume expansion, program, production and market flexibility.
12 Process group is the set of words used by DAP Singapore to which production capacity is coupled. 13
AOP AOP + 20% Process Group Max. Capacity14 (k/wk) Shortage (# months) Max. Capacity15 (k/wk) Shortage (# months) Diecast XXX XXX XXX XXX Solgel XXX XXX XXX XXX Autocoat XXX XXX XXX XXX Heating Element XXX XXX XXX XXX Xylan XXX XXX XXX XXX
Table 5: Shortages for Each Process Group (In Months)
The second index for defining volume flexibility will include the absolute number of products, as the first index does not state how big the shortage for each month is. For example, a shortage of one product only will already affect the RVFI. Therefore, the absolute volume flexibility index (AVFI) will be created. For this index, it will be assumed that the amount of planned demand exceeding planned capacity during a certain month will be produced in another month with enough planned capacity left. The difference between capacity and demand divided by the demand represents the AVFI. The AVFI has been given as formula 2.
Formula 2: Absolute Volume Flexibility Index (AVFI) =
∑
∑
∑
= = = − 12 1 12 1 12 1 m m m dem dem capwith cap as capacity per month, dem as demand per month, m as month. Based on table 6, it can be stated that in case demand is according to AOP07, every process group can deal with demand and each process group is rather flexible, with respect to volume. However, in case demand is according to AOP07+20%, planned capacity is too low for three out of five process groups. It is likely the actual AVFI will be closer to the AOP07 + 20% numbers, as years before 2007 showed the same trend.
Process Group AVFI
(AOP07) AVFI (AOP07+20%) Diecast 0,12 -0,08 Solgel 0,55 0,11 Autocoat 0,19 0,17 Heating Element 0,09 -0,07 Xylan 0,20 -0,01
Table 6: AVFI for each Process Group
14
Based on the low AVFI for Diecasting, Heating Elements and Xylan, there is a shortage in products, that cannot be solved by producing in other months with remaining planned capacity. Together with the low RVFI’s for these categories, it can be stated that the volume flexibility is too low: the current manufacturing set-up cannot only deal with changes with respect to increasing demand, but with the current planned demand neither.
Variety Flexibility
Variety flexibility represents the ability of the manufacturing system to produce a number of different products and to introduce new products (D’Souza and Williams, 2000). Gerwin (1987) suggest using the number of product innovations and the number of design changes as a measure for variety flexibility. D’Souza and Williams (2000) state that the distinction between new product introduction and product modification is very indistinct. Therefore, they made a simplifying assumption that new product introductions can also be used as an appropriate surrogate for product modification/innovation.
For these reasons, for DAP Singapore, the number of new product models introduced every year will be a measure for variety flexibility (D’Souza and Williams, 2000). Therefore, this index has been defined as:
Formula 3: Variety Flexibility Index (VFI) = cPTy
with cPT as number of new product models, y as year ranging from 2004 to 2008. As can be concluded from table 7, the VFI is quite steady each year, although there is a peak in 2006: this peak is not relevant by knowing that the high number of new product models in 2006 lead to an introduction of XXX new product models in 2007. Therefore, on average the number of new product models introduced to the manufacturing set-up of DAP Singapore is XXX.
In the situation of DAP Singapore, the ability to introduce new product models is amongst others defined by costs needed to invest in manufacturing set-up for new product models, and the current manufacturing set-up, that determines the costs needed to invest. Combined with an increase in product models as was defined in statement 4, DAP Singapore is able to introduce relatively less new product models. Therefore, it can be concluded that the variety flexibility of DAP Singapore is decreasing.
Year VFI Year VFI
2004 XXX 2007 XXX
2005 XXX 2008 XXX
2006 XXX
Table 7: VFI in period 2004-2008
Process Flexibility
Williams (2000). They propose to measure this dimension by calculating the number of different operations a machine can perform. In case of DAP Singapore, this dimension will be measured by calculating the different types of products each station or line in a process area16 can produce (the
defined process areas are different from the process groups defined for the volume flexibility index). The process flexibility index has been given in formula 4.
Formula 4: Process Flexibility Index (PFI) =
∑
= 12 1 j j j n fwith f as flexibleness in process area, n as number of stations in process area, j as process area. In table 8, an overview has been given of the 11 different process areas. In each process area, one or multiple stations can be identified, which is denoted by the number of different numbers for each process area (for example, process area ‘HE’ consists of two stations). The flexibility for each station has been calculated by the number of products that can be made by the station, divided by the total number of products that can be made in the process area. The PFI is the average flexibility, based on all stations.
As can be concluded from table 8, the PFI is equal to 0.5. In a flexible situation, a machine can make each product, which would lead to a PFI of 1. Another fact that can be derived from table 8 is that for each process area, each product can be made on one station only. This implies that the current manufacturing set-up of DAP Singapore cannot deal with sudden changes: in case product demand increases a lot, this cannot be captured by another station. Based on this, together with the PFI, it can be concluded that the process flexibility is too low.
Process Area Flexibility
(# of products in station / # of products in process area)
Process Area Flexibility
(# of products in station / # of products in process area) 1. HE XXX 7. Ovens XXX 2. Diecasting XXX 8. Solgel XXX 3. Wheelblast XXX 9. Autocoat XXX
4. Steam Promotor XXX 10. Laser XXX
5. Part A XXX 11. R&S XXX
6. Sandblast XXX
Table 8: Flexibleness for Each Station (October 2006)
Material Handlings Flexibility
Material handlings flexibility represents the ability of the materials handling process to effectively deliver materials to the appropriate stages of the manufacturing process (D’Souza and Williams, 2000). For this research, the manufacturing process is the production of irons from heating elements to assembly. In this way, material handlings flexibility is considered to be the
process of moving an item from one process group to another. In that case, the material handlings flexibility index can be determined as in formula 5.
Formula 5: Material Handlings Flexibility Index (MHFI) =
!
12
12 1 12 1∑ ∑
= = + j k j jkPA
with PA as process area, j and k as relation between process areas. As none of the process groups is connected to another, there is no physical material handlings system. However, moving products from one process group to another is done by employees, and therefore together they form the material handlings system. As the employees can connect every process group to another, the MHFI is 1. However, inside the process group different processes are linked to each other by conveyor belts amongst others. But as this aggregation level is considered to be lower than the aggregation level used in the calculation of the previous dimensions, this will not be taken into account. Therefore, the material handlings flexibility can be defined as high.
In this sub chapter, the volume and process flexibility were considered to be too low and the variety flexibility is decreasing. As all four define the flexibility of the manufacturing set-up, overall the flexibility is low. Therefore, it can be stated that the current manufacturing set-up is inflexible.
Statement 5: Manufacturing set-up is inflexible.
3.1.6 Information Viewpoint
As described in the problem area, a difficult choice needs to be made during the investment decision-process. As was stated, the best decision can only be made based on data and information about future conditions. For supporting better business decision making, business intelligence can be used. The term business intelligence consists of a set of activities. The decision-making process at DAP Singapore will be described based on this set of activities. The set of activities is:
• Collecting data.
• Integrating data.
• Analyzing data.
• Presenting data17.
There are two reasons why data and information about future conditions is not used (enough) in the decision process at DAP Singapore. On the one hand, data from which information can be extracted simply does not exist when decisions need to be made. The data that does not exist cannot be created for a large part, as it is impossible to predict all variables of the future changing environment. On the other hand, data and information do exist, but separately. This implies that the collection of data, both available and unavailable, is hard.
Data and information about future conditions on their own have a certain information level for DAP Singapore, but in case they will be combined or integrated, more information can be extracted
17
from them by analysis techniques. In that case, the information level will be higher, which is wanted to make a good decision. At the moment, combining or integrating existing data and information about future conditions is not used for making the right decision at DAP Singapore. Decisions are made based on common sense, intuition and experience.
In this research, that information level and the way to get to that information level by collecting, integrating and analyzing data, is called integrality of information. As it is hard to collect data, integrating data is not used for making the right decision and a thorough analysis is missing, it can be stated that the current level of integrality of information is rather low. This means there is no fully informed decision-making which affects the quality of decision-making.
Statement 6: No fully informed decision-making / Low integrality of information.
3.1.7 Personnel Viewpoint
As part of their job, employees of DAP Singapore get trained. Philips has created a list with courses that its employees can take. This list is the same for every Philips location in the world. By the end of each year, the performance of each employee will be examined. During the conversation, skills will be defined that need to be improved. From the course catalogue, a course will be selected for the employee that will try to increase the selected skills. Normally, within a year, the employee will follow the course and learn new skills to adopt in its work.
On average, most courses from the list are on topics like communication, leadership style, presenting skills and team building. As can be derived from the Training Plan 2007 for the Engineering Department, the majority of the courses selected for employees contain one of these topics18. This implies that the level of knowledge and skills on topics as communication and presenting skills needs to be improved and thus that the current level is considered as too low.
During an investment decision-process, knowledge and skills in communicating and presenting are needed, amongst others, to present investment options and communicate them to other employees. The low level of skills needed for decision-making shows from a wrong presentation of relevant results and data and investment amounts that are not calculated properly, for example. Results presented in the wrong way easily lead to a wrong decision, in case no one takes notice of the mistakes that were made. As a result, a wrong decision will worsen the manufacturing architecture.
Based on the fact that most of the trainings given are on topics needed for improved decision-making, the mistakes that are made during the investment decision-process and the effects a wrong decision can have, it can be said that there is a need to increase the level of knowledge and skills to improve decision-making. This means that currently not enough knowledge and skills are available to improve decision-making.
Statement 7: Not enough knowledge and skills available to improve decision-making.
3.1.8 Quality Viewpoint
Regarding quality, one statement could be posted: the call rate of a certain number of system irons is too high). However, employees of DAP Singapore have already decreased this rate and the rate is expected to drop even further. As this statement can only be made on a very low aggregation level in comparison with the other statements made earlier, this will not be part of this research. No other quality issues related to the problem area were mentioned, that have not been described in the previous sub chapters.
3.2 Conceptual Model
In this sub chapter, the set of seven statements will be categorized. Based on argumentation derived from literature and the problem area, relations between the statements can be defined and a conceptual model can be created. Finally, variables and the relevant problem will be chosen that will be the input for the research design in the next chapter.
3.2.1 Categorizing Statements
The statements defined in sub chapter 3.1 will be used to structure the problem area. First, the statements will be categorized. Categorizing the statements will be done based on the similar properties the different statements share. Combining statements into one category will only be done when they share a very obvious property. If not, the statements will be categorized into its own category. In this way chances on a wrong categorization are limited, which is necessary as this process of categorizing still consist of choices that can be made differently by anyone.
Management Factors
1. No specific choice has been made on which competitive strategy to focus. 3. No steady numbers on production allocation for some product categories.
Level Of Knowledge And Skills
7. Not enough knowledge and skills available to improve decision-making.
Change Of Manufacturing Costs
2. The manufacturing costs increase for some product models across product categories.
Optimality Of Manufacturing Architecture
5. Manufacturing set-up is inflexible.
Market Developments
4. Number of different product models a year increases.
Integrality of Information
6. No fully informed decision-making / Low integrality of information.
Table 9: Groups of Statements Categorized
Starting with statement 1, it can immediately be noticed that statement 3 shares the same important characteristic. Both subjects of the statement (strategy and allocated production) are set in a collaboration between the higher management outside DAP Singapore (business unit irons) and the management of DAP Singapore itself. As an outside factor (the higher management) is involved in both statements is involved, these statements are grouped together in ‘management factors’. The subjects in other statements are not set by (higher) management, and therefore they will not be put into the same category.
statement 5 will be put into ‘optimality of manufacturing architecture’ and statement 6 into ‘integrality of information’. Finally, statement 7 will be put into ‘level of knowledge and skills’.
An overview of these groups is given in table 9.
3.2.2 Developing the Conceptual Model
Now the problem categories are known, a conceptual model can be created. This conceptual model has been displayed in figure 2. The argumentation of the relations in this conceptual model is given next.
Market Developments Optimality Of Manufacturing Architecture
As was previously defined, the manufacturing set-up is rather inflexible. This causes problems as the diversity of the products that have to be made increases, but the numbers of each type does not19. In general, it is expected that in future products tend to get more customer-specific, which
means a further differentiation of products and an increase of different types of products (Kotha, 1995). This implicates that a flexible manufacturing architecture is necessary. However, the current manufacturing set-up is not flexible. Based on the market developments, a flexible manufacturing set-up is essential. Therefore, market developments are considered to be part of the problem in this research report.
Change Of Manufacturing Costs 2 Manufacturing costs increase for some product models across product categories.
Level Of Knowledge And Skills 7 Not enough knowledge and skills to improve decision-making.
Management Factors 1 No specific choice on which competitive strategy to focus.
3 No steady numbers on production allocation for some product categories. Integrality of Information
6 No fully informed decision-making / Low integrality of
information. Optimality Of Manufacturing Architecture 5 Manufacturing set-up is inflexible. Market Developments 4 Number of different product model a year
Cause(s) Problem(s) Symptom
Optimality Of Manufacturing Architecture Change Of Manufacturing Costs
The second category to attach to the manufacturing architecture, is ‘change of manufacturing costs’. As was defined earlier, the inflexibleness of the base shows for example from the fact that for every new type of iron, belonging to the same product category, a large investment needs to be made. For the product category Azur for example, approximately once in two years a new product model will be created, which is for approximately 90% comparable to the previous type. During an investment decision-process, only the next Azur iron will be considered. No attention will be given to the Azur iron after that one. This means that advantages that could be gained by flexibilizing the current Azur iron in order to decrease the investment needed for another Azur iron are neglected. Because no attention will be given, it is not calculated whether a larger investment that increases flexibility costs less than two investments (for the next Azur iron, and the one after that) separately (figure 3). In case it is, manufacturing costs can be lowered, as the larger investment can be tracked to two models, instead of one.
Figure 3: Investment 1 (Separated Decisions) and Investment 2 (Integrated Decisions)
Considering changing the manufacturing architecture leads to changing the manufacturing costs and the predictability of the impact of the change, it can be concluded that a causal relation exists between manufacturing architecture and manufacturing costs (De Leeuw, 2000). For these reasons, the manufacturing costs can be considered as an effect of the optimality of the manufacturing architecture.
manufacturing costs increase. This means that the increase in manufacturing costs is not directly related to the inflexible manufacturing set-up.
In the conceptual model, an arrow displays the relation between the optimality of the manufacturing architecture and a change in manufacturing costs. However, as the increase in manufacturing costs is likely to be largely caused by the material costs which are not directly related with the inflexible manufacturing set-up, the arrow is dotted: a direct relation exists between the categories, but no direct relation between the individual statements exists.
Cost Type Share (in %) Cost Type Share (in %)
Equipment Costs XX.X Material Costs XX.X Tool Costs XX.X Labour Costs XX.X
Table 10: Manufacturing Costs Divided (source: CAPEX Overview 2007)
Management Factors Optimality Of Manufacturing Architecture
The management factors category consists of two sub problems. No specific choice on strategy means that there is neither full attention for an optimal manufacturing architecture, nor for best products. Porter (1980) and Treacy and Wiersema (1995) have two different opinions about focusing on two strategies. Porter (1980) says a company should only focus on one competitive strategy. He has visualized the three generic strategies into a triangle (figure 4). In case a company focuses on more than one strategy it is likely to end up in the yellow rectangle. This is called ‘getting stuck in the middle’, which is similar to creating no competitive advantage. According to Porter (1985) DAP Singapore faces the risk of getting stuck in the middle by focusing on two competitive strategies. However, Treacy and Wiersema (1995) argue differently, based on their Values Proposition Model. According to them, a company should select one value in particular to focus on, but should nevertheless give attention to the two remaining values as well. In this case, DAP Singapore will face a problem as well, as there is no clear choice made on which particular strategy to focus.
Figure 4: DAP Singapore in Porter’s triangle (1985)
The production allocation has a relation with manufacturing architecture as well. The relatively small changes in product allocation do not affect the installed base that much, as it is designed to deal with small changes. However, in case product categories are suddenly not allocated to DAP Singapore anymore, a lot of overcapacity is created. As a large overcapacity is unwanted, the installed base should be flexible enough to use it for other products. As the process flexibility of the installed base is low, this is not easily possible at the moment. Therefore, it is necessary that the manufacturing set-up becomes flexible, to deal with these changes. This means that the production allocation are part of the problem in this research as well: in case predictions on product categories were steady, a flexible manufacturing set-up would have been unnecessary, i.e. for production allocation.
Cause(s) Optimality Of Manufacturing Architecture
The final two categories form causes for a non-optimal manufacturing architecture. The level of knowledge and skills of employees influence the manufacturing architecture directly. In interviews it was mentioned that the engineering knowledge of employees was low. Engineering knowledge is needed to improve the manufacturing set-up and thus the manufacturing architecture. The other category contains the integrality of information. When the integrality of information is low, not enough information is available to make the best decision. Best decisions are necessary to improve the current manufacturing set-up.
Besides a direct relation between knowledge and skills and the manufacturing architecture, the level of knowledge and skills is related to the integrality of information as well. As was stated during the definition of this statement, employees have a low level of knowledge and skills that are necessary for improving decision-making.
3.2.3 Selecting Relevant Problem And Causes
Problem
Taking the manufacturing architecture as a central theme in the description of the problem area suggests a choice has already been made on a certain strategy. This idea is supported by the fact that the inflexible manufacturing set-up is considered to be a problem in the conceptual model as well. Therefore, operational excellence seems to be the chosen strategy. In this way, this research has dealt with this problem more or less and thus it will not be relevant for the rest of this research anymore. Therefore, the lack of choice on a competitive strategy will not be selected as problem for creating the research design.
Production allocation is based on a number of factors. According to DAP Singapore, price is probably the most important one, although other factors may influence decisions on production allocation as well. However, there is no clear view on that, as these decisions are largely made by the complete business unit, not by DAP Singapore only. As multiple stakeholders are involved and a large part of them are not and cannot be involved in this research, it will be nearly impossible to control and to influence the steadiness of the production allocation numbers. Even if the numbers could be influenced, it cannot be expected that the numbers of production allocation will become completely steady, as conditions can always arise that were unforeseen at the time the numbers had to be stated. Therefore, the changing numbers of production allocation should be considered as a characteristic the manufacturing architecture should deal with. In that way, the resulting effects of this problem are supposed to be limited, but the problem itself will not be changed. For these reasons, the problem itself will be excluded from further research, but the manufacturing architecture should partly be able to deal with the effects of the steadiness of the production allocation numbers.
For the market developments, the same reasoning goes as for the production allocation. As was said before, based on market in general, in future it is more likely the number of product models will increase even more, as products tend to get more customer specific (Kotha, 1995). In that case, reducing the number of product models will only affect the competitive advantage of DAP Singapore as it does not act according to market demands. Therefore, the increasing number of product models will be another characteristic the manufacturing architecture has to deal with, and thus it will be excluded from this research as well.
Causes
The low integrality of information and the level of knowledge and skills should be reviewed at the same time, as they are all interrelated according to the conceptual model described previously. By increasing the level of information, a better informed decision-making will be created and thus better decisions can be made that improve the optimality of the manufacturing architecture. Decisions about investments are needed to improve the current manufacturing set-up, and therefore increasing the level of information will improve the current manufacturing set-up. Without these better decisions, the manufacturing architecture will stay on the current level.
knowledge and skills, it will be unlikely that the level of integrality of information can be raised, which will affect the manufacturing architecture again.
The direct relation between the level of knowledge and skills and the optimality of the manufacturing architecture suggests that an improvement in integrality of information alone will not improve the optimality of manufacturing architecture. This implies that engineering knowledge is important as well. However, the researcher has a limited knowledge about engineering knowledge. Therefore, no valuable advice can be given to the organization about how to improve the level of this type of knowledge and skills of employees. Although this limited knowledge of the researcher can be increased by examining literature, the large difference in experience between researcher and employees will limit or even impede the creation of valuable advice. For these reasons, the direct relation between the level of knowledge and skills and the optimality of the manufacturing architecture will be dropped, and will not be part of this research. This implies that the results of this research will only be a part of a solution to increase the optimality of the manufacturing architecture.
This results in figure 5 for this research being the relevant part of the conceptual model. In the next chapter it will be explained in what way these selected causes have to be changed, in order to improve the optimality of the manufacturing architecture, given that engineering knowledge needs to be improved as well.
3.3 Summary – Problem Analysis
To analyze the problem area, multiple viewpoints and statements were created:
• Strategic Viewpoint: 1. No specific choice has been made on which competitive strategy to focus.
• Financial Viewpoint: 2. The manufacturing costs increase.
• Organizational Viewpoint: 3. No steady numbers on production allocation for some product categories.
• Marketing Viewpoint: 4. Number of different product models a year increases.
Level Of Knowledge And Skills 7 Not enough knowledge and skills to improve decision-making.
Integrality of Information 6 No fully informed decision-making / Low integrality of
information. Optimality Of Manufacturing Architecture 5 Manufacturing set-up is inflexible. Cause(s) Problem(s)
• Logistics and Production Viewpoint: 5. Manufacturing set-up is inflexible.
• Information Viewpoint: 6. No fully informed decision-making / Low integrality of information.
• Personnel Viewpoint: 7. Not enough knowledge and skills to improve informed decision-making.
• Quality Viewpoint: -.
For the development of a conceptual model, every statement was categorized. Statements 1 and 3 were categorized into ‘Management Factors’. The other statements were all categorized in separate categories: ‘change of manufacturing costs’ (2), ‘market developments’ (4), ‘optimality of manufacturing architecture’ (5), ‘integrality of information’ (6) and ‘level of knowledge and skills’ (7). Next, relations were identified between those categories: integrality of information and level of knowledge and skills are considered causes for the optimality of the manufacturing architecture that is influenced by market developments and management factors. An effect of the optimality of the manufacturing architecture is the change of manufacturing costs.
4
Research Design
In this chapter, the research design will be created. This will be done in three steps. First, the research question will be posted. Second, sub questions based on the research question will be created. Finally, an approach for answering both the research question and the sub question will be given.
4.1 Research Question
Now the main problem and causes this research has to deal with are known, a research design can be created. In this research design, the answer on the research question that needs to be constructed has to increase both the integrality of information and the level of knowledge and skills needed for increasing the integrality of information as discussed previously, as these are the two causes this research will largely focus on.
To increase the integrality of information, first the focus of this research should be on collecting and integrating data that is already available. Once the collection of data has been executed, the collected data requires a place to store it in, so anyone can access it every time one needs it. Therefore, a database seems necessary. However, a database on its own is not very useful. Presentation of this database during a decision-making process will not help increasing the integrality of information, as there is no need for data, but for information derived from those data. For this reason, data needs to be analyzed first, before information can be created. In this research, this database and analyzing part will be called information tool: a tool to collect and integrate and analyse data to retract information from that data. As this needs to increase the integrality of information, part of the research question shall focus on what an information tool should look like.
As a failure in the development of an information tool can drain an organization of people, funds and vitality (Vaughan, 2001), factors relevant for a successful implementation of the information tool needs to be found and used in the development process of the information tool. The successful implementation of the information tool as defined in this research can be compared to the definition of information system success (ISS) as developed by DeLone and McLean (1992). Based on a comprehensive survey of prior literature, DeLone and McLean (1992) proposed, but did not empirically test, a model of information system success that included six factors or constructs: besides quality of both system and information, they identified use, user satisfaction, individual impact, and organizational impact, all related to a successful implementation. Sabherwal, Jeyaraj and Chowa (2006) defined information system success (ISS) by even more constructs. This implies that in this research, a successful implementation of an information tool cannot only be determined by the quality of the information tool, but by other surrounding elements as well. Therefore, in the research question, the scope of a successful implementation does not only have to focus on the information tool itself, but on its environment as well.
improved based on an information tool, the level of knowledge and skills should be directed towards the information tool as well. Therefore, the relevant knowledge and skills needed to work with the information tool have to be part of the research question.
For these reasons, the research question belonging to this research consists of two parts. First, attention will be given to what an information tool should look like. A requirement on this information tool is that it can be implemented successfully. Second, knowledge and skills necessary to work with the information tool should be retrieved. As the Engineering Department is the principal of this research, the research question will be directed towards this group.
Therefore, the research question will be:
“What does a successfully implementable information tool for the Engineering Department of DAP Singapore have to look like
and which knowledge and skills are necessary to work with it?” N.B.:
• Implementable: the implementation of the information tool into the organization, not the implementation of the results of the information tool into the organization.
The relation between the research question and the selected problem and causes is given in figure 6. In this chapter, this figure will be enlarged and used to structure the research design.
Figure 6: Research Structure, Version 1
4.2 Sub Questions
To answer the research question properly, it has to be divided into sub questions. By answering the sub questions, the research questions can be answered. Each sub question will focus on a different part of the research question. Four relevant parts of the research question have been identified, each focusing on a different part: successful implementation, the information tool, a combination of those two and the required knowledge and skills to work with the information tool:
