KM-oriented business process reengineering for construction firms

Automation in Construction 21 (2012) 32–45

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Automation in Construction j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / a u t c o n

KM-oriented business process reengineering for construction firms Min-Yuan Cheng a, Hsien-Sheng Peng b,⁎, Chih-Min Huang a, Ching-Hsin Chen a a b

Department of Construction Engineering, National Taiwan University of Science and Technology, Taiwan Ecological and Hazard Mitigation Engineering Research Center, National Taiwan University of Science and Technology, Taiwan

a r t i c l e

i n f o

Article history: Accepted 12 May 2011 Available online 8 June 2011 Keywords: Knowledge Management (KM) Business Process Reengineering (BPR) Construction firm Architecture of Integrated Information System (ARIS)

a b s t r a c t This study develops a KM-oriented BPR model by combining Knowledge Management (KM) with Business Process Reengineering (BPR). In addition to improving weak/complicated processes in construction firms, this integrated model merges KM on routine process operations, and therefore enhances business competitiveness and promotes company innovativeness. This study developed and represented business processes based on a modified Architecture of Integrated Information System (ARIS). Furthermore, this study pioneered the application of single- and double-loop KM learning to analyze business operation processes, allowing process effectiveness and service gaps to be identified via the knowledge/activity/process-target Achievement Matrix and Knowledge-Life-Cycle constructing sheet. A KM-oriented process was then redesigned and developed based on process analysis results. The research possibilities were identified and tested by validating the model using a real case study. This study establishes a new direction for future KM-oriented process reengineering research. © 2011 Elsevier B.V. All rights reserved.

1. Introduction Due to their massive scale, large number/types of professional participants, long life cycle and complicated interfaces, construction projects generate massive quantities of complicated data. Hence, construction firm operation processes are highly complex and have a strong demand for knowledge and experience feedback [1]. In recent years, the construction industry has increased their attention to the potential benefits of using Knowledge Management (KM). However, to date, KM activities in this sector have largely been employed in tasks such as file management and knowledge community. This has resulted in unsatisfactory integration of KM into business activities. Business Process Reengineering (BPR) [2] was introduced in recent years as a revolutionary business administration concept. It radically rethinks traditional business administration concepts and completely renovates operation processes in order to obtain progressive business performance improvements. Most businesses regard information technology (IT) as the crux of BPR [3–5]. However, the special demands of construction firms cannot be satisfied if the key knowledge necessary to supporting operation processes is not considered. Therefore, how to incorporate KM in business operation process and turn it into a part of routine assignments becomes a subject awaiting urgent investigation. This research integrates two major methods, BPR and KM, to assist businesses to establish a KM-oriented BPR model able to merge KM on ⁎ Corresponding author at: #43, Sec. 4, Keelung Rd., Taipei, 106, Taiwan. Tel.: + 886 2 27301277; fax: + 886 2 27301074. E-mail address: [email protected] (H.-S. Peng). 0926-5805/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.autcon.2011.05.010

routine assignments and promote company innovativeness and competitiveness. The main subjects of this research include: 1. Adopt appropriate KM theory to serve as the execution tool of BPR and, concurrently, consider short- and long-term business developments. 2. Establish a KM-oriented BPR model able to analyze clearly business knowledge asset and management demands for business operation processes. Furthermore, fuse relevant KM activities to the BPR model effectively to serve as the basis to construct the KM business environment. 3. Discuss and verify the feasibility of the KM-oriented BPR model by applying it to an actual construction firm case in order to promote the concept in future research directions and practical applications. 2. The KM-oriented BPR model: A summary 2.1. Evolution of the role of KM in the business operation processes While traditional business output and feedback mechanisms presume it to be an inherent part of the business processes, business knowledge is, in practice, downplayed or overlooked by companies. Practical business knowledge and experience is typically retained only in individuals and not transferred to the business organization. When personnel change positions or leave their company, their knowledge leaves with them, leading to a permanent loss to the company. The Organization Knowledge Base helps exteriorize the business process feedback mechanism and leverages information technology (IT) to retain relevant knowledge and experience related to the business

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Fig. 1. Assessment concept for business processes.

processes for recall by other company decision makers. First generation KM [6] (see Fig. 1) focuses on collecting and conserving business knowledge. Traditional data centers and file digitization treatment methodologies popularized in recent years represent this type of KM. Utilizing such knowledge conservation systems, companies are able to conserve a significant body of the knowledge that is constantly generated by the business process. However, it is difficult to sort through in the data to identify information relevant to a specific decision maker need. Therefore, KM has increasingly focused in recent years on integrating database content and developing user interfaces that are easy to use in order to improve business operation process efficiency and quality. Results are known as second generation KM [6]. Commonly used methods include creating information platforms, building knowledge classification systems, setting up knowledge maps and developing knowledge communities. Time-induced change impels business competition models to adjust and evolve constantly, and the business process must adjust flexibly and quickly to changes in the competitive environment. For this reason, companies should have mechanisms to detect problems in the processes. Systems in which new knowledge is produced via the Knowledge Production (KP) operation, classified and then entered into the organization knowledge base for future use in solving new business process problems are referred to as third generation KM. Knowledge in third generation KM [6] systems goes beyond current knowledge to include innovative knowledge derived from coping with business process problems, thus increasing the value of KM to the business process. Details are shown in Fig. 1. 2.2. Concept of KM loop learning Businesses utilize experience and information in the organization knowledge base to implement business processes, after which feedback and achievements are looped back into the knowledge base. Such processes, which belong to KM organizational/individual learning models, may be classified into two types, i.e. single-loop learning and double-loop learning, in accordance with implementation characteristics (as Fig. 1). Argyris and Schön [6] defined single-loop learning as ‘cyclical processes which send feedback and achievements to the organization knowledge base utilizing the established general or specific knowledge in the organization knowledge base, and carry out proper adjustments for relevant activities based on the new knowledge produced by special incidents and demands of activities’. Such a concept tallies with the auxiliary concept of business processes in first

and second generation KM. However, business process problems that accrue due to environmental changes can only be effectively addressed through single-loop learning. To address this, Argyris and Schön proposed the idea of double-loop learning, defining such as ‘a cyclical process which sends feedback and achievements to the organization knowledge base utilizing the problems accrued in the business processes to solve and revise the established general or specific knowledge in the organization knowledge base, and carries out proper adjustments for relevant activities.’ This concept tallies with the auxiliary concept for third generation KM business processes. Single- and double-loop learning in the KM model, shown in Fig. 1, includes three major KM activities, namely ‘knowledge conservation’, ‘knowledge integration’ and ‘knowledge production’. There are already numerous mature theories, methods, and information technologies and platforms that support the first two. The latter, i.e., ‘knowledge production’, the activity designed to solve problems generated by business operations, is a main research focus of the KM field today. In addition to the ‘knowledge creation’ process, the ‘knowledge production’ process should also include the ‘knowledge evaluation’ process to verify knowledge effectiveness. As shown in Fig. 1, research utilizes the operational sequence of double-loop learning proposed by Argyris and Schön to assist and solve problems that single-loop learning cannot. The construction concept of the KMoriented BPR model is shown in Fig. 2. 2.3. Description of the overall scheme of the KM-oriented BPR model Based on the BPR theory, this research developed a KM-oriented BPR model, which fuses KM and loop learning concepts and practices (Fig. 1) [7] after a careful review of general BPR models in the literature [8–16]. Its basic scheme is shown in Fig. 3. The model encompasses five main processes, including process representation, process evaluation, process analysis, process redesign, and process validation. 1. Process representation: This research thoroughly reviewed and analyzed processes already selected. The elements of process reengineering, e.g., activity roles and items, related knowledge, and relationships with other processes, were progressively assessed and depicted in the context of construction firm management systems. The main purpose of process representation is to model relevant process information so that follow-up work, i.e. process evaluation, may be executed. Furthermore, the model may serve as the basis for similar process reengineering tasks in the future. This research stipulated that documents describe the process model

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Fig. 2. Conceptual sketch of KM-oriented BPR.

based on the ARIS (Architecture of Integrated Information Systems) process model concept. ARIS House includes four points of views, including that of the data, organization, function and control. These four points of view were appropriately adjusted by this research. The data view was replaced and expressed by the knowledge view, for which the knowledge classification table was used. The organization view was replaced and expressed by the role view, for which the exercised cases chart was used. 2. Process evaluation: The reengineering activity aimed to achieve regeneration in light of unreasonable/inefficient process problems, and, thereby, accrue the greatest benefit. Consequently, process performance must be assessed and diagnosed before changing. The crux that obstructs the operation process should be identified in order to serve as the basis of process redesign. The purpose of process operation lies in linking into a company's actual business functions, and, thereby, helping to maintain or enhance company operations. Hence the degree to which functions are reached by the process is an important indicator of process performance. Meanwhile, the company must introduce operation objectives and philosophies fully into company function completely, in order to make process objectives identical to those of business policy and company direction in order to facilitate company objectives. 3. Process analysis: In this stage, analytical work was divided into two parts, i.e., ‘analysis for gap of performance’ and ‘analysis for gap of service’, in which KM single-loop and double-loop learning concepts were, respectively, involved. Tasks in the processes that should strengthen KM (single-loop learning) and the activities that should accrue or redevelop to redeem the process (double-loop

learning) were also investigated. The result was identification of a process redesign policy necessary to solve process problems. 4. Process redesign: This stage focused on the problems and defects found during process evaluation and analysis as well as to revise or reconstruct processes in order to make them fit process objective requirements. The new process model established through process redesign was then available to serve as the basis of the following stage (process validation) and as input data for the process to execute reengineering again. The result both reduce the difficulty of constructing the process model during the procedure representation stage and generates reengineering experience that is available as feedback input for future tasks. 5. Process validation: Performance of the process before and after reengineering should be further inspected and validated to help ensure the effectiveness of the redesigned process. Should the execution performance of redesigned process not improve significantly on the original, the process should cycle back to the process redesign step. After establishing a new process utilizing the KM-oriented BPR model, a company may implement process reengineering and adjust in a flexible manner to satisfy operation demands at a particular point in time in accordance with the engineering management PDCA (PlanDo-Check-Action) circulation concept. First, process representation and process evaluation are utilized to plan process reengineering direction (i.e., “plan”). Second, the new process is actually executed utilizing ‘procedure redesign’, in which KM provides assistance (i.e., “do”). Appropriateness of the reengineered process can then be

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tion engineering comprised its main business focus. The number of employers is about 500. The model was expected to promote effectively business process efficiency and quality, and also to provide a reference for the person who quotes this model. 3.2. Process representation ‘Process representation’ expressed the process as the modeling type in order to facilitate follow-up assessment and analysis activities. This research established the relationship between process task and knowledge utilizing the ‘knowledge/operation subject matrix’. Interface relations among the reengineering process and other processes were deduced using the matrix. Therefore, the process model may be constructed using the process model method. Steps in the process representation can be illustrated as follows: 3.2.1. Identify relevant knowledge and operation subjects in the processes The business process comprises numerous business activities and knowledge that correlate with each other. This step aimed to define clearly the operation and knowledge subjects of the reengineering process in order to construct the ‘knowledge/operation subject matrix’. The construction firm offered relevant data, including project obtainment, construction and management. The inventory of relevant operation and knowledge subjects could then be arranged from business execution information, e.g., ‘bidding forms’, ‘contract forms’, ‘purchase/subcontracting forms’, ‘quality forms’, ‘constructing forms’ and ‘financial forms’.

Fig. 3. KM-oriented BPR model.

checked utilizing ‘process validation’ (i.e., “check”). Finally, the reengineered process is implemented in the new business environment (i.e., “action”). 3. Implementation and application of the KM-oriented BPR model 3.1. Introduction to the verification case This research selected construction firm A as the example to verify KM-oriented BPR model applicability. Construction firm A is a public limited company in Taipei City which is in operation for about 30 years, and capitalized at about 30 million USD. Civil engineering, building engineering, high-tech factory engineering and transporta-

3.2.2. Developing the knowledge/operation subject matrix Operation subjects obtained in the most recent step were listed in order in the first matrix column, while knowledge subjects were listed at the top of the matrix. Corresponding relations between knowledge and operation subjects were then entered to complete the matrix. In the matrix, C (Create) means produce knowledge, U (Use) represents read/revise/delete, and blank means irrelevant to one another. Rearranging operation subjects and adjusting the order of knowledge subjects allows the C to be represented from the top left to the bottom right. Operation subjects can then be classified by process based on similar characteristics. Based on an analysis of the operation category of the process in place at the construction firm in the example, processes were classified into the eight groups of ‘Business Management’, ‘Human Resource’, ‘Financial Accounting’, ‘Bidding/Contract’, ‘Cost Estimates/Construction Planning’, ‘Purchase/Subcontracting’, ‘Construction Management ’, and ‘After-Sales Service’. 3.2.3. Process modeling 1. Knowledge view: This research incorporated the ‘analysis of process knowledge’ of Eppler [17] (as Fig. 4) into the ‘knowledge/operation

Fig. 4. Conceptual model of the relationship between process and knowledge.

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subject matrix’, and defined categories of knowledge by applying U/C relations: Knowledge about the process: Defined as the external knowledge to which the process implementation should refer. It is usually produced by other processes or historical experiences with this process. This kind of knowledge usually needs to be prepared before executing the process and will only be consulted and used without any change when executing the process. Knowledge within the process: Defined as procedural knowledge generated during process implementation, knowledge within the process is necessary for follow-up activities in the process. This type of knowledge is provided only for internal use within the process, with no relationship to other processes. Knowledge derived from the process: Defined as outcome knowledge produced during the course of process implementation, knowledge derived from the process is provided for internal use within the process and referred by other processes. This kind of knowledge must also consider the demands of other processes in addition to being available for use within the process. This research chose to implement reengineering in the purchase/ subcontracting process. In the knowledge/ operation subject matrix, knowledge subjects with the symbol U and located on the left side of the purchase/ subcontracting interval are ‘knowledge about the process’ subjects, which were produced by other processes. Knowledge subjects with a C or U symbol and located inside the purchase/subcontracting interval are ‘knowledge within the process’ subjects. Knowledge subjects with the symbol U and located on the upper or lower side of the purchase/subcontracting interval are ‘knowledge derived from the process’ subjects, which were generated by this procedure. 2. Role view: Describing participants in the process from a ‘role view’ accords with the execution model of the purchase/subcontracting process, which often serves customers via the ‘project’. This step focuses on operation subjects contained in the process category. Scanned individually in accordance with the actual tasks helps define all roles that need to participate in the process execution. According to practical experience and abovementioned processes interface, it is known that there are three roles participating in the purchase/subcontracting process, including the ‘cost controlling agent’, ‘purchase agent’ and ‘construction director’. 3. Function view: Operation subjects in the process category were subjected to function decomposition one by one. It can be seen that main purchase/subcontracting process operation subjects for construction engineering should contain six steps. These include: ‘purchase/subcontracting budget planning’, ‘subcontracting task’, ‘change order’, ‘assessing subcontractor’, ‘purchase/subcontracting budget inspecting’, and ‘purchase/subcontracting performance inspecting’. 4. Control view: After finishing the three process views noted above, this research utilized extended Event-Driven Process Chains (eEPC) to connect various details of the process in series in order to establish the process operation model. 3.3. Process evaluation ‘Process evaluation’ must first draft target ‘customer orientation’ components, then measure the expected and actual degree of achievement of a target component that process activities contribute in order to confirm the necessity of process reengineering. Furthermore, it can serve as a reference basis for assessing the problems of the process.

process into target components after investigating and arranging, and evaluated the relative importance of each target. The customer correlated with the process could be divided into two types, namely, internal customers (parties participating in the process and used in the procedure model to define the process ‘role’) and external customers (consumers accepting process products; most often companies). After customers have been validated, their requirements may be better understood through interviews and questionnaires. 3.3.2. Analysis of target component importance The relative importance of target components is identified utilizing the relative importance weight matrix [10]. In the matrix, customer demands are listed vertically on the left-hand side, while target components are listed at the top. The corresponding number rij is determined based on the relationship between the two, with the rij value positively correlated to the number of customer demand targets accomplished. rij is then represented as pi (considering the weight placed by customers on each demand) and entered on the right-hand side of the matrix. The higher the pi value, the greater customer attention the demand elicits. Finally, Eq. (1) is used to calculate the score of relative importance (wj) of each target component. m

∑ rij × pi

wj =

n

i=1 m

j=1 i=1

where relative importance weight for target component j corresponding rating between the j th target component and ith customers' demand, rij = 0–5 degree of emphasis of the i th customers' demand, pi = 1–5 number of customer demands number of target components

wj rij pi m n

3.3.3. Analysis of target component achievement The target component achievement matrix (Table 1) is utilized to calculate the degree of achievement of each target completed by the existing process. Operation subjects are placed on the left and target components and relative importance scores (wj) are listed at the top. The mutual relationship amongst each were investigated, and m

expected contribution degree value Aij (Aij = 0.0–1.0, ∑ Aij ≤1:0) i=1

and actual value aij (aij = 0.0 ~ Aij) of each operation subject inserted into corresponding positions. Values utilizing Eq. (2)–Eq. (10) were then calculated and used to complete the table. n

CEi = ∑ Aij × wj

ð2Þ

j=1 n

CRi = ∑ aij × wj

ð3Þ

j=1

m

EAj = wj × ∑ Aij

ð4Þ

i=1 m

Raj = wj × ∑ aij

ð5Þ

i=1

n

Gi = ∑

j=1

3.3.1. Determination of target components Adopting the quality function deployment (QFD) concept [18–21], this research transformed customer demands that correlate with the

ð1Þ

× 100

∑ ∑ rij × pi

  Aij −aij × wj = CEi −CRi

n

m

j=1

i=1

TEA = ∑ EAj = ∑ CEi

ð6Þ

ð7Þ

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37

Relative importance weight (wj) Basic document comprehending Market survey Purchase/subcontracting subjects planning Detail purchase/subcontracting subjects Quantity accounting data Unit price analysis data Purchase/subcontracting subjects budgeting Applying purchase/subcontracting budget Purchase/subcontracting budget comprehending Purchase/subcontracting budget inspecting Subcontractors selecting Ask for bidding Quotation negotiation Subcontractors inquiry Subcontractors appraisal Purchase/subcontracting budget revising Contract revising Purchase/subcontracting performance inquiry Expected achievement value (EAj) Actual achievement value (Raj) Gap of service for each target component

Expected Actual Expected Actual Expected Actual Expected Actual Expected Actual Expected Actual Expected Actual Expected Actual Expected Actual Expected Actual Expected Actual Expected Actual Expected Actual Expected Actual Expected Actual Expected Actual Expected Actual Expected Actual

2.8 0.1 0.1

0.1 0.1 0.2

0.2 0.2

0.1 0.1

7.8 3.6 2.0 3.0 1 . 0 3.4 0.1 0.2 0.1 0.1 0.1 0.2 0.1 0.1 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.3 0.3 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.1 0.1 0.1 0.2 0.1 0.2 0.1 0.1 0.1 0.2 0.4 0.1 0.4 0.2 0.2 0.2 0.2

3.8

5.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.1 0.1 0.1

0.1 0.1 0.2

0.3 0.2 0.1 0.1

2.1

0.1 0.1 0.2 0.2

0.1 0.1 0.1 0.1

2.3

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2

2.9 9.9 3.3 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.1 0.1

0.3 0.1

5.5 3.7 0.1 0.1

0.1 0.1 0.2 0.1

0.1

0.1 0.1 0.3 0.1

0.1 0.1

aij

4.2 4.8 7.2 3.5 4.0 2.8 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.1 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.3 0.3 0.1 0.1 0.3 0.1 0.2 0.1

3.9 0.1 0.1

1.3

3.5

4.3 4.0 3.0 2.9

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

7.1 6.9 11.6 5.6 1.9 1.7 7.0 3.7 4.8 4.6 0.4 0.4

Aij

0.1 0.1 0.1 0.1

0.1 0.1 0.1 0.1

0.3 0.1

0.3 0.3 0.1 0.1

0.2 0.1

0.1 0.1 0.1 0.1 0.1 0.1

0.1 0.1

0.2 0.1

0.2 0.1

0.1 0.1 0.1

0.1 0.1 0.4 0.2 0.2 0.2

0.2 0.1

0.2 0.2

0.1 0.1 0.1 0.1 0.1 2.3 3.6 0.8 2.5 5.5 --

0.1 0.1 0.2 0.1 0.1 0.2 0.1 0.1 0.1 0.1 0.1 0.1 2.0 3.0 1.0 2.0 2.4 0.9 -- ---

0.1 0.1 0.1 0.1 0.1 0.1 3.4 3.8 3.4 3.4 ---

0.1 0.1 0.1 0.1

5.0 4.5 --

0.1 0.1 0.1 0.1 0.1 0.1 2.1 2.1 --

0.1 0.1 0.1 0.1

2.3 2.3 --

0.1 0.1 0.1 0.1 0.1 0.1 2.9 0 2.0 0 -- 9.9

0.1 0.1 0.1 0.1

0.1 0.1 0.1 0.1 0.1 0.1 3.3 5.5 2.0 3.8 ---

0.2 0.1 3.7 1.8 --

0.1 0.1 0.1 0.2 0.1 0.1 4.2 4.8 0 3.0 3.8 0 --- 7.2

0.1 0.1

0.2 0.2 0.1 0.1 3.5 4.0 2.8 2.5 2.8 1.9 --- --

n

ð8Þ

Gsv = 100−TEA

ð9Þ

Gpf = TEA−TRa

ð10Þ

j=1

CEi CRi EAj Raj wj n m Gi TEA TRa Gsv Gpf

expected contribution degree value of the i th operation subject actual contribution degree value of the i th operation subject expected achievement value of the j th target component actual achievement value of the j th target component relative importance weight of target component j number of target components number of operation subjects gap between expected and actual contribution degree value of the i th operation subject total expected achievement value of all target components, TEA = 0–100 total actual achievement value of all target components, TRa = 0 ~ TEA service gap performance gap

The calculated TEA value was 77.5, so that Gsv was 22.5. This result indicated that the operation subjects the present process contains can only serve about 3/4 of the target components at most. This is defined as the service gap in the research process to be redesign utilizing

4.5 2.0 0.3 0.8 0.8

0.1 0.1

0.2 0.1

1.7 1.6 1.2

0.1 0.1 0.1 0.1 0.1 0.1 3.9 3.5 --

0.1 0.1 0.1 0.1 0.1 0.1 1.3 1.1 --

TRa

4.4 6.9 6.5

0.3 0.2 2.8 1.7 --

0.39 0.10 0.13 5.96 0.13 3.28 0.16 -0.10 5.46 0.15 --0.16

1.2 TEA 3.5

0.2 0.1 0.2 0.1 3.5 2.4 Gsv

TRa = ∑ Raj

2.8 9.9

0.3

0.1 0.1 0.2 0.2 0.3 0.3 0.1 0.1 0.1 0.1

2.9

2.2

0.1 0.1

0.1 0.1 0.2 0.1 2.8 2.0 --

Actual contribution degree value (CRi) Gap between expected and actual contribution degree value (Gi)

2.8

0.3 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

Expected contribution degree value (CEi)

Abundant unit price analysis data

Systematized delivery time Standardized reorder frequency Standardized delivery duration Standardized producing efficient Standardized operation sequence Standardized production quality Transferable experience of historical cases Delivery fit in with design requirements Standardized evaluation activity Applicable results data Purchase/subcontracting confirms budget and construction requirements Automated Purchase/subcontracting schedule control Abundant subcontractor categories Standardized evaluation criteria

Standardized coding system

No visual defects

Standardized detail items of materials Transparent asking bidding data Budget unit price fit in with market Confirm the realistic customer’s demand Purchase/subcontracting budget fit in with construction cost Standardized purchase/subcontracting budget form

Operation subjects

Accurate production stander

Target components

Planned delivery time fit in with customer’s demand Budget fit in with market function

Table 1 Target component importance of purchase/subcontracting process-target component achievement matrix.

7.2 5.4 77.5 58.5 22.5

0.91 0.35 1.76 19.0

Gpf

double-loop learning. The TRa value was 58.5, giving a service gap in process Gpf of 19. This part must be improved and strengthened using single-loop learning. 3.4. Process analysis 3.4.1. Performance gaps in the process — Single-loop learning From the four major process modeling views, it is known that factors influencing process efficiency include ‘knowledge subjects’ (Knowledge view), ‘organizational human resources’ (Role view), ‘operation functions’ (Function view), and ‘logical relationship’ (control view). Among them, the knowledge subjects most obviously influence the process. Hence this research investigated the relationship and their degree between knowledge subjects and process efficiency in accordance with knowledge orientation and established a ‘knowledge subject contribution degree accessing matrix’ in order to verify important knowledge with regard to the process. Step 1 Assess demand knowledge intensity of the operation subject The achievement of a target component derives from the execution efficiency (f) of every operation subject in the process. The execution efficiency may be further subdivided into the sum of four items, i.e. knowledge (fk), role (fr), activity (fa), and integration (fi). Necessary processes when the construction firm executed bidding, purchasing, construction managing, and delivering, were mostly within the ‘process with knowledge’, which must be assisted and finished via relevant knowledge. This is different from the general management process, which possesses structural characteristics and standard information flows.

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Table 2 Knowledge subject contribution degree accessing matrix of purchase/subcontracting process. Operation subjects

Process characteristic factors

Component importance Basic document comprehending Market survey Purchase/subcontracting subjects planning Detail purchase/subcontracting subjects Quantity accounting data Unit price analysis data Purchase/subcontracting subjects budgeting Applying purchase/subcontracting budget Purchase/subcontracting budget comprehending Purchase/subcontracting budget inspecting Subcontractors selecting Ask for bidding Quotation negotiation Subcontractors inquiry Subcontractors appraisal Purchase/subcontracting budget revising Contract revising Purchase/subcontracting performance inquiry

External dependence

Activity variability

Operating innovation

Knowledge conservation

Producing autonomy

Skill difficulty

Indicator of strength for knowledge demand (KIIi)

0.4 0.6 0.7 0.8 0.6 0.8 0.4 0.2 0.6 0.8 0.2 0.1 0.5 0.1 1.0 0.2 0.4 0.6 0.7

0.4 0.2 0.5 0.5 0.2 0.6 0.4 0.2 0.2 0.8 0.2 0.2 0.3 0.2 0.5 0.4 0.2 0.2 0.5

0.4 0.4 0.6 0.8 0.2 0.6 0.6 0.2 0.4 0.6 0.3 0.1 0.3 0.2 0.4 0.2 0.2 0.2 0.5

0.2 0.3 0.4 0.6 0.4 0.5 0.6 0.2 0.6 0.5 0.5 0.3 0.5 0.1 0.6 0.2 0.4 0.3 0.6

0.2 0.2 0.2 0.7 0.2 0.4 0.4 0.2 0.2 0.6 0.8 0.6 0.4 0.8 0.8 0.2 0.4 0.2 0.6

0.2 0.2 0.2 0.6 0.8 0.4 0.2 0.2 0.2 0.2 0.3 0.3 0.3 0.1 0.2 0.2 0.2 0.2 0.4

0.3 0.3 0.4 0.7 0.4 0.6 0.4 0.2 0.4 0.6 0.4 0.3 0.4 0.3 0.6 0.2 0.3 0.3 0.5

In order to distinguish the process with knowledge, this research evaluated the demand degree of knowledge for each operation subject in the process according to the six factors of ‘attributes of process with knowledge’ that Eppler [17] addressed. Hence the ‘indicator of strength for knowledge demand’ (KIIi) was defined and calculated. A larger value indicates greater demand for an operation subject. The calculation method treated the operation subject as the assessing unit. After the questionnaire was completed, degree to every characteristic factor was expressed using a number value of 0.0 (weak) to 1.0 (strong). Average values were then calculated. Table 2 shows assessment results. Step 2 Establish the knowledge/operation subject matrix This analysis focused on the knowledge subject demand of each operation subject. In other words, evaluation objects were the knowledge about the process and knowledge within the process. Step 3 Calculating the degree to which knowledge subject contributes to a target component This step aimed to analyze the degree to which knowledge subjects contribute to target components. This research developed the ‘knowledge/activity/process-target achievement matrix’ (Table 3) to analyze and verify relationships

among ‘target component’, ‘operation subject’ and ‘knowledge subject’ in order to serve as a reference for drafting an appropriate process reengineering policy. where Aij

expected achievement value of the jth target component contributed by the ith operation subject, Aij = 0.0–1.0, m

∑ Aij ≤1:0, i = 1 ~ m, j = 1 ~ n

i=1

efficiency of the ith operation subject, 0 ≤ fi ≤ 1, fi = fKi + fRi + fAi + fIi, fKi, fRi, fAi, and fIi are the operation efficiency functions of the ith operation subject for knowledge, role, function and control aspects, respectively expected achievement value of the jth target component demand degree of the kth knowledge subject for the i th

fi

EAj Kik

q

operation subject, Kik = 0.0–1.0, ∑ Kik ≤1:0 KFk KIIi TEA

k=1

contribution degree of the k th knowledge subject to target component, k = 1 ~ q indicator of strength for knowledge demand of the i th operation subject, 0 ≤ KIIi ≤ 1 total expected achievement value of all target components, TEA = 0–100

Table 3 Knowledge/activity/process-target achievement matrix. Indicator of strength for knowledge demands

Knowledge subject 1

…

Knowledge subject k

…

Knowledge subject q

x1

…

xk

…

xq

KII1 : KIIi : KIIm

K11 : Ki1 : Km1

… : … : … …

K1k : Kik : Km3

… : … : … …

K1q : Kiq : Kmq

TK

KF1

…

KFk

…

KFq

Knowledge

Target components

Operation subjects Relative importance weight for target components Indicator of manage completion of knowledge subjects Operation subject 1 (f1) : Operation subject i (fi) : Operation subject m (fm) Expected achievement value of target components Contribution degree of knowledge subjects to target component

Target component 1

…

Target component j

…

Target component n

w1

…

wj

…

wn

A11 : Ai1 : Am1 EA1

… : … : … …

A1j : Aij : Amj EAj

… : … : … …

A1n : Ain : Amn EAn TEA

M.-Y. Cheng et al. / Automation in Construction 21 (2012) 32–45

TK wj xk

total expected achievement value of knowledge subject to all target components, 0 ≤ TK ≤ TEA relative importance weight of target component j indicator of completion of the k th knowledge subject, assuming that degree of contribution degrees for the operation subjects of each knowledge subject are independent, 0 ≤ xk ≤ 1

Relationships amongst target components, operation subjects and knowledge subjects are extremely complicated. Thus, it is difficult to obtain directly the degree to which the knowledge subject contributes to the target component. Therefore, this research derives excepted contribution degree values of knowledge subjects for target components according to the abovementioned structure, and then assesses real contribution degree values. The knowledge subjects that caused lower target component achievement could thus be obtained and targeted for strengthening through reengineering. There were 18 operation subjects, 26 target components and 19 knowledge subjects in the purchase/subcontracting process knowledge/activity/process-target achievement matrix (Table 4). 3.4.2. Service gap in the process — Double-loop learning As learned in the process evaluation stage, some target components cannot be achieved via existing processes. This gap is not obtainable by analyzing the service gap in the process. Therefore, this research adopted a KM double-loop learning model for investigating this part. The operation and knowledge subjects that should be added or modified were analyzed and verified in order to improve total achievement of all target components. Step 1 Validating problems for the service gap in the process This research defined a target component that is unable to be served by the process or which has a poor service state as ‘service gap in the process’. Based on the knowledge/activity/ process-target achievement matrix, the element of target component achievement gap was defined as wj minus (−) EAj. Elements were then rearranged from small to large in order to identify target components unable to be served by the process, i.e., the service gap in the existing process. Step 2 Investigating problems using the Knowledge-Life-Cycle construction sheet This research adopted knowledge production and knowledge integration procedures to realize the double-loop learning concept of KM as well as to investigate problems using Knowledge-Life-Cycle construction sheet. Its content is as follows: 1. Knowledge creation: Operation subjects that were executed for solving the problems produced with the business processes. Because the produced knowledge subjects belong to an assumptive solution that reflects problems in the process, it is known as a ‘knowledge claim’. 2. Knowledge evaluation: Operation subjects for evaluating the knowledge claim produced by the abovementioned operation subjects. This transforms the knowledge claim into organization knowledge for future reference and application. 3. Knowledge integration: Deliver organization knowledge to the process participating roles utilizing suitable approaches, such as knowledge dissemination, searching and sharing. Therefore, the efficiency and efficacy of the business process may be improved effectively. This step aims to analyze and validate the relevant operation subjects that the abovementioned processes must adopt and derive knowledge subjects.

39

The three target components unable to be serviced effectively by existing process are known as the ‘problem statement’. These necessary knowledge subjects are then subjected to ‘knowledge production’, ‘knowledge evaluation’ and ‘knowledge integration’, and the relevant content of ‘knowledge claim’ and ‘organization knowledge’. The obtained three major knowledge subject categories must then each merge with existing process operation subjects. Therefore, gaps and omissions in the existing operation subject may be augmented or improved while redesigning the new process. On the other hand, ‘knowledge claim’ and ‘organization knowledge’ should also be compared with the existing process model. Newly-added knowledge subjects may be arranged in terms of the knowledge view of the new process model. When the Knowledge-Life-Cycle constructing sheet analysis is used to address the serve gap in the Purchase/subcontracting process, twelve KM operation subjects are involved in the existing process problems. Among them, ‘quote the unit price analysis data’ is already part of the existing process, although it is unconnected with historical database and so should be revised. The other 11 items are not provided by the existing procedure and should be classified as newlyadded subjects. Also, there are twelve relevant knowledge subjects in all that address existing process problems. The ‘ratify the standard purchase/subcontracting budget and application form’ item was already part of the existing model, with the other 11 items classified as newly-added subjects. 3.5. Process redesign 3.5.1. Verifying process redesign principles The principle of process redesign was verified through the comprehensive investigation of the target component achievement matrix in the process evaluation stage, the detailed analysis of gap of efficiency and service in the process analysis stage, and practical experience. 3.5.2. Establishing the new process model This step established a new process model in accordance with the principle previously verified. However, the modeling procedure should be revised as: 1. Control view: Based on the e-EPC chart prior to reengineering, fuse the above-mentioned principles of process redesign and establish the e-EPC chart for the new process (see Fig. 5). 2. Function view: Revise the existing operation subjects of the process based on the e-EPC chart of the new purchase/subcontracting process. 3. Role view: For making contributions to the experience feedback mechanism, the new process adds the ‘conservation of the purchases/subcontracting knowledge’ item in order to make the process efficiency more complete. 4. Knowledge view: Revised knowledge subjects may be obtained by analyzing the new process e-EPC chart. The newly added knowledge subjects are address the new purchases/subcontracting process. 5. Knowledge/operation function matrix: The revised knowledge/ operation function matrix may be obtained by reviewing knowledge, role, function, and control views separately. 3.6. Process validation The new process should be estimated in advance in accordance with demand in order to validate the results and performance of reengineering procedures. This research adopted efficiency and process cost to assess process performance. Process value (PV), defined as the ‘executing efficiency per unit cost’, was chosen to serve

40

0.1 0.1 0.3

0.4 0.1

0.1 0.1

0.2

0.1

0.3 0.2

0.4

0.4

0.1

0.1

0.1

0.2 0.2

0.4

Detail purchase/subcontracting subjects

0.6 0.1 0.2

0.1

0.4 0.1 0.2

0.1

0.1

0.3 0.1 0.2 0.4

0.1

11.6

6.0

0.1

0.1

1.9

0.1

0.3

0.3 0.1

0.1

7.0

3.3

0.1

4.8

0.2

0.4

0

0.2

0.2

0.1

0.1 0.1 0.1

0.1

0.2

0.1

0.1

0.1 0.1 0.3

0.1

0.1

0.1 0.2

0.3

0.1

0.1 0.1

0.1

0.1 0.1

0.3 0.3 0.3 0.2 0.1

0.2

0.1 0.2 0.1 0.2

0.1

0.4

0.1

2.9

0.1

0.1

0.4

9.9

5.5

0.2

0.2

0.2

0.1

Subcontractors inquiry

0.2

Subcontractors appraisal

0.3 0.1

0.1

0.1 0.1 0.1

0.1 0.1 0.1

0.1 0.1 0.1 0.1

Contract revising

0.1

0.1 0.2 0.1 0.1 0.1 0.1 0.1

0.1 0.1 0.1

Purchas performance inquiry

0.2

0.1

0.1

0.1 0.1

0.1

Expected achievement value 2.8 2.3 3.6 2.0 3.0 1.0 3.4 3.8 5.0 of target components Contribution degree of 1.2 5.2 0.2 1.9 0.7 2.1 0.8 3.5 3.5 1.3 9.0 0.2 0.7 0.8 0.9 0.2 0.2 0.2 1.7 knowledge subjects to target component

0.1

0.1

Purchase/subcontracting budget revising 0.1 0.1 0.1

Standardized evaluation criteria

0.1

0.3 Quotation negotiation

0.2 0.2

Expected contribution degree value (CEi) Gap between expectedand actual contribution degree value (Gi)

0.1 0.1

Ask for bidding

0.3

Abundant subcontractor categories

0.2

Subcontractors selecting

0.1 0.1 0.2 0.6

Applicable results data

0.1 0.2 0.3 0.2 0.1

0.1 0.1 0.3

0.4

Purchase/subcontracting confirms budget and construction requirements A utomated Purchase/subcontracting schedule control

Standardized evaluation activity

Delivery fit in with design requirements

Standardized production quality

Transferable experience of historical cases

Standardized operation sequence

Standardized delivery duration

Standardized producing efficient

Systematized delivery time

Standardized reorder frequency

Standardized coding system

0.2 0.1 0.2

Purchase/subcontracting budget inspecting

0.1

Abundant unit price analysis data

Confirm the realistic customer’s demand

Purchase/subcontracting budget fit in with construction cost Standardized purchase/subcontracting budget form

Transparent asking bidding data

Budget unit price fit in with market

No visual defects

Standardized detail items of materials

0.3 0.1 0.1 0.2 0.1

0.1 0.1 0.3

0.3

0.5

0.2 0.1 0.3

0.2 0.4

0.2 0.4 0.4

0.2 0.1 0.2 0.1

0.1

Purchase/subcontracting budget comprehending

0.2 0.1

0.1

7.1

0.1 0.1 0.3

0.6

3.0

0.1

0.1

0.3

0.4

0.1 0.1

Applying purchase/subcontracting budget

0.6

0.3

4.3

0.1

0.4

0.1

0.1

0.1

0.1 0.1 0.1 0.1 0.1

Purchase/subcontracting subjects budgeting

0.4

0.1

0.1

0.1 0.1 0.1

0.3

0.1

0.1 0.1

0.1

0.1 0.1 0.1 0.1 0.1

0.1 0.1 0.3 0.2

0.1

0.1 0.1

1.3 3.5 2.8

0.1 0.1 0.1

0.2

0.1 0.3 0.2

0.1

0.1

Unit price analysis data

0.1 0.1 0.1

0.4

0.2

0.3

0.2

2.1 2.3 2.9 9.9 3.3 5.5 3.7 4.2 4.8 7.2 3.5 4.0 2.8 3.9

0.1

Quantity accounting data

0.2

0.2

0.1 0.2 0.1 0.1

Market survey

0.1

0.1

Accurate production stander

0.1

0.1

0.4

Budget fit in with market function

2.8 7.8 3.6 2.0 3.0 1.0 3.4 3.8 5.0

Basic document comprehending

0.7

0.4

Planned delivery time fit in with customer’ s demand

Component importance

Purchase/subcontracting subjects planning

0.6

Target components

Knowledge subjects

Subcontractor inspect record

Comprehensive policy

Subcontractor’s contract

Insurance confirming record

Bidding reminder

Request Quotation form

Manuscripts of bidding form and contract

Subcontracting budget form

Subcontracting applying form

Bidding form

0.3

Operation subjects

0.1

0.1 0.2 0.1 0.2

0.1

0.2 0

0.8

0

1.7

0.2

1.2

0

0.1

4.4

0.9

0.2 0.1

0.1 0.2

6.9

0.3

0.1 0.1

0.1 0.2 0.3

7.2

1.8

0.1 0.2

0.1 0.1

2.2 0.3

2.1 2.3 2.9 0 3.3 5.5 3.7 4.2 4.8 0 3.5 4.0 2.8 3.9

1.3 3.5 2.8 77.5 19.0

M.-Y. Cheng et al. / Automation in Construction 21 (2012) 32–45

0.3 0.2 0.1 0.1 0.1

Materials conjuncture

Budgeting form

Progress schedule

Cost of substitute constructing method

Detail construction cost sheet

Purchase law

Quantity accounting sheet

Working drawing

Construction specification

Indicator of strength for knowledge demand' (KIIi)

Table 4 Knowledge/activity/process-target achievement matrix of purchase/subcontracting process.

M.-Y. Cheng et al. / Automation in Construction 21 (2012) 32–45

41

Fig. 5. e-EPC chart of the purchase/subcontracting process after reengineering.

as the basis for assessing process performance. If the value of the new process was greater than that of the original process, process reengineering results would be considered validated.

where

PV = TEA = TC

TC

ð11Þ

TEA

total expected achievement value of all target components, TEA = 0–100 total cost of the process

42

Selecting historical data

0.1

7.2

3.5

4.0

2.8

0.1

3.9

1.3

3.5

2.8 5.4

0.1

0.1

Market survey

0.2

0.6 0.1

0.1

Expected contribution degree value (CEi)

4.8 0.1

Standardized evaluation criteria

4.2

Abundant subcontractor categories

3.7

Applicable results data

5.5 0.1

Purchase/subcontracting confirms budget and construction requirements Automated Purchase/subcontracting schedule control

3.3 0.1

Standardized evaluation activity

9.9

Delivery fit in with design requirements

2.9 0.1

Transferable experience of historical cases

2.3

Standardized production quality

2.1

Standardized operation sequence

5.0 0.1

Standardized producing efficient

3.8

Standardized delivery duration

3.4

Standardized reorder frequency

1.0 0.1

Systematized delivery time

3.0 0.1

Abundant unit price analysis data

Confirm the realistic customer’sdemand

2.0 0.2

Standardized coding system

Budget unit price fit in with market

3.6 0.1

Purchase/subcontracting budget fit in with construction cost Standardized purchase/subcontracting budget form

Transparent asking bidding data

7.8

0.1

Standardized detail items of materials

2.8

Basic document comprehending

Operation subjects

No visual defects

Budget fit in with market function

Relative importance weight (wj)

Target components

Accurate production stander

Planned delivery time fit in with customer’s demand

Table 5 Target component importance of redesigned purchase/subcontracting process-target component achievement matrix.

0.1

2.4

0.3

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

7.8

Detail purchase/subcontracting subjects

0.2

0.1

0.3

0.3

0.1

0.1

0.2

0.1

0.2

0.1

0.2

0.1

0.2

0.3

0.2

0.1

0.2

0.1

0.1

0.1

13.0

Selecting standard contract template

0.1

0.1

Quantity accounting data

0.2

Revising unit price analysis data

0.1

Purchase/subcontracting subjects budgeting

0.2

Selecting standard contract annotations

0.2

0.1

0.1

0.3

0.2

0.1

0.1

0.1

0.1

0.1

0.1

0.2

0.1

0.1

0.3 0.3

0.3

0.1

0.1

0.1

0.1

9.1

0.1

4.3

0.1

2.2

0.1 0.1

Purchase/subcontractingbudget comprehending

0.2

0.8 0.4

0.1

Purchase/subcontracting budget reviewing

1.1

0.1 0.3

0.1

Applying purchase/subcontracting budget

Purchase/subcontracting budget and applying form inspecting

0.1

0.1

0.2

0.1

0.1

0.1

0.1

0.1 0.3

0.3

0.3

0.2

0.1

0.1

0.2

0.1

0.2

0.1

0.1

4.9

0.1

0.4

12.0

0.1

0.3

Expediting time reviewing

0.1

0.1

0.8

Delivery time reviewing

0.1

0.1

0.8

Evaluating Purchase/subcontracting budget knowledge

0.1

Subcontractors selecting

0.3

0.2

0.1

0.2

Ask for bidding

2.0

0.2

0.4

0.1

Quotation negotiation

0.2

0.1

Subcontractors inquiry

0.2

Subcontractors appraisal

0.3

Purchase/subcontracting budget revising

0.1

0.1

Contract revising

0.1

0. 1

Purchase/subcontracting knowledge conservation and performance inspecting (revised)

0.2

0.1

0.2

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1 0.2

0.1

0.1

0.2

1.1 0.1

0.2

1.5 1.1 4.2

0.1

0.1

0.2

0.1

0.1

0.2

0.1

0.1

0.1

0.2

7.9 0.3

7.4

Evaluating Purchase/subcontracting budget data

0.1

0.1

0.1

1.1

Evaluating contract manuscript knowledge

0.1

0.1

0.1

1.1

Evaluating special contract clauses knowledge

0.1

0.1

0.1

1.1

0.1

0.5

Evaluating Purchase/subcontracting gross margin Expected achievement value(EAj)

2.8

7.8

3.6

2.0

3.0

1.0

3.4

3.8

5.0

2.1

2.3

2.9

7.9

3.3

5.5

3.7

4.2

4.8

5.8

3.5

4.0

2.8

3.9

1.3

3.5

2.8

96.6

M.-Y. Cheng et al. / Automation in Construction 21 (2012) 32–45

Purchase/subcontracting subjects planning

M.-Y. Cheng et al. / Automation in Construction 21 (2012) 32–45

43

Table 6 Cost structure form of the Purchase/subcontracting process before reengineering. Operation subject

Resource

Unit

Quantity

Unit price

Resource cost

Cost percentage

Basic document comprehending Market survey Purchase/subcontracting subjects planning Detail purchase/subcontracting subjects Quantity accounting data Unit price analysis data Purchase/subcontracting subjects budgeting Applying purchase/subcontracting budget Purchase/subcontracting budget comprehending Purchase/subcontracting budget inspecting Subcontractors selecting Ask for bidding Quotation negotiation Subcontractors inquiry Subcontractors appraisal Purchase/subcontracting budget revising Contract revising Purchase/subcontracting performance inquiry Total cost

Purchasing agent Purchasing agent Purchasing agent Purchasing agent Purchasing agent Purchasing agent Purchasing agent Purchasing agent Cost engineer Cost engineer Purchasing agent Purchasing agent Purchasing agent Appraise cell Appraise cell Purchasing agent Purchasing agent Cost engineer

Person/day Person/day Person/day Person/day Person/day Person/day Person/day Person/day Person/day Person/day Person/day Person/day Person/day Person/day Person/day Person/day Person/day Person/day

3 5 5 7 14 25 25 5 7 8 7 10 5 15 2 3 1 4

2000 2000 2000 2000 2000 2000 2000 2000 3500 3500 2000 2000 2000 2000 10,500 2000 2000 3500

6000 10,000 10,000 14,000 28,000 50,000 50,000 10,000 24,500 28,000 14,000 20,000 10,000 30,000 21,000 6000 2000 14,000 347,500

1.73% 2.88% 2.88% 4.03% 8.06% 14.39% 14.39% 2.88% 7.05% 8.06% 4.03% 5.76% 2.88% 8.63% 6.04% 1.73% 0.58% 4.03%

3.6.1. Evaluating new target component achievement While evaluating the operation efficiency of the new purchase/ subcontracting process, expected achievement degrees for every operation target were assessed individually. It was found that the expected contribution degree value of the operation subjects achieved as much as 96.6 (as Table 5 shows), which is significantly higher than the high of 77.5 achieved by the original process. Such indicates that the post-reengineered process can fill service gaps that the existing process cannot. 3.6.2. Analyzing process cost structure A process is composed of many activities that possess input/ output relationships. Therefore, process cost may be obtained by calculating the total cost of each activity. In view of the above, this research adopted the measure of ‘Activity Based Costing (ABC)’ to distinguish the cost structure of the process [10]. In terms of the professional and technological construction management services provided by construction firms, executed business processes are usually knowledge-intensive processes. ‘Manpower’ is the primary resource consumed in the process, so that the occupation rate is much higher than the sum of the other resources. Hence this research proposes an analysis of the cost structure of the process that considers only the amount of human resources used in each operation subject in order to simplify analysis loading without losing analysis result significance. From the pre-reengineering cost structure form of the purchase/ subcontracting process (Table 6), it is obvious that almost 1/3 of total process cost involves the two items of ‘establishing unitary analysis’ and ‘establishing detailed purchase/subcontracting budget items’. Such indicates that these two should serve as the core operation subjects of the project cost estimating process. The cost structure form of reengineered purchase/subcontracting process is shown in Table 7. The ‘quantity’ and ‘unit price’ of necessary resources needed by operation subjects in the new process were obtained by analyzing relevant cases and experience. Comparing the total cost of the new process to that of the existing process, a slight increasing cost trend is apparent. This is because of the significantly increased number of operation subjects in the new process. The two operation subjects with the higher cost rate in the existing process (‘establishing the unitary analysis’ and ‘establishing the detail budget items of purchase/subcontracting’) were consolidated into a new subject — ‘adjusting the unitary analysis’, with a

significantly reduced cost. This indicated that the expected achievement of reengineering was already achieved. 3.6.3. Evaluating the improvement of process reengineering Analyzing operation efficiency and process costs before and after 77:5 ðbefore reengineeringÞb reengineering shows a PV evaluation 347; 500 96:6 ðafter reengineering Þ. This indicates that the operation efficiency 422; 000 per unit cost of the new process is superior and that, thus, the result of reengineering is acceptable. 4. Conclusion This study focused on the integration and application of two management theories — BPR and KM. Using an example of a real construction firm, we established a KM-oriented BPR model and took the purchase/subcontracting process as an example to verify attained results. This research established a process model utilizing the four major views of knowledge, role, function and control, and cooperated with the operation/knowledge subject matrix. The relationship between the business process operation model and organizational knowledge could be expressed clearly. It is valid to serve as a KM-oriented BPR model. Also, this research used KM as the main instrument to establish a KM-oriented BPR model, and fused with process analysis the concepts of single- and double-loop learning. KM could be thus implemented into the daily operation process in order to strengthen business competitiveness. Knowledge production, knowledge evaluation and knowledge integration were the most important tasks in the forming and reusing processes of organizational knowledge, which facilitated complete comprehension of the service gaps in the existing process. Utilizing the KM-oriented BPR model, this research executed process reengineering for the purchase/subcontracting process of the construction firm. Process performance and service efficiency were significantly improved. Briefly, this study established a KM-oriented BPR model able to analyze clearly business knowledge asset and management demands for business operation processes, and fused relevant KM activities to the BPR model effectively to serve as the basis to construct the KM business environment. Furthermore, the feasibility of model was

44

M.-Y. Cheng et al. / Automation in Construction 21 (2012) 32–45

Table 7 Cost structure form of the Purchase/subcontracting process after reengineering.

Operation subject

Resource

Unit

Basic document comprehending

Purchasing agent

Person/day

Quantity 3

Unit price 2000

Resource cost 6000

Cost percentage 1.42%

Market survey

Purchasing agent

Person/day

5

2000

10000

2.37%

Selecting historical data

Purchasing agent

Person/day

1

2000

2000

0.47%

Purchase/subcontracting subjects planning

Purchasing agent

Person/day

3

2000

6000

1.42%

Detail purchase/subcontracting subjects

Purchasing agent

Person/day

5

2000

10000

2.37%

Selecting standard contract template

Purchasing agent

Person/day

2

2000

4000

0.95%

Quantity accounting data

Purchasing agent

Person/day

12

2000

24000

5.69%

Revised unit price analysis data

Purchasing agent

Person/day

18

2000

36000

8.53%

Purchase/subcontracting subjects budgeting

Purchasing agent

Person/day

18

2000

36000

8.53%

Applying purchase/subcontracting budget

Purchasing agent

Person/day

4

2000

8000

1.90%

Purchase/subcontracting budget comprehending

Cost engineer

Person/day

6

3500

21000

4.98%

Purchase/subcontracting budget and applying form inspecting

Cost engineer

Person/day

9

3500

31500

7.46%

Purchase/subcontracting budget reviewing

Cost engineer

Person/day

5

3500

17500

4.15%

Expediting time reviewing

Cost engineer

Person/day

4.5

3500

15750

3.73%

Delivery time reviewing

Cost engineer

Person/day

4.5

3500

15750

3.73%

Evaluating Purchase/subcontracting budget knowledge

Cost engineer

Person/day

5

3500

17500

4.15%

Subcontractors selecting

Purchasing agent

Person/day

6

2000

12000

2.84%

Ask for bidding

Purchasing agent

Person/day

8

2000

16000

3.79%

Quotation negotiation

Purchasing agent

Person/day

5

2000

10000

2.37%

Subcontractors inquiry

Appraise cell

Person/day

12

2000

24000

5.69%

Subcontractors appraisal

Appraise cell

Person/day

4

10500

42000

9.95%

Purchase/subcontracting budget revising

Purchasing agent

Person/day

3

2000

6000

1.42%

Contract revising

Purchasing agent

Person/day

1

2000

2000

0.47%

Purchase/subcontracting knowledge conservation and performance inspecting (revised)

Cost engineer

Person/day

4

3500

14000

3.32%

Evaluating Purchase/subcontracting budget data

Cost engineer

Person/day

2

3500

7000

1.66%

Evaluating contract manuscript knowledge

Purchasing agent

Person/day

3

3500

10500

2.49%

Evaluating special contract clauses knowledge

Constructing engineer

Person/day

3

3500

10500

2.49%

2

3500

7000

1.66%

Evaluating Purchase/subcontracting gross margin Total cost

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