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Innovative Organisations - Research Paper Example

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Computer-aided engineering (CAE) tools have been incrementally replacing manual methods in the traditional design process for a long time. However, in recent years, the increasing availability of ever-more-powerful computing capacity has accelerated the rate of change in CAE technology. …
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Innovative Organisations
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Running Head: ORGANIZATIONAL INNOVATION Organizational Innovation of the of the Executive Summary The purpose of this research study is to recognize the best management strategies for civil/architect- engineering organizations operating in an advanced computer aided engineering technology environment. By doing research and surveys a two-phase strategy has been suggested to advance and integrate the use of CAE automation of the design quality management process. The impact of this plan on the organizational structure, human resources, and business management has been described. It was observed that the change in business environment, quality control, and design production are required in order to improve company performance. Organizational Innovation in Civil Engineering Introduction Computer-aided engineering (CAE) tools have been incrementally replacing manual methods in the traditional design process for a long time. However, in recent years, the increasing availability of ever-more-powerful computing capacity has accelerated the rate of change in CAE technology. Using the new technologies to the greatest advantage will necessitate changes in a civil or architect- engineering (A-E) firm’s design delivery and quality control processes as well as its human resource and business management strategies. Consequently, to remain competitive, A-E managers are finding it necessary to change the way they manage in order to realize the full potential of the new technologies available. The objective of this paper is to identify the best management strategies for A-E organizations operating in an advanced CAE technology environment. Present Status of CAE Technology Early computer-aided design (CAD) applications were direct replacements for manual drafting activities in the design process. Computing resources were derived from mainframes. There was little increase in initial drawing production efficiency, but drawing quality and clarity were greatly improved (Golish et al. 2003). The introduction of the remote workstation provided a technology platform to advance the CAE design process. Business Environment Architect-engineering design services are project driven businesses. The typical project is a custom designed facility to satisfy the specific requirements of a single customer. Revenue is generated on a project-by-project basis (Kerzner 2002). It is estimated that over 35,000 firms are providers of A-E design services (Golish et al. 2003). Fig 1: Impact of CAE on Labour distribution (increase in TLM over time) Increased use of CAE technology will alter key financial measures used in the industry. Fig. 1 shows projected trends in TLM as CAE technology use increases (Schriener 1996). Productivity will increase and cycle time will decrease. Direct hours to produce projects will decrease and overhead costs will increase while overall design cost will decline. This cost allocation trend is consistent with that experienced in the manufacturing sector as computer-aided engineering and production methods evolved (Noori 2001). Design Production and Quality Control Process The objective of A-E design services is to interpret customer requirements for facilities and infrastructure, including performance expectations, cost, and schedule. The products of design services are drawings, technical specifications, and other documents that provide the information necessary to construct a complete and functional facility. Failure to maintain an effective design quality management system can lead to design errors and omissions resulting in construction cost overruns, litigation, higher insurance costs, and even criminal liability, when public safety is compromised (East 1998). Fig. 2 shows the results of research indicating that the predominate source of change costs during construction deficiencies is plans and specifications (over 50%) (East 1998). Fig. 3 provides additional data which indicate that the largest source of design errors found during traditional quality control reviews are coordination and clarification (almost 45%) (Golish 2003). Fig 2: Sources of construction deficiencies Fig 3: Sources of Design Errors Organizational Structure Providing the depth of special expertise in each professional discipline, as well as assuring consistent design service processes across multiple projects, favours a functional organization for design staff (Kerzner 2002). When an engineering staff is assigned to projects, the staff is responsible to the project manager and team for the execution of their specialty and the specialty’s successful integration into the overall design. Human Resources Effective execution of the design production and quality control process is dependent on the expertise of the management and engineering staff. The traditional sequential design process is well understood and documented by design firms. The key managers in each engineering discipline have been selected based on their experience in these processes, and they are expected to train new employees and mentor them to reach full capability. The traditional process relies on experienced senior personnel to make use of their knowledge-based expertise in the quality control role during project development. This knowledge is passed to younger designers as they create designs through mentoring and on-the job training (Kinney and Jang 2005). Fig 4: Skills Requirement Fig. 4 shows the results of an industry survey that indicates A-E managers’ assessment of skill priorities in new engineers (Farr and Sullivan 2006). Proposed CAE Design Quality Control Benchmark Model The foregoing search of the literature provides the basis to propose an A-E design services quality control model that takes maximum advantage of current CAE technology. Design quality management should maximize the degree to which quality control is built into the production process. Fig 5: CAE Quality Control Model Applications of CAE as identified in the literature search can provide the basis for reaching this goal. Fig. 5 illustrates a conceptual model of a quality control automation process integrated with the design production process. The eight activities in the proposed quality control process provide the basis to maximize concurrent design production and quality control. Summary of Model Full implementation of the proposed model, along with the requisite management supporting actions, would result in a work process with the following characteristics: • All members of the design team would work through a shared project database using three-dimensional (3D) CAD and linked specification system. • Applications software working off the common project database would automatically maintain design document organization. • Applications software working off the common project database would perform continuous interference checking, code compliance, reference checking, and feedback to the designer on reference checking. • Material take-offs would be automatically generated from the 3D model and transmitted electronically to the cost-estimating software system. • Requirements documents would be available electronically continuously online to the designer for assuring design intent during production. • A designer’s ‘‘expert assistant’’ application would be linked directly to the designer’s CAD system. It would provide continuous online advice to the designer on proper use of codes and standards, specifications, constructability issues, and proper assembly of project documents. Industry Survey The above model suggests how state-of-the-art CAE technology should optimally be utilized by A-E design services organizations. The next logical step is to determine how closely the operations of representative firms conform to the dictates of the proposed model. To answer this question, engineering and quality managers in eight A-E service organizations were interviewed. The design staffs ranged from a hundred to a few thousand in size. Figs. 6 and 7 show the range of the firms surveyed in terms of revenues range and staff size. Design managers were asked to describe their current organization, approach to quality control, and degree of CAE technology utilization, as compared with the eight CAE activities in the proposed model. A qualitative ranking of degree of CAE technology implementation was constructed. Ordinal rankings for each of the eight elements were assigned based on the following criteria: • Manual activity: value of zero • Isolated CAE activities with negligible integration: value of one • Partial CAE integration—firm has initiated some CAE technology which supports integration of the individual activity in overall quality control process: value of two • Substantial CAE integration—firm has CAE technology applications involved in the actual integrated design quality control process: value of three • High CAE integration—firm has broad-based applications of CAE integrated activities, particularly in integration of data to develop construction cost and to reduce errors in plans from physical interference and specifications conflicts leading to construction changes: value of four • Full CAE integration—the CAE systems are fully integrated into the design process, expert systems are available to support the design delivery process and accomplish a large part of the quality control process, and human resources and organizational structure provide support to maximize the benefits: value of five Fig 6: Revenue breakdown of surveyed A-E firms Fig 7: Breakdown of surveyed A-E firms by Staff Size Firms were also asked if their strategic planning considers implementation of CAE technology, and what effect this technology is having on human resources and management processes. Organizational Structure Two of the organizational structures identified in the research were encountered among the firms surveyed. Four of the larger firms used a modified matrix approach to managing the design staff. Each of these companies maintained an engineering function with branches of individual disciplines. Among the smaller firms interviewed, organization was analogous to the adhocracy rather than the matrix. The underlying organizational issues for all the firms surveyed were: • The requirement for staff to support multiple projects of varying duration. • The requirement for strong project management to manage cost and schedule. Most work was fixed fee, and close customer contact was required. • The need for an organization structure and managers to develop and maintain specialized expertise. • The need for well defined, auditable quality control, clearly linked to management, and controlled to minimize deficiencies and limit financial liability. Quality Control Process All firms interviewed had formal quality control plans that were intended to meet the standard of care recommended by the Society of Civil Engineers. Quality control was the responsibility of the engineering manager. For all other aspects of the project, the design team reported to the project manager. Four larger firms also used procedures that were designed to allow ISO 9000 certification if required by a customer. Detailed functional design was reviewed by an independent engineer of at least equal qualifications, and quality assurance was checked by a supervisor in the same discipline. Level of CAE Technology Each A-E firm was asked to describe the manner in which it was currently performing each of the eight specific quality control activities in the CAE model. Based on the response, an ordinal rating was assigned. Figs. 8 and 9 summarize the data. Fig. 8 provides a summary of the implementation of the proposed CAE model at each firm. The firm rating shows the range of highest and lowest ranking and the average for all activities combined. Based on the 5-point scale selected, firms ranged in average degree of implementation of the proposed model from less than one to 3.75. The figure shows that lower levels of implementation were found in the smaller firms. Fig 8: Industry Survey: CAE use by firm CAE use in quality control Fig 9: Degree of use of individual model elements The data as presented in Fig. 9 demonstrates the degree of CAE implementation for each of the eight individual activities in the proposed model. This chart presents the high, low, and average value of each activity. The data shows that those activities having the most direct perceived impact on construction changes are being implemented more aggressively. Human Resource Management As discussed earlier, the impact of CAE on human resources is changing as the technology evolves. Engineering management requirements are in a transition period. Many current managers are not CAE literate. However, knowledge and experience in CAE is becoming a more important factor in the selection of new managers. There is wide variation in the importance individual firms are assigning to this requirement. Firms with the most advanced CAE applications demand a degree of CAE literacy for all managers. All firms, however, are assigning a high degree of importance to CAE literacy in the selection process for new engineers. The survey found most managers did not recognize the impact advanced CAE technologies will have on management activities associated with design production and quality. Recommendations Based on the results of this research, a two-phase implementation plan is suggested for firms desiring to pursue integrated automation of the design production and quality management process. The benefits and commitment to such a CAE technology program should be formally identified and included in the firm’s planning process: Phase I CAE Technology This phase is estimated to take between 12 and 18 months. Fig. 9 suggests the four CAE activities that have the highest current implementation levels. Phase I will focus on each of these activities and the necessary supporting actions. 1. Electronic data management: This activity was selected as the highest priority because it provides the foundation for all other quality control activities. This element includes acquisition of necessary software and development of internal procedures to capture and maintain engineering data in an integrated electronic data management system. 2. Interference checking: Implement a 3D CAD modelling strategy. The literature search and the industry survey identify this as an activity with immediate high payoff. It is already in use by many firms. 3. Design organization: Implement a common database for design file organization and management. Seek and acquire software that can provide continuous coordination of in-progress design drawings. This is another high payoff activity with low implementation cost and process impact. 4. Integrated cost estimating: Acquire software that will link existing automated estimating system to the common project 3D model database. This activity will greatly reduce cycle time for estimates and increase accuracy and responsiveness. Phase I should be implemented through the current organizational structure. Engineering managers will still be the source of critical expertise. Their ability to hire, train, and mentor engineers and designers and to perform effective design reviews during the transition period will greatly influence the success of the process revision. Phase II This phase is estimated to take an additional 12 to 24 months. It should extend CAE use to the remaining four activities in the model. In addition, implementation of expert systems should be considered. Additional software applications are expected to be available that will perform reference, code, and requirements checking, and constructability analysis. Online expert assistance software can provide designers guidance that will supplement the engineering manager and develop the designers’ expertise. Managers, rather than the designer, will manage the CAE design process. Use of expert assistance software will reduce the time the manager must spend on technical mentoring and allow him to spend more time on fostering an environment suitable for knowledge based learning organization (Senge 2000). Conclusions Current CAE technology implementation in the A-E design profession is largely in the form of ‘‘islands of automation’’ for individual steps in the traditional design process. These islands are linked by low technology or manual methods. Thus, there is a significant gap between current state-of-the-art capabilities and the technologies typically used by today’s practitioners. A major challenge of the strategy will be to develop realistic financial ratios and measurement parameters for costing design services. Recognition of the technology implementation issues rose in this paper and strategies to deal with them will be important to the competitiveness of the A-E design profession during the next decade. References Burns, T., and Stalker, G. M. (2001). The management of innovation. Tavistock, London. East, W. E. (1998). ‘‘Opportunities for design quality improvement through architect-engineer (A-E) liability management.’’ Rep. TR-88/3, U.S. Army Construction Engineering Research Laboratory, Champaign, Ill. Farr, J., and Sullivan, J. (2006). ‘‘Rethinking training in the 1990s.’’ J. Mgmt. in Engrg., 12(3), 29–33. Golish, M., McCunn, C., and Symonds, B. (2003). ‘‘The use of design automated software by government-contracted architect-engineer firms: a status report.’’ Army Construction Engineering Research Laboratories, Champaign, Ill. Kerzner, H. (2002). Project management, 4th Ed., Van Nostrand Reinhold, New York. Kinney, J. R., and Jang, W. R. (2005). ‘‘Training entry level engineers in civil engineering and design consulting firms.’’ J. Mgmt. in Engrg., 11(3), 35–40. Noori, H. (2001). Managing the dynamics of new technology. Prentice Hall, Engelwood Cliffs, N.J. Senge, P. M. (2000). The fifth discipline. Doubleday, New York. Bibliography Fanning, W. (1996). ‘‘Designers pump up profits.’’ Engrg. News Record, 237(11), 15. Magee, G. (1996). ‘‘Financial management primer for new project managers.’’ J. Mgmt. in Engrg., 12(5), 62–67. McCullough, R., and Patty, R. (2005). A constructibility tool for transportation facilities. Purdue University, West Lafayette, Ind. McIntyre, C., Parfitt, K., and Syal, M. (1994). ‘‘CAD based intelligent drawings: an automated quality control approach to land development.’’ Proc., 1st Congress on Comp. in Civ. Engrg., Reston, Va., 547–554. Parfitt, K., Syal, M., and Hroarsson, H. (2003). ‘‘Framework for the automated quality control system in working drawing production.’’ Proc., 5th Int. Conf. on Comp. in Civ. Engrg., Reston, Va. Tulacz, G., and Rubin, D. (1997). ‘‘The top 500 design firms.’’ Engrg. News Record, 238(15), 61. Schiener, J. (2006). ‘‘Computer spending on the rise as firms expand networks, WEB.’’ Engrg. News Record, 237, 17. Read More
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