Project Management Strategies to Maximize Performance in Exploratory Research: Case Study in Solar Thermal Energy Storage Technology Development
Publication: Leadership and Management in Engineering
Volume 12, Issue 2
Abstract
Exploratory research and development projects bring inherent risk due to the unfamiliar nature of the technologies investigated. No consensus exists as to a project management methodology that will consistently add value and increase the rate of success in the exploratory research process. In response to this problem, the authors present observations from their vantage point in the overall project management effort of the design, construction, and engineering of new solar thermal energy storage technologies. The project integrated the efforts of academic institutions, industry representatives, federal energy organizations, and energy utility companies. Based on observations from this case study, the authors propose a project management model to increase performance and more consistently add value in innovative settings such as exploratory technology development projects, specifically with respect to the engineering design and prototyping effort to develop commercially viable technologies. The proposed model aims to reduce schedule slippage, increase accountability, and maximize innovation through performance measurement, preplanning, and team alignment strategies in exploratory design and construction projects.
Exploratory research and development (R&D), defined as “useful knowledge building” in a particular field of inquiry, is one of the most advantageous applications of engineering in the business world (Beall 2002). The overall goal of exploratory R&D is to improve relevant performance parameters of new technologies in such a manner that the knowledge gained can be employed in a useful application (Mankins 2007). The potential benefits of exploratory R&D are appealing to academic researchers and industry members alike, since success can result in an increase in knowledge, prestige, market share, and company profits.
Unfortunately, investing time and money to explore unknown technologies is inherently risky since exploratory R&D often does not result in the level of success that is originally desired (Beall 2002). New products and systems that are contingent on the advancement of new technologies “inevitably face three major challenges during development: performance, schedule, and budget” (Mankins 2007). Exploratory R&D programs are often unable to overcome these challenges, which can lead to costly over-budget projects that not only fall behind schedule but also fail to produce the desired technological performance. As an added frustration, even when R&D programs successfully improve performance, reduce risks, or advance the maturity of a technology, these three benchmarks of success almost never progress at the same rate, which can hinder the commercial viability of a technology (Beall 2002).
These difficulties present challenges for project managers leading R&D programs. To be successful, project managers of exploratory R&D projects must implement a management structure to measure the performance of both their project team and the technological systems produced, all while maintaining the fundamental goal of exploratory R&D: promoting high levels of innovation.
Industry Efforts to Improve Exploratory R&D Performance
Despite the potential benefits of successful R&D efforts, our review of the literature and industry practices revealed no single agreed-on and tested process for conducting exploratory research and development. Several industry initiatives, however, have been undertaken with the goal of perfecting an R&D strategy to consistently deliver effective results. Some common industry strategies are discussed in the sections that follow.
NASA Technology Readiness Levels
One of the largest efforts to systematically increase the performance of R&D projects was established by the National Aeronautics and Space Administration (NASA). In the late 1980s, NASA developed the concept of technology readiness levels (TRLs) to support maturity assessments of exploratory technology as part of an overall risk assessment process (Smith 2005). The TRL system focuses on the readiness of a given technology to perform at the intended level, with the readiness level of a technology defined as a “measure of the risks of using it in the larger system: higher readiness denotes lower risk; lower readiness denotes higher risk” (Smith 2005). NASA developed a scale of technology readiness levels that could be applied to exploratory R&D programs to assess the performance level of any exploratory technology. As shown in Table 1, each TRL number is a “standard measure of the maturity of a technology” established for new technologies through a series of experiments, testing, demonstration, and analysis (Smith 2005).Table 1. National Aeronautics and Space Administration Technology Readiness Levels
| Maturity level | Technology readiness level | Definition |
|---|---|---|
| System development, test, launch, and operations | 9 | Actual system proven in successful mission operations |
| 8 | Actual system completion and qualification in test demonstration | |
| 7 | System prototype demonstration in relevant environment | |
| Technology demonstration and development | 6 | Subsystem prototype demonstration in relevant environment |
| 5 | Component or desktop validation in relevant environment | |
| 4 | Component or desktop validation in laboratory environment | |
| Research to prove feasibility of basic technology | 3 | Analytical or experimental critical function proof of concept |
| 2 | Formulation of technology concept and/or application | |
| 1 | Observation and reporting of basic principles |
NASA uses technology readiness levels to track and assess the readiness of technologies throughout its many exploratory R&D projects. At the beginning of a NASA project, an exploratory technology is given the TRL rating of 1 or 2, which signifies that the basic principles of the technology have been observed and concepts for the future application of the technology formulated, but the technology is still unproven and represents a risky investment. NASA project teams are then given the task of advancing the technology’s maturity through analytical and experimental functions to demonstrate the technology on relevant scales (TRLs 3–6). In NASA projects, TRLs of 7 and above require that the new technology be tested in a relevant environment. Once a technology has reached this level of readiness, it is considered to be validated on the experimental level and is cleared to progress to the demonstration scale. In this manner, NASA tracks and measures the development of all its new technologies with a progressive rating system.
Automated Performance Rating Systems
NASA’s TRL system has been refined and adopted by other agencies, companies, and research groups to assist in their own research and development of exploratory technologies. One of the main additions to NASA’s original TRL rating system is the advent of automated systems that assess the status of technologies under development and automatically calculate their TRL levels. One of these automated systems, the Technology Assessment and Readiness Analysis System (TARAS), has been designed to automatically perform two tasks: identify the specific TRL level of an R&D project and assess the maturity levels of individual technical components within a research project (Britt et al. 2008). Automated systems such as TARAS aim to augment the TRL rating process by consistently analyzing and classifying TRL levels for exploratory technologies, and such systems may have the potential to “grant an organization the ability to reliably gauge readiness levels in a cost efficient, mathematical model that can meet, or exceed, the accuracy of human analysts” (Britt et al. 2008). Automated TRL systems have not been perfected, however, and are not yet widely used. Although automated systems may have the potential to be useful tools in identifying the readiness of new technologies, they represent a movement toward a more complicated methodology for tracking the performance of developing exploratory technologies.
Technology Need Values
Additional modifications to the exploratory research process have been proposed that strive to assess how a project team should focus its research efforts to best develop a technology. One method is the technology need value, which consists of a separate weighting scale to assess the importance of a particular aspect in a technology’s development (Mankins 2007). Other proposals insist on the importance of mathematical modeling to produce TRL–schedule risk curves that enable project managers to “make risk-informed decisions regarding the appropriate schedule margins for a given program, or the appropriate TRL to consider” (Dubos et al. 2007). These mathematical models often require an extensive set of inputs to compute a modeled performance level for exploratory technologies.
Summary of Industry Efforts
While various methodologies offer improvement in the realm of exploratory technology development, the overall impact of these systems has been to further complicate the R&D process. These proposals mainly serve to include additional ranking criteria, complicated mathematical modeling, and automated computer software systems that can be confusing to the user and costly to implement. Moreover, none of these proposals has been proven to assist the research team in its quest to develop innovative value; instead, they are aimed at assessing the risk levels of new technologies so that companies can make more informed decisions regarding their implementation on a commercial scale. These systems are more a measure of technical risk than of actual research team performance in adding value.
Objective
The purpose of this paper is to present a project management structure that increases the efficiency of exploratory research teams with respect to the design, prototype construction, engineering, and testing of new technologies. The proposed structure was developed based on observations from the management effort of a case study project that focused on the development of exploratory renewable energy technologies. The authors directly participated in the R&D efforts by providing project management support for the research teams, and we used this vantage point within the project to document the overall project management effort with respect to engineering development of exploratory technologies for storing solar thermal energy.
We use our observations from the case study to propose a project management structure that emphasizes the need for performance measurement, focused preplanning efforts, and proper team alignment to achieve greater success in exploratory research design and engineering development. The observations and strategies learned from the case study can provide project managers with ideas on how to add value within the exploratory research process.
Research for this paper was conducted in a solar thermal energy storage (TES) technology development project that is constrained by intellectual property restrictions. The authors therefore cannot disclose specific design details of the TES technologies referred to. The organizations involved in this project also remain anonymous.
Case Study Background
The management structure proposed in this paper results from observations made in a renewable energy technology R&D project. The goal of the project was to engineer and demonstrate new thermal energy storage systems as cost-effective heat storage mechanisms for concentrating solar power plants. Efforts for the TES R&D project focused on the development of two different thermal energy storage systems, which will be referred to as TES Technology 1 and TES Technology 2. TES Technology 1 used sand as the thermal storage medium, whereas TES Technology 2 focused on the advancement of thermocline technology. As noted, specific design details for these systems are confidential and are not discussed in this paper because of intellectual property restrictions.
This case study project was a part of a federal grant awarded to a solar energy developer and an electric utility company. The diverse project team consisted of engineering departments from three major universities in addition to members of the construction industry, including a steel fabricator, a general construction company, an earthwork and foundation company, and a screw conveyor materials handling specialist. The authors directly participated in the research work to provide project management support of the research team’s efforts.
The project schedule was composed of three phases: Phase 1, design; Phase 2, prototyping; and Phase 3, demonstration. The design phase has been completed to deliver preferred engineering design approaches, and Phase 2 prototyping of these technologies is currently nearing completion.
Research Methodology
The authors provided direct project management support for the research and development of two new thermal energy storage technologies, but we also held a secondary role: to observe and document the strengths and weaknesses encountered in the efforts of the management and research teams. In this way, the TES R&D project functioned as a real-time case study of the effect of management strategies on the value produced in exploratory research.
The methodology we used to accomplish this goal was to measure various performance indicators within the TES R&D project. Performance measurement documented information regarding the project team’s performance on tasks and responsibilities that directly influenced valuable output deliverables in terms of budget, schedule, and overall performance. The following performance metrics were measured:
1.
Project schedule: The project team’s original intended schedule and scope proposals were measured against the team’s actual performance in completing valuable output items such as engineering research reports, prototype construction, prototype research testing, and engineering analysis. The project schedule was a simple document that focused on the completion of valuable output milestones; it did not include the many smaller tasks required to support the completion of the milestones.
2.
Prototype procurement: Every piece of equipment ordered for the TES technology prototypes was tracked to identify the exact budget and schedule. This information was used to identify the impact of delays in the procurement and construction process compared with the originally proposed construction schedule. In an exploratory setting, the construction and testing of new technologies is critically dependent on engineering design development and preplanning.
3.
Unforeseen risks: Unexpected design flaws encountered during prototype construction and testing were recorded, along with their proposed or enacted solution strategies. Documenting unforeseen risks ensured that lessons learned within the project were translated directly into knowledge advantages gained by the project team.
4.
Innovation tracking: Significant design improvements based on new ideas and findings were documented, along with cost and performance impact and source of innovation within the project team.
Research Findings and Discussion
Observations from the TES R&D project resulted in lessons learned that can improve exploratory research success. These findings can be incorporated into project management practices by using the following three major project management strategies, which will be discussed in detail:
1.
Performance measurement: Performance tracking of value-added deliverables improves accountability in an exploratory setting, where project scheduling must be flexible to accommodate new ideas and innovations.
2.
Focused preplanning: Research teams must focus planning efforts to define critical technology performance indicators and acceptable and unacceptable levels of performance. Preplanning should result in complete and specific plans for base prototype systems (these are not so unpredictable that they cannot be preplanned with accuracy before iterative testing and improvements). Unforeseen risks must be documented to measure deviation from the original plan and to chronicle valuable lessons learned.
3.
Team alignment: Identifying and properly integrating all project resources, individual personnel, and research teams to maximize innovation by creating a pipeline for idea development.
Performance Measurement
Schedule Tracking
Schedule tracking is a performance measurement device that functions to document the progress of the project in terms of the completion of value-added deliverables, defined as tangible project outputs that can be viewed, analyzed, or implemented by entities outside the immediate project group. An effective methodology by which to measure overall project performance is to create a schedule of value-added deliverable milestones and then track the team’s actual progress. In the TES R&D project, Phase 1 (design) deliverables included engineering design reports, presentations of progress results, engineering system design drawings, and initial cost estimates, while Phase 2 (prototyping) deliverables focused on applied engineering, prototype construction, research testing, and engineering performance analysis of various design components. In Phase 2, valuable output items for prototype construction were classified as the completion of significant construction events that enabled the prototype to support research testing on a component or subsystem level. Engineering analysis resulting from prototype research testing is a critical function in exploratory research processes; therefore, the completion of engineering design and construction activities is an important aspect of any innovative engineering project.
When tracking schedule milestones and valuable output items, the goal of project managers should be to maximize the use of dominant information by the project team. Maximizing information use is not the same as increasing the creation and flow of information; in fact, maximizing the creation and flow of information has a negative impact because it causes confusion among the project team. Not all data are important to completing a project, and it is important to communicate only pertinent information with clear documentation to promote transparency and increase accountability (Kashiwagi et al. 2006). In the TES R&D case study, we observed that exploratory projects present many opportunities for the project team to become sidetracked in details that do not always support the achievement of key performance indicators.
For these reasons, schedule tracking in an exploratory research environment must be simple and hinge on the completion of high-level action items that directly support the completion of value-added deliverables. In the TES R&D project, for example, a prototype system may be tracked according to several major subtasks such as materials procurement, construction, various stages of testing, and reporting of results and analysis. By tracking value-added deliverables in the project schedule, precedence is placed on bottom-line performance requirements while maintaining flexibility with respect to the smaller subtasks contained in the experimentation process inherent in every R&D project.
Schedule Flexibility: New Ideas versus Missed Deadlines
Schedule flexibility is warranted in exploratory research to accommodate innovation. As the project team encounters new challenges and makes new discoveries, schedule flexibility is necessary to allow the team to adapt to new ideas. Yet a schedule that is too flexible may decrease the team’s accountability to complete deliverables in accordance with the original schedule. Accountability deteriorates in exploratory research when schedule changes become so frequent that responsibility to meet deadlines becomes less emphasized. In this environment, the project team may overemphasize the impact of new ideas and blame schedule delays on the exploratory nature of the project. Project managers must be careful to differentiate between reorganizing the schedule to accommodate new ideas that may add value and allowing delays caused by a lack of execution in completing value-added deliverables according to the original schedule.
We documented the impact and cause of delays to valuable output items in the TES R&D case study to determine which delays were a natural product of the technology development process and which were avoidable (shown in Table 2). The cause of each delay was classified as technology performance or lack of execution. Technology performance delays were a direct result of either innovative improvements or lower performance than desired. Lack of execution delays resulted from poor performance by the project team because of inadequate preplanning, management, scheduling, or task completion.Table 2. Delays in Completed Valuable Output Items in Phase 1 (Design) of the Thermal Energy Storage (TES) Research and Development Project
| Valuable output item | Number of delays | Total delay (days) | Cause of delay | Impact of delay |
|---|---|---|---|---|
| TES Technology 1 Phase 1 report | 1 | 18 | Lack of execution | Schedule delay |
| TES Technology 2 Phase 1 report | 0 | 0 | — | — |
| Presentation to energy utility | 1 | 45 | Lack of execution | None |
| Presentation to federal agency | 0 | 0 | — | — |
| TES Technology 1 initial cost estimate | 1 | 64 | Lack of execution | Schedule delay |
| TES Technology 2 initial cost estimate | 1 | 64 | Lack of execution | Schedule delay |
| Phase 1 continuation report | 4 | 123 | Lack of execution | Delay in funding |
| Phase 1 annual report | 2 | 9 | Lack of execution | Delay in funding |
| Quarterly report (4th quarter 2009) | 1 | 1 | Lack of execution | Delay in funding |
| TES Technology 1 provisional patent | 1 | 75 | Lack of execution | Schedule delay |
| TES Technology 1 design drawings | 1 | 44 | Technology performance | Schedule delay |
| TES Technology 2 design presentation | 0 | 0 | — | — |
| Total | 13 | 443 | — | — |
Note: — = not applicable.
The data presented in Table 2 were compiled for Phase 1 value-added deliverables, which encompassed the highly exploratory engineering development work completed during this phase. The project experienced many delays (75% of all value-added deliverables), and most delays (89%) resulted from the project team’s poor execution of action items with respect to their original schedule projections. One reason for these delays is that the design phase for new and relatively unknown technologies is highly exploratory; it is expected that the team cannot predict results with perfect accuracy. Other delays, however, may have been avoidable. Overall, most delays had a negative impact on project performance by delaying project funding and schedule. Financial delays had a cascading effect that slowed work on future deliverables.
The many delays in the completion of high-level deliverables indicated a fundamental phenomenon that is detrimental to exploratory research project scheduling: With a consistently shifting schedule, the project team began to view delays as a normal cost of doing business in exploratory research. Completing tasks behind schedule came to be viewed not as a problem but as an unavoidable consequence of the exploratory nature of the work, thereby reducing accountability within the project.
The result of a constantly changing (and therefore unaccountable) project schedule meant that initial deadlines set for action items were not established as the result of understanding gained from preplanning efforts. Instead of preplanning, the team set overly optimistic timelines for tasks to be completed since they believed new information would inevitably cause the original schedule to change. Thus, due dates were considered nothing more than basic guidelines for the team to follow, and internal deadlines set by project managers to develop value-added deliverables were frequently not met. As this trend progressed, valuable output items were not fully completed until they were actually due to be provided to another organization, often after the original intended deadline (e.g., engineering analysis and results often were not finalized until due to project partners or funding agencies in the form of presentations or progress reports).
The commonly held perception that unforeseen risks are unavoidable results in the assumption that exploratory research projects generally cannot be executed as planned. This approach to exploratory research is inadequate; better results can be achieved through a project management model that strives to properly preplan action items and expected performance levels and to document unforeseen risks and related lessons learned.
Focused Preplanning
While accurate preplanning may appear to be futile in an exploratory project in which outcomes are often unknown, preplanning is still an essential component of project success and simply requires modified planning techniques. Observations from the TES R&D case study revealed insights into which items can and cannot be accurately preplanned within exploratory research.
Impact of Inadequate Preplanning
The construction and engineering schedule for the TES Technology 2 prototype system provides the best example of preplanning difficulties in the TES R&D project. This system was planned based on the preferred engineering design options developed during the design phase, and the overall goal was to create a prototype system to produce empirical performance results for system designs and related thermodynamic modeling tools. The project team proposed an engineered prototype construction design, schedule, and budget, but the actual performance fell short compared with the original proposed schedule.
The prototype system construction and assembly process was delayed by a total of 8 months beyond the originally proposed completion date before the system was able to support research testing. Evidence that this delay was caused by inadequate preplanning processes, and not by the exploratory nature of the technology, is the fact that most (64.6%) equipment orders for the prototype system were placed after the original construction deadline. Thus, when the team proposed its schedule, it was not yet fully aware of the equipment that was needed to build the prototype. Of the equipment orders placed after the original construction deadline, approximately 20 percent resulted from unforeseen changes to the original prototype design concept. The remaining 80 percent consisted of equipment that was necessary to build the original prototype design. Some flexibility may be appropriate when interpreting this data, for it is understandable that the original design did not account for every individual piece of equipment needed to build a first-generation, new-to-the-world prototype. However, the fact that more than 50 percent of the total equipment needed to fulfill the original design was ordered past the construction deadline demonstrates a failure in preplanning.
As a result, planning and procurement delays eventually delayed research testing by a full 8 months in relation to the original intended deadline. Therefore, much of the delay in prototype construction in the TES R&D project could have been avoided if the team had properly preplanned the design, procurement, and construction process of the TES Technology 2 prototype.
Preplanning Responsibilities
Too often, emphasis on the unknown factors of exploratory research is used to justify delays that are truly a result of poor preplanning and a lack of focus on defined performance results. In fact, the responsibility to preplan is greater in exploratory research than in typical projects because the team is required not only to plan action items, but also to specify the level of performance expected from results in order for the project to be deemed successful. The project manager’s role is to focus the project team on defining the final, tangible performance levels required for success, which is how exploratory research teams ultimately quantify their deliverables.
Preplanning to define the expected level of performance on completion is important for exploratory research action items for two main reasons. First, the research team must identify what tasks can be fully preplanned and what other tasks require documentation as truly unforeseen risks. Second, the team must define key success indicators to expressly communicate whether it has accomplished its goals.
Identifying Seen and Unforeseen Risks
While a team cannot be expected to have perfect designs for a new prototype system, it is realistic to expect that the base system can be designed accurately because the team should have a definition of the performance results they aim to achieve by experiments with the prototype system. Once the base system is in place, the team should be able to quickly identify additional equipment or refinements needed and act to incorporate them with relatively minor delays. Once the base system has been built, the exploratory nature of the system takes effect as the trial-and-error learning process transpires via operations and research testing. As the project team identifies areas of improvement, the prototype system can be augmented to examine new ideas. Acceptable delays are ones in which new ideas for testing and setup are encountered; however, these ideas must be documented as important knowledge gained in the prototype process. Unforeseen risks that are uncovered in the prototyping process are extremely valuable in that they represent know-how that provides the research team with a distinct advantage over the competition in the development of commercial-scale systems.
In the TES R&D project, prototype construction, engineering, and research testing progress has uncovered 17 important unforeseen risks to date. These risks are shown in Table 3 according to the specific area of knowledge gained. For instance, important know-how was gained from the TES Technology 2 prototype mainly in the areas of construction and engineering, operation, and maintenance that can be directly applied on the commercial scale. Unforeseen risks discovered in the prototype process for TES Technology 1 were more evenly distributed among the knowledge areas and included more risks specific to design performance. It is important to note that in the documentation of unforeseen risks, the project team not only identifies the existence of unplanned risks but also formulates a preferred strategy to overcome the challenge presented. As a result, the TES R&D prototype process has already uncovered 17 solutions to risks that were previously unknown, of enormous value when considering the feasibility of future commercialization plans.Table 3. Unforeseen Risks Encountered in the Thermal Energy Storage (TES) Technology Prototypes
| Area of knowledge gained | TES Technology 1 | TES Technology 2 |
|---|---|---|
| Technology construction and engineering | 3 | 4 |
| Technology operation and maintenance | 3 | 4 |
| Design performance | 2 | 1 |
| Total | 8 | 9 |
Defining Key Success Indicators
Defining key success indicators provides a documented and agreed-on expectation for the level of performance that will be considered successful for the new technology. In the TES R&D case study, the project team often claimed to have successfully achieved the desired results even when tasks were completed late or at lower levels of performance than originally expected. Unless indicators are specific and measurable, failure to achieve milestones as expected will be attributed to inevitable setbacks that could not be controlled, and no one will be held accountable.
Team Alignment
Innovation derived from original ideas and new knowledge is the true source of value in R&D projects. Promoting innovation requires proper alignment of resources within the project, and project managers must focus on identifying the capabilities of all team members to determine how to maximize innovation. For the TES R&D case study, maximizing innovation involved properly integrating a project team comprising multiple academic institutions, industry experts, federal agencies, and utility companies in a way that would improve the development of new ideas from initial concepts into tangible and achievable design outputs.
Collaboration with industry representatives was a major point of success that spurred most major innovations in the TES R&D case study. While the academic teams established the major theoretical concepts for each thermal energy storage system, the development of these concepts into commercially viable systems depended heavily on the input and professional knowledge of industry representatives. Often the research strategy of the academic team was to brainstorm general design strategies and then survey industry experts to get a reality-checked assessment of existing commercial capabilities that could be applied to the team’s ideas. This strategy also frequently led industry members to propose innovative design alternatives that would otherwise have remained unidentified.
For the TES Technology 1 subproject, collaboration with industry directly resulted in multiple significant design refinements. A summary of major design changes for the TES Technology 1 subproject is shown in Table 4. Innovative discoveries gained from industry affected nearly every critical aspect of the system for TES Technology 1. Design alternatives identified by industry experts included superior storage strategies for the heat storage material, improved materials handling design strategies, and enhanced heat exchanger designs. Each of the innovative design opportunities identified by industry experts provided value to the TES R&D project in some form; for example, the storage system innovation resulted in a huge cost saving opportunity (20:1 component system cost reduction), the materials handling system was identified as a significant risk that had been previously unforeseen, and industry feedback on the heat exchanger technology resulted in improved design feasibility that directly influenced scaling and heat storage capacity.Table 4. Major Design Innovations in the Design Phase of the Thermal Energy Storage Technology 1 Subproject
| Major design change | Value added | Source of innovation |
|---|---|---|
| Alternative storage system design | Realized 20:1 cost reduction for storage system | Industry (earthwork company) |
| Storage system arrangement | Minimized heat losses (improved construction and heat storage at scale) | Industry (earthwork company) |
| Materials handling system designs | Identified important unforeseen risk, initiated designs to minimize | Industry (screw conveyor company) |
| Heat exchanger design options | Surveyed commercial capabilities, selected design approaches | Industry (heat exchanger company) |
| Heat exchanger design testing | Examined design feasibility, identified preferred options | Industry (steel fabrication company) and academia |
Alignment of the research team to focus on the input of industry expertise was one of the greatest areas of success in the TES R&D case study. A key challenge was to enhance the efficiency with which new design concepts initiated by academics were delivered to industry representatives and subsequently developed into workable designs through proper alignment of efforts between various team members with varying areas of expertise. Without the knowledge gained from industry experts, critical innovations in the TES R&D project never would have been realized. This is a crucial lesson for research teams that are driven by the goal of commercialization: They must draw on the resources, knowledge, and experience provided by industry experts to verify the real-world feasibility of their designs and increase the probability of success for their project.
Discussion
Project managers can implement the performance measurement strategies described in this paper to reduce schedule slippage, minimize unforeseen risks, and increase accountability within their exploratory R&D projects. They can also align their project teams and resources to maximize innovation regarding the overall economic and technical feasibility of the technology being developed. Furthermore, one of the lessons learned from the case study project is that preplanning efforts are not futile in an exploratory setting in which expected results are not explicitly known. Instead, preplanning is an essential activity in defining the levels of performance that must be reached in order for the project to truly be deemed a success.
The use of performance information is an important management technique that increases accountability and performance, even in an exploratory setting that may not have fixed deliverables. The suggested project management structure leads project teams to focus on the valuable output produced by their research and provides simple strategies to increase project innovation and value as opposed to other more complicated technology development theories that are currently used in industry. The observations and strategies learned from the TES R&D case study are a valuable tool for project managers who are striving to develop novel technologies into innovative and commercially viable products in engineering settings in both industry and academia. Combining these factors into an overall project management strategy for exploratory research will have a beneficial impact on the value of an R&D project in terms of performance, schedule, budget, and overall innovation.
Conclusions and Recommendations
Exploratory research and development is often perceived as a venture that generally cannot be managed as predictably (and successfully) as more traditional efforts, especially in regard to preplanning, minimizing risks, and maximizing value. Instead, the uncertain nature of exploratory R&D commonly results in management approaches that conform to a more reactive, “whatever happens, happens” mentality. This approach has a negative impact on project performance, and the uncertainty involved in exploratory R&D projects is simply another aspect of the project that must be considered in management planning to optimize value.
Observations and lessons learned from a thermal energy storage R&D project provide the framework for a project management model that can be used to maximize performance in exploratory design, construction, and engineering. This model consists of three elements:We present these findings with the goal of educating project managers on ways to improve performance in their exploratory research processes. This exploratory research management model is not limited to the design and construction of renewable energy technologies, but rather consists of simple management principles that can be applied within any type of exploratory project to increase accountability, maximize innovation, and improve performance.
1.
Performance measurement is critical to increase accountability in an exploratory setting, and the project schedule should focus specifically on value-added deliverables that have tangible value to users outside the project team. Although schedule flexibility is important to provide time to explore newly discovered innovations, project managers must be conscious that too much flexibility may lead to a constantly shifting schedule in which accountability is reduced and deadlines are missed more frequently.
2.
Focused preplanning is essential in the R&D environment to define intended performance levels. Project teams not only must preplan the actions they are going to take to complete project tasks, but also must spend time up front to identify and define key success indicators that will determine if results have achieved acceptable levels of performance. R&D efforts are iterative by nature, and unforeseen risks are encountered more frequently than in traditional, nonexploratory projects. These unforeseen risks and their solutions should be formally documented because they represent extreme value in terms of technical know-how with the new technology.
3.
Team alignment is vital to promote high levels of innovation. Individual members of an R&D team may perform different roles, all of which contribute to project success. Some members directly generate new ideas, others take the ideas and strive to create workable technologies, and still others carry out analysis to provide a reality check for developing technologies. Project managers must recognize the different roles of project team members and properly align them to generate, communicate, test, and analyze new ideas in a structure that maximizes innovation.
References
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Britt, B., Berry, M., Browne, M., Merrell, M., and Kolpack, J. (2008). “Document classification techniques for automated technology readiness level analysis.” J. Am. Soc. Inform. Sci. Technol., 59(4), 675–680.
Dubos, G. F., Saleh, J. H., and Braun, R. (2008). “Technology readiness levels, schedule risk, and slippage in spacecraft design.” J. Spacecr. Rockets, 45(4), 836–842.JSCRAG
Kashiwagi, M., Sullivan, K., Kashiwagi, D., Chong, N., and Pauli, M. (2006). “Reduced information flow maximizes construction performance.” Proc., Int. Conf. in the Built Environment in the 21st Century, Universiti Teknologi MARA, Faculty of Architecture, Planning and Surveying, Shah Alam, Malaysia, 1–10.
Mankins, J. (2007). “Technology readiness and risk assessments: A new approach.” Proc., 58th Int. Astronautical Congress, Univ. of Hawaii, Shidler College of Business, Manoa, Hawaii, 7293–7301.
Smith, J. II. (2005). “An alternative to technology readiness levels for non-developmental item (NDI) software.” Proc., 38th Annual Hawaii Int. Conf. on System Sciences, 1–8. 〈http://csdl2.computer.org/comp/proceedings/hicss/2005/2268/09/22680315a.pdf〉 (Dec. 13, 2011).
Biographies
Kenneth T. Sullivan is professor, Del E. Webb School of Construction, Arizona State University, Tempe, AZ. He can be contacted at [email protected].
Brian C. Lines is a Ph.D. student, Del E. Webb School of Construction, Arizona State University, Tempe, AZ.
Information & Authors
Information
Published In
Leadership and Management in Engineering
Volume 12 • Issue 2 • April 2012
Pages: 71 - 80
Copyright
© 2012. American Society of Civil Engineers.
History
Received: Jul 5, 2011
Accepted: Dec 21, 2011
Published online: Mar 15, 2012
Published in print: Apr 1, 2012
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