Dynamic Performance Monitoring and Management: A Metric-Based Framework to Better Predict Project Success

Fluctuating macro-economic conditions require design and construction teams to effectively and efficiently respond to project risks through improvements in management practice. The lack of meaningful performance metrics, infrequent assessment of project deficiencies and inaccurate prediction of Client satisfaction result in misaligned project management strategies. To develop and test the Dynamic Performance Monitoring and Management (DPMM) framework, this proposal draws on literature in the areas of organizational effectiveness for key performance indicators; strategic management for continuous improvement and client satisfaction; and applied microeconomics for measuring management practices. Proposal authors will implement the framework on several case studies to validate DPMM as a mechanism for tactical alignment. A representative set of metrics will be continuously tracked and reported. The project execution team will interpret metrics results and shift attention to deficient performance areas. Improvements in management practice are directly correlated with large increases in productivity and decreases in project risk. Motivating Business Problem Based on my observation of practice during six years of project management for a large-scale commercial General Contractor in California, management is predominantly ad-hoc. Project execution is based on a reference framework that is intuitive and gathered from professional experience and judgment. Initial project planning involves mental models of risks and challenges for that particular contract and those particular stakeholders. Project managers use analytical skills to adjust as needed so that the project is achieving towards project outcome objectives. The ad-hoc process is not formally documented; only informally deduced. In current practice, performance measures tracked in the dimensions of quality, cost and schedule are not effective predictors of project success. Consequently, the project team cannot consistently interpret performance to identify deficiencies in their management process. Specifically, we observe three weaknesses with current practice faced by the project execution team regarding performance monitoring. To empirically demonstrate these issues, the authors conducted one 4-month case study in Northern California on a hospital project (approximately $80 million contract value; 2 year scheduled construction duration; 66,000 sf). We implemented three performance metrics to evaluate existing management practices. 1. Management process deficiencies cannot be readily identified because certain performance measures are not tracked at all. Client Satisfaction was introduced to the case study. The Client reported weekly on a scale of 1 to 5 (most satisfied) how satisfied they were with one party of the design and construction team on each of the following:  Overall quality performance  Flexibility in aligning with Client priorities  Responsiveness in terms of efficiency  Responsiveness in terms of effectiveness FIGURE 1: Results of Client Satisfaction Metric From Figure 1, the Client developed an issue towards the beginning of August for the next two months. All measures of Client Satisfaction went down to a 1 and 2 satisfaction rating. Meanwhile, the design and construction team reported on another new metric: Latency of Critical Issues. Project team members were asked at the week’s end to list 5 of the most critical issues. For each issue, they were asked to report latency defined as the time from asking a question to receiving a useful response back. I interpret Figure 2 to signify that high latency started to emerge in August – around the same time that the Client was dissatisfied. FIGURE 2: Results on Latency of Critical Issues Metric Client satisfaction and Latency of Critical Issues were independently reported and not publically revealed. Only the research assistant received the survey results. There appears to be positive correlation between Latency and Client Satisfaction after preliminary statistical analysis. Results of this case study shows preliminary evidence that measuring and reporting latency of critical issues on a project could indicate to the management team where their process is deficient. Management focus can be justifiably diverted. Furthermore, certain metrics can bring insight to strong correlation between management deficiencies and client satisfaction whether it is causal or not. 2. Project teams cannot tactically align to project deficiencies and Client priorities because performance monitoring is not frequent and public. Six months into the project, one party of the design and construction team was replaced. Had the latency and client satisfaction metrics results been revealed each week it was surveyed to the entire project execution team, perhaps the party could have identified an issue and mitigated it. Current measures such as monthly cost reports and weekly 3-week look-ahead schedules do not indicate if management objectives are being met. These performance measures cannot be easily interpreted and translated into actionable measures because they are not frequent enough nor public enough. 3. Performance measures that are tracked do not effectively predict client satisfaction. Managers currently track latency of Requests for Information (RFIs). The average latency of all RFIs was reported during the case study. Figure 3: Latency of RFIs and Client Satisfaction Reported Over Time As described above, Client satisfaction was also measured. However, there does not appear to be direct correlation between latency of RFIs and Client satisfaction. High latency of RFIs in a week was not paralleled with low Client satisfaction. Beyond RFIs, cost reports and schedule updates that are reviewed weekly or monthly do not lend themselves to an immediate identification of management deficiencies. While this may be an appropriate metric, a different way to measure and interpret latency of RFIs is necessary to better direct management focus.