(TCMA-3054) Data Analytics to Drive Reporting and Insights for Timely Decisions and Improved Business Performance
Author(s)/Presenters(s): Aleshia Ayers; Susan Bomba; Lamis El Didi
Time/Room: TUE 5:15-6:15/Room 1
Many large organizations have centralized reporting teams and data analysts who develop a variety of reports for communications with senior management and project and portfolio stakeholders. In an ideal world, the team understands the intricacies of the work and possesses strong data management and analysis skills. The challenges for these teams include having to use data that is often contained in various disparate systems as opposed to one source, making analysis complicated and time-consuming. Both reporting and data analysis play key roles in influencing and driving decisions and actions that lead to greater value for organizations; however, what often results is significant effort to manually curate the data to update recurring reports and less time for analyzing the data to drive key insights for timely decisions and improved business performance. In addition, large organizations cannot pivot as quickly to adopt industry-leading software or data solutions, resulting in a mixture of incompatible systems with different data formats and components. By developing a standardized reporting framework and a robust system architecture with a historical database from a data-driven perspective, an organization can be equipped with an end-to-end reporting structure and process that allows for transparent data analytics, helping project and portfolio stakeholders and leadership reach decisions more quickly and manage their business more effectively.
This paper will focus on four key areas to consider when developing a standardized reporting framework for large organizations: data automation and management, assessing effectiveness and consistency of key performance indicators, layered reporting that caters to the various levels of the target audience, and current systems and tools, including the integration of business intelligence and data visualization solutions. It will include the requirements to implement the framework, the development process, and the benefits that it offers.
(TCMA-3130) Implementing UniModel in an Owner Environment
Author(s)/Presenters(s): John B. Newman, CCP CEP; Philip D. Larson, CCP CEP PSP FAACE
Time/Room: WED 10:30-11:30/Room 1
Leveraging the existing capabilities of BIM, and 2D representation, with the addition of metadata (3D + 2D + 1D) one will get a UniModel. What is a UniModel? It is a relatively new word that describes an adherence to a process that accounts for the majority (@99.9%) of project construction costs. Considering that the concepts of total cost management (TCM) involve determining the quantity of work, including costing and pricing; using a combination of a sophisticated library (or database) of cost items with detailed resources (labor, material, equipment, etc.), factored and intelligent assemblies, standardized cost and WBS (work breakdown structure) coding structures; will allow cost professionals to more efficiently provide valuable cost data. Project control at the Central Puget Sound Regional Transit Authority (RTA), aka Sound Transit (ST), which services Pierce, King and Snohomish Counties in Washington State, have successfully employed part of this process with their unit cost library (UCL) used for the ST3 program presented and approved by voters for $53.8B, in year of expenditure dollars (YOE). There remain challenges that have yet to be overcome. However, a proof of concept (POC) has been established and the future of managing project cost looks bright.
(TCMA-3227) Forecasting Cost to Complete on Major Projects
Author(s)/Presenters(s): Christopher W. Ronak
Time/Room: WED 8:00-9:00/Room 1
This paper demonstrates the importance of regularly and accurately calculating forecasted cost-to-complete for major construction projects. The objective is to assist project controls professionals achieve better cost control, oversight of their projects and to deliver accurate projections of cash flow to all project stakeholders. Calculating forecast-to-complete is a critical aspect of project controls. It demands a careful process of budgeting, data gathering, progress measurements, change order management, time-phasing and detailed forecasting, to achieve a reliable result. This paper will dive into the processes and methods required to be able to deliver consistent, accurate results for predicting remaining project costs over a timeline and early identification of critical issues. It will clearly delineate the difference between forecast-to-complete (FTC) and the commonly used industry metric, estimate-to-complete (ETC) and the best practices for the use of each. Where ETC is a calculated metric based on past performance, FTC is a predictive metric made by project controls that forecasts remaining costs based on empirical evidence of work remaining. What’s equally significant to this method, is that it is practical and achievable and the result of working with many project controls professionals in a variety of industries over the past 10 years. This method stands out from previous methods in that it strategically leverages both distributed and automated techniques for capturing and processing key data to feed the forecasting and project controls engine.
(TCMA-3278) Developing and Implementing Visual Dashboards Using P6 Data
Author(s)/Presenters(s): Gino Napuri, EVP
Time/Room: TUE 4:00-5:00/Room 1
This presentation will focus on how to create enticing and attractive business intelligent dashboards to share with colleagues and clients using data from the most used scheduling tools.
The author has experience in large program scheduling with multiple Contractors, and has developed a workable and efficient method of handling the program scheduling reporting using two dynamic and interactive business intelligent analytics tools, Microsoft Power BI and Google Data Studio. The sharing of multiple effective and successful implemented dashboards will tempt the reader to use this new technology in their everyday work and improve client's satisfaction when it comes to dynamic visual reporting of project scheduling.
(TCMA-3285) Optimizing Construction Projects through Effective Information Governance and Data Analytics
Author(s)/Presenters(s): Sean Callahan; Heather Leins, JD; Sarah Lounsberry, JD; Vinay Nair, PE; Trent Williams
Time/Room: TUE 2:15-3:15/Room 1
The construction industry is generating data and information at an exponential rate. Due to the rapid increase of available construction data, information governance and analytics have become two of the most pressing industry processes. This paper provides an introduction to information governance, outlining the potential benefits for stakeholders throughout the project lifecycle. In addition, this paper presents a maturity model that defines a four-level information governance framework to describe the level of information governance at each phase of the construction lifecycle. Finally, this paper describes how construction projects can leverage information governance and advanced analytics to make informed project decisions, locate information quickly, mitigate risk, and prepare for potential claims and litigation.
(TCMA-3312) (Panel Discussion) TCM Analytics
Author(s)/Presenters(s): Dr. Manjula Dissanayake, CCP
Time/Room: SUN 1:00-2:00/Room 5