Article #133 How Can Entities Involve in Capital Projects Delivery Start Taking Advantage of Artificial Intelligence When It Comes to Managing Their Projects?

Artificial Intelligence (AI) and Big Data are closely interconnected as AI is the output of Big Data, it is the intelligence that results from the processed everyday data captured during capital projects delivery life cycle phases. Therefore, to start taking artificial intelligence, those entities need to start building their big data. They need to collect data from every project management process performed during the project life cycle phases across their complete projects portfolio to provide valuable learning information for artificial intelligence applications. Artificial intelligence is a form of computing that allows machines to perform cognitive functions, such as acting or reacting to input, similar to the way humans do.

Nevertheless, the issue that faces the construction industry is that it continues to be among the least digitized. This means that the majority of the everyday data generated from delivering those projects will continue to be wasted and not captured in a way that will benefit this industry.

To understand the significance of the lack of digitization on the volume of big data that could be captured on capital projects, we will take as an example the process of Request of Information (RFI) which exists in all capital projects regardless of where they are located, size, type, complexity among others.

In most Construction Documents (agreements, drawings, specifications, and bills of quantities), developed by the Engineer, inevitably, those documents will not adequately address every single matter. There may be gaps, conflicts, or subtle ambiguities. The goal of the Request for Information (RFI) is to act as the project communication management process to resolve these gaps, conflicts, or subtle ambiguities during the bidding process or early in the construction process to eliminate the need for costly corrective measures. Should the response to the RFI lead to additional work that represents added cost or delays to the project’s scope of work, then this could lead to a change order request by the contractor.

Similar to all other project management processes, managing the Request for Information (RFI), Request for Interpretation, or Request for Clarification, the process requires to have a document template to be used by the project parties to raise the RFI query and receive the answer for this query. In addition, the details of those RFIs will be then logged in a register to provide the status of submitted, responded, and pending RFIs. Usually, the data that gets captured manually will be the RFI number, date issued, subject, date of response, and response document number if it differs from the RFI.

Using MS Excel to capture details of the submitted RFIs, additional details although not much can be added to the register. Nevertheless, this data will continue to be manually captured depending on when the information becomes available for the register administrator. Data relevant to the question raised, proposed solution, and response among others will continue to be missed from the captured data. In addition, the option to capture more data that could help in not managing the RFI but also improving the quality of the RFI such as scope, time and cost impact, project schedule activity affected, WBS level, location of affected works, specification section among others will not be a possible option.

In addition to the many RFI missing data, the MS Excel register will exclude the details of the documents attached to the RFI when it was submitted as well as responded to. Those could include drawings, specifications, bills of quantities, and pictures. Again, maybe additional effort can be forced into recording those document names and references but again there will be no option to view those documents from the register.

The missing RFI data does not end with the data on the document template but continues to include the missing data relevant to the review and response workflow steps to the RFI. The MS Excel RFI register will usually capture the date that the RFI was submitted by the contractor and the date the contractor received the response from the consultant. The register will not include the details of who had reviewed the RFI which could differ if the RFI was for mechanical, electrical, or other building systems as well as who had reviewed the RFI if the RFI was out of the project scope and if had cost and/or time impact. For each workflow step, the data that will not be captured will include who performed the step, when the action was taken, comments made by the reviewer, and action taken whether it was rejected, return or approve among others.

This means not only does less than 10% of the data that an RFI template includes getting captured but also this data will end up being captured manually and after the fact with little transparency and accountability on who has provided this data. In addition, this RFI data is captured on a separate MS Excel file similar to the many other data types captured for the hundred-plus other processes that are needed to manage the capital project. Now imagine what will be the quality and reliability of this data that need to be collected and aggregated from all those separate MS Excel files that were created and shared from the different projects managed by the organization that could be located at different locations of the world.

What Can Technology Do About This?

Using a Project Management Information System (PMIS) like PMWeb where all project management processes across the complete organization’s projects portfolio will be managed. For example, with the RFI module which is available in PMWeb by default, organizations can capture the whole data that is part of every single RFI issued including Project, Phase (Design, Tender, Construction), WBS Level, RFI Reference ID, RFI Subject or Description, Reference, Status, Revision, and Revision Date, RFI Date, Trade (Substructure, Superstructure, etc.), CSI Specification Section, Category (Structural, Mechanical, Electrical, etc.) and Priority (High, Normal, Low).

In addition, there is no limit to the additional custom fields that can be added as attributes to the RFI using the specification section. Further, if the project schedule was imported to PMWeb, then the RFI can be linked to the relevant project schedule activity.

In addition, all drawings, specification sections, contract agreements, bill of quantity, pictures, videos, and all other supportive documents to the RFI, will be attached to the RFI record. Although those can be uploaded directly into the RFI, it is recommended that all those documents be uploaded first to the PMWeb document management repository and then attach to the RFI. In addition, PMWeb allows linking project-related emails that were imported to PMWeb as well as creating hyperlinks to external websites like those for seismic activities, and building ng codes among others. All these documents and records can be viewed online from within PMWeb.

PMWeb Workflow will detail the different roles involved in submitting, reviewing, and responding to RFIs. What is important in PMWeb workflow is that all possible workflow scenarios can be mapped using the conditional workflow rules and branches. Those rules could be specific to the RFI category, CSI specification section, location, WBS level, reason, impact on scope, cost, and schedule among other RFI attributes or fields. This will ensure that the RFI will be properly distributed and circulated among those who are part of the pre-defined RFI management process.

The data captured in the PMWeb RFI form can be consumed in different ways. To start with, it will be used to generate the output form needed to formally communicate the process. This is usually contractual for all formal project communications where an output form needs to be printed, wet-signed, stamped and submitted. In addition, the data RFI data can be consumed to generate the real-time RFI log and registers. The RFI Log could be grouped by reason, status, and location among others. Similarly, the data can be sorted by those fields or RFI data, or priority level. In addition, logs can be designed to filter reported RFIs by the same codes or any other possible fields.

The RFI data along with the data captured from the hundred-plus other processes across the organization’s complete projects’ portfolio is the beginning of building the organization BIG DATA in a trustworthy, accountable, and auditable format. So, if we only consider the captured RFI data, the organization can use this data to analyze and identify trends in RFI growth patter, RFI issued by contractors, RFI issued on projects designed by a specific consultant, RFI that resulted in change orders, RFI by reason, RFI by specification section, RFI by location among others. This will enable organizations to better predict the impact of RFIs on the project’s success measures. This is one of the main key benefits of artificial intelligence and that is improving the predictability of future impacts of today’s results.

About the Authorfounder

Bassam Samman, PMP, PSP, EVP, GPM is a Senior Project Management Consultant with more than 35-year service record providing project management and controls services to over 100 projects with a total value of over US $5 Billion. Those projects included Commercial, Residential, Education, and Healthcare Buildings and Infrastructure, Entertainment and Shopping Malls, Oil and Gas Plants and Refineries, Telecommunication, and Information Technology projects. He is thoroughly experienced in complete project management including project management control systems, computerized project control software, claims analysis/prevention, risk analysis/management (contingency planning), design, supervision, training, and business development.

Bassam is a frequent speaker on topics relating to Project Management, Strategic Project Management, and Project Management Personal Skills. Over the past 35 years, he has lectured at more than 350 events and courses at different locations in the Middle East, North Africa, Europe, and South America. He has written more than 250 articles on project management and project management information systems that were featured in international and regional magazines and newspapers. He is a co-founder of the Project Management Institute- Arabian Gulf Chapter (PMI-AGC) and has served on its board of directors for more than 6 years. He is a certified Project Management Professional (PMP) from the Project Management Institute (PMI), a certified Planning and Scheduling Professional (PSP), an Earned Value Professional (EVP) from the American Association of Cost Engineers (AACE), and a Green Project Management (GPM).

Bassam holds a Master’s in Engineering Administration (Construction Management) with Faculty Commendation, from George Washington University, Washington, D.C., USA, Bachelor in Civil Engineering – from Kuwait University, Kuwait, and has attended many executive management programs at Harvard Business School, Boston, USA, and London Business School, London, UK.


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