
Construction management software currently in use at many DOTs includes the capability to generate or document change orders. Change order information the system captures includes construction contract number, dollar amount, document number, location, type of contract, change order reason code, description, and remarks (or comments). Clear, complete, and concise change order descriptions should make it easier to classify and document UR change orders properly.
It is common to use change order reason codes. However, not every DOT uses them. In the current practice, UR reason codes are often ambiguous and do not describe the root cause of a change order effectively. In other cases, a change order might cover several topics, but the system only allows users to use one reason code or, at most, a limited number of reason codes. Even in cases where the system allows users to enter multiple reason codes, it is common to only use one or two reason codes.
If a DOT uses change order reason codes, a recommendation for UR change orders is to use the disaggregated reasons listed in Table 2. If the DOT does not use reason codes or it is not possible to change the list of reason codes, a recommendation is to include the appropriate reason from Table 2 as part of the change order description.
The following are recommendations to include effective, relevant information in the description or remarks column of a change order. The examples included with each recommendation (text in italics) are real-world examples. Italicized text in bold is intended to call attention to a specific issue.
determined to add item 161-2006 compost manuf topsoil (pb) in the landscape areas. This pre-blended manufactured topsoil includes soil amendments and replaces the need for the topsoil that was to be placed. This change order will add item 161-2006 compost manuf topsoil (pb) and deduct a portion of item 160-2002 compost manuf topsoil (bos) (4).
A recommended practice to facilitate the extraction of utility-related change orders and claims from an existing database is to implement a cloud-based intelligent decision support system (IDSS) that interacts with the database and includes components that enable the classification of records, various analyses, and preparation of reports. The IDSS could be owned by the DOT or hosted on a commercial platform. Figure 9 shows the main system components, including a web application programming interface (API) to extract change order data from an existing project management system; components to process and analyze data, generate reports, and manage the system; and a user interface to interact with and run the IDSS.
Processing and analyzing change order data in the IDSS would involve a combination of automated record classification and manual review and editing. It is feasible to use AI models to automate the detection of UR change order records. It is also feasible to use trained AI models using data from one DOT to classify change order records from other DOTs if the change order description structure is similar to that used for training AI models. The feasibility of using AI models to extract UR change order records from other DOTs decreases if change order descriptions are too short or use too many acronyms. It would be necessary to train AI models specifically for these cases.