The construction sector plays an essential role within the Canadian economy. As a result of COVID-19, the construction industry has experienced its fair share of supply chain interruptions of small equipment, tools, and consumables (SETCs) leading to productivity loss as well as cost and schedule overruns on many projects. Proactively managing supply chains can help avoid frequent handling, expedited shipping, and overstocking of SETCs. Optimizing the value supply chain on construction projects has therefore been harboring increasing interest from the Canadian construction industry. The current approach for managing and forecasting SETCs’ demand heavily relies on individual field experts’ experience and judgment causing inconsistency among the projects within one organization. Yet, little research has been directed toward a supply chain planning and forecasting perspective for these types of indirect resources. Construction supply chain research has focused on the demand and supply of direct resources such as material and labor while dismissing SETCs although they constitute a considerable portion of project costs and are essential prerequisites to performing any construction task. Given these setbacks in research and practice, this study aims to develop a data-driven forecast solution for SETCs throughout an industrial construction project’s lifecycle. This study documents the Exploratory Data Analysis (EDA) including data visualization, data wrangling, data modeling, and investigation of all possible correlations, underlying structures, and insights within a historical dataset provided by an industry partner. The EDA revealed that most orders are placed at the beginning of the project regardless of when the demand for them is needed. A deep neural network was further developed to forecast the demand quantity and request date for different SETCs. By accurately forecasting the demand for SETCs, project managers can avoid delays and workflow interruptions resulting from late deliveries. Moreover, they can mitigate indirect costs associated with early overstocking of SETCs including storing, handling, maintaining, and transporting them. This analysis and forecasting model can improve the flexibility, agility, and resilience of SETCs supply chains and aid decision-makers in balancing demand/supply schedules. To facilitate further study, additional data such as project type, crew size and labor hours, and work package schedules are needed.