A goal-oriented, business intelligence-supported decision-making methodology

Abstract

In many enterprises and other types of organizations, decision making is both a crucial and a challenging task. Despite their importance, many decisions are still made based on experience and intuition rather than on evidence supported by rigorous approaches. Decisions are often made this way because of lack of data, unknown relationships between data and goals, conflicting goals, and poorly understood risks. This research presents a goal-oriented, business intelligence-supported methodology for decision making. The methodology, which is iterative, allows enterprises to begin with limited data, discover required data to build their models, capture stakeholders goals, and model threats, opportunities, and their impact. It also enables the aggregation of Key Performance Indicators and their integration into goal models. The tool-supported methodology and its models aim to enhance the user's experience with common business intelligence applications. Managers can monitor the impact of decisions on the organization's goals and improve both decision models and business processes. The approach is illustrated and evaluated through a retail business scenario, from which several lessons were learned. One key lesson is that once an organization has a goal model, data can be added iteratively. The example, tool support, and lessons suggest the feasibility of the methodology.

Supply Chain Performance with Target-Oriented Firms

“…Targets can significantly steer firms' operational decisions (Shinkle 2012). A Canada-based retailer, for example, implemented a goal-oriented decision support system developed by Pourshahid et al (2014). The system recommends various operation strategies such as order quantities for groceries to meet multiple criteria such as target profit.…”

Implementation of Business Intelligence for Sales Data Management Using Interactive Dashboard Visualization in XYZ Stores

“…[2]. BI's goal is to help decisionmakers get the right information and make the right decisions to manage the business [3]. BI also has several advantages in its use, including first, eliminating jobs based on assumptions [4] because BI can provide more accurate historical data.…”

Goal Model Evaluation Based on State-Space Representation

“…A software development methodology has also been built around goal modeling [7]. Other applications of goal models in autonomous agentbased systems can be found in [6], [27]; also, other examples for applications in decision making are described in [21], [26]. A goal can be described as a desirable condition in the world, and the goal model is a graph or a language that represents the relationship between some goals from some viewpoint.…”

“…Goal models are promising in the field of strategic planning and public policy decision support, where a goal model can serve as the depiction of policymaker understanding of how to achieve his final goals [21], [26]. Figure 1 illustrates an example goal model that policymakers can think to handle the coronavirus COVID-19 pandemic.…”