Trends in Business Intelligence (BI)
There are multiple trends going on in the area of business intelligence. These trends are not mutually exclusive. Their basic motivation is the same: speed, quality, and quantity, at reduced cost. In the center is the data.
Business Decision Intelligence Analysis
A business environment is dynamic, complex, and unpredictable. There is a need to remove the unstructured, ad-hoc decisions that are siloed and not connected with other departments. Local optimization is done at the expense of organization-wide efficiency. The combination of human collaboration and AI techniques such as NLP (natural language processing), ML (machine learning), and so forth helps foster automation and consistency in making decisions, reducing the risk.
Tighter regulations from risk management teams are more prevalent. From privacy and legal guidelines, new laws impact decisions. It is important to track decision-making and provide consistency regarding decision-making across the organization.
Transparent but structured and automated decision-making combined with AI techniques is another trend that is improving and automating the decision-making process. This process is intended to improve decision making by understanding how decisions are made and how outcomes are evaluated, managed, and improved.
Generally, the metrics in BI and reports keep on accumulating with time. There may be KPIs that are not key indicators for business and do not add value. However, on the other end of the spectrum, there may not be indicators that are key in making decisions but are not included in reports/dashboards.
Evaluating how a decision is made reduces technical debt and increases visibility. This improve the impact of business processes and increases the sustainability of organization decision models based on the factors like transparency, auditability, resilience, and relevance.
Proper coordination between business units (BU) and helpful critical decision flows among them bring effectiveness of efforts. Being transparent about the way decisions are made and encouraging collaborative efforts among business units and buy-in from leadership is critical.
Decision modeling across the organization often focuses only on technical skills, but we also need to focus on social, economic, and physiological factors. Creating a Center of Excellence for BI/BA/AI would be helpful for sustainability.
Improve the predictability and alignment of decision makers by simulating their behavior.
Develop staff expertise in traditional and emerging decision automation techniques that include description, diagnostic, prescriptive, and predictive analytics. Also, collaborate with SMEs (subject matter experts) in AI and business processes.