So here, I am going to describe three phase of
evolution of IT applications for enterprises from office automation to
business intelligence.

Office Automation:- During the first wave
of IT enablement of companies, different business tasks and processes
are automated (e.g. invoicing, stock-keeping, accounting, payroll and
others). These kinds of IT systems commonly known as ERP (enterprise
resource planning), MRP (material resource planning), CRM (customer
relationship management), HRMS (human resource management system), etc.,
accelerate the business process and provide quick access to information
across the enterprise.

Commonly, they keep records in a
database at the lowest level with all details of the transaction. They
are used for data entry and operational reporting.

Businees Intelligence applications:

The rising class of IT applications which use information assets to aid
in better decision-making is business intelligence applications. A
variety of tools and techniques such as data mining, predictive
analytics and data visualisation are employed to provide valuable
insights into past, current and future business metrics.

BI
applications serve a critical function in achieving operational
efficiency, integrated planning and coordination and monitoring.

Here are the highlights of BI applications.

Single version of the truth: It provides consistent information in real
time across the enterprise, thereby eliminating debates on the validity
of data. It also visualises information through meaningful dashboards
to allow for coordinated decision-making.

performance metrics
trees: Business performance metrics are related to KPIs and are
computed at different levels within the
organization. Metrics are linked to each other to create a
metric tree, which connects the low-level performance metrics with
high-level outcome measures.

The golden triangle (budget, time
and quality): One can foresee impact of changes in specifications and
business case. This helps to manage the trade-off between budget, time
and quality.

Business modelling: It captures business dynamics in robust and transparent models.

These are useful for sensitivity analysis, simulation and scenario-based decision-making.

Looking backward, moving forward: It does not rely only on historic
data to look into the future, but integrates external and internal data
for better forecasting and predictive analytical capabilities.

It is vital for enterprises to be well-informed and take quick,
fact-based decisions in the dynamic marketplace. Business intelligence
offers a ripe set of solutions that plug into existing IT infrastructure
and bring out valuable insights.