There is a need for faster decision-making in an environment of increasing complexity and information overload. Business intelligence (BI) applications help enterprises take fact-based decisions rapidly by better utilising and presenting data from within and outside the enterprise.
This article describes the three broad phases in the evolution of IT applications for enterprises, from office automation to business intelligence. Most large enterprises have passed Phase 1 or 2 and are poised to reap the benefits of Phase 3.
Phase 1: Office automation
During the first wave of IT enablement of enterprises, various business activities and processes are automated (e.g. invoicing, stock-keeping, accounting, payroll and others). These IT systems commonly known as ERP (enterprise resource planning), MRP (material resource planning), CRM (customer relationship management), HRMS (human resource management system), etc., speed up the business process and provide quick access to information across the enterprise.
Typically, they maintain records in a database at the lowest level with all details of the transaction. They are used for data entry and operational reporting.
Phase 2: Data management
Over time as office automation systems mature and became pervasive, it becomes apparent that enterprise data is siloed and fragmented across the enterprise. Data management becomes even more challenging when there are mergers and acquisitions and multiple data sets need to be consolidated.
These pose several challenges such as poor data quality, incompatibilities between data sets, duplication of data and overheads in managing multiple systems. Consequently, the next phase of IT evolution is targeted at simplifying the information landscape of the enterprise.
Master data management is an approach to standardise data comprising tools and technologies for classifying, normalising, consolidating and aggregating data across the enterprise to provide a consistent view. Typically, a data warehouse is established to centralise company-wide information on a uniform platform. This warehouse can be accessed by tools for reporting and analysis.
Phase 3: Business intelligence
Business intelligence is the emerging class of IT applications that use information assets to aid in better decision-making. 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.
Metric trees: Business performance metrics are related to KPIs and are computed at various levels within the enterprise. 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.
(The author is founder and CEO, Cloud Engineering.)