Business Analytics has improved significantly over the last few years. It refers to the skills, techniques, applications, and practices for iterative exploration and investigation of business performance to derive insight and drive business planning.
This focuses on developing a consistent set of metrics to measure past performance and guide planning, based on data and statistics. Business intelligence makes extensive use of data, statistical and quantitative analysis, explanatory and predictive modeling, and fact-based management to create a drastically new decision-making setup.
Customers are the foundation of most businesses – from Fortune 500 companies to small and medium enterprises. The time to analyze data and creating predictive models is a process that yields calculable results.
With hundreds of business analytics solutions in the market, the solutions differ in price, technology, time and effort. Business intelligence is not a new phenomenon, and while some solutions talk about innovative technology, browser-based dashboards, and other tools, the basic idea is to know the customer inside out.
As millions of clickstream records are generated daily, there is a need for comprehensive analytics. Predictive modeling and detailed training records can work wonders for companies that vary in size, need and business objectives.
Especially in the financial and telecom sector, actual business analytics departments are set up, that are designed to support processes and drastically improve performance.
An organization is nothing but a system technical landscape, where it is essential to look at it as a huge amount of processes. Also identify which ones bridge the technical and business-driven side of the organization, with focus on the right path.
Making information strategy is essential, as Business Analytics works to support the improvement and maintenance of the company. Dreamfire works with vendors such as IBM to provide business optimization functions that span policy, analytics, processes, organization, applications and data.
Business analytics has an emphasis on data mining, statistical sampling and forecasting. Most enterprises want information that is convenient, so that it can feed into growth and profitability. Most of this is in convenient forms, such as executive dashboards, that show high-level measurements of corporate data.
Most people look at past purchases to predict what customers may buy next. IBM sees analytics expanding to include extracting information from unstructured data. This is usually scattered across the Web or stored in text documents.
The goal is to gather information from different systems into common repositories, and ensure discrepancies are taken care of. There are products available for every firm, so that is not a cause of concern.
Adoption is dependent on the internal mindset of the company, and the willingness to make analytics ingrained in the setup. Most businesses need to decide with confidence, and take bold steps.
Understand the business impact of your decisions, anticipate change and proactively balance risks and opportunities. Collaborate and take coordinated decisions on the best decision possible. Learn from best practices, adapt and create continuously.
As patterns and relationships are discovered, new questions are asked and the analytic process iterates until the business goal is met. It also supports tactical decision-making and creates new processes with an emphasis on statistical/quantitative analysis, data mining, predictive modeling, and multivariate testing.
Better insights come from concentrating on fewer metrics, and validating existing data. There is also an inability to properly assess business analytics in the company setup. Grid computing is touted as a method to accelerate the adoption of business analytics in the firm.
Reducing TCO is a major priority for organizations. Also, incrementally adding capacity as demand grows can make business analytics more integral to the enterprise. Companies are also now increasingly adding sustainability data into actionable insights.
Focused business analytic solutions can help get more value out of CRM solutions. Analyzing the sales and the revenue process, understanding historical forecasts and gaining insight into future trends can be done with practical analytics solutions.
Business analytics helps to create a more intelligent, intuitive enterprise setup that helps businesses cope with rapid and volatile corporate dynamics.