DATA + INFORMATION + KNOWLEDGE + DECISION MAKING
Business Intelligence is the collection of information about your customers, your competitors, your business partners, your competitive environment and your own internal operations that gives you the ability to make effective, important and strategic business decisions.
“Business Intelligence” is a term used by hardware and software vendors and information technology consultants to describe the infrastructure for warehousing, integrating, reporting, and analyzing data that comes from the business environment. The foundation infrastructure collects, stores, cleans, and make relevant information available to managers. E.g, Databases, data warehouses, and data mart. “Business Analytics” is a vendor-defined term that focuses more on tools and techniques for analyzing and understanding data. E.g, (OLAP) online analytical processing, statistics, models, and data mining.
The underlying foundation is a powerful database system that captures all relevant data, which are stored in transactional databases or combined and integrated into an enterprise-data warehouse or series of interrelated data marts to operate the business. The result from BI are delivered to managers through MIS, DSS, and ESS platform. SAP, ORACLE, IBM, SAS,, and MICROSOFT Institute are the five major systems vendors of these software and hardware suites.
According to MIS Quarterly, as a data driven approach, BI&A has its roots in the long-standing database management field, which rely heavily on various data collection, extradition, and analytics technologies (Chaudhuri et al 2011; Turban et al. 2008; Watson and Wixom 2007).
These technologies and applications are considered as BI&A 1.0 where data are mostly structured, collected by companies through various legacy systems and stored in commercial relational database management systems (RDBMS). Data management and warehousing are considered the foundation of BI&A.
The goals of Business Intelligence & Analytics is to deliver accurate nearly real-time information to decision makers.
Main functionalities of BI systems are:
- Production Reports
- Parameterized reports
- Ad hoc query search/report creation
- Drill down
- Forecasts, scenarios, models
- 80% are casual users relying on production reports
- Senior executives- Use monitoring functionalities for firm activities using visual interfaces like dashboards and score cards
- Middle managers and analysts- Ad-hoc analysis
- Operational employees -prepackaged reports. E.g Sale forecast, Customer satisfaction, loyalty and attrition, supply chain backlog etc.
Looking at the information availability through big data, business intelligence (BI) as a concept provides a means to obtain crucial information to improve strategic decisions and therefore plays an important role in current decision support systems (Inmon 2005)
According to kimball et al. (2008), the data warehouse industry – as the technological basis of BI – has reached full maturity and acceptance in the business world.
So many enterprises are making use of BI to gain competitive advantage. For instance, looking at a case study of how a fashion company (Desigual) used Business Intelligence tool through a vendor called (Board) to analysed, monitored, and improved their business performance on varied channels which composed of 200 single-brand stores (retail), 1700 department store concessions, 30 franchises (Franchising) and over 7000 multi-brand clients ( Wholesale) distribution in over 70 countries on 5 continents.
According to (Board) Desigual used a standard fashion data model based on item (Colour/Size), sub-families, families, and collections – data, which are analysed with special attention paid to organic growth, e.g. the evaluation of increased sales (excluding the contribution made by the opening of new stores in the case of the retail channel and by the acquisition of new client stores in the case of the wholesale channel.
With the BI tool, the company was able to carry out an hourly analysis of the footfall-to-sales conversion ratio, accurately evaluate the level of services provided to customers and the performance of sales staff in each individual store.
With the BI tool in use, planning and distribution to sales outlets were analysed, the tool provided the company with a precise up-to-the-minute overview of the entire logistics flow at any given time.
Customers base segmentation was analysed through Loyalty cards. In this area they were able to divide their customer base into two dimensions: Average spend and frequency of purchase; from this analysis four macro-segments were identified (High frequency, High Spend, High frequency Low Spend; Low frequency, High Spend; Low frequency, Low Spend.
Tableau software is another example of business intelligence that shows and tells. It shows you the story that’s hidden in your data, then helps you tell it to others in a clear and compelling way.
In today’s competitive corporate world, and if organization wants to stay ahead of its rivals, they need to recognise that the data and information they collect is a key asset. Data visualization tools help users see patterns and relationships in large amounts of data that would have been difficult to discern if the data were presented as traditional list of text. The ability to utilise and analyze this data provides the business with the intelligence needed to make both strategic and operational decisions. With (BI) an organisation can effectively measure its business strategy and leverage the data to make a quicker and better decision.
Kenneth C & Jane P. Laudon. Management Information System 12th ed. Managing the Digital Firm.
www.board.com/us/case-studies-12/2013-01 – 10- 17-42-54/item/227-Desigual
Business Intelligence and Analytics. From Big Data to Big Impact http://hmchen.shidler.hawaii.edu/Chen_big_data_MISQ_2012.pdf. Accessed August 2015. 02:56 am