Posted in Operations & IT Articles, Total Reads: 4011
, Published on 10 January 2014
Business Intelligence is popularly known as BI in the computer world. The term “business intelligence” was first coined by the IBM researcher ‘Hans Luhn’ in 1958, and then reused by ‘Howard Dresner’ in 1989 at Gartner Group. The whole game of BI revolves around one simple and short word DATA. Though its sounds very simple to pronounce or spell, the context and impact of the same is beyond limit of sky.
Let’s consider an example of a Rubik’s cube as shown in the figure. Cubes when scattered are very difficult to arrange and predict, but once arranged where all same coloured cubes are at one corner, it looks very attractive and simple to figure out.
Fig 1: BI Implementation
Thus, BI can be defined as a tool which converts raw data into meaningful data which can be modified with changing business climate. It is in the process of evolving from a tool reserved for technicians to an important resource for business professionals. To succeed in one’s business, one needs to be smart, really smart. Previously, when BI was not in place, business operators had to rely upon IT professionals and technicians for managing, maintaining, analysing and executing various data and data sets. With today’s BI tools, business folks can jump in and start analyzing data themselves, rather than wait for IT professionals to run complex reports.
In fact, IT companies own BI very often. The reason for this is not that they possess the best analytical capabilities but because they oversee the implementation of software tools – the so called Business Intelligence (BI) applications. The problem is that despite huge investments in BI software and solutions in recent years, many organisations still fail to convert data into strategically valuable knowledge. IT infrastructure and software alone cannot make this happen – BI must be owned by business leaders and managers who are supported by IT. Having said this, today’s BI applications come with a lot of out-of-the-box functionality that allows managers to start analysing data even without the help of statisticians and IT professionals. The figure below shows how BI connects your business and its management with IT.
Fig 2: Relationship pattern
Sophisticated technologies and skills are needed to process data (e.g. updating, deleting and refreshing data annually or quarterly), find patterns and relations (e.g. customer’s buying patterns for a given product), develop insights from past transactions (e.g. online purchases made by a user in a particular month), and make predictions (e.g. how many times a user is coming on your website and what he is looking for). Thus companies use BI to improve decision making, cut costs and identify new business opportunities.
Components of BI can be majorly classified into 4 categories:
Fig 3: Steps/Components of BI
• Collecting/Gathering Data
Process involved: ‘garbage in garbage out’. A major challenge of gathering data is making sure that the relevant data is collected in the right way at the right time.
• Keeping/Storing Data
Process involved: ‘follow physical library concept, store it as books are stored in library’. Data Warehouse and Data Marts are very important tools of BI.
• Checking/Analysing Data
Process involved: ‘format and approach data quantitatively and qualitatively’. Data mining approaches such as Probability theory of Classification, clustering and Bayesian networks and visual analytics can be done.
• Giving/Providing Access to Data
Process involved: ‘allow user not to just read or watch data but to utilize the same’. This can be explained as many websites now-a-day’s provide full access to some of their web pages not only as frontend but user can explore it as well, depending upon its importance, e.g. Dashboard and Scorecard tools and applications. The figure below shows the technical aspect of the same:
Fig 4: The key Tools
BI also uses some important tools extensively for e.g. Artificial Intelligence, Neural networks and Fuzzy logic. Then come ‘Prediction tools’ which include predictive modelling tools that design models of data to enable businesses to make profitable decisions and to predict sales levels from factors such as price, ad-spend, competitors’ activity and season.
According to many solution experts, BI is the globally recognized standard for IT professionals. It transforms IT from a cost centre to a business asset by standardizing on a single, scalable BI platform that empowers business users to easily create their own reports with information relevant to them.
The potential benefits of BI are many, some of them can be
• Quick response times, when exceptions and events occur.
• Potential ability to research access and format.
• Data comprehension without IT involvement.
• Influential and vivid decision making
• Faster and collaborative metric tracking
The market of BI is huge and spread across different sectors. The major sector areas are:
• BI vendors which includes IBM Cognos, Information Builders, Microsoft, Microstrategy, Oracle, SAP, and SAS
• Health care providers are collecting and storing volumes of data about patients. The next step is turning that data into actionable information.
• Big Restaurant chains like Ruby Tuesday and T.G.I. Friday’s are heavy users of BI software. These restaurants use BI to make strategic decisions, such as what new products to add to their menus, which dishes to remove and which underperforming stores to close. They also use BI for negotiating contracts with food suppliers and identifying opportunities to improve inefficient processes.
• One crucial component of BI which is ‘Analysing Data’ is quite essential in a wide range of industries, especially professional sports teams such as the Boston Red Sox, Oakland A’s and New England Patriots.
• Manufacturers need data- information that allows them to optimize performance, quickly respond to changing business needs and manage complex global supply chains. The data should be truly effective, data has to be actionable. It must be presented in a context so that busy manufacturing managers can quickly spot patterns, share knowledge and formulate and act on plans to drive growth and efficiency. That’s the power of business intelligence.
• Wal-Mart is the best example of vast amount of data and category analysis depending upon the customers and their types & patterns to dominate the industry.
• Amazon and Yahoo aren't just e-commerce sites; they are extremely analytical and follow a "test and learn" approach to business changes.
The next ruler of IT is Business Intelligence is well conveyed from the examples and ideas presented above. BI is about making sense of vast amounts of data collected about all dimensions of business and then taking a relevant decision that will generate value for a company. It is more than software tools and technologies, it’s a new way to understand and comprehend data in a simplified and more accessible manner.
This article has been authored by Apurva Ramteke from IIM Raipur
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