In businesses, when projects fail, the blame comes on poor planning and Lack of communication. This is the reason why 66 percent of the projects are not expected to get completed on time or budget. Analytics has become the buzzword of this decade. Almost every business type is focusing on using it to change the way it makes decisions and wanted to hire business analytics professionals. The reasons behind this swift drive are need, availability and affordability. Businesses are in constant pressure to innovate due to the increasing competition and customers have become more demanding. So, to survive, managers must make the best decisions promptly to respond to market-driven forces. And, analytics is a promising method to gain insights required to make better and faster decisions. When it comes to availability and affordability, organizations are collecting tremendous data. This is mainly due to the recent technological advances and the affordability of software and hardware. So basically, companies have all the raw data possible, but they are in dire need of experts who can make sense of all it and draw relevant outcomes.
How it was started?
Since business analytics is based on statistics, it can be argued that business analytics existed during the time humans first created the barter economy. The use of statistics truly began shortly after the industrial revolution in the late-1800s, when Frederick Taylor introduced the first-ever system of business analytics. This system was used to analyze the production techniques used by manufacturing plants and the body movements of workers to identify means to attain greater efficiencies. During the 1900s, Taylor’s system inspired Henry Ford who measured the completion time on his assembly line of each component of his Ford Model T. The analysis not only transformed his work in the automobile sector, but also the manufacturing industry across the globe.
Traces of the use of business analytics can be seen as far back as World War 2 when Gordon Welchman worked at Bletchley Park with Alun Turing to break the enemy’s enigma code. They devised a method called ‘traffic analysis’ of encrypted messages which enabled them to understand which of the messages were important and worth deciphering. This was a turning point in the world war and brought about a new era for code-writers and breakers.
In the 1970s, the advent of business computers and their regular use at large corporations led to the mass use of Decision Support Systems (DSS), which helped sort and filter larger quantities of data from various business processes. The use of computers across the globe continued to increase during the 1990s, the information age. The technology boom in the information age led to a tremendous increase in information storage capacity. As a result of this, company performance reports became an accepted means to communicate the current state of business and began fueling the decision-making process.
Microsoft Excel was introduced to the world in 1985. This completely removed the need for hand-written ledgers. From being confined to analysis of data in Excel, business analytics expanded to building simulations and models to create scenarios, understand realities, and predict future states, marking the birth of predictive analytics. One of the best business analytics application examples has been seen with the business giant Microsoft when in 2015 its engineering groups’ offices moved. The company figured out that they needed to have more face-to-face interaction with their staff for improving performance by increasing collaboration. The MS Workplace Analytics team came out with the hypothesis that if a group of 1200 people moved from 5 offices down to 4, it could provide better collaboration between employees since it would reduce the distance that staff needed to travel for meetings. This move saved 100 hours of work per week and they gained a net saving of 520,000 USD per year in terms of employee time.
During the 2000s, more advancements were made in both hardware and software which also enhanced analytics capabilities. The advent of big data-enabled organizations to handle tremendous volumes of data and gather actionable insights from them with ease. The interpretation of data became more and more real-time and enabled business professionals to make changes in their processes in real-time to obtain desired results.
In the last decade, big data, cloud computing, advanced analytics, and automation have become an integral part of all business operations across the globe. Today, business analytics has become a must-have capability for organizations across industries, and the job market for analytics experts like data scientists, data engineers, data analysts, visualization experts, chief analytics officers is growing tremendously. The future of business analytics is making use of cognitive analytics, artificial intelligence, and machine learning which enables technologies to have human-like intelligence to make decisions and optimize end-to-end operations and processes while requiring very low to zero manual inputs/intervention.
Data for Business Analytics
Gathering the right data is key to getting the desired results and developing accurate forecasts. The accumulation of data for analysis two very important aspects:
- Kind of Data
- Primary Data – Raw data extracted directly from the organization’s official sources is called primary data. It is collected using methods like experimentation, observation, interviews, surveys, questionnaires, etc.
- Secondary Data – Secondary data is the data that has already been collected and used for another analysis.
- Source of Data
- Internal Source – The data found within the organization is an internally sourced dataset. The cost and time consumption for this type of data is considerably less. For example sales records, website traffic data, production data, inventory data, etc.
- External Source – The data that is not available internally and must be sourced from an external resource is externally sourced data. They cost more and consume more time in sourcing and cleaning. For example news publications, government publications, private data repositories, satellites data, etc.
Benefits of Business Analytics
- Improved Customer Service
Customers turn to analytics to ensure organizations can maintain their client base. Companies should examine the relationship between consumers and prior buying behaviors, for example. Based on this knowledge, they can analyze trends and enhance the efficiency of their website. It can be as easy as delivering a push prompt product to the shopping cart by consumers. In general, this would lead to improved consumer service and consequently more loyalty.
- Making Informed Decisions
Companies also outsource some of their operations to increase productivity. When choosing a vendor to do so they must know which vendor would offer additional revenues. The pace of delivery of the order, consistency, etc. can be measured using analytics based on consumer reviews. These data help them determine which one fits better for the company.
- Performance Enhancement
Businesses uses many tools to evaluation. For example, by simply measuring the temperatures of in-store coolers, the grocery store chain has lowered cooling costs. It was noticed that many degrees less than required were kept in the refrigerators, thereby increasing the power consumption. Thus the cost of energy decreased without impacting healthy food storage by raising the temperature.
- Fraud Identify
Finance businesses have been using fraud reduction analytics. One way of doing this by using data in an audit of past consumer sales to detect possible suspicious purchases. To determine the consumer profiles and risk level, the businesses use predictive analytics. The importance of business analytics methodology helps to assess the probability of losses and to create better consumer connections with the customers.
Scope of Business Analytics
Business Analytics has a broad variety of uses and implementations or it has a high scope of business analytics. It can be used for descriptive research in which knowledge is used to explain the situation in the past and present. This kind of descriptive research is used to determine the company’s current market position and previous business decision effectiveness.
- Analytics tools and techniques for dealing with the massive amounts of structured and unstructured data generated by the Internet of Things (IoT) will continue to gain importance.
- For predictive analysis, which is used to analyze the previous performance of the organization.
- For prescriptive analysis, which is used to formulate optimization strategies for better company results, business analytics is often used.
- To excel in a business analytics career, one needs to learn a specific skill-set. Inquisitiveness, ability to analyze, detailed knowledge of instruments and techniques, the ability to do an in-depth analysis, and quantitative skills are important for the subject to succeed.
Future of Business Analytics
- The method of using data to drive business strategy and results is business analytics. It is experiencing major, disruptive changes that will fundamentally shift the way analytics is thought about by the industry and clients. A key driver of this shift is the exponential growth in data. Also, enterprise-wide widespread acceptance of cloud computing continues to place pressure on enterprises’ capabilities to integrate all related data from various data sources.
- Business analytics moves from looking at reports generated by a system of business intelligence (BI) to an algorithm that can make choices for you. Right now the trend is to produce large quantities of data right here, later it will be the future of business analytics
- As organizations of all sizes and analytical skill levels get into the big data game, the scope in the field of business analytics is rising, and enhancing it enhances the mainstream. Exploring business analytics needs the right emphasis, the best technologies, the right people, a clean culture, and the best promise of leadership.