Often businesses and large entities and mega corporations reach a dead point despite hard driven sales efforts, to the extent that they reach the point of shutdown. To revive from such crisis various tools, technologies and methodologies are required.
Business analytics refers to the usage of statistical and technological procedures to facilitate intelligent decision making.
Analytics enables to provide a data management solution that scrutinizes and evaluates data into meaningful information.
Data analytics is a broader term comprising of business analytics. Data analytics is the means of investigating data sets using the help of expert systems and software. Primarily it includes Business Intelligence (BI), however advanced form is Online Analytical Processing (OLAP).
Off lately, Business and Data Analytics have played a pivotal role in boosting revenue, convalescing operational efficiency and making judicious use of marketing-oriented activities.
The tools and technologies used in such analytics often provides the user with first mover advantages and enables organizations to have an edge over competitors.
Generally, Data is of two types: Quantitative and Qualitative. While the former includes numbers and other information that can be easily measured, the latter assess characteristics and attributes of data like audio, images, themes, conversations etc.
Major Steps involved in Business Analytics are as follows:
First step is gathering and collection of information. The Primary data can be collected from various sources like interviews, questionnaires, surveys, reviews etc. Secondary data can also be referred from official sites like Census, government verified publications etc.
The next step is commonly referred to as ‘data mining’. Data mining is the process of using large data sets to predict trends and future consumer preferences. This step lets the entity establish relationship between variables like sales and marketing, cost of raw material and production output etc.
Once the relationships are established, future course of action can be determined. Plans can be formulated to achieve the desired objectives.
After the formulation of plans, workforce shall be aptly trained to execute the plans and if need, requisite personnel and experts shall be hired to get accurate results.
Besides the above-mentioned steps, business analytics ropes in major components such as Text Mining, Predictive Analysis, Optimization and Data Visualization.
Predictive analysis is a peculiar and interesting tool that creates models, curves and correlations from historical data to predict future opportunities. It assists in anticipating what will happen and why will it happen. Data visualization helps in presentation of conclusions drawn via charts and graphs to facilitate easy understanding and comprehension.
For instance, Business analytics succors in setting up prices of products with the help of historical data, and trends in the prevalent industry.
Application of Business Analytics:
a) Banking Industry:
To minimize risk before lending and escape the happening of fraud, many banking and credit card companies analyze withdrawal and spending patterns.
b) Stock Marketing and Brokerage services:
Many brokerage firms heavily depend on analytical tools to evaluate the performance of stocks and advice clients correctly- whether to buy, sell or hold the shares. Accurate strategies positively affects the reputation of brokerage firms.
c) E-commerce players:
E- commerce giants largely optimize business analytics to derive consumer preferences and page viewing patterns. This helps in building long lasting relationships and loyal customer base.
d) Online Web content providers:
In fact, online movie and web-series also fundamentally expend on business analytics to increase viewer screen time and offer show recommendations
e) Call centres:
Call centre personnel is hugely associated with business analytics to have current information of callers.
f) Pharma and health industry:
Health care industry, specifically in the field of treatment of cancer, uses business analytics to predict effectiveness of treatment offered. Other than that, analytics is used to predict stock of medicines, impact of disease, slots of patients, shifts of staff like nurses etc.
g) HR professionals:
Data analytics is used to predict employee retention rate by many Human Resource personnel.
h) Procurement and Investment:
Before larging investing in heavy machinery, its efficacy is measured used data tools, to predict the cost of repairs and future economic value and benefits reaped from the machine. This lets the organizations take informed decisions.
The credit period to be allowed and status of the supplier can also be ascertained before procurement of raw materials.
i) Agricultural Business Analytics:
Through controlled calculations and estimates by business analysts the availability of crops on time, quantity of seeds, fertilizer requirements can be assessed. Such analytics also considers effect of climate changes and efficiency of flood and draught risk management.
j) Bond Marketing:
This is a relatively new emerging field. With the use of info-graphic reports, businesses can overcome their liquidity crisis by accessing information and choosing suitable bonds.