Have you faced a situation when studying for your final examinations, and you decided to skip a few unimportant chapters only to realise it was a big mistake? Questions from those chapters were a part of your paper. Situation sound familiar? But what if there was a methodology or a system that studies everything in-depth and projects results accordingly.
The world of analytics works more or less on the same lines. Analytics of any sort works in highlighting the inherent information that often gets ignored. The primary purpose of analytics is to get to the root of problems through findings driven by research, pattern based clustering of data and identifying similarities in data trends. There are multidisciplinary facets of analytics such as those in business, data-sciences and several other fields. The following article aims at rounding up various attributes that define the world of business analytics.
Given the rapid changes in the analytics field and the associated ups and downs in terms of market fluctuations that undergo while setting up acceptable business practices, managers need to be trained and skilled enough to deal with uncertainties. The XLRI business analytics program has been developed keeping in mind these crucial elements and hence proves to be an excellent resource for touching base with different subtleties that comprise analytics.
Also Read: Kickstart your Career in Analytics with Data Science Program
Just like scuba diving leads to the discovery of the oceanic flora and fauna that otherwise remain ignored and free from human eyes. Similarly, the world of business analytics presents itself with nuanced insights that get overlooked or mixed up in the sea of information. Drowning in such data, analysts need to project trends and patterns that can help businesses optimise their operations and work upwards in international markets. However, in order to learn the significant functions of business analytics, first up professionals need to understand what comprises business analytics.
Major Constituents of Business Analytics
Business analysts portray mastery in numbers, data, and skill-sets that help develop different corporational strategies. The vastness of the field lies in leveraging appropriate models for dealing with various aspects of organisational business. Business analytics is a warm fuzzy way of looking at the data at a microscopic level and drawing feasible conclusions from it.
Establishing Workable Business Models
Business models are action plans that put forth a mechanism for bringing theoretical strategies into practicality. Business analytics aims at chalking up sustainable road maps for achieving targets set up by their organisations. Analysts and managers both work in unison while drawing effective business models to keep track of its activities, procedures, end results and conclusions.
Business planning and modelling render analysts with an experimental setup for delving deep into data sources and accumulating insightful information. Once the business model has been developed and implemented, the data collecting processes, protocols and objectives can be established.
Storing Data Appropriately for Future Reference
Business analytics is a career role wherein analysts need to work with a variety of data sources on a regular basis. Once the data patterns and trends have been devised from humongous data sets, it needs to be stored appropriately for future purposes. Storage of data helps different analytical teams understand the scope and nature of information generated without reverting to the root problems.
Processing of data by leveraging computers and other computational devices is referred to as data storing and can be achieved by utilising advanced machinery for the same.
Also Read: Trends that will Transform the Future of Data Analytics
Data Visualisation for Representation of Information
Amongst the significant components of business analytics, data representation acts as the aggressor for channelizing reposts and other critical information. The process of data analytics is done via programming languages, and the results generated might not be understandable by non-programming personnel. Hence, business analysts need to be tactful in converting their findings into readable documentation.
Taking the help of visual representation software and tools will help company employees to better understand the data trends and for its efficient application. In addition, adding animations, interactive visuals, and other features will lead to increased interaction and engagement with its content.
Security of Data to Avoid Breaches
In the modern digital landscape, there lies a threat to information. Cybersecurity norms help in reducing these risks and hazards. Several leading projects today incorporate lots of fragile and sensitive data that, if not handled responsibly, can lead to major repercussions. With the advent of technology and holistic approaches for integrating information across shared devices, there needs to be a certain degree of security that prevents data from being manhandled.
In the modern environment, firewall breaches, scanning of codes and other information is quite common and calls for stricter and sterner cybersecurity measures that reduce the risk of threats and sharing of fragile data. Programmers and business analysts need to work together to build robust, encapsulated, and end-to-end encrypted data to avoid the risk of being shared for malicious reasons.
Today most of the software and tools come pre-equipped with firewalls, antivirus and anti-theft options that further reduce the risk and vulnerability of data as it gets used. Moreover, licensing of data sources can also lead to fewer breaches.
Data Mining: Digging out the Insights
Business analytics is a potent example that digs up the past for coming up with new and fresh perspectives that can help strengthen the existing strategies, work systems, patterns and other critical attributes. Just like coal miners get to the base of Earth’s ground to extract coal for its utilisation, the similar methodology works for data mining/extraction. Business analysts set up adequate and goal-specific mining models for squeezing out meaningful insights from data trends and past patterns for helping with conclusions and developing efficient policies.
The groundwork for the same starts with looking at five to ten years of historical data, researching what has worked in the past, the techniques followed, the preferred systems, and deploying mining and extracting methodologies to assist business analysts in enriching business procedures, networks, and networks overall scheme of things.
Forecasting and Future Projection
“The goal of forecasting is not to predict the future but to tell you what you need to know to take meaningful action in the present.”
The insightful quote mentioned above by Paul Safe holds true for different walks of life; the same can be applied into the world of data forecasting and projection. Although we earlier understood as to why business analysts need to dig up the past for developing result-driven strategies, this component highlights the need for mapping out those trends for future insights.
Forecasting is an essential practice that needs to be developed and inculcated within business analytics since it helps in measuring the risk of potential hazard, threats and obstructions that can hinder from finding plausible business insights, allows businesses to look how their different departments such as finances, human resources, marketing, sales and talent acquisition world look like in the near future.
Having a well-developed framework for understanding the future trends and patterns that help in bettering bottom lines, brings in more profits and income for the firms is a quintessential part of business analytics.
Also Read: How can I pursue a Career in Business Analytics in 2022?
Specifying Different Types of Business Analytics
Business analytics poses as a data vessel that drives primary income, profits and revenues for the company. The in-depth analytics help in rendering insights about the various inherent processes and intel that comes in handy while performing critical tasks for the companies. Different departments such as healthcare, finances, real estate, manufacturing, retail and others require result-driven and well-structured analysis for figuring out their budgets, business roles and additional information.
The entire process of conversion of raw and unstructured data into processed, meaningful intel is carried out by business managers. Therefore, there are several applications of analytics that partake in catering to the needs of organisations and help them arrive at deductions that would have been otherwise hard to fathom.
There are different types of analytics that govern the world of modern business, and each of these following types are instrumental in paving the way for long-lasting and sustainable strategies:-
Benefits of Descriptive Analytics
Descriptive analytics is amongst the most vital analytics types that have a direct impact on the outcome of strategies and business plans. Descriptive analytics, as the name suggests, is used for describing the path of action for a particular analysis of data and its different sources. The advent of technology today has made it easier to condensate large chunks of information into smaller digestible parts. As per studies conducted on various forms of analytics, the descriptive one proves to be at the heart of nearly 90% of businesses and has shown to boost productivity of operations.
Descriptive analytics considers creating a practical, feasible and achievable pathway for deducing results from past information sources and studying it intensely to assist future business procedures. These analytical types are at the starting point of several business tasks and arrears primarily because of their course of action. Moreover, descriptive analytics provides the information of more profound concepts in a clear and concise manner for better understanding and implementation.
Descriptive analytics makes the analysis process and its utilisation more efficient and robust by making systems capable of learning from their past behaviour and making better models in the future. Descriptive analytics render key attributes for managing various aspects of research and insights based study that helps in gathering information from varied sources, online databases and other reports. The by-product of successful and comprehensible descriptive analytics leads to great decisions and helps in strengthening overall working patterns.
Also Read: How to Initiate a Career in Business Analytics in 2022?
Benefits of Predictive Analytics
Predictive analytics helps in predicting near-future events based on the data gathered through descriptive analysis. The results found on predictive analytics help in projecting the upcoming sales, marketing, customer feedback, policies and other metrics that constitute the analytics domain. Earlier steps made using insights drawn from various sources and databases can help display the outcome of strategies and whether they can help achieve the desired objectives. The action plan drafted using descriptive analytics is brought into action through predictive mechanisms and chalk up achievable goals that lead to success and growth for companies.
Predictions come with a probability of happening, and thus, their chances can be questionable; however, rationalising and comparing different metrics can be sustained for yielding positive results. So how does predictive analytics actually work? All these predictions are conducted using collecting past and historical data, identifying data trends and patterns that appear familiar through a given period and keeping a tab over competitors for optimising business strategies and building successful strategies.
Predictive analytics are used for analysing, evaluating and testing the robustness of hypotheses and their impact on the final strategies. This type of analytics assists end-users in understanding the success of a particular event. Again several industries such as retail, social media, marketing and sales and also for developing products that perform well at the international market by observing purchase trends of customers. Potent examples of predictive analytics include popular search engines such as Google, Bing and others.
Also Read: Why You Should Become Business Analyst: Opportunities & Growth?
Benefits of Diagnostic Analytics
Diagnostic analytics provides isolated patterns and trends that conform to a specific type of data set. These analytics models delve into the root cause of the occurrence of events predicted by predictive analysis. Diagnostic analytics conducts a diagnosis of different features, detecting anomalies, clustering of data using nuanced techniques and figuring out what works best for a given data set. Diagnostic analytics helps in assessing the cause and effect of certain events and their correlations between each other.
The diagnosed based analytics augurs strategies based on probabilities, likelihoods of events happening and equal distribution of outcomes. The various areas that work using diagnostic analytics include- data discovery, mining and extraction of data, and other correlations and interactions between data patterns. Diagnostic analytics utilises different techniques such as feature importance, principal component analysis, sensitivity analysis and conjoint analysis. Social media campaigners use diagnostic analytics for analysing the things and processes that didn’t come as expected the last time around.
Diagnostic analytics provides the resources for bettering business plans, strategies and policies that undergo a successful and long-lasting workflow system. Different job sectors can utilise this analytics for getting their desired results. Retailers can track their sales and gross profit for various products and services. Moreover, healthcare departments can take the help of diagnostic analytics for taking the preferred medicines and their preferred impact on patients for studying effects upon treatment and after-effects.
Also Read: What Can You Do With a Degree or Certificate in Analytics?
Benefits of Prescriptive Analytics
Prescriptive analytics is a one-step above predictive counterpart that focuses on highlighting the probable events that are expected to happen in the forthcoming future. More than focusing on what are the ingredients and elements that help in achieving the objectives, prescriptive analytics tells business managers the exact things or planning that needs to be done for meeting corporational goals. Prescriptive analytics leverages tools that help stimulate and optimise the different outcomes and possibilities of these events transporting in the upcoming future. It brings all the theoretical planning, stagy development and other aspects into practicality.
Prescriptive analytics, also known as business optimisation data analytics, helps in providing a solution based approach for dealing with adversities and uncertainties. This type of analytics takes into consideration different outcomes and suggests practical and feasible actions based on those for rendering successful analytically backed results. Moreover, prescriptive analytics acts as the culmination point for taking in the deductions, outcomes and assessments offered by diagnostic, predictive and descriptive analytics for coming up with methodologies that can help in tactful dealing of issues.
The availability of a feedback system inherent in the prescriptive analytics algorithm assists analysts in constantly learning, updating and strengthening the relationship between action and their results. Much of the success and popularity of prescriptive analytics lies in rendering different scenarios based on outcomes instead of just one and their implementation. Prescriptive analytics is an advanced concept that learns on the go and gathers conclusive evidence based on past results for throwing future outcomes. It works in two ways, first up based on optimisation that helps understand the best outcome and set up appropriate measures for its achievement. Secondly, simulation works through assessing the critical performance areas and attaching a value along with their metrics that help get the job done.
Prescriptive analytics is an assumption based model with solid networks and pathways that help in reproducing conducive results for the firms. The prescriptive model presents the best course of action for a pre-specified event and enlists the outcomes based on several factors.
Also Read: Data scientists Vs Business Analytics: Which One is a Better Career Choice?
Benefits of Cognitive Analytics
Cognitive analytics is amongst the most advanced and innovative analytics employed by business managers in modern landscapes. The new and improved form of business analytics takes the help of artificial intelligence and nuanced data sciences mechanisms for performing insights driven tasks and displaying results. In addition to artificial and business intelligence technologies, cognitive analytics utilises semantics and machine learning principles and leverages deep learning algorithms to offer credible and valuable intel.
Cognitive analytics is peaking at the right time primarily because the current models of digitally banked data systems help in understanding and mimicking the actions performed by humans for better computation of results. Once the conclusions have been synthesised, they then need to be fed through a computer system for further evaluation. The by-product of such a novel technological mechanism helps in developing capable chatbots, virtual voice related assistants, image and bar code recognition, segmenting information gathered from different sources and forming a database for similar patterns observed throughout the research.
Given the sophisticated nature of cognitive analytics, there is a requirement for real-time data for drafting strategies and mapping out the entire data set. Therefore, cognitive analysts need to work on multiplying their sources of knowledge bases and augur processes accordingly. Along with real-time data, a combination of artificial intelligence and machine learning techniques backed by the start of the art algorithms and neural network semantics, cognitive analytics is able to extract and deploy action-driven insights.
Benefits of Different Analytical Models: A Conclusion
As seen from the broad spectrum of different analytical models mentioned above, each of the types described brings its own advantages. In terms of business applications and procedures, the availability of various analytical types helps in understanding past patterns and trends for making future projections. The XLRI business analytics program focuses on cultivating the learner’s capacity to get to the root level of problems and identify similarities between data sources. Business analytics gives firms, organisations and other enterprises foresight for improving their bottom lines by rounding up the accurate resources that lead to success.
Each business analytics- descriptive, predictive, prescriptive, diagnostic and cognitive render business managers with their unique working styles and help them enhance the quality of strategies, business plans, and other workflows by setting up pathways for an in-depth understanding of spaced out models. In addition, these various data analytics types help in enriching different aspects of business attributes and thus act as catalysts for improving predictions and recommendations required for future actions.
These different types of business analytics methodologies assist companies in harnessing growth and success through their policies and business strategies. Business analytics works in cohesion with leading technologies that assist with research, pattern search, clustering and deploying algorithms that help in achieving objectives through brilliantly set up parameters. Moving on, it’s essential to know the real world applications of business analytics that utilise these different models for making both professional and personal lives smoother and better.
Also Read: How are Business Analytics and Data Science Different?
Applications of Business Analytics
Given the knowledge obtained from the above sections about the different types and benefits of business analytics, now is the time to open the chamber of applications that rock the business analytics domain. The assimilation of various business analytics and their benefits studied above allow in giving perspectives over the business world. As part of a business manager role, working personnel require technical applications that can help solve problems and provide solutions. Each business firm aims at bettering its past performance to outclass its competitors and focuses on developing strong economic plans that bring in more revenues for the companies.
A plethora of business analytics applications, tools and software today help businesses upscale their marketing, sales and branding departments and make their product competent enough for surviving the international markets. The multidisciplinary advantages of business analytical models allow firms to understand their data sources and makes them better equipped for dealing with challenges, market fluctuations and other uncertainties. The amalgamation of applying business principles with data-driven technologies proves to be a remedy for success and higher financial returns.
The modern world of business analytics offers several applications of business analytics that have found a home in corporational settings. The applications of business analytics are manifold, with different industries utilising its practices and software for various purposes. Given how the analysts work in unison with managers for identifying patterns, trends and dig up the past data for coming up with future projections, it offers an end-to-end connection between past, current and future policies.
Today, there are various sectors that have adequate and achievable business analytics methodologies involved in their landscapes for offering desirable results. The following section looks at those sectors that are extensively incorporating business analytics tools and techniques.
Also Read: Top Benefits of Business Analytics for Marketing
Applications of Business Analytics in Agriculture
The agriculture sector reaps many benefits of business analytics that help in projecting better investment and growth patterns. Bring the most essential component of the Indian economy; the agriculture sector acts as the primary contributor that channelizes financial growth for the country. Much of the success of crop harvesting, blooming, and other factors rest on external climatic conditions, rainfall patterns, water levels and the availability of fertile lands for irrigation. Growers and agricultural experts can exploit the benefits of data driven analytical technologies for livestock management, farming and soil health.
As successful and competent business analysts, they need to foresee the upcoming climatic conditions, identify trends and patterns for waterfall and monsoons and help farmers with the ideal timings for laying out seeds for crops. Moreover, data insights and other credible sources can help make better decisions regarding introducing new and advanced mechanisms for crop production, developing and commercialising new products, and deploying IoT solutions for nuanced agriculture equipment.
The several applications of business analytics in the agriculture department include the following:-
- Successful management of product research for plants, livestock and soil health.
- Offers deep intel about agricultural practices that lead to the precise performance of crops yields.
- Provides monitoring and insights for livestock wellness and its management for maintaining the health of animals.
- Leverages live streaming data that covers all bases of agriculture from farming to crop harvesting and other processes.
- This leads to better integration and communication between the food chain by building transparent and workable models.
- It helps in understanding the impact and performance of sustainable initiatives launched by the government bodies.
As understood from the several benefits above, the application of business analytics in agriculture can prove to be a game-changer and help devise successful strategies. Furthermore, embracing the digital wave can transform the agribusiness topography and ensure that farmers get duly paid for their efforts.
Applications of Business Analytics in Finance
Business analytics in the finance field renders a variety of analytical techniques and tools for improving the financial disposition of companies. There are plenty of economic issues that require a nuanced understanding of concepts and regular evaluation of specific aspects for generating solutions. A financial setup is based on different secure systems, firewalls and alarms that help the managers know in case there are any anomalies. However, given the pace at which innovations and developments are taking place today, some several challenges and complexities conform to the financial world.
Therefore, business analysts need to be stringent enough to deploy adequate financial protocols in place that avoid mis-happenings and hazards. Moreover, modern organisations take projects that combine different elements, and hence it becomes hard to keep a tab over cash-flows, development of potential risks and other economic hindrances. In such a scenario, it’s viable to invest in business analytics tools and software that help with fraud detection, mitigating potential and future risks, pricing of products that need to be sold to end-users, marketing campaigns, financial planning, forecasting, etc.
Also Read: Improve business performance with Business Analytics & Big Data
The application of business analytics in finance settings leads to the following advantages:-
-
Helps in Reducing Costs:
The world of finance works on the principle of gathering opportunities that lead to profits. Cost management plays a direct role in maintaining profitable prospects and a higher revenue turnover. So the practice of cutting costs is essential for a business’s success and overall growth. That’s where business analytics steps in by developing practical pathways that help in reducing costs and multiplying profits. It offers a centralised methodology for workflows, operational schemas and systems that affect all levels.
-
Leads to Better HR Practices:
More often than not, companies spend a large sum of money on hiring and training new staff personnel, but sometimes they prove to be a bad fit for the companies. Therefore, taking the help of business analytics and making decisions regarding hiring specific individuals or not can prove to be cost-effective and time-saving. Analytics helps in looking at the past experiences of their new recruits, their skill-sets and acumen that further assist HR managers in understanding whether they’ll be a good match for their companies or not.
-
Identification of Market Trends and Cash-Flow Movements:
Nowadays, markets tend to be volatile in nature, and hence there are always fluctuations regarding trends and patterns. Business managers need to sit and consult with analysts for auguring strategies that are tactful to deal with changes in the modern digital age. Moreover, business analysts need to be mindful of the emerging trends and USPs for making their policies successful in the international markets. The predictive and descriptive-analytical models play a titular role in foreseeing opportunities and their association in their firms.
Furthermore, business analytics assesses and oversees product performances and assists managers in tracking the movement of money and its resources across corporations. Evaluating the cash-flow patterns leads to sustainable strategies with real-time indicators for mapping their performances.
-
Mitigation of Risks:
Among the financial department’s trickiest areas, risk management and mitigation pose the most challenging areas to navigate. Given the advantages of predictive analytics and diagnostic models, it can help predict emerging financial risks and hazards. Still, it needs to be dealt with attrition for avoiding any economic lapses. Business analytics aims at measuring the frequency of losses and debts incurred by specific organisations and their management.
One of the main advantages of analytics is its ability to categorise different risks by taking the help of data-driven intelligence mechanisms. Business analytics has therefore streamlined all the financial transactions and assists managers in probing further into problems. Risk mitigation backed by robust analytical models leads to lesser losses while making international transactions, and hence risk management strategy becomes crucial.
Also Read: Trends in Business Analytics 2022
Applications of Business Analytics in Marketing
Business analytics is helpful for sales and marketing departments and holds the key to unlocking a world of opportunities for the same. Marketing professionals require effective strategies that can attract a broader target audience and generate better ROI for their marketed products, goods and services. The different marketing elements aim to create higher customer engagement, retention, and interaction that determine the success of brands. An in-depth and well-researched understanding of the past trends and the policies that have worked for companies can help in developing future plans that are more customer-ideated.
Business analytics helps segment audiences as per their preferences, geographical locations, and other demographics for deploying strategies that target those customers. Analytics also enables marketing professionals in understanding the fashion trends and utilising them while launching new products. Moreover, the data accumulated helps in giving insights about the mode of communication- social media channels, emails, newsletters, blogs and other mechanisms that work towards driving online traffic.
The combination of analytics and marketing has led to the development of marketing analytics which offers the best of both worlds to both professionals and their customers. As per the marketing analytics principles, it caters to the demands of customers by establishing a loyal consumer base through strategic planning, marketing and deployment of tools and techniques that bring in more buyers for specific goods, services and products. Marketing analytics also influences the sales of organisations. Well-formulated marketing strategies help in closing sales by recognising customers who will sit well for the products.
Also Read: Best Business Analytics Tools For Every Business Analyst
Applications of Business Analytics in Healthcare
Business analytics can prove to be a game-changer in the healthcare arena. The critical insights help in saving lives by giving personalised treatments and mapping out the patient’s vitals based on their past healthcare history. Moreover, the healthcare and hospital services can improve their diagnosis immensely by getting to the root cause of diseases. Often doctors spend time studying a patient’s problem and could prove to be a timely affair, more so in cases where there’s a need for urgency.
Business analytics can help set up emergency room cares for the elderly and figure out their medical problems. Given the right set of medications, nursing, rest and other services, patients can recover quickly. Moreover, with the current Covid situation, the installation of systems that assess customers pulse rates and temperature levels can help in reducing the risk of contracting the virus. Business analysts take the help of statistical tools for determining the course of action for dealing with diseases and their eradication. Maintaining a database for the patients and their problems can help in handling out reports to doctors.
Hospitals are being burdened with costly administration practices and are on the lookout for solutions. Nearly one-fourth of healthcare systems go towards paying for administrative charges. Taking the help of insights rendered by business analytics allows hospitals and other clinics to streamline their administrative tasks, deploy medicines according to patient’s past history, and free up funds for better healthcare services.
Maintaining the health of employees is vital for corporations, and as such, the deep insights offered by analytics programming and research can help in recognising harmful diseases. Moreover, even for personal reasons having an analytically driven software that offers live information about the crucial details like pulse rate, cholesterol, fat percentage, and calories helps in keeping them on track and avoid major health issues.
Also Read: Top 50 Business Analyst Interview Questions & Answers in 2022
Applications of Business Analytics: Wrapping it Up
As seen from above, business analytics is a multifaceted field, having found its feet in various sectors. The applications of business analytics help develop well-rounded strategies that offer more profound insights about vital operational and financial aspects, leading to innovative business practices and financial settings. Moreover, business analytics has transformed healthcare, marketing and sales domains immensely by getting to the root of issues and offering practical solutions.
Risk mitigation and management have been a success only due to the advanced mechanisms rendered by business analytics tools and techniques. Therefore, knowing about the practical applications that lead to better utilisation of different analytics models allows new comers in this domain to understand its subtleties.
Enrolling for a well-bridged course such as the XLRI business analytics program can enable learners to familiarize themselves with its critical facets. The plethora of applications of analytics has transformed several domains today. The business analytics world offers heaps of solutions and remedies for several sectors to better equip their end-users and improve their ROI and bottom lines.
More Information:
Embarking on a Successful Career in Finance
Lucrative Job Options In The Financial Sector
What does a career in Data Analytics look like?
How to start a career in Financial Analytics in India?
Top 50 Interview Questions and Answers for Analytics Freshers in 2022
