Analytics In Business – Surging Ahead

The analytics business is on a remarkable trajectory, with companies increasingly leveraging data-driven insights to drive growth and stay competitive. As the world becomes more interconnected and data-intensive, businesses are turning to analytics to optimize operations, improve customer satisfaction, and enhance decision-making. Let’s delve into the current state of analytics in business, including real-world examples, expert insights, and market trends that highlight its surging growth.

The growing field of business analytics

Analytics and its different dimensions – data analytics, and business analytics – have been on a growth path for a long time. 

Today’s modern business organisations that happen to use data more frequently face a myriad of complex challenges, unlike traditional business organisations. 

Fast-paced technology changes involving data science, global markets, informed and empowered customers who use data, and stiff competition are top factors for organisations to compete across the world.

There is a growing need for organisational agility, astute mechanisms, and sophisticated systems that use data analysis to guide companies to leading positions. 

Yet another environmental trend common to organisations is the deluge of data – structured and unstructured data – surrounding them. The ability to glean relevant data, analyze data, and use it for strategic decision-making marks the power of data science-driven organisations. Let’s take a closer look at the data sets involved in this process.

In a survey study spanning 100 countries among 3000 executives, managers, and analysts from 30 different industries (partnered by MIT Sloan Management Review and IBM), some of the key findings were reported as follows:–

• The use of big data analytics was 5 times more in top-performing organisations than lower performers.

• Big data usage to guide future strategies, as well as day-to-day operations, was twice as likely in these organisations.

• Decision-making in these organisations was based on rigorous analysis of data and this exceeded double the rate of lower-performing organisations (Zhao & Zhao, 2016).

Studies like these underline the power of data and the application of the analytics process in organisations. 

Let’s now discuss the basics of analytics in business and its importance. 

What is analytics in business? What does analytics mean in the context of business?

Analytics in business refers to the systematic analysis of data using statistical, mathematical, and computational methods to gain meaningful insights. The primary goal of business Analytics in business is to help businesses make informed decisions based on data analysis. 

The process of Analytics in business involves techniques such as data mining, predictive analytics, descriptive analytics, data visualization, etc. Business analytics enables organisations to identify opportunities, increase efficiency and reduce future risks.

How business analytics work?

The method of analysis you need to choose depends on the specific goal or the need of the business. So it is important to identify the needs first and then set specific parameters for data collection. 

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The process of Analytics in business begins with the collection of data. Data aggregation is the process of gathering and collecting data. The data which is collected needs to be cleaned and filtered before it can be analysed. 

Once data collection is completed, these datasets are processed with the help of analytical tools. The reports generated using BA tools help to extract valuable insights for decision-making, strategic planning, and gaining a competitive edge. 

Types of analytics in business

There are broadly 5 types of analytics in business namely: 

1. Descriptive Analytics: It is used to analyse historical data and provides a summary of events. It involves the use of key performance indicators (KPIs) to assess the present performance of a business.
2. Predictive Analytics: As the name indicates, predictive analytics involves forecasting future events or outcomes based on historical data and statistical algorithms. Predictive analytics is useful in areas like customer service, business efficiency, fraud detection and prevention, and risk management.
3. Diagnostic Analytics: This type of analytics business technique allows you to understand why certain events occurred in the past by analysing data patterns and trends. Using this analytical method, you can find the root cause of problems and certain business outcomes.
4. Prescriptive Analytics: This is a method that suggests specific actions to optimise outcomes based on predictive analytics. In other words, prescriptive analysis recommends ways to make certain situations happen based on past performance.
5. Cognitive Analytics: Cognitive analytics is the most advanced type of business analytics. It combines several intelligent technologies like AI, ML, and deep learning algorithms to mimic the human brain and make decisions that match human intelligence.

Uses of business analytics tools

Business analysts make use of a variety of software applications to collect and process data from different sources. These applications are also called business analytic tools. Analytics business tools consist of data mining tools, statistical tools, software for predictive analysis, and so on. 

Most organisations use a mix of these business analytic tools to gain actionable insights that help to improve efficiency, productivity, and profitability. 

Some examples of BA tools are: 

• • Jira
  • Confluence 
  • Trello 
  • Wrike
  • Balsamiq
  • Pencil
  • Microsoft Visio
  • Google Docs and Spreadsheets

Benefits of analytics in business

The benefits of using analytics in business are plenty. Let’s take a look. 

• Improve operational efficiency by identifying inefficiencies and areas of improvement
• Presents valuable data to support decision-making and to convince stakeholders
• Provide deep insights into customer behaviour and purchasing habits
• Allows businesses to plan for the future and understand potential outcomes of company initiatives
• Measures overall performance or KPIs and drives business growth
• Helps to uncover valuable data patterns and trends to gain a competitive advantage in the marketplace

Business Analyst Jobs

A major challenge faced by today’s organisations is the lack of skilled human resources that is adept at tackling data. 

It is estimated that by 2020, the amount of digital information will grow to 40 zettabytes (a mind-boggling byte that is!). It is against such background information that institutions like the World Economic Forum pitch the increasing importance of data analyst jobs across all industries (Thompson, 2016). 

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According to the job report by the World Economic Forum (May 2023), there is a 30-35% increase (1.4 million) in demand for roles such as Data Analysts and Scientists, Big Data Specialists, Business Intelligence Analysts, Database and Network Professionals, and Data Engineers. 

The employment of data scientists is projected to grow 35% from 2022 to 2032, much faster than the average for all occupations.

The growth of analytics in business

Analytics has become a cornerstone of modern business strategy, allowing companies to make informed decisions and navigate complex market landscapes. The integration of analytics into business operations not only enhances operational efficiency but also fosters innovation and competitiveness.

Importance of analytics

Data Analytics enables businesses to analyze vast amounts of data to uncover hidden trends and patterns. This helps in developing targeted marketing strategies, optimizing supply chains, and improving customer experiences. Moreover, analytics provides a platform for predictive modeling, which is crucial for anticipating future market conditions and making proactive business decisions.

Role in business growth

Analytics plays a pivotal role in driving business growth by:

– Enhancing Customer Experiences: Personalized services and products are designed based on customer behavior data.

– Optimizing Processes: Analytics helps in streamlining operations, reducing costs, and improving productivity.

– Making Data-Driven Decisions: Businesses use analytics to assess risks and opportunities, leading to more informed strategic decisions.

Real-world case studies

Walmart: Inventory management

Walmart is a prime example of how analytics can transform inventory management. By using predictive analytics, Walmart optimizes stock levels across its stores, ensuring that each location has the right amount of inventory. This approach reduces costs associated with excess inventory and minimizes stockouts, thereby enhancing customer satisfaction.

UnitedHealth Group: Predictive analytics in healthcare

UnitedHealth Group uses predictive analytics to improve patient outcomes. By analyzing extensive datasets, they identify patients at risk of developing chronic diseases and develop targeted care plans. This proactive approach enhances patient outcomes and optimizes healthcare resource allocation.

Starbucks: Strategic expansion

Starbucks uses data analytics to pinpoint optimal locations for new stores. By evaluating demographic data and competitive landscapes, Starbucks ensures strategic expansion and maximizes market penetration.

Market trends and statistics

The analytics and business intelligence software market grew by 22% in 2022, according to Gartner. This significant growth underscores the increasing reliance on analytics across industries.

• Growth rate: The analytics market is expected to continue growing rapidly, driven by the demand for data-driven decision-making.
• Industry adoption: Businesses from all sectors are adopting analytics to improve operational efficiency and enhance customer experiences.

Future of analytics in business

As technology evolves, the future of analytics looks promising. Emerging trends like AI, machine learning, and cloud computing are expected to further enhance analytics capabilities.

• AI integration: AI will play a crucial role in automating data analysis and providing real-time insights.
• Cloud analytics: Cloud-based analytics platforms will offer scalability and flexibility, enabling businesses to process large datasets efficiently.

Key takeaways

• Analytics for Growth: Businesses are leveraging analytics to drive growth and improve competitiveness.
• Real-World Applications: Companies like Walmart, UnitedHealth Group, and Starbucks are using analytics to enhance operations and customer experiences.
• Market Trends: The analytics market is seeing rapid growth, driven by industry demand for data-driven insights.

How will organizations fill up these job positions?

There could be two ways in which organisations go about filling up the requirement for data analyst job positions – one, they could hire talent, or two, they could train/ retrain existing talent. 

Whatever the route that organisations take, one thing is sure – the learner community needs to be ‘analytics-ready’ (the author’s idea of being future-ready). 

Conclusion

The analytics business is surging ahead, driven by its ability to provide actionable insights that enhance business operations and drive growth. As technology advances, the role of analytics will only become more pivotal. Businesses must continue to invest in analytics capabilities to stay competitive in a data-driven world.

If you’re considering a job in business analytics, now is the right time to embark on this exciting journey. Join our EMBA in Business Analytics course. Whether you’re a fresher or an experienced professional looking for an opportunity, you can start by enrolling in online courses, PG courses, or certifications to equip you with the necessary technical skills.