- IMD Business School
Digital transformation & AI

What is business analytics and why is it important?

In today’s data-driven world, your business’s success hinges on your ability to extract valuable insights from vast amounts of information. Enter business analytics, the transformative discipline that empowers organizations to make informed decisions, drive growth, and gain a competitive edge. In this article, we delve into the fundamentals of business analytics, explore its key components, and, most importantly, discuss why it has become an indispensable tool for thriving in the modern marketplace.

  1. What is business analytics?
  2. 6 ways business analytics can help your organization
  3. What are the types of business analytics?
  4. How business analytics works in different industries?
  5. What are some tools and tricks of the trade?
  6. What challenges come with business analytics?
  7. How can you advance your organization and career with business analytics?

What is business analytics?

It’s the systematic exploration, interpretation, and analysis of data to extract actionable insights that drive informed decision-making and improve organizational performance. It involves various statistical and quantitative techniques, data modeling, predictive analytics, and data visualization to uncover patterns, trends, and relationships within complex datasets. 

Leveraging business analytics allows you to gain a comprehensive understanding of your business operations, customer behavior, market trends, and internal processes. This helps you identify opportunities, optimize business strategies, mitigate risks, and enhance your organization’s overall efficiency and profitability.

Business analytics methods, and how they work

  • Forecasting: Since the aim of business analytics is to make data-driven decisions, business analysts use predictive modeling to analyze trends, predict outcomes, and inform business decisions. For example, you can use past sales data to predict future sales and decide how much inventory to stock for a particular season.
  • Data visualization: In data visualization, insights gleaned from data sets are contextualized and communicated through visual reports, such as charts, graphs, models, and data dashboards. Analysts use data visualization techniques to make complex data easier for an audience to digest.
  • Data mining: In data mining, the goal is to use machine learning, information technology, and statistical methods to discover patterns within data sets. It aims to uncover valuable information for decision-making, strategic planning, and gaining a competitive advantage.
  • Artificial intelligence (AI): Because it’s impossible for humans to manage and interpret big data on our own, we use AI to automatically aggregate and identify patterns within datasets. It uses algorithms and machine learning techniques to identify patterns, trends, and correlations and generate insights and predictions.
  • Optimization: This involves using mathematical algorithms and models to maximize profits, minimize costs, or optimize resource allocation. It helps organizations make informed decisions by identifying the best course of action aligned with their goals, constraints, and available data.
  • Simulation: Business analysts can create a virtual representation of a real-world system or process to analyze and understand its behavior under different scenarios. Organizations can run simulations and experiment with various inputs to gain insights into potential outcomes, assess risks, and make informed decisions that optimize performance and mitigate uncertainty.

Business analytics is all about modeling quantitative data to identify the best business decisions backed by empirical information. In the world of business analytics, there’s no room for decision-making based on gut feelings. 

What do business analysts do?

Because of the constant influx of data for organizations to deal with, data management and data analytics play an increasingly important role in every industry. Data analysts have a hand in an organization’s problem-solving and strategic decisions. Their actionable insights are valuable in all departments of an organization, from human resources and operations to marketing and finance.

A business analyst’s job is to gain insights from business data to solve business problems and do things like evaluate a company’s performance, run predictive analytics on customer behavior, and model marketing analytics. 

Beyond data analysis, they also create data visualizations that explain the findings they glean from data sets using a wide range of communication skills and visualization tools. These help clarify the reasoning behind their actionable insights. After all, understanding the best strategic decision is one thing. Convincing key stakeholders to take that course of action is another. 

6 ways business analytics can help your organization

Business analytics can do a lot, but what can it do for you? Here are the top six benefits:

1. Increase day-to-day operational efficiency

Business analytics helps organizations streamline their operations by identifying inefficiencies, bottlenecks, and areas for improvement. Businesses can use data-driven analysis to optimize processes, allocate resources more effectively, and enhance productivity, ultimately driving operational efficiency to new heights.

2. Provide insights into customer behavior and habits

Organizations can delve deep into customer data to uncover valuable insights about preferences, purchasing patterns, and behaviors. This can help them personalize their marketing strategies, tailor their product offerings, and improve customer experiences to foster long-term loyalty and boost customer satisfaction.

3. Predict the impact of company initiatives

With business analytics, organizations can create data-driven forecasts that shed light on potential outcomes, allowing for proactive decision-making and risk mitigation. Analyzing historical data, market trends, and customer insights helps businesses anticipate the market response to new product launches, marketing campaigns, or strategic investments so they can allocate resources effectively. 

4. Promote success through strategic and well-informed business decisions

With access to comprehensive data analysis, organizations can make strategic decisions based on insights rather than relying solely on intuition. Business analytics creates a solid foundation for informed decision-making so they can identify emerging trends, market opportunities, and potential risks. This results in more effective strategies that drive success and reduce uncertainties.

5. Evaluate and measure performance

Business analysts can monitor and measure key performance indicators (KPIs) to gauge their progress and success. Tracking these metrics and analyzing trends lets them assess the effectiveness of business strategies, identify areas for improvement, and align performance with broader company objectives as needed.

6. Leverage patterns and trends for a competitive advantage

Organizations can use advanced data analysis to uncover valuable data patterns, correlations, and trends. These insights help businesses anticipate customer demands and seize opportunities that can position them ahead of the competition.

What are the types of business analytics?

Here are the three main types of business analytics and how each one works:

Descriptive analytics

This branch of business analytics focuses on analyzing historical data to provide insights into past events and trends. It involves summarizing and visualizing data to understand what has happened and how certain variables are related. Descriptive analytics enables organizations to uncover data patterns, trends, and anomalies, providing a foundation for making informed decisions and identifying areas for improvement.

A real-world example of descriptive analytics is tracking sales across a designated time frame, such as a business quarter or multiple years, to understand how these fluctuations resulted in the current sales figures. 

Predictive analytics 

Where descriptive analytics looks at the past, predictive analytics looks at the future. It uses historical data, statistical modeling, and machine learning techniques to predict future outcomes. This involves analyzing data patterns and relationships to generate forecasts and probabilities. Predictive analytics enables organizations to anticipate trends, identify potential risks and opportunities, and make proactive decisions to optimize outcomes.

For example, a company can apply predictive analytics to its finances to anticipate future cash flow and profits. 

Prescriptive analytics

Prescriptive analytics goes beyond studying past data to make predictions – it uses it to create targeted solutions to business problems. It leverages advanced techniques like optimization and simulation to determine the best course of action in complex decision-making scenarios. Prescriptive analytics considers various constraints, objectives, and potential outcomes to help organizations make data-driven decisions that optimize resources, minimize risks, and maximize desired outcomes.

Prescriptive analytics in action could look like studying the results of past investments to influence future decision-making about which investments a company should (or shouldn’t) make.

How business analytics works in different industries

Because virtually every field involves some level of data management, business analytics has a hand in many industries’ decision-making processes. Here’s how it works in a few different applications:

  • Health care: With predictive modeling, data analysts can anticipate future clinical, financial, and operational needs. These forecasts can apply to things like operational costs, staffing, and resource allocation, and it can also help anticipate patient outcomes.
  • Marketing: Marketing companies can use business analytics to gain insight into customer behavior. This enables data-driven decision-making and lets them target their strategies and measure their marketing campaigns’ effectiveness.
  • Finance: Business analytics allows finance professionals to harness vast amounts of data to predict investment performance, assess risk, and evaluate potential return on investment (ROI) to make informed decisions and optimize their investment strategies.
  • Supply chain logistics: Using historical data to predict consumer demand is essential for inventory management. Business analytics can also help optimize shipping routes, vehicle performance, and delivery logistics.
  • Human resources (HR): Tracking certain KPIs and employee-related data enables HR to make better-informed decisions about recruitment and organizational structure. Businesses can gain insight into their staffing needs by analyzing workforce productivity KPIs, turnover rates, and business demands.

What are some tools and tricks of the trade?

Finding data-driven applications to business problems using big data often requires investing in the right data management and data visualization tools. Let’s take a look at some of the most commonly used business analytics tools on the market:

  • Knime Analytics Platform: This user-friendly platform lets users perform machine learning, data pipelining, and advanced analytics tasks.
  • Dundas Business Intelligence: This tool is known for its comprehensive features, including automatic trend forecasting, and helps organizations gain valuable insights into future patterns to make data-informed decisions.
  • QlikView: This tool excels in data visualization and text analysis, helping users explore and analyze their data through intuitive visualizations and interactive dashboards.
  • Sisense: This software is renowned for its data warehousing capabilities, allowing organizations to efficiently store, manage, and analyze large volumes of data.
  • Splunk: Data visualization is one key feature of this tool, but it also offers powerful data search and analysis capabilities. This helps organizations gain deep insights from machine-generated data, detect anomalies, and troubleshoot issues in real time.
  • Tableau: Tableau goes beyond traditional data visualization by incorporating natural language processing and text analysis.
  • Tibco Spotfire: If you’re looking to do statistical and text analysis, this is the tool for you. It comes with everything you need to perform advanced statistical modeling, explore patterns and correlations, and gain insights from unstructured text data.

Before investing in a business analytics tool, consider what type of data you’re analyzing and its source. This will tell you what type of usability, functions, and statistical methods you’ll need to get the insights you want. Also, decide which dashboards will be most helpful in visualizing your data depending on the unique business problems you may face.

What challenges come with business analytics?

Common challenges that may arise when implementing business analytics include:

  • Too much data from different sources: Scattered data set sources can make it difficult to synthesize the information. Your data might also be formatted as different file types, which can further complicate the data analytics process. 
  • Hiring the right business analyst: While it’s hard to know which software and tools to invest in, it might be even more difficult to bring in the right talent for the job. Ensure you understand the type of data analytics your business needs so you can find the right person to handle it.
  • Data storage: Storing and managing vast amounts of data requires robust infrastructure, efficient data architectures, and scalable storage solutions to ensure data accessibility, security, and optimal performance for analytics processes.

How can you advance your organization and career with business analytics?

An overwhelming amount of big data drives today’s decision-making, and it’s only getting larger. Data science tools like predictive modeling and forecasting allow you to identify business decisions, initiatives, and actionable insights that can lead to sustainable success for your organization. 

And with valuable benefits like improved operational efficiency and data-driven decision-making, investing in business analytics is a wise investment that can help you in the long-run. However, it’s important to weigh the costs and benefits of the tools and labor needed to do it right based on your unique needs.

If you’re inspired to leverage the power of business intelligence in your company, look no further than IMD’s Business Analytics for Leaders online program. This learning experience will equip you with a digital analytics roadmap to your company’s future success. 

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