While information systems have always been a critical component of effective business management, the phenomenal pace of technological advancement has made it increasingly difficult to keep up with best practices.
Today’s digital technologies have resulted in the development of information systems that are radically transforming the very nature of managerial work, the structure of organizations, and the way firms operate and compete in an ever-changing global marketplace. In turn, the importance of business analytics continues to grow.
Delivering Business Intelligence in Real-Time
Business processes must be efficient and responsive. Managers need real-time business intelligence and predictive analytics to make the right decisions quickly and confidently. This is a big change from the traditional business model, where decisions were made at the top and only after a laborious process involving numerous meetings, formal presentations, and pie charts over lunch.
Today, managers interact regularly with co-workers and partners located in cities and countries around the world. Technology-enabled mobility has made us increasingly agile in responding to customers, challenges, and crises no matter where they occur. Business teams have the capacity to connect wirelessly across multiple devices, access data stored in the cloud, and share that data via web meetings and live video feeds.
The growing importance of business analytics is evident in the most recent development in business intelligence: prescriptive analytics, which not only predicts future business trends but suggests the actions managers should take to capitalize on them. Forbes explains that prescriptive analytics removes much of the uncertainty managers encounter when planning marketing strategies, for example, by leveraging artificial intelligence and machine learning to identify which specific groups to target and the most effective media to use to have the greatest impact.
Why Analytics is Important for Your Business
The challenge business managers face is to apply the optimal analytics approach that supports decision-making in real-time while accommodating the ever-increasing amount and complexity of the data being analyzed. Business intelligence vendor MicroStrategy describes the four types of data analytics now used by companies to improve their business decision-making processes:
- Descriptive analytics presents a complete snapshot of business conditions as they were and as they are via data aggregation and data mining. The goal is to make existing data easily accessible to decision-makers throughout the organization, as well as to shareholders and investors.
- Diagnostic analytics digs deeper into the data to determine why current conditions exist and how future trends will influence those conditions. Probabilities, likelihoods, and the distribution of outcomes are applied based on attribute importance, sensitivity analysis, and classification and regression via training algorithms.
- Predictive analytics uses statistical models and machine learning to forecast future events based on models created from data generated through descriptive analytics. One use of predictive analytics is sentiment analysis, which projects how people will respond to new products and services based on opinions gleaned from social media.
- Prescriptive analytics builds on predictive analytics by recommending specific courses of action that are most likely to achieve future desired results. The forecasts depend on a strong feedback mechanism and continual iterative analyses to model various relationships between actions and outcomes.
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How Managers Meet the Challenges of Business at Light Speed
Often the greatest obstacle to accurate business decision-making is the inherent biases and assumptions of the managers making the decisions. Chartered Global Management Accountant defines cognitive bias as “a pattern of deviation in judgment that occurs in particular situations, leading to results including perceptual distortion, inaccurate judgment, and illogical interpretation.” The organization identifies common cognitive biases in data analysis:
- Framing occurs when managers view a matter too narrowly and miss potential causes and consequences that require a big-picture perspective.
- Hindsight bias causes managers to believe past occurrences were predictable.
- Fundamental attribution error happens when managers place too much emphasis on people’s personalities to explain their behavior rather than on the situation’s influence on their behavior.
- Confirmatory bias is managers’ tendency to seek out only information that confirms their suppositions about a situation, causing them to pursue their preferred course of action rather than a plan based on accurate data analysis.
- Self-serving bias occurs when managers claim more responsibility for successes than for failures and interpret ambiguous data in whichever way benefits them.
- Belief bias affects data analysis when managers base their decisions on their belief in information’s accuracy or inaccuracy.
As an MBA graduate, you may be responsible for the innovative and effective use of information technology in your department or division. The best online degree programs will prepare you for this, helping you gain knowledge of the fundamentals of adopting, investing in, deploying, and leveraging technology to its full capacity.
Mobile devices and wearable computers such as the smartwatch will continue to accelerate the pace of business. Additional petabytes of information will enter the cloud, making big data even bigger. With these trends, of course, comes the increased danger of intentional—and unintentional—security breaches from more people in more places. Being aware of the challenges and opportunities that technology presents can be your greatest asset in the years ahead.
Ohio University’s Master of Business Administration Degree
Ohio University’s online Master of Business Administration emphasizes the importance of business analytics to organizations’ success. The program includes a concentration in business analytics, with courses focused on data mining, database management prescriptive and predictive analytics, and business intelligence.
Students can also choose to concentrate in accounting, strategic sales and selling leadership, executive management, finance, health care, operations and supply chain management, or business venturing and entrepreneurship.
Learn more about the online MBA concentrations offered by Ohio University and how they prepare graduates to apply the latest data analytics technologies to solve real-world business problems.
Ohio University Blog, “MSM vs. MBA: Which Degree Is Right for You?”
Ohio University Blog, “5 Essentials for Implementing Data-Driven Decision-Making”
Ohio University Blog, “Career Comparison: Chief Accounting vs. Controller”
Chartered Global Management Accountant, “Business Analytics and Decision Making: The Human Dimension” (PDF)
Forbes, “Why the Future of Data Analytics Is Prescriptive Analytics”
IDC, “IDC Forecasts Revenues for Big Data and Business Analytics Solutions Will Reach $189.1 Billion This Year with Double-Digit Annual Growth Through 2022”
MarketWatch, “Business Analytics Market Movements by Trend Analysis, Growth Status and Revenue Expectation Forecast to 2026”
MicroStrategy, “Business Analytics: Everything You Need to Know”
Orbis Research, “Business Analytics Market-Growth, Trends and Forecasts (2019-2024)”