The Future of Business Analytics
The world of business analytics is evolving at an incredible pace as organizations around the world collect and process more information than ever before. In fact, Forbes.com recently reported, “90% of the data in the world was generated in the past two years alone”. With this growth in data collection, it is not surprising that Forbes also estimates that the global market demand for data and business intelligence will top $200 billion in 2020. With this rapid increase comes the need for trained professionals to transform this raw information into actionable insights that drive results.
The rapid expansion of business analytics means that interpreting data is no longer reserved for a small team of computer programmers sitting in an underground office. Modern analytics is ubiquitous across all industries and job functions as global competition increases and customer expectations of the companies they do business with rise exponentially.
The Demand for Business Analysts
This advancement of business analytics needs has created an explosive job market with IBM confirming that the annual demand for data scientists, data developers and data engineers is expected to lead to 700,000 new recruitments by the year 2020. According to McKinsey.com, Anil Chakravathy, CEO of Informatica, states that as the business analytics landscape evolves, “the hunt for such talent is taking place in what has become the world’s hottest market for advanced skills.” The way data is collected, stored, and analyzed needs to be redesigned to meet this incredible and growing need. Properly trained business analysts and analytics professionals across all industries will be key to this reinvention.
Where is Business Analytics Needed?
Within the field of business analytics, there are numerous career possibilities. In addition to the expected career opportunities of business analyst, data analyst, or analytics manager, where there are more than 100,000 jobs currently posted on indeed.com for just the United States, there are countless positions in every industry that are using or planning to use business analytics to help their organizations become more effective.
“Companies are using big data to perform predictive analysis that enables them to understand and interact with their customers and reducing churn rate,” states Quertime.com. Call centers utilize analytics to maintain adequate staffing levels, route calls and reduce recurring concerns from customers. Analytics also helps businesses work to understand the root cause of customer issues earlier so they are addressed before they affect a larger population of customers. Modern analytics has also seen the introduction of chat bots and AI tools to leverage technology for the good of the customer.
The healthcare industry uses an enormous amount data to make smarter, patient-driven, cost-effective decisions. Data helps hospitals understand the need for clinical staff so there are no gaps in the workforce. It is also used to predict patient risk and act on preventative care improving patient outcomes and reducing cost. It is vital that analysts use data to help decisions-makers improve this industry. The data collected in the health care industry can also be used to identify emerging trends in health care to prevent large-scale disease outbreaks or develop new approaches to improve outcomes.
Data analytics helps the finance industry align strategic goals through customer insights. Digitalistmag.com recommends that we “automate personal finance management, which gives customers a holistic view of their finances and provides forward-looking advice.” This type of reporting can show financial trends and give advice based on the historical data that is helpful to the customer and gives the industry data that can help create new products to better serve their consumer. Analytics also helps financial institutions detect financial irregularities like fraudulent charges on credit card accounts, evaluate credit risk and predict accounts with a high probability of delinquency.
Data is one tool that teachers can use to help students progress through the curriculum. Student data is collected and analyzed to improve learning outcomes. Through testing, a teacher can learn where a student is deficient and create a plan to help that student reach the desired level. By tracking student progress, intervention can happen earlier and as needed to help a student before they get too far behind.
Marketing and Communications
Competition in most industries is fierce and data analytics can help marketing and communications teams sift through the noise and get to data that is relevant and meaningful so they can develop more effective tactics to reach their customers. Analytics helps teams make sales projections, stay on budget, create brand loyalty, and provide market insights to create an impactful message that resonates with their audience.
These are just a few examples of the diversity of opportunities within the analytics field. In every industry, analytics is currently being used to develop more innovative and successful business practices. This trend will continue well into the foreseeable future creating even more demand for analytics trained professionals.
Primary Types of Data Analytics
Within the field of business analytics, there are a myriad of possible options to review and present data. The ultimate choice of how to build these models will be determined by the use case and future needs of each organization coupled with what they intend to use the data for.
- Descriptive analytics is a preliminary stage of data processing that creates insight into historical data to uncover useful information about activities that have already happened. For example, a health-care provider would use descriptive analytics to determine how many patients were admitted to the hospital in a particular month. A retailer might learn about average weekly sales for each of its stores, or a sales leader could research how many prospects their team generated in a month and where they came from.
- Diagnostic analytics provides in-depth insights into a particular problem where historical data can be used to identify patterns. An example might be for a retailer to analyze their sales and profit data to identify why they missed their net profit target.
- Predictive analytics utilizes techniques like data mining, predictive modeling and machine learning to analyze current data to make predictions about future events. An example of predictive analytics might be a bank using data to identify consumers who are at risk of becoming delinquent on their accounts and taking steps to help them in an effort to minimize any losses to the bank.
- Prescriptive analytics is the use of technology to help businesses make better decisions about how to handle specific situations through the analysis of available resources, past performance and current performance. A university might use prescriptive analytics to evaluate the higher education marketplace and determine which new programs they should offer to raise their overall enrollment and student retention.
These models work together to give companies a better view of the markets they operate in and how they can best compete efficiently within that environment. Modern analytics is constantly evolving and the field will continue to undergo significant change in the coming years.
To be effective, analytics professionals need to develop the base skills required to analyze the data they have, the intrigue to find new and alternative data sources to enhance their analysis, the critical thinking skills to interpret the data and the strength to act upon the findings they develop.
The MS in Business Analytics program at Quinnipiac University can prepare you with all these skills. The program is designed for working professionals building careers in analytics or leaders in any industry seeking to build on their analytics skillset to be more effective in their role and advance their careers. Learn more at Quinnipiac Online Programs.