Do Business Analytics And Automation Go Hand In Hand?

Introduction 

Will AI and Machine Learning replace the human brain shortly? It’s more likely going to be a collaborative job. Big data and analytics are bringing many challenges to the world. Thus, Business Analysts are using advanced technologies with their business knowledge to resolve business problems. 

Automation in Business Analytics may benefit the workforce rather than replace it. Since Business Analytics requires human oversight, one must ask: Will Business Analytics be automated? If so, how does automation impact business analytics in the future? 

Globally, every industry has seen a rise in business process automation. Nearly 51% of businesses have increased their use of automation as of now. By using automated business analytics, Domino’s Pizzas’ share price has increased from $3 per share in 2008 to $550 per share in late 2021, currently at $397.  

The benefits of automation are numerous, especially in the competitive world of business analytics. This article outlines the true potential of automated Business Analytics and Data Analytics. 

Will Business Analytics Be Automated? 

Analyzing business data for actionable insights is the objective of business analytics. The process involves taking raw data and transforming it into something that can improve decision-making analytics. The importance of business analytics lies in the following aspects: 

1. Developing cost-saving strategies 
2. Maximizing revenue potential 
3. Enhancing adaptability 

Business Analytics aims to formulate compelling insights based on data. However, a clear understanding of the differences between different analytics terminology is also important. For example, a business intelligence analyst is different from a business data analyst. The focus of business intelligence is more on descriptive than prescriptive analytics. Technology can help you streamline your processes regardless of what data you’re analyzing. 

There are several ways in which businesses can apply automation to valuable insights across the data pipeline. And one of these powerful technologies is changing the landscape of Business Analytics. The steps are as follows: 

1. It is possible to automate the data collection and update it across all your data channels. 
2. A data dashboard with integrated analytics algorithms automates data visualization and interpretation. 
3. With the availability of many business intelligence tools, this can be automated. 

Data analytics companies will undergo big changes in the future as a result of this automation. Businesses will be able to derive more effective competitive strategies with the improvement of business analytics tools and practices. As with any change, these tools come with pros and cons for businesses and analysts. 

Pros and Cons of Automated Analytics 

You can increase productivity, reduce errors, and save money by automating analytics as part of your overall business process automation strategy. Automated analytics, however, does not always produce positive results. 

You won’t be able to connect with your target audiences effectively if your strategy isn’t optimized. That means the money you spend on improving your data processing will go to waste without generating leads and conversions. It is possible to go beyond this with advanced Business Analytics. 

The future of business analytics and business process automation can able to provide data-driven insights automatically. The following are the pros and cons of business analytics and business process automation: 

Pros 

Businesses can expect greater levels of efficiency thanks to automation in the future of Business Analytics. The definition of data is information. Automated insights can result in the following changes: 

1. An increase in productivity across all business practices 
2. Improved analysis quality through machine precision 
3. Reduction of repetitive and tedious work leads to greater employee satisfaction. 

These benefits already make analytics more efficient. Artificial intelligence, however, is not perfect either. As automation in analytics becomes more prevalent, there are still drawbacks to consider. 

Cons 

Compared with a manual alternative, automated data analysis fails in various ways. We might overlook opportunities when focusing on automation instead of data because data isn’t as comprehensive as we might like. If you are considering a future of commonplace data automation, keep these cons in mind: 

1. Business analysts risk job displacement. 
2. Overhead investment costs are high. 
3. Work that is difficult during a transition. 
4. Some analysts could lose their jobs if analytics departments become highly automated. It all depends on the amount of oversight these software tools require. A company may be hesitant to implement new automated procedures because of overhead costs and transition concerns. 

These pros and cons will determine which businesses succeed and which fail in the future. It will result in a new normal in business analytics, defined by the successful use of automated algorithms and the calibration of software by thoughtful overseers. Those automated practices are essential to Business Analytics in the future. 

Future of Business Analytics and Its Trends 

Technology is constantly evolving. To leverage raw data to reach company goals, professionals must be aware of business analytics trends. These professionals must understand these data and business intelligence trends for their companies to succeed. 

1. Search-Based Discovery Tools 

Raw data can be used to answer specific questions or track trends. People do it routinely when they use search engines like Google to find something. Individuals are accustomed to searching for information, but not every company has user-friendly data discovery technology. 

Data from disparate sources can be sifted through and found more efficiently with these tools. By doing this, key insights into effective business strategies can be found. It becomes increasingly important to cut through superfluous information as the number of potential sources grows. Using search-based discovery tools to enhance analytics operations isn’t the only area where Business Analytics trends shine. 

2. AI and Machine Learning 

ML and Artificial Intelligence (AI) enable high efficiency at a reduced cost. Experts predict that Machine Learning will become increasingly important for customer service in the future. Often, Business Analysts are the ones who keep track of the right information to feed machines. 

Businesses can benefit from AI and Machine Learning. The concepts cited by Business 2 Community as crucial for business effectiveness and efficiency are as follows: 

• Personalized marketing 
• Cybersecurity 

• Talent recruitment, and  
• Customer relationship management. 

For these technology-driven elements to succeed, they still require the human touch of business analytics professionals. 

3. Cloud Computing 

Businesses benefit from Cloud Computing by storing and managing data on remote servers. Among these benefits are  

• Reduced reliance on outdated physical resources, 
• Increased efficiencies, especially when working with teams in different locations, 
• Plenty of options for redundancy management and disaster planning. 

Using Cloud Computing correctly can reduce costs and increase operational efficiency. However these benefits aren’t always easy to access. To protect consumers, companies need to develop workflows that allow them to pool resources, oversee data access, share information efficiently but securely, and maintain the speed and ease of accessing data. 

4. Predictive Analytics Tools 

The future of Business Analytics will likely revolve around predictive analytics. In business, predictive analytics is often about anticipating the next move of customers or clients. Businesses can increase their confidence by analyzing historical data patterns in consumer behavior and market fluctuations. As a result, they could become industry leaders as well as remain consistently relevant in their industry. 

It is important to interpret the information correctly. If not, negative consequences may result. To maintain the usefulness of predictive analytics, a business analytics professional should inadvertently prevent causing business strategies to fail. 

5. Data Automation 

It is becoming time-consuming to sort, store, and manage the growing amount of data that has reached many zettabytes. This is why data automation is so important for the future of business. In business analytics, automation can automate analytics management, so analysts can focus on analyzing and interpreting findings. Scalability issues can also be overcome with it. 

Business analysts can use their skills to develop strategies that integrate efficient and sensible data automation processes. 

Business Analytics and Automation: The Way Ahead 

Here are some of the future expectations of automated business analytics. 

1. A Greater Reliance on Large Data Networks

Companies will increasingly value access to vast data stores, sometimes called advanced data networks. Using consumer data, a company can fill in any gaps in their customer understanding and provide more personalized services to them. 

2. Accelerate Machine Learning Growth

It will be a race for companies to harness Machine Learning and Artificial Intelligence (AI) to create new services. Machine learning is predicted to take over the majority of customer service roles in the near future. 

3. Business Users’ Wider Adoption

As BI and analytics tools focus on usability and natural language, business users will be able to extract data without knowing the algorithms. As a result, companies will be able to increase efficiency and adoption, and the shortage of Data Scientists will be alleviated. 

4. To Optimize Customer Service

Regardless of your business goals, you can collect data from a variety of sources, including social media. Social media platforms offer a wealth of consumer data that can be used to enhance revenue and streamline business processes. A company’s reputation (and revenue) can hinge on the customer experience, for better or for worse, because consumers use social media platforms to share their experiences. If a brand’s customer service is poor, many consumers will abandon it, potentially inspiring others to do the same. 

It may be impossible for your business to recover from a negative social media customer support experience. However, before you reach that point, you can use social data to optimize your customer service experience and build your reputation.  

Conclusion 

If data remains stagnant, it has no real value for long-term business success. As the pandemic continues, businesses are finally utilizing intelligent automation and consumer data to harness an uncertain future. Automated business and data analytics will be key to the future of business, improving efficiency and improving the customer experience, one data set at a time.  

Consider doing a business or data analytics course with UNext Jigsaw if you are planning to shape your career as a successful business analyst. UNext Jigsaw offers the most industry-relevant interactive learning programs across emerging technologies. Expert faculty deliver these SME-designed programs along with living sessions by industry experts. Using these programs, learners will become competent professionals with the necessary skill sets to succeed! 

UNext Jigsaw’s Integrated Program in Business Analytics, in collaboration with IIM Indore. The program offers a perfect blend of management skills and data science. This program helps you to accelerate your career in business analytics.