What is Business Analytics and What is it All About?

What is Business Analytics?

Most restaurants know the power of big data analytics. They may purchase information systems and gather as much raw data as possible. The competition is doing the same thing, so why shouldn't they?

While it's great to prioritize data management and data mining, it only helps if the owner knows what to do with it. Only 12% of restaurants and small companies know how to leverage their business data. Furthermore, 95% of organizations struggle to manage unstructured data. Restaurants are missing many opportunities because they aren't equipped to know the analytics process.

So, how can restaurants capitalize on their analysis data to answer questions and streamline the supply chain? First, owners need to understand what business analytics is and how it works. This will help them make informed business decisions that result in higher profits and more customers.

Business analytics is how companies transform business data into actionable insights. It requires expertise in the form of a data analyst or a specialist with a background in computer science. A data scientist uses machine learning, statistical analysis, and neural networks to generate models. These models enable analysts to predict future outcomes, so owners can optimize current decision-making. Read ahead to learn how business analytics works, the various types, and why it provides a competitive edge.

What to Know About Big Data:

• The big data analytics market is expected to reach $103 billion by 2023
  
• In 2020, the big data market grew by 20%
  
• Automated analytics is increasingly vital to big data
  
• Less than 10% of data has been completely analyzed

Types of Business Analytics

Business analysts use analytics data for different purposes. It depends on the needs of the restaurant, along with the questions the owner wants to be answered. Most companies seek predictive modeling, which uses historical data and real-time data to forecast future events. Other companies need to streamline internal operations and require a full-scope business analysis to pinpoint inefficiencies. Each type of business analytics serves a particular purpose and set of data. All types are connected and come in various stages. Read ahead to understand the 4 categories.

What to Know About Big Data:

• The big data analytics market is expected to reach $103 billion by 2023
  
• In 2020, the big data market grew by 20%
  
• Automated analytics are increasingly vital to big data
  
• Less than 10% of data has been completely analyzed
  

1. Business Analytics Type Descriptive Analysis

Descriptive analytics is the first stage of the analytics program. Descriptive is exactly what it sounds like; it describes what occurred in the past and what is occurring now. This enables owners to take a thorough look at the restaurant's performance across the supply chain. For example, a business analyst may use analytics tools to see how much inventory costs were for the past 3 months. The analyst will use a combination of data aggregation and data mining to carry out this process.

This stage enables restaurants to pinpoint their strong points and weak areas. The owner who looked up inventory costs may note there is also a lot of food waste, which is hurting costs. They can then identify this as a weak area, and allocate resources more efficiently in the future. While this stage facilitates owners to enact new strategies, it does not facilitate extravagant changes. Data analysts need to move towards the next categories of BA to do so.

2. Business Analytics Type Diagnostic Analysis

Now that the owner recognizes which inefficiencies are hurting the restaurant, they need to figure out why. This requires data scientists to move to the next type of BA, diagnostic analysis. Diagnostic analysis pinpoints the root causes of problems and why those issues occurred in the manner that they did.

A research analyst uses models to show the likelihoods and probabilities of specific issues. They will also employ data mining techniques, data discovery, and review correlations between variables. This provides the why, so owners can enact strategies that optimize project management and fix problems.

7 Reasons Restaurants Needs Predictive Analytics:

• Secure a competitive stronghold
  
• Increase sales and grow the customer base
  
• Mitigate fraud and eliminate employee theft
  
• Advance core business capacity competitively
  
• Meet evolving customer expectations
  
• Learn more about internal operations and gain further control over the supply chain
  
• Act on insights to innovate, grow, and evolve
  

3. Business Analytics Type Predictive Analysis

Now that all historical issues are clarified, owners can use predictive analytics to forecast future events. This stage requires data analysts and experts in machine learning to oversee the analysis process. To carry out predictive analysis, analysts use models based on Stage 1 and Stage 2 of BA.

Restaurants primarily use PA to forecast customer preferences and purchasing patterns. This helps to improve marketing campaigns, increase sales, and reach new target audiences. For these reasons, PA is the most sought out form of analysis by executives.

4. Business Analytics Type Prescriptive Analysis

The final stage of data analysis is prescriptive analysis, which is centered on making recommendations. Analysts create models that facilitate reliable forecasts so owners can make changes that result in a better outcome. Analysts also use data models to generate recommendations and specific actions owners should take. As long as the data is high-quality and sound, the prescriptive analysis will be the key that drives business success. Owners no longer need to use guesswork to make decisions, they can use data-driven evidence in the form of models.

Other Uses of Prescriptive Analytics: Restaurants can use PA to identify and minimize fraud, optimize inventory management, and plan ahead for peak seasons. They can also optimize procurement processes when obtaining food from vendors, and save money. Data scientists can even analyze weather data and customer behavior patterns to predict how many exact items to order prior to a specific day.

Key Takeaways of Business Analytics

In conclusion, here is what to know about business analytics -

• Business analytics is how restaurants use data to generate actionable insights that optimize decision-making.
• There are 4 stages of BA. These include descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics.
• Descriptive analytics describes what is happening in the past and in real-time. Diagnostic analytics pinpoints the root cause of specific business problems. Predictive analytics uses past and real-time information to forecast future events. Prescriptive analytics takes models and generates specific recommendations and actions owners can take.