What Is Business Science?

What is business science? That’s a curious question casually popping up here and there these days.

Let’s get to grips with the terminology first. What does the word ‘business’ mean?  According to Investopedia, a business is coined as ‘an organization or enterprising entity engaged in commercial, industrial, or professional activities’. At the same time, science is defined as ‘the study of the nature and behaviour of natural things and the knowledge that we obtain about them’. If we merge these two definitions, we’ll get the ‘study of the nature and behaviour applicable to an organization or enterprising entity engaged in commercial, industrial, or professional activities.’ Not getting any more clear? Hold on.

Leading a business we must always put ourselves in lab shoes and observe, reflect, think, and try things out. This is the only way to foresee outcomes. To ease the burden, businesses need a scientific method and a framework designed and refined to wipe out partiality as best as we can. Here’s when business science comes in the spotlight.

What Is All Hoopla About?

Whether you are in charge of a small, mid-sized or enterprise-grade business, your responsibility is to ensure that you are relying on science and numbers to make the best decisions. Therefore, business science applies the scientific method to obtain and make sense of data relevant to your industry in order to transform it into business intelligence. Scientific methods and empirical evidence that underpin this methodology allow companies to foretell what ideas will deliver optimum results.

Business Science VS. Data Science

Data Science is a discipline that generally studies the analysis and processing of digital data. It involves developing methods of recording, storing and analyzing data to efficiently fetch valuable information in order to make informed decisions. 

Also, data science is a field that encompasses everything that has to deal with data cleansing, preparation, and analysis. This academic subject includes many modern sciences related to statistics, artificial intelligence, and database design. The field primarily uses both structured and unstructured data. Despite its multidimensional nature, many areas of data science are related to pure science and serve as the basis for practical tools needed by business.

Speaking of practical tools. Business science, on the contrary, is an analytical toolkit based on innovations in data science. Unlike the latter, business science handles exclusively structured data and explores trends and patterns from a business standpoint. 

This discipline is fit for solving specific business problems in different areas of activity and optimizing ways to achieve them. As a result, this approach allows for increased profits for companies. 

Real life applications of business science include a gamut of industries such as finance, medicine, marketing, retail, supply chain management, telecommunications, and many others. All those fields have already embraced a wealth of opportunities this disciple brings by analyzing and identifying trends and boosting business operational efficiency. We’ll dwell on the use cases further in the article.

What Is The Difference Between Business Scientist And Data Scientist?

For the uninitiated, those two jobs may seem like the same position. However, business scientist and data scientist cannot be used interchangeably, although they share some overlapping knowledge fields. 

Essentially, the job of data scientist has evolved into a business scientist role. Throughout the years it has taken the best from the positions of a business analyst and a data scientist.

Historically, an analyst used to lack the knowledge and a profound understanding of data science tools also known as predictive analytics. On the other hand, a data scientist is immersed in mathematical research and in-depth knowledge of the subject area, thus overlooking business needs. Without realizing business pains, it is hard to make a choice – whether you should solve this problem within the framework of predictive analytics or you are better off with basic mathematics or statistics.

Therefore, the difference lies in the responsibilities as well. The business analyst’s tasks include:

  • an in-depth understanding of the business, its objectives, needs, and weak points
  • identifying business requirements
  • formulating a solution concept, either independently or in a team
  • formalizing the concept into terms of reference, with specific requirements for the future product
  • breaking down each requirement into specifications
  • consulting programmers and testers during the product development

On the contrary, data scientists are accountable for:

  • studying data from different perspectives, identifying hidden deficiencies, trends and/or application opportunities
  • using various machine learning tools to predict and classify patterns in the data
  • improving the performance and accuracy of machine learning algorithms by fine-tuning and optimizing algorithms
  • coming up with new algorithms to solve problems and creating new tools to automate the work.

Who Is A Business Scientist?

If we sum up the facts mentioned above, we’ll come to the conclusion that a business scientist is a specialist who translates a business problem into a mathematical problem. Apart from that, these professionals are also good at evaluating the necessary tools and solutions and also estimating the financial justification.

The efforts of business scientists are aimed solely at generating profits through mathematical dependencies that should lead to:

  • increase in sales
  • higher customer satisfaction 
  • reduced costs and potential losses

To handle massive amounts of data, a business scientist worth his salt should be on familiar terms with:

  • Data interpretation and analysis – that is, business scientists distill valuable data bits from the huge volume of figures and indicators that modern companies have. Based on the logic and analysis of available data, they build forecasts and recommendations and deal with statistics and mathematical algorithms, since business analysis is based on statistical concepts;
  • Data visualization – conclusions about trends and patterns are then transformed into a visually digestible format, i.e. charts or  graphs;
  • Effective communication – business scientists should demonstrate persuasion and influencing skills, since they have to pinch proposals for business improvement to management and investors.

Real life applications of business science

Today, business science has found wide application in a whole host of industries. From a business standpoint, its contribution is invaluable for everyday business operations. The range of applications is very wide – from attracting new audiences to developing customer loyalty programs and effective marketing campaigns. Business science also allows companies to perform supply chain management and identify risks such as forecasting and preventing equipment breakdowns, or detecting fraudsters and malafide partners.

The Bottom Line

For better or for worse, the modern business marketplace is a data-centered environment. Therefore, companies worldwide have integrated data as a crucial element of their business operations. More than ever, quality data can help business owners to fetch the most valuable insights of the company itself, its rivals, and customers. Business science is what helps companies use an unbeatable combo of scientific methods and hands-on business experience to open up sources of revenues unheard of before.

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