It is 2021, the world is talking about the importance and unlimited power accessed by tapping into the right data and data modelling methods. Any data driven decision making fuels revenues and provides a competitive edge to businesses. There has probably not been a single day in the current decade when an individual can not share any kind of personal data information anymore. Even B2B businesses thrive on data analytics.

So, what is business data analytics?  

Essentially, data analytics involves the process of collecting data and comprehending various insights and inferences it may provide. Business data often involves client data and past performance data, employee data and other key datasets companies get hold of. The purpose of collecting such data is to get useful insights and information that will positively affect a business. The success of a majority of startups and other businesses in today's world is determined by how well they tap into data analytics that suit their respective businesses. The process is not easy and companies often hire a lot of data scientists, analysts and data engineers to help them with the same. Data analytics is actively used in all fields from sales & marketing to operations, supply chain logistics, human resources and finance & accounting.

According to reports, India’s logistics business is worth over 200 billion US dollars and the number is expected to grow at the rate of 10% annually. Any individual working in the logistics sector or department knows the hefty amount of challenges that they have to deal with. The logistics industry is however revolutionizing with the role of data analytics and AI taking over the field providing effective solutions for most problems. 

With the help of the right data, the right statistical methods and techniques; any business can flourish in such difficult and unpredictable business weather.

Take the case of 2020, when the COVID-19 pandemic disrupted supply chains, how were some companies able to pivot so fast and quickly get back on track while others didn't? The purchasing power was one factor, however, the biggest reason was decision making. The untold secret of such businesses is the data-driven factor which has helped with the early stage predictions and reduced supply chain risks. Data analytics brings with it, enhanced supply chain visibility and helps measure supply chain vulnerabilities. Wonder how that is possible? With the help of algorithms, the supply chain drivers can be analysed at multiple dimensions, including the supply side, demand side and the supply chain infrastructure for possible disruptions. Businesses that have taken note of such issues have streamlined their supply chains to reduce risks of disruptions due to man-made and natural disasters. By far, the automotive sector has the most complicated and disruptive supply chain and employing data analytics in their logistics has been their biggest boon. 

That was one case of how data analytics had made supply chain and logistics more resilient. There are so many different ways an organization can improve the logistics business based on business analytics, all it requires is asking the right questions. As data analytics is frequently used from manufacturing to warehousing, to transportation and end-mile deliveries, asking what can be improved, where to cut costs without affecting the supply chain and what models to employ to come to a conclusion are a few questions asked.

Nowadays, many businesses have smart warehouses which collect data for analysis by using the right methods (Internet of Things (IoT) and Warehouse Management Systems (WMS)) that take into account both, present and historical data and provide businesses with warehousing efficiency, increased speed, minimum risks, competitive advantage, and a long term revenue boost. This is how and why data analytics is changing the logistics business. A great example of how data analytics is Hitachi. When they implemented a data analytic approach that uses past work performance information to understand worksite improvements, environmental changes, and issue appropriate work instructions and then conducted a demo test which delivered an 8% work reduction without any additional costs.

In the future, it is predicted that more powerful technological methods will replace current methods and not adapting to the changing environments can negatively affect businesses. Hence, it is highly recommended to tap into the full potential of data analytics after proper and thorough research on what best suits your business and needs.