The 3 Sectors Seeing the Most Disruption from Data Science

Data science is expected to disrupt almost every sector. But some sectors are already being impacted by this technology.

Data is a critical corporate asset, and data science and analytics are changing the way businesses compete. The most forward-thinking companies are using data science capabilities to not only improve their operations but also to launch brand new products and business models.

Here are the 3 sectors seeing the most disruption from data science:

1. Logistics Sector

By 2023, the global logistics market is expected to reach US$15.5 trillion. Some innovative companies in the industry have already recognised how the wealth of data from social media, IoT devices, and business systems can transform the way they view logistics, manufacturing, suppliers, customers, and more.

These companies have already started utilising big data and moving into data analytics, but to make sense of this data many of them will need to use data scientists.

By analysing this data, businesses in the supply chain and logistics industry will be able to use predictive analytics. In transportation, many companies have tens of thousands of vehicles, all needing to be regularly checked and maintained. Data analysis will allow these businesses to determine which components of these vehicles are most likely to stop working. This means that they can be preemptively replaced or repaired and are less likely to break down while on the road.

These businesses will also be able to use dynamic pricing. This can be determined by cost data available in real-time, based on components like transport time, fuel costs and weather patterns.

2. Agriculture Sector

Data science is having such a huge impact in the agricultural sector that it can be difficult to predict the numerous changes it will bring.

Today’s farmers are using sophisticated algorithms to analyse decades of crop and weather data. This allows them to predict yields with almost pinpoint accuracy – before they even begin planting.

Last year, the UN said we’re facing the largest humanitarian crisis since 1945. The global population continues to increase, and temperatures continue to rise, leading to a massive famine in Africa where 20 million people are risking starvation.

Humanitarian groups are gearing up, but data science may play a large part in solving this issue and preventing future famines. Agricultural scientists and chemists have long been analysing plant data, hoping to develop crops that could flourish in any type of environment.

The goal is to use big data to chemically engineer seeds which could end world hunger for good.

3. Automotive Sector

By 2020, there will be at least 250 million autonomous cars on the road. For this to happen, manufacturers will be relying on data scientists to help develop the technology needed for mobility, telematics, and automated driving.

In the United States, government research has predicted that these driverless and autonomous vehicles will cause an 80% decrease in the number of car accidents by 2035.

The massive developments in the automotive sector combined with the intelligence of leading data scientists have encouraged tech firms to partner with automotive companies. Toyota and Microsoft have partnered, with data scientists using big data to connect users to roadside assistance, anticipate when vehicles will need servicing and maintenance, and more.

The only way the goal of autonomous cars will be realised is with the utilisation of data science, which will help code and engineer the technology that will make self-driving cars a thing of the past.

What do you think about this disruption? Get in touch today with your thoughts.

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