Data science applications vary greatly by sector
The applications of data science are useful in many industries. Organizations are setting their priorities for the coming year particularly in the areas of process optimization, inventory management, predicting sentiments in their market, improving control of compliancy and reducing the workload involved. Each sector has its own priorities. This is the outcome of Centric and Markteffect's research into the field of data science and its application.
Transportation and logistics
In the transport and logistics sector, 43% of organizations see a role for the application of data science especially in optimizing inventory management. They see the benefit in minimizing inventory, allowing them to invest more in materials, for example. Furthermore, they see the added value of applications that optimize route and transport planning. Here you can think of algorithms that adjust the route in real time on the basis of expected traffic density on the route. But delivery can also be made more efficient by steering to available parking locations in the vicinity of several addresses in busy places with little parking space. This prevents driving around in circles and therefore delays the delivery.
'In the logistics sector, companies see benefit in minimizing inventory, allowing them to invest more in materials, for example.'"
Finance
For 69% of financial services organizations, the priority of data science is primarily to improve compliance monitoring. For example, 'building in' automatic steps into systems helps to control records. But also when it comes to compliancy of, for example, ISO certification, they see an application for data science in auditing this. Furthermore, 54% of the financial service providers expect that the application of data science will improve risk analyses of business processes. This will be reflected, for example, in a better prediction of the (financial) consequences of projects or a better estimate of the internal capacity and staffing. In addition, 35% of the organizations see that data science can take a lot of the work off their hands when it comes to reporting criminal transactions. This is now a responsibility where permanent alertness is expected from the organization.
'Building automatic steps into systems helps control files.'"
Retail
In the retail sector, 50% of the organizations are setting their sights on predicting market trends in the coming year, when it comes to the application of data science. With analyses based on economic figures, seasonal influences and political events, among other things, they want to provide more insight into the development of trends in the markets in which they are active. In addition, a third of the retailers say they adjust their purchasing to these trends in order to optimize their stock. An equally large group says that application of data science will help them with issues related to the product itself or the type of customer. Then it's about upsell, for example (what items can I sell in addition to the product?) or optimizing the price of a product (can I vary the price for a product depending on the customer?).
'50% of retail organizations are setting their sights on predicting market trends in the coming year.'"
Government
In the coming year, a third of government agencies will give the highest priority to reducing the workload involved in checking audits and work process compliancy. By applying data science they can, for example, monitor compliance with legal deadlines or it can contribute to detecting fraud. They want to make the process more efficient by linking information systems and building automatic controls into the system. For 20% of the governments, the optimization of spatial planning is also a point of attention. They expect to be able to improve the process of spatial planning by, for example, recording and unlocking data about municipal real estate and geo-information.
'The application of data science allows governments to monitor compliance with legal deadlines. It can also help detect fraud.'"
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