Data is the backbone for the growth of businesses in this age of digital transformations. Companies are relying on data analytics to gain insights into their business processes and applications. These tools can aptly support in cost cutting while enhancing efficiency at the same time. Data analytics can help in reducing expenses:
Fleet management expenses: Supply chain companies have started using Internet of Things (IoT) sensors in the company vehicles and other transport arrangements to increase transparency in the entire supply chain processes ranging from truck routes to driver fatigue. Data analytics tools can leverage the IoT data to predict any maintenance needs and assess any discrepancy in fleet management. A study on the effects of big data analytics also reveals that data analytics can help in reducing fuel consumption and CO2 emission.
Indirect costs are associated with the operations, but not with the products sold. Although the categories of these expenses can vary according to a company’s requirement, a few common expenses include rent, utilities, and other office expenses. Big data analytics can provide information about the most substantial indirect costs, helping companies to acknowledge the areas for improvement.
Employee turnover: Employee onboarding is an expensive process for organizations. However, an inefficient employee can incur more significant costs for companies. Enterprises can use data analytics, which will allow them to analyze the likelihood of an employee’s aligning with the company’s culture.
Cyber attacks: Cyber attacks can damage a company’s brand value and reputation to a great extent. These attacks can result in substantial financial losses also. According to a report by Radware, the average cost of a cyber attack was estimated to be $ 1.1 million. Data analytics platforms can monitor network traffic continually and raise alerts if it finds any suspicious activities that could breach a company’s network.