The Role of Big Data in Supply Chain Management

Data Analysis and Transformation in the Manufacturing and Retail Sector

Data from the manufacturing and retail sector are a potent source of information for monitoring product movement. However, its analysis and transformation is crucial in creating an actionable response. We are living in an era where data is a significant raw material for business prosperity. The amount of data generated keeps on increasing providing an opportunity for industries in the retail and supply chain to benefit. For example, specific data such as inventory levels offer details about consumer purchases (Robert). Adequate data is available, but the problem lies in the lack of structured systems to convert it into meaningful information.

Forecasting Data in the Supply Chain

Forecasting data is at the heart of all business decisions more so in the supply chain. Nonetheless, the errors remain significantly higher for many enterprises. They include over-forecasts that result in excess inventory and under-forecast that alters demand expectations (Robert). The situation results in the inability to predict and meet clients’ needs leaving them frustrated correctly. Maximization of the value of big data requires the integration of data from internal and external sources plus investing in new analysis technologies. Large manufacturers are using intelligent applications to mine the data to improve their supply chain. Structured mathematics is the other way to overcome traditional forecast issues, but the techniques require skilled personnel for manipulation. Justification of the investment in capturing daily demand signals comes from the ability to respond quickly and efficiently to changes in demand.

Benefits of Using Big Data in Forecasting

Concerning using bid data in forecasting, some of the benefits include preparation for uncertainties such as rising interest rates, demand improbability, and fluctuating commodity prices (Robert). Use of the technique enhances inventory control, control demand volatility, and improve service levels. The aftermath is cash flow adjustment resulting in better optimization of resources. In conclusion, the data explosion era has provided firms the ability to control their volatility. Technological advances and investments are in place to assist with accurate predictions for businesses in their operations.

Work Cited

Robert F. Byrne. “Supply Chain Management: New math, big data.” Analytics Magazine, 13 July 2016, analytics-magazine.org/supply-chain-management-new-math-big-data/.