How prescriptive analytics can positively affect supply chain management

How prescriptive analytics can positively affect supply chain management

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When it comes to Big Data, the possibilities of the past, the present, and the future coming together is a virtual reality. Acontrolled scenario helps make strategic business decisions. It comprises past results, future outcomes, and of course the current setting. This is where prescriptive analytics, an advanced form of data management, comes into the picture. It helps in averting risks while keeping in mind customer experience, extending the profit curve, and creating unique market opportunities. Prescriptive analytics is truly a game changer impacting businesses worldwide in a positive manner.

Understanding prescriptive analytics

How can prescriptive analysis contribute to supply chain management(SCM)? Why is there so much emphasis on big data for smooth SCM operations? Let’s understand how prescriptive analytics works towards shaping smart work flows and deriving best-in-class business outcomes.

So, what exactly is the contribution of prescriptive analysis to SCM? Why is there so much emphasis on big data for smooth SCM operations? Let’s understand how prescriptive analytics works toward shaping smart work flows and deriving best-in-class business outcomes.

This advanced form of analytics is instrumental in creating actions based on desired outcomes, within the framework of past insights and the current picture. It is a three-fold system thatcreates efficiency in organizational decision-making which in turn helps mitigating organizational risks. Prescriptive analytics is geared to play a big role in supply chain management as businesses look for better management systems. Several domains such as healthcare, logistics, sales and services, oil and natural gas, and automobiles has already started benefitting from it largely.

Across the world, many organizations are leveraging Big Data to manage current functioning and have a grip on future occurrences. It is truly amazing that historical data interpretation once mapped out, can help in decision making for future activities. With advanced computing and massive data warehousing, it is much easier to draw insights that helps one overcome the challenges of supply chain management. The extensive foresight helps companies to not only make better informed decisions but also to stay ahead of the competition. This kind of data management helps companies draw great value and help capitalize on multiple fronts.

How SCM is impacted by Prescriptive analytics

There are several segments within supply chain management wherein prescriptive analytics plays a major role. This includes:

  • Enterprise resource planning,
  • Materials requirement planning,
  • Vendor management inventory,
  • Customer relationship management,
  • Transportation management systems,
  • Logistics-based applications,
  • Total quality control,
  • Collaborative planning,
  • Forecasting and replenishment,
  • Other methodologies.

Big Data indirectly plays a bigger role in scheduling inventory even for smaller companies. In fact when the scale of operations is huge, it becomes even more important to optimize and economize with advanced analytics.

While the expectations are high, it is not so easy to adopt and adapt to advanced analytics. While majority of top executives of global companies understand the importance of prescriptive analytics, only a handful are equipped to successfully implement the same. Many companies on the verge of making huge investments automatically revertto matured data analytics systems. Those who have run big data programs in their firms have many commonalities. They generate a high return from their big data investment in SCM that helps in yielding powerful, potent results.

 

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