Supply chain data analytics solution provider FusionOps recently added additional “prescriptive” data analytics capabilities to its cloud platform that can help companies improve specific supply chain challenges such as inventory management.
The prescriptive capability can be added onto FusionOps’ data analysis tools in its Supply Chain Intelligence Cloud solution. FusionOps previously offered what CEO Gary Meyers described as three levels of data analysis: descriptive, diagnostic and predictive.
Descriptive analytics can provide answers for supply chain managers to basic questions like “What products do I have on hand?” or “What customers are we delivering to on time?,” Meyers said. The second level, diagnostic analytics, provides insight into why a problem occurred — for instance, why the company didn’t have the right amount of inventory at a specific time. The third layer, predictive analytics, uses historical data to predict what may happen in the future.
For a while, this is where FusionOps has thrived, especially with descriptive analytics and providing insight into the “why” a supply chain was experiencing a certain problem. However, with the newly released prescriptive analytical capabilities, FusionOps can now dive deeper into a company’s supply chain data. The prescription analytics gathers data from the various levels of analytics and provides a possible solution to solve a supply chain problem, Meyers said.
Data Analytics for Inventory Management Challenges
The FusionOps supply chain intelligence solution taps into a company’s existing ERP software platforms, such as SAP and Oracle. Many FusionOps customers are using the data analytics tools to tackle inventory issues, Meyers said, and the new prescriptive analytics provides additional insight to optimize a company’s inventory. For example, the data analytics help determine how a company can reduce inventories to a level that will cut carrying costs without negatively impacting customers.
Making Data Analytics Accessible to Everyone
Another goal of FusionOps is to present data analysis to customers in an easily digestible way so organizations can actually use it to improve supply chains. Meyers said the FusionOps solution was “very” business-user friendly.
“You don’t need to be a data scientist to use it,” he said.
It’s an important factor for data analytics companies to consider, especially for those working in supply chain analysis. While Meyers said we are still in the early adoption stages of supply chain analytics solutions, companies are increasingly realizing the significant impact their supply chains have on the business. When organizations are able to understand what is happening in the supply chain, they can gain competitive advantage. FusionOps “takes the blinders off,” Meyers said, allowing organizations access to real-time supply chain information and identifying areas of possible improvement. But presentation of the data is key — the front-end of a data analytics solution needs to be intuitive and easy to understand so users can actually access the data and gain insights from it, he said.