Supply chain management, as a practice, is in a continual state of improvement. Since adjustments in time and cost during the production process can often lead to significant increases in profit, managers should always analyze data to make sure that paths are cleared and bottlenecks eliminated. One of the best ways to do so is to use real-time analytics, which can drastically improve the effectiveness of your supply chain production.
New Insight for Business from Real-Time Analytics
Data gathering, analysis, and delivery have grown increasingly more sophisticated over the last decade, and as a result, companies are beginning to split their time between analysis of business activity both after the fact and as it happens. The reason for doing so is simple: real-time data allows managers to head off potential crises and find new solutions, faster.
Real-Time Analytics and the Supply Chain
A large part of the current improvement in supply chain management practices includes the application of real-time analytics. Many emerging software applications are allowing companies to analyze production processes while they’re happening, and then get the pertinent data not only into the hands of traditional decision makers, but also to individuals in direct contact with the process—operators, packers, and so forth.
By getting analysis into the hands of both decision makers and those in direct contact with processes, four common problems in the supply chain can be improved and/or rectified.
Problems Solved In the Supply Chain by Real-Time Data Delivery
- Supply chain improvements are often difficult to make because analysis done after the fact typically passes through multiple hands, with a focus toward corrective action. With real-time data analysis in hand at the point of action, individuals at every level of the process can be empowered to take timely action and effectively solve problems.
- Supply chain coordination is impossible with data delivered after the fact, as decisions and adjustments are made based on metrics and not on diverse sources and systems. On the other hand, real-time analytics allow individuals and different links in the chain to make decisions based on what’s coming next or even what’s happening now. This fact alone is almost certain to save significant costs if a company implements it correctly.
- Often, even the best supply chain partners aren’t in a position to foresee unexpected problems or their potential solutions. For example, if data comes to a decision maker after the fact, how would he/she do something as complex as optimize delivery and pick-up schedules? In keeping with the current example, real-time analytics would allow a company to combine weight, freight, and customer relationship data to make decisions about the most efficient delivery schedule possible.
- One of the most impactful considerations for profitability is whether or not a company’s data allows it to respond effectively to fluctuations in demand. It is impossible to make adjustments in parts, materials, and labor based on historical data. While this data is helpful for planning, managers can’t use it to meet a customer’s need that moves based on particular trends (online or offline). Real-time data can be used by decision makers at any point in the supply chain that requires a response to spiking demand.
Of course, the results will depend on how collaborative an organization can be in real-time problem solving. However, with the aid of real-time analytics, these problems will become clearer, and their solutions much more apparent.
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