The primary goal of Big Data Analytics is to help companies make better business decisions by enabling analysts or other users to analyze huge volumes of transaction data as well as other data sources that may be left untapped by conventional business intelligence programs.
Ask yourself, does your company:
- Use advanced analytical techniques (e.g., simulation, optimization, regression) to improve decision making
- Routinely use data visualization techniques such as dashboards to assist users or decision-makers in understanding complex information?
- Combine and integrate information from many data sources for use in decision-making?
- Use systems that automatically make operational changes, based on performance criteria, business rules in response to signals from sensors?
- Use systems to give you the ability to decompose information to help root cause analysis and continuous improvement?
If your answers are yes then your company is on the road to implementing Big Data Analytics. If your answer is no, then read on to learn more.
We see companies develop and employ enterprise applications that use advanced analytical techniques to explore Big Data and generate optimal supply chain plans to improve decision making. These applications allow management to visualize their supply chain before and after optimization, helping to identify areas of risk and recommending and allowing management changes to these plans in an almost real-time environment.
The most advanced applications use sophisticated mathematical algorithms, typically mixed integer programming optimization models, to analyze their Big Data and generate optimal schedules and supply chain network designs. In addition, these tools allow the user to modify those plans in real time to align with their tactical or strategic goals.
For example, in S&OP optimization some of these advanced technologies implement color-coded information, which allows users to identify shortages or constraints with their production operations by SKU. The user then has the ability to point and click to drill down for further data analysis and quickly make the needed changes to modify the plan. The key to this type of a system is to provide actionable insights into their global supply chain, and allow worldwide operations the ability to make changes or corrections to their production process at any time 24/7. This process of examining Big Data using advanced technologies provides global supply chain plan visibility and an improved decision-making process. Contact us to explore a professional approach to take advantage of Big Data Analytics.