Big Data

Every 10 to 15 years, a tectonic shift comes along in our industry disturbing the status quo, fundamentally changing how technologically is consumed, purchased, and delivered.

Distribution or dissemination of information is probably one of the most critical aspects of supply chain business intelligence and information management.

Collaboration of information and timing and are two extremely critical aspects of supply chain business intelligence and information management.

New Survey from GE and Accenture finds less than one-third of companies have predictive analytics capabilities although big data analytics is a top priority for 88 percent of executives.

Analytics are now an integral part of any supply chain information management system. Modern computing power and advances in analytical software have made powerful analytics not only possible, but practical for most businesses sitting on top of a cornucopia of supply chain data. Analytics run the gambit from historical data dumps to models that suggest the best course of action based on a set of probable outcomes.

The reason why there has been so little progress on the visibility front is that today’s supply chains are too sprawling, too outsourced, and too complex for traditionally architected systems to handle.

You don’t get anywhere near the depth and breadth of visibility with 3PL tools as you would if you engaged a standalone TMS solution from any of the leading providers especially with respect to rate data, carrier acceptance data and overall visibility.

You can’t predict anything with 100% certainty, and your predictive power wanes the farther out you gaze. The study of KPIs over time is all about finding patterns and signals, then applying human intelligence in order to make better decisions and gain wisdom.

With organizations that rely heavily on their supply chain, designing actionable performance level metrics, those that actually matter is even more important than the top level financial drivers.

Evaluating BI vendors can be a confusing and complex process. However, knowing the right questions to ask can greatly reduce the risk of selecting the wrong solution provider. The right BI solution must provide business decision makers with the information needed to obtain operational and strategic business objectives.

Why risk building you own business analytics solution from scratch? How long will it take you, how much will it cost to support and how confident will you be in the data?

Okay, so you’re committed to rolling out Business Intelligence across your supply chain, you have tons of data, so how do you turn that data in to actionable information?