Integrated visual analytics raise the bar for Business Intelligence (BI).
The question of how Big Data helps solve supply chain challenges is on the minds of executives and managers across all segments of industry. But how is Big Data different from the ERP and Supply Chain Management (SCM) technology already employed by enterprise-level supply chains? The answer lies in the scope, complexity and velocity of the data, and the promise that Big Data holds. Enterprises that adopt analytical visualization and discovery tools will capture a clear competitive advantage in an industry that already prizes BI.
Having the right BI architecture gives decision-makers the power to control costs more securely and respond to events in near real-time. That means that supply chains can operate more efficiently and be more responsive to changing business conditions. Compared to competitors that lag behind in applying the latest tools, the application of data science and integrated analytics has a measurable advantage if leaders have the foresight to make the investment and reap the rewards.
The Dynamics Of Big Data
Big Data is such a nebulous phrase that it is easy to dismiss it as a buzzword, a term that only reframes the information management techniques that enterprises have been practicing for years. The most useful aspects of Big Data are the tools for discovery that it gives to decision-makers. In companies that have extensive supply chains, raw data floods in from databases, onsite ERP instances and documents dispersed across the world. Big Data BI analytics integrate all of this data with the potential to capture valuable hidden insights in real-time.
According to Forbes.com, 89% of enterprises across all industry segments expect that the rollout of Big Data tools for BI will be a critical factor in keeping up with their competitors. Big Data is a fact of life, as disparate organizations become ever more interconnected, and it is the source of many solutions to keep supply chains competitive and able to handle rapidly expanding data sets.
What Will Supply Chains Gain From Big Data?
While it is still a developing technology, Big Data already goes beyond ERP and SCM software to connect disparate sources such as onsite ERP instances, databases, and geospatial information. This ability to unify all data into one set empowers users to collect the useful business intelligence and to find the hidden connections and patterns. The solutions available today give supply chain managers control over logistics, order management, and inventory, and accelerate forecasting and planning cycles to near real-time.
Transforming your supply chain with Big Data analytics will make it more agile. It will give you the capacity to track all information and materials and every point in the value chain, from raw materials through to customer delivery. The ability to achieve this depends on the leadership and management implementing the right solution and ensuring that the organization follows through with policies and procedures to make the best use of the potential in the tools.
Investment In Supply Chain Software Architecture
Research by IDC indicates that the changes are happening now and at a rapid pace. To make the trend even more challenging, here are likely to be shortages of knowledge workers who have the right skill sets to get the most from the new technologies in the near-term. However, it will be mandatory to have Big Data initiatives in place by 2018. 70% of enterprises already purchase data from external sources; this trend will grow as a tool to use to be competitive and as an opportunity to monetize data.
Having an integrated Big Data analytics solution is going to be ever more critical as the technology evolves. Supply chain management will continue to be challenging and competitive with vanishing profit margins and near-zero response times. However, supply chain based enterprises that invest and upgrade to exploit the potentials of Big Data architecture will be placed to massively out-compete those that fall behind.
Do you agree with the latter?