In today’s business world, making good, fast decisions based on strong data is essential to sustaining a competitive edge, and the combination of multiple technology trends is quickening the advancement of real-time data analytics.
The amount of useful data is doubling every three years as it flows from smartphones, wearables, wireless sensors and other sources. The capacity to store all of this data has increased, while the cost to do so has dropped significantly. Data professionals now have remarkable computing power available, and they are building algorithms that are more and more intricate.
Industry-leading businesses are using their abilities not just to enhance their core business functions, but also to launch completely new revenue models. The result is typically a winner-take-most scenario, driven by these companies’ deep wells of analytical talent. These companies are addressing big, complex problems and actively trying to find ways to get into adjacent industries. These businesses can leverage their scale and analytics insights to expand and broaden, increasingly blurring long-standing boundaries between sectors.
Legacy businesses must do the difficult work of revamping or modifying existing systems. Adjusting to an era of data-driven decisions made in real-time is not always a straightforward proposition. Some businesses have invested greatly in their legacy systems but have not yet altered their companies so they can maximize these investments. Many are finding it difficult to develop the talent, operations, and organizational strength to capture significant value from analytics.
The first step is integrating analytics into a tactical vision. The next step is creating the proper business functions and capabilities, including both information infrastructure and talent. It is not sufficient to just stack a technology system on top of existing operations. All these facets of transformation have to combine to realize the total potential of data and analytics.
New analytical means can fuel discovery and innovation. Most importantly, company decision-makers no longer have to rely so much on instinct: They can use information and analytics to make smart, choices faster and back those decisions on gigabytes of evidence.
Real-Time Analytics in the Supply Chain
The supply chain is one major area where data-driven decisions are particularly critical, as decisions have to be regarding procurement, manufacturing, quality and delivery. Real-time analytics is transforming the supply chain into a “glass tunnel” that enhances decision-making abilities and overall agility.
Supply chain reports that had taken hours to produce can now be produced in real-time thanks to faster access to information. This makes supply chain planners more efficient at optimizing company operations, driving a high level of quality and supplying greater degrees of customer satisfaction. The analytics-driven transformation of the supply chain includes refined data pipelines; self-service evaluation; higher information quality by eliminating the reconciliation of information across systems; and real-time analytics that recognize, analyze and even react to problems.
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