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Why A Modern IT Infrastructure Is The Cornerstone Of Data-Driven Enterprises

Cisco's Connected Futures

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Even the most sophisticated analytics technologies, like artificial intelligence and machine learning, can’t deliver results by themselves. To make the most of these technologies, enterprises must have a solid IT foundation to ensure underlying data sets are complete, timely and accurate.

Effective analytics capabilities ultimately depend on an IT infrastructure that has these core elements:

  • The ability to collect data in real-time from a wide range of sources
  • Tools to process, store and manage data
  • Appropriate means for sharing data and insights within the enterprise

While it appears some companies understand this need for solid IT infrastructures, many are still learning the lesson. In fact, in a recent Forbes Insights/Cisco survey, when executives were asked how they’ll be furthering analytics initiatives in 2018, the top response among the most successful analytics users was IT infrastructure modernization. However, not even a third of less advanced companies are prioritizing upgrades to their IT foundation.

This may haunt followers as they try to improve their analytics maturity. Inaccurate or incomplete underlying data are just two potential consequences. Just as troubling is the risk that business professionals will avoid using analytics for important projects because they don’t trust the results.

Take a page from the playbook of the savviest analytics users and focus on these three key areas when updating your infrastructure.

  1. Networks. Modern networks are the lifeblood of advanced analytics. Analytics leaders pay particular attention to upgrading their networks to improve capabilities for collecting and aggregating vital information from various internal and external sources. A key investment in this area includes spending for intelligent networks, which use sensors for collecting real-time data about customers, production facilities, supply chains and other core operations. Eighty-eight percent of leaders will earmark new spending for these next-gen communications pipelines in the next 12 months, with many citing a desire to improve their organization’s ability to collect and aggregate important data and give them greater access to more accurate and timely data. Also, nearly half will invest in software-defined networking to complement their spending for intelligent networks.
  2. Data Management Resources. Closely managed data is trusted data. Once data is collected, it must be managed effectively to remain secure and reliable. That’s why other top investment targets for analytics leaders include spending for cloud and server technologies. The latest technologies reduce the risk of data fragmentation and inconsistent results that can lead to a lack of trust in the accuracy and timeliness of the information.
  3. Analytics Tools. Analytics leaders draw on a wide variety of tools to provide senior management and decision makers with the information they need, when they need it. For example, large manufacturing companies use machine learning to identify problematic parts, suppliers or buyers within their organizations. Algorithms can identify buyers who regularly overstock supplies or who routinely file late purchase orders leading to expensive expedited deliveries. These analyses also look out about 24 weeks to see which part suppliers are likely to be short of, and then send alerts to the appropriate buyer. Help like this puts companies in a better position to balance prevailing customer demand with the delivery capabilities of suppliers.

There’s also an important role for more conventional data visualization tools that present quick summaries of important statistics. One global hotel chain delivers data via electronic dashboards that show executives the latest sales figures plus near-term projections for hotels, restaurants and other revenue streams. Having ready access to these insights gives organizations time to pivot and improve performance with special promotions or a revision to their sales strategy for an upcoming season.

With a solid IT foundation in place, enterprises can forge ahead with new investments in next-generation resources like AI and machine learning.

To learn more, read, “Advanced Analytics: The Key to Becoming a Data-Driven Enterprise.”