Survey Finds Business Insights in Operational Data

Operational intelligence derived from automated data collection and traditionally used to manage IT infrastructure could also be leveraged to gauge how transaction-based businesses are performing.

Furthermore, machine-generated data could even be exploited to adjust business systems and processes in real-time to account for customer preferences, concludes a recent study that looked at ways of gleaning business insights from seemingly mundane operational intelligence.

The study, “Masters of Machines: Business insight from IT operational intelligence,” argues that turning operational intelligence into business insights will require new tools capable of collecting machine data from a variety of sources while providing analytics to leverage raw intelligence for decision making.

The research behind the study was conducted by Quocirca Ltd., a UK-based research and analysis company that focuses on IT and telecommunications technologies.

Bob Tarzey, Quocirca’s service director, noted in a blog post that daily commercial transaction volume driven by enterprise IT systems in Europe average about 40,000. For telecommunications companies, that total nearly triples to 110,000 transactions a day.

The more transactions a business processes, “the more likely it is to have changed the way that infrastructure is provisioned to serve the requirement,” Tarzey said. “The bottom line is that more transactive organizations recognize the need more than their less transactive counterparts.”

According to the study, 90 percent of telecom firms surveyed said access to machine data was essential to obtain the operational intelligence needed for higher-level business insights. For telecommunications, transactions can be automated or initiated by customers in the form of account creation, device activation or call routing.

Hence, “most organizations are likely to become more reliant on IT to drive more transactions over time and they need to be prepared for that and realize the long term benefits to be gained,” Tarzey argued.

The business insight study concluded that failing to make use of machine data generated in huge volumes on a daily basis represents a lost opportunity. Leveraging the data means companies could adjust business processes in real time to better reflect customer preferences.

For example, in demonstrating its predictive analytics tool at a conference this week, Microsoft demonstrated a big data dashboard that tracked usage of elevators installed across the United States by German manufacturer ThyssenKrupp. The tool tracked operational details like which elevators in individual buildings were called most often and the time it took for doors to close.

Microsoft said the manufacturer and building owners used the operational data to determine how often elevators should be maintained. The machine data also provided insights into how building managers could plan “proactive maintenance” to avoid outages, Microsoft claimed.

Such use cases underscore the growing role of operational intelligence in improving business practices. Hence, the study concluded that “many areas of management and, in some cases, partners, need access to IT operational intelligence. This needs to be in a context relevant to their role and the challenges they face.”

Moreover, these new users “need to be able to manipulate the machine data that this intelligence relies upon to gain new insights that would not otherwise have been possible,” the study found.

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