Risk Management

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Lev Lesokhin
Lev Lesokhin
Commentary
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Is Analytics a Must Have? Wall Street IT Executives Donít Seem to Think So

Operations spearheaded analytics in IT because the need for it was evident on the surface. But on the software development side, the software risk is behind the scenes until a glitch brings it to the CIO's attention.

Over the last decade, analytics has become a requirement for running any modern business. Some of us might recall that, in the late 1990s or even the early part of the last decade, data warehousing and data mining (and, later, business intelligence) took many years to gain serious adoption. We know we need databases, e-commerce platforms, and enterprise apps, but analytics was an overlay that took a while to make the broader leap to a must have.

Financial services institutions and marketing organizations were among the first to deploy analytics at scale. Certainly, algorithmic and high-frequency trading are advanced examples of real-time analytics-driven business -- sifting through mountains of data looking for indicators of how a stock might move. And the amount of social, local, and mobile data to which marketers have gained access in recent years has driven the application of analytics to predict customer behavior, price patterns, and even web traffic.

Today there is no question that analytics has become a critical enabler to management and many business processes. Executives in any technology-driven business know that, if they're not already working on big data and real-time analytics, they're falling behind -- except the executives in the technology organization itself.

Unfortunately, many IT leaders are like the shoemaker's children when it comes to analytics. To be more precise, the IT operations part of the organization has become adept at using analytics to improve their resilience and monitor software risk. But on the software development side, IT has no analytics on the myriad projects and enhancements being pushed through their software assets on an ongoing basis.

This separation of concerns is one of the root causes of the many glitches and crashes we've seen in the news the past few years. Developers build their modules to spec, assemble the whole system, and test it before sending it to operations, but ops has no idea what could be lurking inside.

And it's not for lack of trying. Datacenters -- mission control for operations -- are sophisticated analytics practitioners. With so much important data coming in and out of one central location, they almost compensate for the paucity of analytics on the development side. Real-time monitoring has been commonplace for years. Some of the more advanced have become adept at analyzing past incidents or slowdowns as a prevention measure -- rewinding the tape, looking for patterns of activity preceding the crash, and then feeding the data into a predictive model to head off future incidents.

The reason operations spearheaded analytics in IT was because the need for it was evident on the surface. But on the software development side, the software risk is behind the scenes until a glitch brings it to the CIO's attention. It's organizationally and sometimes technically difficult to connect the dots from code to glitch. Some IT shops on the street have figured out how to use analytics to make these connections. For IT managers to be smarter about how they run their business, they need to empower their organization with analytics at every step of the software development lifecycle.

It's no secret that technology is becoming more complex. As a result, the regulatory framework for keeping tabs on IT is becoming more sophisticated. With glitch after glitch spelling an early retirement for IT executives, the need is higher than ever for more advanced analytics to manage the technology controlling more and more of our daily lives.

It's not that all IT is analytics-poor, but the most complex and variable part of the organization -- the development side -- needs to invest in more structural quality and productivity analytics. This will enable IT to address the complex software risk that plagues businesses. Armed with holistic software analytics, CIOs can determine just how their cost is funneling into IT, how they can manage it better, and exactly what their output is to each line of business.

Lev Lesokhin is an executive vice president at CAST, a software risk management and analysis company with headquarters in New York City, that aims to capture and quantify the reliability, security, complexity and size of business applications. Lesokhin has over 20 years of ... View Full Bio
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