Using Big Data Analytics to Manage Business Risk
It’s been an interesting journey to watch the “Big Data” evolution unfold and, through discussions with EMC customers, gain insight into how and where this will take the IT industry. While in New York recently, I had the opportunity to meet with a representative of a major financial institution to discuss efficient use of technology in the service experience, including Big Data analytics.
The conversation moved in the direction of Key Performance Indicators (KPIs) and differentiated between two main categories – reactive and proactive. The reactive category is an obvious one and covers the somewhat traditional metrics used today in Performance Management: i.e. call statistics, frequency, and product trending. While this is an extremely important practice and should always play a role in successfully running the business, in this instance the really interesting discussion took place around the proactive side of Performance & Infrastructure Management metrics.
Frank Coleman’s recent blog posts have provided great insight into the B.A.D. data discussion – and Frank makes a very valid argument that we all need to start measuring our initiatives and looking for trends, even in early stages. At our customers’ business level, trend-watching becomes an even more critical component for identifying risks to business continuity. Getting real-time trend data is becoming one of the most important facets of being flexible in business. It allows customers to make IT decisions in other areas too, such as storage provisioning or increasing performance availability for business processing – in other words, IT-as-a-service.
This data analysis also allows our customers to identify their real-time business risk. The New York conversation I referred to was centered on being able to see the trend that potentially poses a risk, in order to proactively help our customers save an enormous amount of time and effort – not to mention cost.
In saying all of the above, these conversations should not focus on business risk alone. This type of data analysis can also be a hugely positive business enabler. If we can monitor (and thus predict) workload levels, we can ensure the infrastructure is capable of handling the business peaks. Asking questions around workload demand, workload trending, predictability, and structure of workload allows our customers to proactively service their end-users’ needs.
More and more, the analysis of Big Data, both structured and unstructured, is becoming a mainstream requirement and our customers (and competitors) are seeing the need for expanding their focus in this area. At EMC, we have a growing Data Compute Division including Greenplum and Isilon technologies. Within the larger IT industry, you have to look no further than IBM’s announcement to acquire i2 (a specialist in big data analysis) to see how quickly the focus is narrowing in on this opportunity.
As we all continue to search for new growth opportunities, the ability to see trends faster and thus predict the outcome will be a critical business enabler. Are you seeing this in your own role yet? What plans do you have in place for success?
Note: If you’re interested in learning more about how Big Data is transforming business, I encourage you to attend an upcoming EMC Forum. We have several lined up in Europe and the Americas over the next few months. I will be attending the one in Boston on October 20 and look forward to speaking with customers (and non-customers!) about virtualization and cloud, Big Data, and service and support.