Analytics and the Universal Pursuit of Insight

What makes space so amazing? Every time human kind takes a deeper look, we find something that we didn’t know was there before. The same concept applies to analytics. Gathering deeper insight into any data set through automation allows you to make better and quicker decisions, expose gaps, and identify areas for cost reduction or investment.

However, before you buy the next seat on Virgin Galactic, let’s explore how you can maximize and quantify value from your investments in analytics. The first step is a detailed understanding of your organization’s business plan. For example, if your analytics strategy is focused on your infrastructure, you should ask: “How does my infrastructure provide value to the top priorities in my organization’s business plan?”

Based on these insights, the next step is to identify and establish key performance indicators (KPIs) to measure results and action items for continuous improvement. Your results will depend on the ability to track KPIs, determine the amount of data available, and identify and/or correlate trends across multiple data sources.

On this journey to the outer space of analytics, Cisco Advanced Services has built the experience and framework to help enterprises and services providers navigate and maximize the value from their data.

The value of analytics comes in multiple shapes. In addition to using an analytics approach to drive insights, another meaningful and often unrecognized side effect is internal efficiency. Tasks that used to be done manually in days can now be automated with information instantly available. This benefit reinforces fishing for value in a digital world across the entire lifecycle of IT services.

Many organizations see the analytics engine as the biggest hurdle of implementing the analytics strategy. And, initially, it will be. However, once selected, there are multiple components that require unique skills and efforts beyond simply coding the use case. To gain a better understanding and the ability to identify and engage the right types of resources, Cisco Advanced Services created an analytics reference model.

During the implementation of our analytics model, we looked at many different alternatives. We picked a solution where the learning curve to code the use cases into the analytics engine was the shortest.

What happened? We were presented with a pleasant surprise! Our consultants embraced the opportunity to get trained on analytics. They started to use the platform and explored new use cases based on their interactions with customers. Typically, we would have had a team of 10 developers. Now, we have over 1,000 consultants who are all enabled to build and contribute in a true crowdsourcing model.

Data acquisition is the most important area to have a dedicated team. Data availability through easy-to-consume APIs is the key for a model like this to work—effectively and efficiently.

With six months invested in the program, we have data from 2.7 million infrastructure devices (routers and switches) in customer networks around the world. These are correlated with a number of our internal data sources, like reactive cases, ‘Mean Time Between Failure’ calculations, and our software defects tracker.

Key takeaways for you to consider:

Build value from analytics (number of sources, ability to correlate, number of use cases, etc)

Drive external insights AND internal efficiency

Establish an analytics reference model to determine the analytics engine

Create an engine that addresses your organization’s objectives and needs—today and future

Shoot for the moon

Want to hear more? Join us at Cisco Live in Las Vegas from June 25th to 29th and attend my Critical Insights: Industry-leading Analytics Platform session to learn more about Cisco Advanced Services’ latest analytics platform. Don’t forget to check out Matt Lewis and Joel Prothro explain how to prepare network operations for the digital future. See you there!