The need to be more agile comes up a lot in customer conversations, especially from frustrated executives who want to be more sure-footed and flexible in moving their businesses forward. Too often, they feel stymied by a lack of useful insight, which hampers their ability to respond quickly and effectively to changing customer, market and business demands.
Luckily, this gives me an opportunity to bring up one of my favorite topics: analytics agility. With the right mindset, tools and technologies, organizations can become much more adroit about how they use the power of analytics to improve decision making. As with most things, the toughest part is getting started.
According to Dell’s 2014 Global Technology Adoption Index, 61 percent of companies worldwide have big data waiting to be analyzed—and yet only 39 percent of those polled felt they had a firm grasp of how to go about extracting value from that data. What it takes is a mix of intellectual curiosity and intestinal fortitude to develop an understanding of how your business works from a data perspective.
In my experience, there’s usually a group of naturally curious intellectuals in every company that are eager to drill down into business facts and figures to discover trends, triggers and roadblocks impacting business success. Thanks to our increasingly connected world, these data miners have more tools and techniques at their disposal than ever before to look at data from all angles.
Also critical is having a supportive, equally curious leadership team that encourages the use of data to figure out the business. I met recently with a large sportswear manufacturer that invests heavily in analytics to support a variety of marketing initiatives. The challenge for the analytics team is that when the data supports what the marketers want to hear, it’s all good. When the analytics reveal a different outcome, the marketers claim that the data is bad and do what they want anyway.
Unfortunately, having the right analytics tools and smart people driving the process won’t make much difference if company leaders aren’t open to learning and following what the data reveals. After all, the point of analytics agility is the opportunity to quickly and nimbly change direction completely or make a minor course direction before it’s too late. As we all know, however, sometimes it takes a few lessons learned the hard way to realize the data was good to begin with but the business decision was flawed from the start.
Another critical success factor to increasing analytics agility is having the support of an IT team that continually and consistently collects, manages and exposes data for a variety of analytics efforts. Historically, this has been one of the biggest stumbling blocks as traditional, centralized IT teams often were too overwhelmed with “break-fix” tasks to respond quickly and efficiently to analytics requests. In the past, many early analytics efforts died as soon as the financial, sales and marketing people generated data from separate silos of information and nothing matched up.
Thanks to continued IT decentralization and increased data sharing, it’s much easier now for IT to build an infrastructure that brings different types of data together and delivers a single version of the truth that everyone can get behind. When that occurs, the journey to analytics agility becomes a shared experience that produces tremendous insights and business breakthroughs.
And in some cases, even medical miracles. I’m still sharing the story about Dr. John Cromwell at the University of Iowa Hospitals and Clinics. As reported in the Wall Street Journal’s CIO Journal, Dr. Cromwell is using Dell Statistica to better predict which patients face surgery risks and then expedite surgery room decisions on which medications or wound treatments will be most effective. Now, that’s a prime example of the power of analytics agility.
I also recently spoke with Danske Bank, the largest bank in Denmark and one of the leading financial institutions in northern Europe. This Dell customer is doing some amazing things with Statistica and various credit scoring tools to produce real-time insight that enables cutting their credit risk exposure nearly in half. By taking advantage of analytics agility, the bank can make up-to-the-minute decisions about which markets to serve to gain a competitive edge while mitigating risk.
Today, we have the analytics tools to drive fast, flexible business decisions. And, each day, I hear about another customer with a strong IT and leadership team backing efforts to push the analytics envelope. I’m encouraged to see more companies getting a firmer grasp on what they can do with greater analytics drive and dexterity.
I’m looking for more examples of how companies are flexing their data muscle with analytics agility. Drop me a line at [email protected] to share what you’re seeing.