Predictive analytics has become an increasingly hot topic in analytics circles as analysts discuss how we effectively model and use big data, and more people realize that predictive modeling of customer behavior and business scenarios is “the big way to get big value out of data.”
But we’re not anywhere near broad implementation for understandable reasons: time and money top the list, along with a scarcity of talent to transform and match data with priority decisions. But let’s motor on for a couple of minutes. It will be worth it.
There are much bigger potential business benefits for organizations that have invested in predictive analytics software. If a company’s competitors aren’t doing predictive analytics, it has “a great opportunity to get ahead,” Mike Gualtieri of Forrester Research recently reported in a discussion with an online blog. The benefits of predictive analytics are immense and span across various industries.
Virtually all of us are overwhelmed with data and starving for information, but that doesn’t mean it’s just a matter of rolling out the technology and letting analytics teams play around with data. When predictive analytics is done well, the business benefits can be substantial. However, there are some mainly strategic pitfalls. Many companies perform analytics purely for the sake of “doing” analytics, and they aren’t pursuing analytics that are measurable, purposeful, accountable, and understandable by leadership.
Data scientists don’t know it all!
With that in mind, data scientists end up looking for experienced data analysts who have all the required technical skills and also understand their business practices—a combination that can be nearly impossible to find. Difficult, yes. Impossible, not really. An array of other people, from within the business leadership pool and IT, should also play roles in predictive analytics initiatives. When you have the right balance with your team, you’ll end up with a purposeful and thriving analytics process that will produce results.
Companies looking to take advantage of predictive analytics tools also shouldn’t just jump into projects without a plan. You can’t approach predictive analytics the way you do with many other IT projects, so it’s important to think strategically about an implementation upfront and to plot out a formal process that starts with a comprehensive assessment of analytics needs and internal resources and skills. That’s where and how you will see not only a greater adoption of predictive analytics, but far greater results.
Do your research. Ask a lot of questions. Engage a successful, seasoned team of data integration analysts. We cost less and deliver more. Our Austin, Texas location keeps us at the epicenter of planning analytics and data-driven healthcare innovation and keeps our global capabilities and services at the forefront of our industry.
Email us at kcerny@mia-consulting.com or call us at 512.478.3848 to start a friendly, productive conversation.