You have most likely heard the term “predictive analytics” used in Business Intelligence conversations and, chances are, you recognize the incredible value this data can unlock. You may even be considering how to factor it into your IT spending.
Despite the obvious advantages, many organizations struggle to get their predictive analytics projects off the ground. As business intelligence consultants, we recognize a few common questions asked by organizations who are excited about the prospect of predictive analytics, but aren't sure where to begin.
Here are some of the most frequently asked questions regarding predictive analytics:
How do I prove the value of a Predictive Analytics project?
Recent studies have shown that companies that are using predictive analytics effectively in 2016 will increase their profitability by 20% by 2017. The most common adoptions happen in the marketing, sales, and customer retention, where it can aid in developing strategies for growth and attrition. The KPIs of each predictive analytics model may be different, but the basic principles remain the same. For example, if your goal is to reduce customer churn, and you have tracked a 5% decrease since using your predictive analytics model, what value would that bring to your organization? The cumulative sum is typically substantial.
What makes a Predictive Analytics project successful?
Predictive projects can be challenging to get across the finish line, and Gartner studies have shown that up to 60% fail to move past the initial launch phase. To be successful, a sound process is the key component to making your Predictive Analytics project a success. Define what actions you want your organization to take and understand what responsibilities need to change once the solution is in place. Have an understanding how the new solution will be utilized, who in the organization is affected by it, and what you need to adjust in your current business processes in order to utilize Predictive Analytics to its full potential. BDO Digital has a proven predictive methodology and step-by-step process to help organizations realize results, and can help guide your Predictive Analytics endeavors.
How do I know which data is important to include in my model?
There is no all-encompassing rule, but in most instances - more is better. If you’re like most organizations, your data is not all organized in one location – it is dispersed across many systems and hidden in places that you may not even know exist. The more data you feed into your model, the better insights you will get in return. Chances are, you already have the data you need to draw real value through Business Intelligence, but you need to know what to do with the data before building your model.