Top 5 Things to Consider When Getting Started with Predictive Analytics

By BDO Digital| May 05, 2016

We are in the middle of a tremendous period of change in how we conduct business. This change is driven, in part, by the massive explosion of data and advanced analytics at our fingertips. With the latest business intelligence software such as Power BI or Tableau, and the upcoming release of SQL Server 2016 on June 1, the ability to predict future success through analytics is now within reach of organizations of all sizes.

While most business leaders recognize the incredible value of predictive analytics, many still feel overwhelmed by the prospect of transforming data into actionable insights. As a result, they are putting off getting their predictive analytics projects off the ground despite how accessible these insights have become. When done correctly, developing predictive analytics insights can be a high-value, high-return initiative that can help organizations drive real value to the bottom line quickly.

Companies that are using predictive analytics effectively in 2016 will increase their profitability by 20% by 2017

- Gartner

Organizations that aren’t taking advantage of the latest innovations in analytics are at risk of falling behind the competition. If you are excited about the prospect of predicting your future success, the time is now to get started. Here are some things you should already be considering in order to start building a predictive analytics solution for your organization.

Define Your Business Goals

Begin with the end in mind. Define what business issue you are hoping the predictive analytics solutions will solve. The most common adoptions happen in the marketing, sales, and customer retention use cases. Whether entering new markets is essential for your revenue growth, or you struggle with retaining long-term customers and need to develop new marketing strategies to reduce churn, predictive analytics can be applied to any number of situations. It’s important to select one area you want to focus on and then build from there.

Prepare for Change in the Way You Analyze Data

Predictive analytics will enable your business to do much more in the future, but it will also require some changes in how you analyze data now. Define what actions you want your organization to take and change once the predictive analytics solution is in place. Make sure you understand 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

Data.  More is More.

It’s all about the data. If you’re like most organizations, your data is not all neatly stacked and organized in one place – it’s scattered across a large number of systems and hidden in places that you may not even know exist. The more data you put into your model, the better insights you will get out. Chances are, you already have enough data in your organization to draw real value through predictive analytics, but you need to know where and how to retrieve it before getting started on building your model.

Identify and Realize ROI

Always look for the ROI.  Most organizations fail to capture the results and share ROI with key business stakeholders and then integrate this into their process.  Do this and do it often.  It will provide tremendous value to you and your organization.  If you were to reduce your customer churn and attrition by 5%, what would the value to your organization be?  It’s usually a large amount of dollars to the bottom line.

Believe in Yourself

Be confident! Most organization I talk to get overwhelmed at getting started and feel they need a huge army of data scientists and support staff to get going.  This is not the case.  Predictive Analytics is not new. It has been used by larger enterprises for years. What’s new is the technology that has made it accessible to the masses and now allows organizations with limited staff and resources to get started and taking advantage of predictive analytics. Once your predictive analytics model is started and up and running, it’s easy to pull actionable insights based on highly accurate predictions – even for those without a technical background. The hardest part is being confident and getting started in the first place.  Trust me, you will be happy you did.

The essential guide to data-driven