• This field is for validation purposes and should be left unchanged.
Guidance and results for the data-rich, yet information-poor.

How To Lower The Risk Of Analytics Failure

Introducing advanced analytics can be a complicated undertaking for any enterprise. Adding to the confusion is a wealth of buzz words that can be difficult to explain to most employees, such as business intelligence, big data, the internet of things, and predictive analytics.

The relentless pace of new and emerging tech also adds to the challenge and many businesses find it difficult to figure out how all of this relates to their operations. When enterprises analyze the resources needed — time, skills, hardware, software, and more — any attempt at analytics can be daunting.

Here are a few steps you can take to help lower the risk of failure and significantly raise the chances of succeeding with analytics:

1.) Forget About Choosing A New Tool

More tools and software will just add to your expenses even before you’ve achieved anything. As your analytics program expands, that’s when you should outgrow your present toolset. Take note that many analytics efforts fail not because of a lack of technology, but they fail because of a lack of clear plans, execution, and skill. A new tool won’t help you with inaccurate or unavailable data, so don’t think that it will solve your problems in that area.

2.) Think Small — Find An Easy Win

The problem with beginning with big projects is that they tend to lack a unified vision and direction. Start with a project that’s easy to focus on and solve, and has low costs. Choose an area in your enterprise that you feel suffers from a lack of insight. An ideal situation is when you have a problem that already has complete and accurate data available. Once you solve the issue and are able to present a positive return on investment (ROI), it’s time to present to leadership.

3.) Shift Your Organization’s Thought Process

When you present your successful analytics project, include an ROI calculation as a reporting metric. This helps your group to change how leadership views analytics: from being an added expense, to a source of revenue.

The ideal outcome is that leadership will trust you again and allow you to reinvest into another project. There may be dozens of available tools at the moment — with more and more popping up regularly — but it’s best to stick to the basics. While tools are helpful in discovering and analyzing data, they won’t be able to solve your business’ challenges by itself.

Data Mining Webinar

Learn How to Get Predictive Modeling
Off the Ground and Into Orbit
1 Hour Live Interactive Event

Why Train With TMA?

Determine whether TMA training is right for you, and learn why TMA is truly the best option for live classroom analytics training.