Top 5 BI and Analytics Worst Practices: What Everyone Is Doing Wrong

Melissa Treier
March 21, 2019

Many business intelligence (BI) and analytics implementations don’t deliver the results business leaders, managers, and analysts anticipate. There are many statistics from an industry analyst perspective to support this, like a Dresner Advisory Services study1 which showed that only 35 percent of organizations polled said they “completely agree” that they’ve had success with BI.

I have personally witnessed this as well as I travel the country working with various prospects and customers. It doesn’t seem to matter what industry or how small or large the organization is – the one thing that organizations have in common is less-than-stellar results when it comes to BI & analytics.

It seems that in spite of the best intentions and plans, organizations suffer from oversights and poor judgment calls during planning, vendor selection and rollout – mistakes that can be detrimental to success.

Has your BI and analytic investment ended up on the shelf? To find out, let’s solve a simple math equation. What you’ll need are the numbers on the left:

 
analytics value formula

So how do you compare the industry average of 20%?

The list below, culled through real-world experiences of many Information Builders’ experts, comprises what we’ve found to be the five worst practices that lead to poor BI and analytics deployments:

  1. Depending on humans to operationalize insights
  2. Expecting self-service BI to address all your needs
  3. Underestimating the importance of data prep
  4. Using tactical BI tools to support broad BI strategies
  5. Ignoring important data sources

Stay tuned as I dig deeper into each one, outlining their negative impacts from both a tech and business perspective and offering some approaches that will help your organization avoid them moving forward. Our goal is to help you learn from the mistakes of others to ensure maximum adoption and success in your next BI and analytics initiative.

Continue on to BI and Analytics Worst Practice #1: Depending on Humans to Operationalize Insights.

 

1 “2015 Wisdom of Crowds® Advanced and Predictive Analytics Market Study,” Dresner Advisory Services, LLC, 2015.

Hoping to steer clear of the top 5 worst practices in data and analytics?