By Deepak Mittal , Sidharth Mittal

In today’s agile fast-paced world, “Data” is the king. Actionable and insightful reports using unstructured and structured data from multiple sources can drive organizations towards their Key Business Imperatives, Identify New Opportunities, and making Evidence-Backed Decisions. While organizations have invested a lot of resources in analytics projects, the success rate of these projects is low. As per our study, the following are seven main reasons for an analytics project failure. Our analytics solution Best Practices avoid these pitfalls and delivers value.

1. Missing Data and Poor Data Quality (Poor Data Handling)

Poor data handling can lead to incorrect and invalid results that can lead to making sub-optimal business decisions. Here are some of the challenges:

 

2. Unmanaged Analytics Solution

 

3. Poor Visualization Standard

A very big cause of analytics project failure is, when visualization does not highlight actionable insights, and forces executives, managers to spend time in deciding actions to be taken based on their experience rather than data. Here are the some of the challenges:

 

4. Missing Insights

When Insights, KPIs , benchmarks go missing from any analytics solution it cannot be successful. There could be one or many of the causes for missing the insights

 

5. Missing Opportunities and Trust

A timely insight can save time, effort and add to the top line. That opportunity is lost if insight is missing in charts. Executives and managers need to be able to trust the numbers provided to make decision. The following are some of the cases that if not managed can lead to the failure of an analytics solution.

 

6. Missing or Inaccurate Predictive Analytics

One of the biggest reason business initiates and invests in analytics solutions is to be able to predict the outlook of your business with greater certainty and minimize the risk. When Analytics solutions do not support predictive models or models have lack of confidence it loses its ROI.

 

7. Poor Report/Dashboard Performance

High response time to be able to view your analytics can be the cause of any solution to fail. Analytics solution  slow down can be caused by multiple factors such as unsound schema architecture, unhandled null values within data attributes, too many reports or not breaking data into smaller data sets to consume.

For an analytics solution to be successful for any organization, a focus on the above seven key aspects are needed. If any of these key aspects are missing, it can lead to the failure of a business that relies on analytics solutions. Remember, data is the king. For an analytics solution to succeed, it is important that the data is correctly cleaned and structured, delivered in a timely manner, and correctly computed and visualized. All this will drive the business through any market condition.