What are the most common organizational pitfalls in machine learning projects?

Predictive analytics projects often fail. Learn more about the top 12 reasons why it happens in a complimentary Gartner research, which offers great insights about how you can plan for successful predictive analytics project. 

Per Gartner¹, organizations cite a shortage of skills (56%) and a lack of understanding of the benefits of AI (42%) as being among the top hurdles to executing data science projects.  

How can Tangent Works and TIM help you to overcome these problems?

Tangent Works delivers an automatic model generation solution for time series data called TIM. It provides an augmented predictive analytics application for forecasting and anomaly detection in various industries. TIM solution is lightning fast, accurate and explainable.

TIM can help you overcome problems mentioned in the Gartner research by providing:

  • Faster time to business value of your all your time series data use cases – dealing with the pitfalls by using augmented, democratized Machine Learning.

  • Use Case Library – Inputs, ideas on potential use case related to your industry and environment. 

  • Seamless integration to platforms  - such as Analytics and BI platforms, Data Integration platforms , Cloud platforms, IoT, Data Science Platforms.

Curious about the rest? Leave us your email address and we will send you a download link to the research.




¹Gartner "Top Organizational Pitfalls of Machine Learning Initiatives",

25 November 2019,  Alexander Linden, Farhan Choudhary, Pieter den Hamer


GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Tangent Works.


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