RPA Guide:
How to Prepare Data to Avoid Pitfalls

An estimate says that 30-50% of all first-time RPA initiatives don’t succeed.

Why such a high failure rate? For starters, data. Data is messy, sensitive, and scattered.  

Forrester reports that 60% of decision-makers at organizations adopting automation technologies like RPA cite, “data quality as either challenging or very challenging — it’s their top challenge when trying to deliver AI capabilities.” 

Thanks to this guide, you'll discover: 

• how to set up data for RPA success, 
• what story does your data tell, 
• primary ways data impacts RPA deployments, 
• the road to RPA success with Process Mining. 

Get the guide