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.