The estimated market for Robotics Process Automation (RPA) is $ 11 Billion by 2027.
What is possibly the reason this sector is growing at a CAGR of 34% from last 7 years?
The answer is very simple. (No Prize for guessing).
Robotics Process Automation (RPA) is capable of automating repeated mundane task. Earlier these tasks were done by humans.
Intelligent Document Processing is an important part of process automation in any organization. Hence a lot of RPA providers have IDP offerings. When it comes to IDP effectiveness, the only thing that matters is not price, not total cost of ownership, not how fancy your marketing campaigns are, how big funding rounds you have raised, but IDP success ONLY and ONLY hinges on how accurate the data extraction is.
If the data extraction and interpretation accuracy is low, everything else just does not matter.
Since, IDP is a relatively new branch of technology, the market is highly fragmented.
Clearly there is a lot of competition and a clear winner is yet to emerge. However while everyone talks about accuracy percentages, there has been very shallow discussions about how one can achieve high precision.
In fact, this is the precise reason why KlearStack was born.
Let us take a use case to understand this better.
Imagine what would happen if the cameras start reading the fast tags wrongly on national highways?
Even better, what if you never pulled out your car out of the garage in the last 7 days. However, the traffic department sends you a receipt.
This blog discusses 3 reasons why accuracy is the key to success for the right fitment of IDP in complex commercial environments.
Processes within organizations have too many moving parts. In fact, most processes are operated by multiple internal and external teams. This requires direction from the top managements of the organization. In fact, at many times top management of multiple companies/clients/vendors/Partners. The human involvement can be very high, hence even a 1% increase in accuracy can mean huge deal for throughput and turnaround time.
Any IDP uses machine learning/Natural Language understanding/Optical Character Recognition to read the contents of a document. The system then interprets the contents of that document. Based on the artificial intelligence of the IDP system the process moves forward.
2. Information security
What if a business implements an IDP tool and later realizes that 90% of data requires human verification, because the IDP was not able to extract data based on “What You See Is What You Get” principle?
In this case, multiple agencies will have to review the contents of the final version that is processed by the IDP.
Since multiple stakeholders from many companies work together a lot of data security issues come up when manual verification requirement is high.
3. Compliance issues
Businesses have to comply with many laws and regulations. In fact, multinational companies have to follow compliances of more than one country.
In many cases, inaccurate interpretation of data from documents might end up crossing deadlines.
Non submission of tax receipts, consignment documents etc. can have a huge commercial impact.
In fact, the damages aren’t limited to finances. Such, misinterpretations owing to inaccuracy by the IDP might negatively impact the reputation of the company as well.
KlearStack a team of passionate automation engineers led by seasoned industry leaders realized this problem in 2018.
Since then, we are creating systems that integrate people and systems to deliver best in the class accuracy.
KlearStack begins with a high field level accuracy on day one and based on self-learning AI technology, continues to improve the accuracy to > 90% in a few weeks.
To conclude, implementing IDP is successful only if the tool can be trusted for high level of precision. Even if the tool costs slightly higher as compared to other cheaper tools it is wise to look for high precision while choosing your IDP.