Robotic process automation (RPA) software is the fastest-growing segment of the global enterprise software market. It’s easy to see why.
Intelligent Automation (IA) and RPA tools automate repetitive and mundane tasks, freeing up employees to do more high value work. In turn, this helps organisations deliver better customer experiences, increase business agility and improve productivity. Yet, many companies are struggling to realise these benefits, or are not exploring them at all, due to the real and perceived challenges associated with the technology.
As an analytics and data processing firm, Data Reply has helped many businesses implement IA and RPA solutions.
Although IA and RPA have applications in almost every industry, many of the logistical and technological challenges that businesses face – from making the business case to automate to implementing and embedding the technology, are the same.
Data Reply supports companies in solving these common issues, which include achieving scale with automation, embedding security into systems and overcoming roadblocks in artificial intelligence (AI) projects.
IA has many individual
sensory capabilities; from using image recognition to scan photographs, to converting the spoken word to text, to predicting the future based on past actions. However, scaling this technology is essential to achieve true business transformation. Getting it right means marrying vision and strategy. This follows three stages:
IA at scale can have many applications, for example the technology can be used to automate ID card processing for global money transfers. By automating this process, valuable man hours were freed up as the technology could automatically locate and extract 4 fields of data from each ID card: Name, DOB, Address and Expiry Date,
thereby ensuring its validity. The process was complicated in that the original system was unable to read non-Roman script being presented on certain ID cards. Automation however meant that the data then passed to a RPA solution for external translation services, which translated the text to the Latin alphabet which could then be read and automatically processed.
With any technology, security absolutely needs to be a main priority. For IA the biggest security issue often arises at the point where human and machine interact. For example, human error during an automated financial reporting process can result in one company losing-man weeks and a delay on the reporting of the group’s finances.
Other security issues that need to be considered include rogue access; data loss; hacking; privilege abuse; vulnerabilities and malware, which all show the centrality of security to IA implementations.
But like well backed up data – all is not lost! Those looking to implement IA should heed security protocols like encrypting data and multiple layers of authentication, along with reducing access rights and requiring human validation on certain processes.
No discussion of IA would be complete without an examination of the
organisational changes that are taking place. New technologies will create a number of different roles in the future, with a rise in titles like: ‘human thinking coach’; ‘cloud cleaner’; ‘chief productivity officer’; and ‘data detective’.
When we think of the benefits of automation, we typically consider things such as time saving, headcount reduction and reducing processing times. But there are other significant benefits which Data Reply have delivered for their customers, which don’t typically appear in business cases:
IA impacts also AI. Faulty data or human error could affect AI and its smooth running. IA can overcome the roadblocks in AI implementation. It explores how faulty data or human error could affect AI and its smooth running and how too often highly qualified data scientists were not conceiving new ways of utilising data but cleaning and correcting faulty data.
AI “eats data”. It needs a lot of correct data to be able to function. There are practical considerations – things like enforcing two factor authentication – but
human considerations as well. Indeed, successfully implementing AI also meant incorporating fairness; reliability & safety; privacy and security; transparency and accountability.
IA has already been shown to have profound and far-reaching benefits and, while it is difficult if not impossible to predict with complete certainty where the technology will go next, what is more certain is that its use will only proliferate.