You have investigated and done some Google research. RPA sounds good, it seems like it could be used in your business but you have questions, such as:

• How long to implement RPA?
• How long does it take to automate a process?

Of course it depends on the process being automated is the generic answer, but that does not help when you are first starting to consider RPA.

RPA, or Robotic Process Automation to use the full term, is about using software robots to simulate human activity on computer systems and hence free staff time from repetitive routine activity so that their skills can be more effectively deployed on other tasks.

Lets consider the effort required and the approach for the implementation.

As an IT Director, CIO, IT Manager, you are likely to be considering “Automation” to improve the business. The questions are how to achieve the automation and what is involved?

It seems like with so many articles in the media referencing Artificial Intelligence (AI), to the extent that every Board director is at least aware of the term, taking on AI must be easy. That is a myth, using AI is not easy if it is “Real” AI and not something exploiting the AI hype which might be easy.

As organisations are already operating business processes, automation is about delivering improvements as it is a core assumption that the business processes are required and integral to the business.

The activities will be generating quantities of data that is passed through the computer systems. With this data as an asset, it is possible to deploy AI to analyse the data and potentially discover something useful.

Gartner the leading independent computer industry analysts have place “Hyperautomation” as the number one trend for 2020 in their report “Top 10 strategic technology trends for 2020”.

What is Hyperautomation?

Hyperautomation brings together several components of process automation, integrating tools and technologies that amplify the ability to automate work. 

It starts with robotic process automation (RPA) at its core, and expands automation capability with artificial intelligence (AI), process mining, analytics, and other advanced tools. 

The idea is to automate more and more knowledge work, and engage everyone in an organization to be part of the transformation. This achieves depth and breath of the automation activity across an organisation. It is more than the term "Intelligent Automation" as that can be applied to a single instance, Hyperautomation is for the collective implementation of many instances of automation.

There are many businesses that engage third party providers to deliver part of an overall service to customers. Acting as a reseller can deliver significant benefit to customers but it does give some challenges when it comes to cost allocation processes. Some examples of this type of activity are:

• Telecoms service resellers receive invoices from telecoms companies that need to allocate costs to their customers
• Digital Agencies receive invoices from hosting companies for web traffic that need to be charged onto their customers
• Fulfilment Service providers receive invoices from courier delivery organisations that need to be divided across their customers

There is so much hype about AI at present. The terms AI for Artificial Intelligence and ML for Machine Learning are getting used in many conversations to add market currency but the reality is often very different.

For many business implementations AI with or without ML is only going to be effective if combined with RPA.

In general terms AI is about applying some “Fuzzy Logic” as mathematicians call it to large quantities of data in order to develop a level of confidence about “Pattern matching”. This is sometimes  termed “ANI” – Artificial Narrow Intelligence. The logic only works on the problem defined using the data set provided for the “Training” / “Base line set”. The hype often portrays AI as being “AGI” – Artificial General Intelligence, that is intelligence which can be applied to anything. The technology is just not there ….Yet!