Introducing the Automation Capability Model

There is nothing new that will be talked about in this paper. It will be told in another way.

I was having a chat with my friend who is a senior professional in the IT industry a while back. He is quite aware of Robotic Process Automation, Analytics, Artificial Intelligence and other new buzzes around, but was not sure how does it all work together to bring about the desired benefits. I later found that he is not alone. This made me write this paper. To give the readers a view of how several influencing factors and certain technical capabilities put together in a right way can deliver significant benefits of automation.

This paper attempts to define what automation means for us “today”, as we observe certain changes and gives us an overview of one possible approach.

Setting the context - Automation “is not equal to” RPA

Automation has been an integral part of human existence. What has changed with time is the availability of new tools and techniques. One such tool of late has been RPA.

By the standard definition - automation is the use of various control systems for operating equipments and applications to minimize human intervention. Whereas RPA is a form of clerical process automation technology based on the notion of software robots. We all knew they are different. Automation is of a much bigger in scope and in concept.

It would be myopic to assume automation is there to help IT maintenance or Business Process outsourcing engagements only. Automation has been helping humans in all spheres of life including agriculture, manufacturing, transportation, commerce, warfare, healthcare and lifestyle for ages. This just gets an impetus due to the new tools and techniques.

It is essential to have a more holistic approach while addressing automation. A tool implementation approach will limit the benefits considerably.

Every automation business problem has to be looked in a way that best solves that purpose. Some may require analytical intelligence whereas the other will need pervasive instrumentation. There may be certain cases for which orchestrated automata will meet the purpose, and certainly several will need a combination of capabilities.

A few things that are changing today

• It is not to be consumed by humans only – it can be used by other forms of life and machines
• Availability of data – about almost everything, some with a price tag though
• Democratization of Artificial Intelligence
• Machines becoming part of a conversational ecosystem
• Availability of improved infrastructure – with the commoditization of mobile, cloud and internet
• Improved capability and a wide variety of automation tools and techniques

What is also changing in a big way is the aspiration of people – in personal lifestyle as well as in business.

Automation like any other initiative almost always thrives with innovation. Innovation is no more a separate function but is now a part of every function.

A suggested approach with Automation Capability Model

It took 45 years after the Watt steam engine was patented to get the first intercity railway. Which means one technology however powerful will not deliver its optimal value. We also have the story of scythed chariot - attaching swords to the axle of a chariot to have deadly effect. A simple but right combination of capability can provide maximum effect.

It is therefore important to use the proper ingredients with the correct recipe. We have tremendous advantage of technology and information today, which make things more achievable. It is essential to use the right techniques in the right way in the right context.

All we need to do is recall a few basic facts that we already know as we introduce the Automation Capability Model illustrated below

At a very high level Automation Capability model addresses the following:

Automation needs to be for everything and everyone. It has to support people and machines. I leave the other forms of life for another day, but that easy to extrapolate. Although there are a lot of similarities, machine and people behave in a different way when interacting. They converse in a different way. People have emotion but some make mistakes. People with ill intentions are becoming everyday news. People can teach machines to behave badly, which can try to mimic human interactions.

With automation becoming a commoditized polycracy, it has to support different usage types and modality.

Interactions going wrong can have severe impacts. Remember Charlie Chaplin with his eating machine in Modern Times? With the new powerful techniques and innovative usage, the effect might not be hilarious. Mistakes need to be carefully contained.

Automation needs to be intelligent. It is essential to understand what is going on. The quicker the problem, the ask, the intention and the context is correctly understood, the result will be better. The best resolution action should be intelligently derived. It should be analytical, experimental, practical and relational. This understanding should be data driven and always quantized to provide confidence.

The problem statement may not be direct every time, it may need to be inferred. There are scenarios that will need a fact based and verification based approach, while at times emotional understanding will be key to success.

The need is not very different from the brain model of Herrmann.

Automation needs to be instrumented. The benefits of automation will be achieved to the maximum when common man and common machines will be able to use this at ease. It should not need IT projects to enable or orchestrate automation, but be capable of hands free automation. It should be flexible, conversational, pervasive and provide self service capabilities. The instrumentation needs to ensure process of interrelating diverse information and also attempt to minimize dependency of the consumer and the actual execution.

In this ever changing and innovative conditions, flexibility is important – flexible to discover and to be discovered with new end points, flexible to be used by newer decisions and processes ad most importantly flexible for new engagement models.

Conclusion

This paper attempted to definite “todays” automation in the midst of several changes. It also gives a glimpse into Automation Capability Model which will be elaborated in subsequent papers. The next 3 papers will talk about the following with some more detail– intelligent automation, instrumented automation and an overview of the Automation Capability Model.