Demystifying automation

Article By
James Cumming
James Cumming
Posted On7th December 2020
Posted On7th December 2020

Our featured blog this week is from Francesca Valli – enterprise transformation delivery expert. She owns and runs a management consultancy called Chrys, helping organisations to change – without all the complexity. She has helped organisations deliver the transformation and secure multi-£m returns on IT investment. In this article we discuss automation change projects and specifically demystifying it.

So, tell us about your expertise in automation?

Recently, I have obtained certification from the London School of Economics and Political Science on ‘automation: implementation in business’. The course of studies explored the strategic deployment of automation technologies in order to secure business value. What I have learnt on the course aligns with my experience and two of the key teachings are – the implementation of automation must be aligned to business strategy and change management is essential for implementation and adoption. Both messages were supported, in the course, by a theoretical framework punctuated by the interventions of business leaders whose automation experience warned of the perils of disregarding both.

What do you mean when you say, ‘demystify automation’?

Automation technology is beneficial and inevitable, as digital increasingly drives economic growth and societal transformation – but in the final analysis, it is just that… technology. I will describe its key features in a simple way. Change is brought about by the collaboration between people, in projects, IT, business operations, with a common objective, supported by shared tools and practices that drive alignment and delivery. I will point, here, to those tools and practices that foster the collaboration making the path to change infinitely smoother. We make change so difficult. It isn’t and it shouldn’t be. Automation does not change this.

The automation technology world

The ‘automation of knowledge work’ is a technological development gathering speed under our eyes. It refers to the use of computers to perform tasks that require expertise previously belonging exclusively to humans.

Whilst we are familiar with the automation of assembly lines, with its futuristic robots populating manufacturing plants, what I describe here is not the automation of production but the automation of services

There are two service automation technologiesavailable to the enterprise:

  1. Robotic Process Automation
  2. Cognitive Automation.

Artificial intelligence, specifically the so-called ‘strong’ AI, a technology aimed at achieving parity with humans, in all its complexity of awareness, understanding, reasoning, decision, action, is not present in the enterprise and we may be decades away from it – if we were ever to get there. This is not just a theoretical debate. Amongst other things, knowing the difference between RPA, CA, AI brings the CXO to a level playing discussion-field with software vendors – and it enables them to support leadership and teams along the automation journey.

Robotic Process Automation (PRA)

RPA is the use of software to automate processes and tasks, in the enterprise, previously performed by employees. It is suited to high volumes of transactions of a low complexity calibre. It is the most appropriate – and fastest – at repetitive tasks.

‘Desktop’, ‘Enterprise’ ‘Cloud’ are the various types of RPA deployed according to enterprise scale and requirements. A ‘desktop’ RPA can be configured by an able user, its technology non-invasive and easily mastered. ‘Enterprise’ RPA needs to be configured and installed by IT professionals, given its likely interfacing within an existing IT infrastructure. ‘Cloud’ RPA is easier to deploy, maintain and scale, in line with cloud technology, plus, it can ‘learn’ from the other robots in the cloud.

From a data perspective, RPA uses, as input, ‘structured’, ‘labelled’, data (think data in a spreadsheet) and, according to pre-set rules, processes that data to produce an expected outcome (‘given A, then B’).

RPA is typically deployed in a back-office context. Think accounts departments’ employees checking payable or receivable balances and transferring the information thus retrieved to a different application. Think insurance employees processing premium renewals. All these repetitive activities, when not complicated by exceptions, can be processed by RPA. An RPA ‘robot’ then is nothing other than the software license needed to carry out these activities, nothing fanciful – or intelligent, in a human sense, there. Seen in this light, RPA technology frees employees to carry out added-value activities, whilst the robot carries out the repetitive, mindless ones, effectively ‘taking the robot out of the human’).

Cognitive Automation (CA)

 CA is the use of software to automate complex processes and tasks also previously performed exclusively by employees. Unlike RPA, CA is more appropriately suited to complex, low volume transactions.

From a technology perspective, CA uses algorithms, intelligent instructions to process both ‘structured’ or ‘unstructured’ data (images, voice) to produce probabilistic outcomes (‘B is more likely given A’). The main CA tools are computer vision (including image processing), natural language processing (NLP) – and more, by the day, digital development and imagination knowing very few boundaries. CA is suited to finding patterns among large volumes of data. Because of ‘machine learning’ capabilities built into the software, CA can ‘learn’ by comparing expectations to results, improving performance over time. However, whilst CA does interact, intelligently, with rules in order to interpret data and complete tasks, CA is still not an artificial intelligence system.

CA typical deployment context is the front-office. Think chatbot assistants deployed in those customer-facing environments we are familiar with, from our own online retail – or banking – experience, all underpinned by CA. Think the virtual agents, such as IBM Watson, Expert System Cogito, IPsoft Amelia, used to engage with customers and employees and that can respond to chats, adapt to detected emotions and execute tasks identified during the chat itself, thanks to memory capabilities (unlike Siri, our phone-residing assistant, who can only respond to simple requests (input) with simple responses (outputs), having no memory or understanding of context).

Where is automation in business heading?

In 2018, the combined service automation market was estimated at US$ 4.1bn, with a predicted rise to US$ 46.5bn in 2024 (8). In a Sep 2020 press release, Gartner predicts that, despite the economic pressures due to COVID-19, the RPA market is expected to grow at double-digit rates through 2024. Indeed, COVID-19 and the ensuing global recession have increased interest in RPA with 90% of large organisations having adopted RPA by 2022, as they look to ‘digitally empower critical processes through resilience and scalability while recalibrating human labour and manual effort’. CA is still a somewhat new technology, with organisations needing to make relatively novel decisions as to its applicability and role within the enterprise. A positive outlook on CA investment comes from IPsoft Amelia’s AI-Powered Telco report on how the telecom industry is using automation to transform operations, forecasting a market size of US$ 36.7bn, annually, by 2025.

And how do you avoid costly mistakes?

For an organisation to prosper in digital times, a CEO must put in place the two success elements for the implementation of automation, namely, strategy alignment and change management.

It is my profound belief, developed in two decades at the coalface, that change – of the extensive type brought about by a new target operating model, a new ERP, a new enterprise architecture – is ultimately about the collaboration between people, in projects, IT, business operations, aimed at a common objective, supported by common tools and practices that form a coherent structure aimed at achieving the transformation.

Out of the universe of change methodologies, I have come up with a combination of business-focused tools and practices, based on my best work. These tools and practices, practical, scalable, easily embedded in a project delivery structure, give the business operations teams a voice and create a collaborative, dynamic culture which, not least, will facilitate the understanding of the benefits and the useful application of automation. It is within this collaborative culture that people can be educated to operate in an environment where automation may be the norm and where people’s fears of losing their jobs to machines can be addressed.

Francesca helps organisations navigate change – she believes projects of transformation fail because business change practices are inexistent, governance is weak and the mechanics of the delivery malfunctioning. She has many years’ experience in transformation, so if you’d like to speak to her, contact her here.

For a deeper exploration of tools and practices for effective business transformation, download the playbook Demystifying Change.

James Cumming is our MD, Interim and Transformation Search specialist. Please get in contact with him directly to discuss any of these topics further.

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