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Intelligent automation that oil rigs can learn from bakeries, and vice versa

Paul Hardy Profile picture for user Paul Hardy January 29, 2018
By sharing process analysis data, businesses as diverse as oil rigs and bakeries can learn intelligent automation tips from each other, writes ServiceNow's Paul Hardy

Oil Rigs & Bakeries ServiceNow use only
The world is moving forwards to grasp a new degree of technology-driven intelligent automation across every aspect of business operations. This is a world where oil rigs and massively-scaled industrial engineering outfits have much to learn from what happens inside small- to medium-sized businesses such as cake bakeries – and vice versa.

Automation offers massive potential advantages and opportunities, but it’s only right to point out that there are also significant obstacles — both real and perceived. But first, let’s define what we mean by this word ‘automation’, intelligent or otherwise.

What is intelligent automation, anyway?

When we talk about intelligent automation we’re not directly referring to whirring robots and human-like androids – although given the proliferation of the devices that make up the Internet of Things, we are talking about robots too. Primarily, we are talking about intelligent automation brought about by software that is designed to manage and subsequently capture workflow efficiencies and process best practice.

In a cloud-centric world that is driven by the use of services-based computing, we now have the chance to analyze which aspects of which service work well, for which type of data, in which kind of computer environment, and in which location.

If we break down the workflows within any organisation then we can start to classify processes by department – and perhaps by team size, work methodology or some other core defining factor – to derive observations about best practice. This analysis is the DNA that we use to formulate intelligent automation.

The question we have to face up to is – are firms using this opportunity for competitive advantage in the right place at the right time? The answer, as is often the way of things, is both yes and no.

The application of automation

Yes, some businesses have sought to apply intelligent automation to their operational models, perhaps especially those which have been increasingly rolled out on cloud-native technology platforms. But no, not every business is using intelligent automation when and where it could be deployed to best effect.

Many businesses could be using intelligent automation to automate tasks and services across their entire business base. But few are being this ambitious. Most use it as something more of a precursor analysis layer – a preparation layer if you will – to perform data analysis, data de-duplication and related actions such as data classification, in order to identify the areas in which they can actually action automation.

This falls frustratingly short. In a lot of ways these companies are getting themselves right to the point where they could really start to bring intelligent automation to bear. But — and here’s the stumbling block — because they are investing so much time in the analysis on ‘steering and righting the ship’ and doing things like vendor management, their focus is always predominantly concerned with day-to-day operations.

Crafting automation playbooks

These same companies sometimes appear to have low expectations for how well tasks can be automated. This is why we as a global technology industry need to start crafting automation playbooks, blueprints, run books, templates – call them what you like – that show how we can codify everything, from onboarding employees to automating stock order flows down the supply chain.

These automation playbooks will be based on shared but often complex and anonymized operational data, so that no single company will ever put its core intellectual property at risk. Thus it’s entirely possible that oil rigs could start learning from bakeries – and vice versa.

What works well for one shape of workflow and use case should work in another similar deployment scenario. Obviously there are degrees of relevance between workflows, but we can quantify that aspect and that will help us then apply the appropriate amount of customization.

Intra- and inter-vertical sharing

As we move to establish our appreciation and understanding of intelligent automation, we need to encourage intra-vertical sharing inside the same industry – and also inter-vertical between different industries. From oil rigs to bakeries and from hospital maternity units to online greeting cards businesses, there should be no barrier to sharing intelligent automation learnings, if it improves the bottom line and helps bring user experiences forward and upwards.

And honestly, what oil rig worker is going to say no to a nice bit of cake?

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