Architecting the new wave of automation
Blog: MWD Advisors
This report tackles the subject of ‘automation architecture’ – the practice of deliberately planning and shaping how your organisation invests in work automation technologies. Automation architecture is important because – on the surface at least – numerous technologies have the potential to compete or substitute for each other in enabling the automation of aspects of knowledge work. For example: Robotic Process Automation (RPA) vendors claim that their technologies can be used to automate not only individual tasks, but also automate sets of tasks. Does this mean that if you use RPA, you don’t need to use workflow technology? This report attempts to help you answer these questions.
Automation architecture is a way for you and your colleagues to establish a set of clear guidelines and patterns that will help teams make the right decisions as they scope and conduct automation projects – making it clear to project teams how different automation technologies complement each other and add value to each other.
A clear strategy is vital if you’re going to get the best out of technology choices on offer
Automation has been on a steady march through business for over 200 years: nevertheless, the past three years or so have seen a huge step-change in the variety of technologies being promoted to help businesses automate aspects of their work.
Given the wide variety of automation-related technologies being pitched to organisations, and the speedy pace of automation technology evolution, your organisation must develop an automation strategy that clearly and deliberately sets out how and where you will look to apply different kinds of automation technology capability – and why you are looking to apply particular technologies in particular places.
Think about ‘how work works’ as your automation starting point
We all know intuitively that not all work is equally amenable to automation: some work is highly suited to extensive automation, whereas the opportunity to automate other work is much less obvious. What is it that makes the difference?
A good starting point is to think about categorising work according to how much expert discretion is required to perform it. The more discretion is required, the less amenable the work will be to automation.
In practice we find that there are three types of work commonly found ‘in the wild’ in organisations, with human discretion tending to be required for different blends of features across the three types (which means each type is amenable to automation or augmentation with digital technology in different ways). We call these exploratory work, transactional workand programmatic work.
Make your architecture work real and practical
Once you’ve begun to analyse how you might use different kinds of automation technology to address opportunities in the different kinds of work you have in your organisation, it’s vital that you think beyond this analysis and put some plans in place to drive that analysis forward into action that will have real impact. There are four things you particularly need to focus on: collaborate and share your work in the open; be deliberate about creating an automation technology operating model; don’t fall in love with any one automation technology too much; and review your assumptions and analyses regularly.
The changing business automation landscape
It might seem like automation in the workplace is a relatively new phenomenon – there’s certainly a huge amount of talk about it in today’s corporate meeting-rooms, conference halls and news media. The reality is that automation has been on a steady march through business for over 200 years: nevertheless, the past three years or so have seen a huge step-change in the variety of technologies being promoted to help businesses automate aspects of their work.
One component of the energy pushing this new wave comes from organisations themselves, as they seek to apply digital technologies and concepts to make them more attractive and more competitive. The other component comes from changes in the economics of automation – the tools are becoming cheaper, quicker to deploy and easier to use, and data to train and improve ‘smart’ systems is more and more easily available.
In industry: digital initiatives are driving automation investments
Businesses the world over are rushing to explore digital initiatives. Some are driving full-on digital transformation programs; others are working more modestly, looking to apply digital technologies to particular business products and services, capabilities, activities or processes.
What’s become abundantly clear is that any organisation thinking about ‘digitising’ aspects of their business needs to think holistically. Customers’ experiences aren’t only shaped by customer service teams – they’re shaped by the interactions they have online; conversations with salespeople; the quality of a product; the accuracy of bills; and so on. By definition, delivering great customer experiences depends on activities that your organisation carries out across many teams and departments.
The implication is this: delivering on a digital transformation agenda ultimately means creating “digital threads” that enable organisations to seamlessly carry out and co-ordinate work, make decisions and share knowledge effectively, consistently and at scale – across teams, systems, channels, media platforms and business locations. The “digital outside” of your organisation must be connected to and supported by a “digital inside”.
Automation – of work, and of how work and information are connected together across an organisation – is a huge part of the answer. End-to-end automation of work is not always possible or desirable. But even where such automation is not possible, there are ways to use digital platforms to improve the work environment.
In technology: automation is cheaper and goes further, faster
It seems that every week we’re bombarded with new work automation technology choices.
From about 2000 until 2015, organisations had three main technology choices if they wanted to automate aspects of administrative work: they could implement packaged business software applications (automating aspects of practices like ERP and CRM); they could build their own applications using traditional custom software development tools (probably based on Java or .NET technologies); or they could use more business-friendly, model-driven platforms to build systems (primarily focused on workflow automation and business rules automation).
Now, those three choices remain – but they’re joined by more:
- Robotic Process Automation (RPA). RPA technology provides a set of tools that organisations use to design, configure, deploy and manage software robots that act as synthetic application users, automating tasks across business software systems. RPA ‘bots’ gather and update information in business software applications by automating actions against their existing Windows-based, web-based or other user interfaces, and provide a non-invasive alternative to creating and using specialised integration APIs or programmed integration by other means. Specialist vendors like Automation Anywhere, Blue Prism, Kryon, Workfusion, UiPath and more offer RPA technology that works in two specific modes: unattended deployment uses RPA bots in a ‘headless’ configuration, working on tasks behind the scenes with no direct human involvement; whereas attended deployment uses RPA bots in an interactive mode, working side-by-side with human users to complete tasks from within users’ desktop environments.
- AI services and frameworks. With a particular emphasis on machine-learning algorithms, a new wave of AI services – particularly focused on automated sense-making and interaction using voice and vision – has started to have a major impact. A big part of this impact comes from the fact that many of the technologies are offered free of charge, or offered via low-cost subscriptions. Additionally to these low-cost, general-purpose frameworks there’s renewed interest in using machine learning to create tailored, predictive analytics models that operate on structured data and can deliver tailored, context-sensitive recommendations to individual business people ‘in the flow of work’. Big brands like IBM’s Watson, Adobe’s Sensei and Salesforce’s Einstein operate across these categories, but there are many other players too – big web platform players Google, Amazon and Microsoft are investing huge resources here, and hundreds of smaller specialist technology vendors also in the frame.
- Low-code application development platforms. Often bringing flexible workflow technology with them, a set of specialist vendors (K2, KiSSFLOW, Mendix, OutSystems, QuickBase and more) are offering increasingly sophisticated application development platforms for teams and departments wanting to drive quick digitally-driven improvements to their operations. Typically cloud-hosted and subscription-based, these tools excel at enabling business-technology generalists (rather than deep software development specialists) to quickly and cheaply build “good enough” business automation systems. Many of these platforms also provide high-grade deployment and administration options that enable systems to support more demanding enterprise-scale requirements.
- Low-code application integration platforms. A set of specialist vendors (Azuqua, Dell Boomi, Jitterbit, SnapLogic, Workato and more) offer sophisticated, primarily cloud-hosted application integration platforms to business-technology generalists looking to quickly integrate cloud-hosted and on-premises applications and systems. With high-productivity, low-code approaches to the design and deployment of integration code these vendors are making application integration technology economical for an increasingly broad and diverse range of scenarios.
How do you make sense of how all these technology options fit together, and make sense of the different opportunities they present?
Building an automation strategy
Given the wide variety of automation-related technologies being pitched to organisations, and the speedy pace of automation technology evolution, your organisation must develop an automation strategy that clearly and deliberately sets out how and where you will look to apply different kinds of automation technology capability – and why you are looking to apply different technologies in different places.
You need an automation strategy that you can communicate widely across your organisation. Without one, the danger is that – because there’s so much technology variety on offer, because there is so much interest from different quarters of business in automation generally, and because there is significant danger of technologies being used for purposes they’re not necessarily most appropriate for – your organisation will end up with big problems. You may waste your investments, introduce unnecessary operational risks, and/or hinder business agility and scalability (through poor-quality, brittle technology implementations).
In this section, we introduce a way of thinking about the work that gets done in your organisation that will help you map out the best potential ‘sweet spots’ for individual automation technologies and see where multiple technologies can potentially be profitably used in combination.
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