An emerging architecture for the new wave of automation

An emerging architecture for the new wave of automation

Every organisation that’s serious about exploring or embracing new automation technologies within their operations needs to understand how they can complement each other and act in different contexts.

We’ve talked for some months now about what we call the new wave of automation: a cluster of related technology trends that are impacting the ways that organisations have traditionally thought about how technology can be used to automate aspects of work.

There’s a whole zoo of technologies playing a role in this new wave of automation: the principal technologies we’re tracking include Robotic Process Automation (RPA), Digital Integration Platforms (some people call these iPaaS), Cognitive systems and services, Digital Assistant Platforms, and recommendation technologies.

But how do the practices that you need to build around these technologies fit together? As an example – do RPA and Business Process Management Suites (BPMS) complement each other or compete? (This is an example I’ve been asked about many times over the past few months).

The answer – as you can see in the diagram below – is that for the most part, when you really look at their applications in today’s digital workplace – these technologies are largely complementary.

What’s also clear, though, is that every organisation that’s serious about exploring or embracing new automation technologies within their operations needs to understand this picture.

In the sections below I’ll explain the colour-coded key and the axes of the diagram.

Colour key: Interaction, insight, integration

As we’ve discussed in other articles, these various technologies align themselves in three areas: interaction, insights and integration. You can see that we’ve colour-coded technologies on the diagram according to this.

New interaction-focused technologies are all about enabling automated systems to sense and respond in more human ways. This is about a continuation of the long-term shift from ‘operator’ to ‘human’ interfaces; which has seen us move beyond the command-line to graphical, to conversational (natural language-enabled, text or speech) interfaces.

New insights-focused technologies are all about enabling automated systems to take advantage of interactive, predictive, advisory analytics. This is about a continuation of the long-term shift from analytics that are static to interactive applications; from analytics that are retrospective to analytics that are predictive; and from analytics that simply surface information to analytics that drive automated recommendations and decisions.

New integration-focused technologies are all about driving the continued componentisation and automation of information and technology resources. This is about a continuation of the long-term shift from information and function representations and protocols that are closed to those that are open; from automations that are built by specialists to those that are model-specified by generalists; and from programming to visual design.

The vertical axis: components of work

In the diagram above, we’ve shown the roles that particular technologies play at different ‘layers’ within work activities.

At the top, we position technologies that have an effect on how work activities are initiated; in the middle we’re focused on how activities are controlled and directed; and at the bottom we’re focused on how activities are executed at their core.

As you can see – not surprisingly – those technologies that are principally focused on interaction innovation appear towards the top of the diagram; technologies focused on insight innovation appear towards the middle; and technologies focused on integration appear towards the bottom.

The horizontal axis: a progression of work types

In our analysis reports and webinars to date we’ve been very careful in explaining that the impact of automation is, for the most part, likely to have its impacts felt at the level of individual tasks rather than in end-to-end processes or jobs. Not all work will be automated in the same way at the same time.

If you’ve read our reports over the past few years focused on assessing Process Application Platforms, you’ll be familiar with the way that we commonly classify work into three types:

  • Routine / programmatic. This work is highly structured, ‘commodity’ work that in many cases is already partially automated through existing structured software systems, managed and orchestrated through strictly-controlled workflows. This kind of work often crops up in operations administration, financial processing, and so on. In many cases organisations have already sought to minimise the costs of this work through business process outsourcing (BPO) arrangements.
  • Transactional. This work is still structured and predictable, but the control, sequencing and orchestration of the work – as well as many of the individual tasks – are typically carried out by people. Examples here include operational and administration work related to answering customer queries, onboarding customers, organising materials shipments or product deliveries, and handling simple insurance claims.
  • Exploratory. In exploratory work scenarios, the set and sequence of actions needing to be performed, and the people or roles needing to perform them, are very unlikely to be known ahead of time. There may be some high-level waypoints or milestones that are common to a particular type of exploratory work (perhaps to ensure consistent quality control, or resolution approval, or archiving) but they provide a very loose, rather than tight, structure. In exploratory work, as the label suggests, the overall experience for both the work participants and the customer is that of a set of possibilities being explored rather than a recipe being followed. This kind of work commonly crops up when organisations need to solve problems, investigate fraud, make key decisions about operational planning, and so on.

Of course, to a significant extent the boundaries between these different types of work are specific to each individual organisations, because they’re a result of organisational maturity in work design and business architecture; as an organisation practices more and more in these areas it tends to design and factor work more deliberately, applying most structure and automation to work that’s most predictable, common and compliance-susceptible.

What’s also true is that over time, as automation technologies become more sophisticated, the presence of automated work will steadily creep from the left to the right of the diagram – changing the boundaries between these work types in practice.

How key technologies fit

So now I’ve explained how the diagram works – let’s talk about some of the different technologies I’ve highlighted.

Robotic Process Automation technologies – despite the name – in an enterprise context are primarily focused today on the automation of individual tasks or sub-processes. Their sweet-spot is in automating aspects of routine/programmatic work, creating data and function integration services through the automated control of legacy application user interfaces. Much of the product engineering and partner development in this space currently revolves around pushing ‘up the stack’ to enable coverage of more of how this kind of work gets initiated and controlled.

Digital Integration Platforms (they’re sometimes called iPaaS offerings) also play in the routine/programmatic work space, and at the boundary with transactional work – creating new, faster, more flexible integration technology choices, particularly in the context of use of digital platforms.

Digital Assistant Platforms (also referred to as bot platforms) come in a variety of shapes and sizes: at one end are the toolkits for creating skills for the likes of Amazon Alexa and Microsoft Cortana; at the other are products like IBM’s Digital Business Assistant. Many focus principally on the interaction aspects of digital assistants, but some (like IBMs) also include specific features and capabilities aiming to help people build core logic and integration functionality into assistants.

There’s probably more to say about this diagram, but for now I’ll leave it there. I’d love your feedback! Do you agree / disagree? What could I explain more clearly?

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