In the modern world, hyperautomation is a way to speed up the development and launch of new digital products and processes – but how exactly can this be done? Throughout part 1 and part 2 of this blog series, we’ve been looking at what hyperautomation is and what it looks like in practice.

To enable hyperautomation, organisations must move away from traditional technology stacks and one programming language towards ‘composability’ – a decentralised IT infrastructure managed entirely in the cloud.

Gartner sees composability as a major technology trend because digitalisation is so fast that IT alone cannot keep pace. Instead, it advocates ‘fusion teams’ of business and tech specialists who can rapidly scale their digital efforts using ‘packaged-business capabilities’ (PBCs) or ‘software-defined business objects’ – a toolkit that enables these tech teams to assemble applications quickly and reduce time to market.

Organisations have already seen impressive results from adopting this approach, including one bank that has saved over 200,000 hours of manual effort.

There is value in multi-modal ways of working. Low/no-code platforms democratise access to analytics, so people from across the organisation can create their models and processes without relying entirely on developers. Business analysts are often best placed to solve their challenges, and if they have access to the software, they can do so more quickly and accurately than a developer.

Why code?

Where code is needed, organisations need the flexibility to work in various languages – such as SAS, R, Java, Python, and other emerging ones – so innovation isn’t constrained by a lack of skills or the language itself. By creating and operationalising digital products and processes at ‘hyper’ speed, they can achieve composability and become more resilient and productive.

We often talk about intelligent decisioning but what organisations are also looking for is decision intelligence. Transparency is critical as organisations enhance their capabilities with artificial intelligence (AI) methods such as machine learning, deep learning, natural language processing (NLP), forecasting and optimisation. Organisations need to know what decisions have been made, whether they have visibility of them, how they affect the business, how they can be accountable for the decision, and whether the AI model is ethical.

To buy or build, that is the question

As organisations embark on their digital transformation journeys, they’re faced with a quandary – should they buy off-the-shelf software and rely on the vendor for support and maintenance, or build a system that gives them a competitive advantage?

If they opt for the latter, they might find that any advantage is negated by the time it takes to build the system in the first place. While off-the-shelf cloud solutions offer faster deployment times, they don’t always meet their requirements, especially in highly regulated fields like banking or insurance.

However, a third, or hybrid, approach involves forming alliances with vendors who work with organisations to build their competencies and then help them extend them further. This type of collaboration means they can rapidly enter a market and supersede their competitors without building and maintaining the infrastructure.

The value of hyperautomation is the speed of innovation, so it’s important to choose a vendor that helps organisations to build and operationalise digital solutions quickly. SAS has worked with Microsoft to deliver a tightly-integrated co-engineered solution that meets organisations hyperautomation needs because no single vendor currently can do that.

Looking ahead

Hyperautomation isn’t a fad but something that will only gather momentum over the coming years. We’re already seeing a growing appetite in banking, where companies continually look for ways to innovate and protect their margins in a competitive industry.

However, there’s also a burgeoning interest in sectors such as telecoms, energy and utilities, which rely on shared networks. Having already deployed automation to some degree, they’re now exploring how hyperautomation could eliminate manual intervention and support intelligent decision-making and advanced AI. For instance, CSPs (communications services providers) are preparing for the widespread adoption of 5G – and hyperautomation could help them to optimise how the network is used as vast amounts of data flows through it.

Hyperautomation, deployed across multiple organisations and shared infrastructure, could radically transform how services are designed and delivered and pave the way for smart cities. The hybrid approach outlined above could happen sooner than we think.

Find out how the SAS® Viya® platform on Microsoft Azure can support hyperautomation in your organisation.






About Author

David Shannon

David has over 20 years of experience as a Director and Consultant in Analytics. He provides strategic and tactical advice across the analytics industry delivering cost benefits, productivity and innovation. With in-depth IT knowledge and a reputation for getting things done. Today, David works for SAS leading the UK & Ireland’s Hyperautomation agenda and helping organisations drive digital transformation with automation. Outside of SAS, David is the volunteer IT Director for The MG Car Club. Formed in 1930, The MG Car Club is the original club for MG owners and one of the world's oldest car clubs with around 10,000 members world-wide.

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