Blog & Newsroom

How does automation-as-a-service work and what are the benefits?

The seismic shift to cloud-based services, both consumer- and business-facing, isn’t driven by a relentless dedication to using whatever’s hot in technology. It’s happening because this service delivery method brings specific advantages: cost, availability and uptime, to name just a few. According to the Forbes’ 2018 State of the Cloud report, 77% of enterprises have at least one application or portion of their infrastructure in the cloud. Many technology-oriented businesses aim to move 100% of services to the cloud.

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Automated scheduling in action: How Whitbread achieved automation success

Since the start of the year, we’ve devoted time to discussing the benefits of automation, as well as the real world costs and potential pitfalls of relying on outdated workload automation (WLA) solutions. And while we pride ourselves on the simplicity, scalability and transparency of the process automation services we deliver, we also know that real-life examples can really help people see the benefits and envisage their own automation journey. Simplify the landscape One of the biggest problems enterprises face when considering newer automation technologies is the patchwork of tools they’ll be replacing.

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The Risks of Out-of-Date Automation Technology Part 2: Beware the Hidden Costs

In the first post of this three-part series, we examined the wider issues that can arise in terms of sustainability and complexity. This week, we’re looking at the costs of relying on out-of-date workload automation (WLA) or scheduling technology. The need for a business to be responsive is – as we and those wiser than us have noted many times before – crucial. Whether it’s customer-facing functions or back-office nuts and bolts, the ability to respond immediately to changes is a constant.

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Growing pains: Why perpetual change is the only answer

If the constant pressure to modernize, transform and generally maintain a state of perpetual change feels like an invention of the modern age, you’d be wrong. In the 6th Century BCE, Greek philosopher Heraclitus stated that “the only thing that is constant is change.” While recognition of the need for change — or indeed, the inevitability of it — isn’t news to businesses, acting on it is by no means easy. The need to implement a digital-first strategy isn’t the sweat-inducing demand that it once was — but the unpleasant truth is that we want to change without going through the uncomfortable process of change.

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What’s the difference between AI and machine learning?

There’s an awful lot of marketing noise around the “machine learning” and “artificial Intelligence” capabilities of much consumer- and enterprise-facing software. But the interchangeable use of terms that mean different things has led to a lot of confusion. So let’s clear up, once and for all, exactly what these terms mean. and why they’re useful. Machine learning In short, machine learning is akin to a human learning how to perform a task more efficiently (or to result in a better outcome) through a process of trial-and-error.

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What does Moore’s Law mean for business?

Moore’s Law wasn’t intended to be a law. When Gordon Moore observed, in 1965, that the number of transistors in a dense integrated circuit was doubling roughly every two years it was exactly that: An observation. Albeit one that held true for half a century and dictated semiconductor development roadmaps. However, more recent discussions have questioned whether Moore’s Law still applies in today’s technological landscape. Intel (two years ago, no less) changed its roadmap to push back new chip models and,

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How does AI fit with automation?

AI, most regularly associated with artificial intelligence, has become a bit of a stand-in term for what is really a broad selection of technologies that encompasses machine learning, predictive analytics, natural language processing, object recognition and more. To the uninitiated, it can be a bit confusing, so everything ends up under the umbrella term “AI.” It’s a bit like that family member who refers to all tablets as an “iPad,” regardless of the actual device they’re holding or referring to.

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The new paradigm: Automation-as-a-service

In mathematics, the idea of “bounded value” generally refers to the notion that there’s a limit to the value of “x.” Conversely, “unbounded value” means there’s no maximum or minimum value of “x.” In automation, a similar notion carries through — there’s no minimum value you can extract by using a tool such as RunMyJobs by Redwood on a limited set of processes, but there’s also no maximum value, as it scales efficiently for businesses of all sizes and complexities.

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Blockchain and automation: A perfect match?

Trust is an important part of any business transaction. Trust within an organization is often implicit but it is a more difficult proposition when it comes to the need to share data to third parties, partners and other external organizations. Most often, this is done via a distributed database of some kind, which could take many forms — for example, a cloud-based platform to share documents. This addresses accessibility but not the trust issue. Blockchain, at least in theory,

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What happens when you automate the finance department?

With increased pressure to do more with less, almost all business units are now required to work in a more agile way to maximize efficiency — and the same is true of finance. The CFO and finance department should seek to collaborate with the wider business, to find ways to modernize and digitize tasks and processes wherever possible using knowledge from the people who perform the tasks day-in, day-out. Finance is a crucial part of any business,

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Is 100% automation really feasible – and do I want it?

Fewer errors. Repetitive tasks eliminated. Speedier execution of processes. These are among the promises of “end-to-end automation,” or “100% automation.” But the shift can still be a daunting prospect for a company without prior experience. Concerns around a lack of process oversight and audit requirements, or vulnerability to errors going unnoticed, are entirely avoidable. In some cases, they’re based on interactions with more primitive automation tools. Consider the path to 100% automation as analogous to regular cars evolving into self-driving cars.

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