Digital transformation may have accelerated dramatically during the COVID-19 pandemic, but deploying digital services is only half the battle.
As companies rebuild around the new digital normal, the real challenge is ensuring those services work together to connect and support employees inside and outside the organisation.
Far from the old world of collaboration – where integration was often as simple as turning the swivel chair to talk to the person at the next desk – in today’s world collaboration means building seamless bridges that link people with applications and services right across the enterprise.
“Employees are depending on digital services to collaborate with their colleagues and to run a lot of their internal processes,” says Dormain Drewitz, vice president of product and solutions marketing with workflow automation firm PagerDuty, a global leader in digital operations.
“Your ability to operate now requires that all these digital services work with the additional integrations that you’ve built, and have to work with inside your organisation,” she adds.
“If that’s not coming through, it’s going to affect your teams – and you have digital complexity standing between you and smooth operations.”
It’s a concept that Gartner has popularised as the ‘composable enterprise’, and it’s shaping the way businesses function as they increasingly integrate core business applications with third-party services that exist within the miasma of the cloud.
As the balance steadily shifts towards the cloud, those services are producing more data about their every action than ever before – but that data often lives in external services that must be accessed and controlled using application programming interfaces (APIs).
“Web hooks and APIs are the lingua franca for being able to have any kind of situational awareness of your operations,” says Drewitz, noting that PagerDuty has nearly 670 different application integrations to facilitate the free flow of information across on-premises and cloud applications.
Effectively orchestrating their operations provides competitive advantages for companies working to build data-driven architectures for cybersecurity, customer service, streamlined business processes, and other data-driven business functions.
The success of a company’s composability links directly to its overall business performance, with a recent Gartner survey finding that 63 percent of CIOs in high-composability organisations report better business performance than their peers or competitors.
“Business composability is an antidote to volatility,” said Gartner research vice president Monika Sinha – noting that as well as enjoying better overall performance, companies with highly-composable architectures “are better able to pursue new value streams through technology, too.”
Automating the workflow
Yet for all their promise, actually making these architectures deliver business value requires a more holistic approach to business services – and a comprehensive understanding of what data each service uses and can provide, and how those services are instrumented.
“You now have more and more dependency on different digital systems, all of those systems are producing data,” says Drewitz.
“They're producing data about what is happening, whether they're functioning, whether there's latency, and what have you.”
Whereas turning that data into business value was once delegated to analysts armed with niche data-analytics tools, today’s data-driven enterprises are increasingly leaning on data platforms to monitor for changes, analyse trends, and pick out meaningful insight from cascades of information.
“With all of this data now available to you,” says Drewitz, “correlating, aggregating and correlating manually is an overwhelming task and really beyond what any human should be working on.”
“You need a system in place that can be listening to all of this data coming in, all the time.”
Enter artificial intelligence and machine learning (AI/ML)-driven architectures, which are rapidly being integrated with modern workflow engines to help contemporary business services stay ahead of the ever-expanding wave of operational data.
In environments such as cybersecurity monitoring, AI/ML architectures have become the only hope of detecting ‘low and slow’ cybercriminal attacks that are intentionally designed to sneak under the radar of ever-fatigued security operations centre (SOC) staff.
For all its benefits, the technology is not a complete replacement for staff, Drewitz points out, but something to support them in jobs that have become untenable without assistance.
“Human attention spans are really limited and finite,” she explains, “and it can be hard ensuring that their attention is on the right work.”
“And with so many different layers in these complex digital ecosystems that every organisation is operating within, you need machine learning to really help focus teams and their attention.”
The challenge has been compounded by the ‘great resignation’, which has seen companies struggling to maintain workforce continuity as employees shun unfulfilling and stressful work – which, unfortunately for companies embracing data-driven futures, often includes critical operational tasks such as incident response and network monitoring.
By tapping AI/ML capabilities to identify important trends – and feeding workflow automation to minimise the number of low-value tasks that employees must deal with – Drewitz said companies can benefit from new digital architectures without dumping more work on already-stretched employees.
“There’s a huge value proposition around being able to offload a lot of the work and letting the humans on the team feel they’re working on stuff that’s interesting and fulfilling,” she explained. “The aspiration is to get to the point where more of this is resolved on its own.”
In a world of ‘digital everything’, are you ready for anything? To find out more about what the future of automation holds, please join PagerDuty at the online or in-person PagerDuty Summit 2022. Click here for more information and to register.
