Traditional principles of digital resiliency have been put to the ultimate test during this pandemic, and they just aren’t cutting it.
So says Rick Villars, VP of worldwide research at IDC. In a presentation at IDC Canada’s recent virtual conference, Villars argued that enterprises are used to approaching digital resiliency on a piecemeal basis: how do we protect the business against specific IT incidents like breaches and outages?
In a global pandemic — when literally all facets of IT and lines of business are completely upended — that piecemeal approach doesn’t work, Villars said.
His new vision of digital resiliency isn’t about trying to anticipate, prevent, react to and recover from specific IT disasters. It’s about adapting to constant change (like, say, a pandemic) so your business can accelerate its digital transformation and become better able to adapt to the next massive change, and the one after that, and the one after that.
Villar believes the key pillars of this new model of digital resiliency are:
- trust (via cybersecurity)
- new software ecosystems
- edge computing
- a flexible, evolving concept of ‘workplace’ as office, home, field
Villars said all of this will be underpinned by one thing. “This all really comes back to automation,” he said. In his words, “the next big task” is how to automate the enterprise at scale, consistently and coherently.
Like everything in enterprise IT, that’s not gonna be easy.
Barriers to automation
According to a survey of 400 IT decision makers in the U.S. and U.K.:
- 48 per cent of businesses have increased their spending on automation initiatives since the pandemic began, directly as a result of COVID-19 disruption
- 78 per cent plan to increase their automation spending even more over the next 12 months
They’ve also run into the following barriers during their automation journeys, however:
- 54% – legacy technology
- 40% – move to remote working
- 39% – lack of internal skills
- 37% – compliance issues
- 36% – buy-in from internal executive stakeholders
- 36% – company culture
- 29% – lack of clear vision and strategy
- 28% – cutbacks in funding
Villars breaks down these types of automation barriers into two main categories:
- Data barriers: getting people to agree on what data they have, where it is and how to integrate it
- People barriers: in Villars’ words, this boils down to “we don’t have the right set of skills in our organization to take advantage of (automation)”
But the danger of not addressing those two key barriers, Villars warned, is the dreaded silo.
Beware of silos
“Beware of creating silos of automation,” Villars cautioned his virtual conference audience. “This is an area IDC believes companies have to focus on aggressively: achieving consistent, coherent, cooperative automation.”
He advised enterprises to model their automation strategy on the human body, where all the parts play very different yet important roles.
“They all can connect and work together,” Villars said. “They’re all linked via the autonomic nervous system.”
He even suggested enterprises create their own autonomic nervous system for automation across their organizations. Here’s what his model of that system looks like (suggestions in brackets are his, not ours):
- common data and app definitions/rules (i.e., OpenTelemetry)
- ubiquitous access to compute/memory resources (i.e., dedicated clouds and multi-access edge computing)
- standard processes for moving data (i.e., Connect aaS)
- common platform for creating and updating functions (i.e., a cloud-native ecosystem like Kubernetes)
- collective governance model for orchestration, performance and configuration
The skills shortage loop
While Villars’ model for avoiding automation silos tackles the data barriers to automation, it all seems like it ultimately hinges on the people barriers — namely, the skills shortage.
Villars acknowledged this conundrum by putting up a slide with this dire IDC prediction on it:
“Through 2023, half of enterprises’ hybrid workforce
and IT automation efforts will be delayed or will fail outright due to underinvestment in building
IT/Sec/DevOps teams with the right tools/skills.”
Among the 400 businesses in the survey we mentioned earlier, almost 40 per cent said a “lack of internal skills” is already hampering their automation strategies.
So how do we tackle the people problem that’s standing in the way of effective automation? It seems like a classic chicken-and-egg riddle: how do we use automation to ease the tech skills shortage if we don’t have enough people with the automation skills to deploy that automation to ease the skills shortage …?
Without some good solutions to this chicken-and-egg riddle, a lot of enterprise automation plans will be walking on eggshells.