It’s hard to believe how much has changed over the past decade. When I first started writing for Allstream expertIP in 2013, ‘collaboration’ was the latest buzzword. Mobile workforces were becoming the ‘new’ normal. And companies were adding UC functionality to their existing PBX investments.

Obviously, a lot has happened since then—including a global pandemic that accelerated digital transformation and permanently altered the way we work.

Technology continues to disrupt, and the telecom industry continues to evolve—as do the companies that service this space.

In 2016, Allstream joined forces with Zayo to provide a unified fiber network spanning the U.S. and Canada, but the two companies largely operated independently.

Now, Zayo will be bringing some of Allstream’s products under the Zayo umbrella to expand voice and connectivity solutions to mid-sized enterprise customers across North America.

But this milestone will also mark the end of expertIP. However, you can keep reading about similar topics on Zayo’s resources page, with insightful blogs, videos and infographics.

Thanks for reading, and for being part of the expertIP community—including a stellar group of people I’ve had the privilege of working with for almost a decade. That’s a wrap!
Vawn

Image: Henrik5000/iStock

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More businesses have deployed AI than ever before, but few are taking steps to ensure they’re using it in a trustworthy and responsible way, according to IBM’s third annual Global AI Adoption Index.

After surveying more than 7,500 organizations in 19 countries, the researchers found 35 per cent have adopted AI, a four-point increase from 2021. Although AI is now more accessible and user-friendly than it was three years ago, the report suggests adoption may be moving more quickly than efforts to define what ‘responsible’ and ‘ethical’ AI looks like.

Here’s a snapshot of how and why organizations are using artificial intelligence today.

Use cases

Based on IBM’s findings, these are the top five use cases for AI in 2022:

• 1: automation of IT processes
• 2: security and threat detection
• 3: automation of business processes
• 4 & 5 (tie): “marketing and sales” and “business analytics or BI”

The pandemic remains a huge driver of AI adoption, with 31 per cent of organizations citing it as a motivator for deploying AI in 2022. But two other factors are also fuelling AI uptake: its greater availability and ‘useability’:

• 43% cite advancements in AI that make it more accessible
• 37% cite the increasing amount of AI embedded into standard off-the-shelf business apps
• 45% say AI is now better designed to fit the needs of businesses than three years ago
• 41% say AI is now more accessible and easier to deploy than three years ago

It’s clear that vendors have heeded the call to make AI easier to procure and use, and businesses are buying into the technology as a result.

Business benefits

What benefits are businesses getting from their AI tools? Here are their top three answers:

• 54% - cost savings and efficiencies
• 53% - improvements in IT or network performance
• 48% - better customer experience

What really stands out in this study, however, is that organizations are harnessing AI as a tool to cope with the global skills shortage. Paradoxically, AI emerges from this research as both an aggravator of the skills shortage and a partial elixir for it.

When asked to name the biggest barriers to AI adoption, 34 per cent of organizations said “limited AI skills, expertise or knowledge,” making it the top answer. At the same time, AI appears to be playing a crucial role in helping them deal with the overall shortage of skilled labour, even in non-IT parts of their operations:

• 30% say AI helps their employees save time by automating repetitive tasks
• 27% use automation “to address the skills gap”
• 39% say automation is helping them “mitigate labour and skills shortages”
• 23% use AI to “address labour or staffing shortages”

Democratization of AI

AI isn’t just for data scientists anymore.

Although the top two user groups of AI within organizations are still IT professionals (54 per cent) and data engineers (35 per cent), AI has made its way directly into the hands of non-IT users across various lines of business, including:

• customer service professionals (25%)
• marketing professionals (23%)
• product managers (21%)
• sales professionals (21%)
• HR professionals (21%)
• finance professionals (21%)

Cloud and data architecture

The way a company architects its IT for cloud and data is a strong indicator of its AI uptake.

“Companies that have deployed AI are 59 per cent more likely to be using a hybrid cloud or multi-cloud environment than those that have not,” the IBM study states.

By comparison, only eight per cent of organizations who describe their cloud environment as “on-premises” have adopted AI thus far.

There’s also a correlation between sophisticated data architecture and AI adoption. Companies that have deployed AI are nearly three times (283 per cent) more likely to be using a data fabric system than those that have not.

“Companies currently deploying AI are more likely to report their company is using a mix of data and cloud environments that allow them to access their data and run their models whenever they need to,” the IBM study reports. “Companies that have deployed AI are 65 per cent more likely to be using a mix of architectures, including databases, data lakes, data warehouses and data lakehouses compared to those that have not.”

Responsible AI

While most organizations have embarked on some sort of path to deploy AI and derive business value from it, they’re still wrestling with how to ensure they’re using the technology ethically and responsibly:

• 74% are not taking steps to reduce unintended bias
• 60% are not developing ethical AI practices

But what constitutes ethical, responsible AI? No one has defined that yet, at least when it comes to creating some sort of global standards. In IBM’s study, more than half of organizations (56 per cent) said the lack of regulatory guidance from governments or industries is a major barrier “when it comes to developing AI that’s explainable and trustworthy.”

AI is now more widespread, accessible, user friendly and business oriented than ever before. As artificial intelligence becomes more woven into businesses, however, the biggest issue to tackle may turn out to be the nuances of humanity rather than the precision of technology.

Image: miakievy/iStock

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Much has been said (and written) about the future of work, particularly around the technology and tools required to support hybrid workplaces. But a critical component in building a resilient workforce is attracting and retaining top technology talent during an IT skills shortage.

The labour market significantly tightened up in 2020 and 2021, particularly in IT. Perhaps more alarming, a  global Gartner survey found that only 29.1% of IT workers have “high intent” to stay with their current employer.

Whether you call it The Great Resignation, The Great Rotation or The Big Quit, it’s trend that’s causing many organizations to perform what Gartner is dubbing The Great Reflection. And that means organizations have to evaluate and re-imagine the employment value proposition.

Employment value proposition

“The hyper-competitive talent landscape has exposed those strengths and weaknesses in organizations, whether it be attractiveness of the culture, the strength of purpose in quality of managers or desirability of the new work models coming out of the pandemic,” said Rob O'Donohue, senior director analyst, during a Gartner webinar.

While compensation is the No. 1 factor for both attraction and attrition, Gartner’s research data shows that not far behind is work-life harmonization, as well as job stability and future career development opportunities.

While it’s important for CIOs to benchmark their compensation plans to understand if they’re on par with the market, they should also reflect on those other factors—particularly since they could serve as differentiators in a competitive marketplace.

When it comes to retention, compensation continues to be the top reason why employees stay. But No. 2 is manager quality.

“Then you have respect, recognition, future development opportunities—all of them tying back to the quality of the manager,” said Mbula Schoen, senior director analyst with Gartner, during the webinar.

“Which means as we look at our talent strategy, we also need to take two steps back and understand (that) we probably need to upskill and reskill our people managers so that they have the skills, the competencies, the tools to deal with a dramatically changed workforce.”

A human-centric approach

That takes on added importance in remote and hybrid work environments where a greater degree of trust is required on both sides.

Gartner recommends a human-centric work model that includes:

• Working hours: empowering people and teams to decide when they do their best work
• Office centricity: recognizing employees can be fully productive remotely, while the office is best suited for collaboration
• Meetings: using asynchronous and synchronous collaboration tools for decision making, collaboration and creativity

Aside from providing flexible work experiences, Gartner also recommends building organizational resilience through a “blended workforce of full-time equivalents.”

That could include private talent pools who have an established relationship with your organization, partner organizations and public talent pools such as freelancer marketplaces and talent exchanges.

Perhaps it should come as no surprise that The Great Resignation would be followed by The Great Reflection. So when considering strategies around the future of work, keep in mind that those who lead the pack will be those who have taken the time to reflect.

Images: jeffbergen/iStock

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Now that summer vacay is sadly over, let’s turn our attention to a less enjoyable form of downtime.

As we reported earlier this year, data centre outages are becoming more frequent and costing businesses more money. In 2021, more than a quarter (26 per cent) of all outages were suffered by large public cloud providers. Aren’t these kinds of unfortunate events covered by SLAs?

Yes … and no.

Under most public cloud provider SLAs, “compensation is offered in service credits, not cash,” according to a report by Owen Rogers, director of cloud computing research at Uptime. “SLA compensation is poor and is highly unlikely to cover the business impacts that result from downtime,” he added.

In a subsequent blog post, Rogers pointed out that the process of seeking SLA compensation after a public cloud outage can be cumbersome for businesses in the midst of trying to keep the proverbial lights on during a downtime incident.

“When a (cloud) failure occurs, the user is responsible for measuring downtime and requesting compensation; this is not provided automatically. Users usually need to raise a report request with service logs to show proof of the outage … These approaches mean that users must detect an outage and apply for a service credit … which is unlikely to cover the cost of the outage,” Rogers wrote.

Rogers also gave a hypothetical breakdown of how much compensation a business would receive based on the actual SLA terms offered by one of the world’s biggest cloud providers.

Under that provider’s 99 per cent uptime SLA, “if a single virtual machine goes down for less than seven hours and 18 minutes” in one month, the cloud provider’s “total compensation for this outage would be 30 cents,” Rogers wrote. “If a virtual machine goes down for less than 36 hours” in a month, he added, the provider’s compensation would be “just under $1.”

For many businesses, $1 in compensation for the financial and reputational losses suffered during a 35-hour outage may not cut it. As Neta Rozy succinctly stated in an interview with Protocol.com, cloud providers “only give you credit for the service you didn’t receive.”

To address the gap between downtime-related business losses and SLA compensation levels, Rozy co-founded a startup called Parametrix to offer cloud downtime insurance.

Downtime insurance

Businesses can buy insurance policies to cover losses they suffer due to downtime at their cloud provider. Those losses can include lost revenue, lost employee productivity, reputational damage and even the domino effect damage of losses suffered by their own customers.

Parametrix has a proprietary system that monitors downtime incidents at cloud providers like AWS, Azure, Google Cloud and Oracle Cloud, plus major cloud-based services like Salesforce, Cloudflare and Shopify. When Parametrix detects downtime at one of those providers, its system automatically notifies policyholders so they can activate an insurance claim.

Parametrix coverage kicks in just one hour after a policyholder is affected by a cloud outage, which is a much shorter period than the window of time required to activate most cyberinsurance policies.

Cost-effective cloud resilience

There’s another way businesses can try to limit their losses after a cloud provider outage. According to Rogers’s report, they can add resiliency to their own cloud and application architecture in the most cost-effective way possible.

To help organizations do that, Rogers examined seven methods of boosting resiliency in IT architectures to protect against cloud provider outages. He evaluated the cost-effectiveness of each method based mainly on:

• how much extra resilience it adds
• the cost (borne by the cloud service customer) of adding that extra resilience
• how much compensation the cloud service customer would receive from a provider’s SLA in the event of an outage

Based on Rogers’s findings, the most cost-effective steps businesses can take to make their architecture more resilient to public cloud outages are:

• distributing workloads across multiple availability zones vs. just one zone
• setting up failover to a backup region using a pre-enabled DNS service

The most salient points of Rogers’s research, however, have as much to do with responsibility as they do with resilience.

The study reminds public cloud users that it’s their responsibility to detect and track an outage suffered by their provider. With most SLAs offering little compensation, it’s also the responsibility of cloud customers to cover the financial losses their business suffers when downtime hits their cloud provider.

Architecting some extra IT resilience might save a business more headaches (and money) than any SLA.

Images: piranka/iStock

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Ten years later, I still remember reading Tom Davenport’s argument that data scientists had the hottest job on the planet.

It’s tough to forget an article with a juicy title like Data Scientist: The Sexiest Job of the 21^st Century. I wasn’t the only person it made an impression on. Since its 2012 publication in the Harvard Business Review, the research study has racked up more than 1,600 citations in other scholarly journals.

Davenport is the prolific author of 17 books, co-founder of the International Institute for Analytics, a fellow at MIT and an originator of the term “attention economy.” He co-authored that 2012 HBR study with DJ Patil, who was later appointed by former U.S. president Obama as the White House’s first-ever chief data scientist.

To mark the tenth anniversary of their original paper, the pair recently penned a sequel for HBR titled (what else?) Is Data Scientist Still the Sexiest Job of the 21^st Century?

I interviewed Davenport to get his take on how the role of data scientist has evolved over the past decade, how effectively businesses use data today vs. in 2012, and how far we’ve come in addressing the data skills shortage.

Looking back

When Davenport and Patil wrote that landmark 2012 research paper, the word “sexiest” did not appear anywhere in their original title.

“I think it was an editor’s idea, although I think we did have to sign off on it,” Davenport tells me.

Davenport and Patil’s 2012 article did describe the occupation of data scientist as sexy, however, in terms of “having rare qualities that are much in demand … difficult and expensive to hire and … difficult to retain.” They defined data scientists as professionals who “bring structure to large quantities of formless data and make analysis possible,” then “communicate what they’ve learned and suggest its implications for new business directions.”

That same think piece raised early warning flags about challenges that were already percolating in the nascent world of enterprise data science, including:

• data overload: “Companies are now wrestling with information that comes in varieties and volumes never encountered before”
• skills and talent shortage: “… demand has raced ahead of supply”
• soaring pay: “… salaries will be bid upward”
• no standardization of skills and education: “There are no university programs offering degrees in data science”

Another observation they made was that businesses were grappling with how to best utilize data scientists to their advantage.

“There is little consensus on where the role (of data scientist) fits in an organization, how data scientists can add the most value, and how their performance should be measured,” Davenport and Patil wrote a decade ago.

They also predicted that instead of coding skills, tomorrow’s data scientists would need to acquire soft skills to “communicate in language that all their stakeholders understand” and forge “close relationships with the rest of the business.”

What’s changed

In the 2022 sequel to their 2012 article, Davenport and Patil acknowledge some things haven’t changed at all. The high demand for data expertise. The tight supply of skills. The soaring salary levels.

And according to new Gartner research, extracting business value from data remains a thorny issue today. Per Gartner, barely half of AI pilot projects at enterprises make it to production these days, and “organizations still struggle to connect the algorithms they are building to a business proposition.”

In their new HBR piece, Davenport and Patil assert that a decade on from their original study, “many organizations don’t have data-driven cultures and don’t take advantage of the insights provided by data scientists.”

But why?

“Cultural change of any type always takes a long time,” Davenport tells me. “It’s happening, but it’s a lot slower than some people might have predicted.”

One thing that’s vastly different from 2012, he says, is the current focus on data ethics, a phenomenon he believes was sparked by the Cambridge Analytica/Facebook scandal.

“The social and political divisiveness (around) social media and the analytics of AI that drive like-minded people toward each other and send them the kinds of news that only supports their point of view, I don’t think anybody really anticipated how likely that was to happen.”

As the fallout continues, Davenport anticipates more government regulation of data use and AI, although he expects Europe to enact legislation long before the U.S.

Another big shift he’s noticed over the past decade? Companies have stopped trying to find all the data science expertise they need in one elusive “unicorn” candidate. Instead, they’re looking for a wider range of skills from a wider breadth of fields. He says today’s enterprises are creating multiple data-related roles within their organizations, including “translators and people who are working closely with the business to understand their needs.”

“The key to value is deploying (algorithms) within the business and that takes a whole broad range of skills,” he adds.

In 2022, just as in 2012, there’s still no universally recognized system of education, skills and certification for data-based professions. Davenport feels that more standardization would help businesses hire—and internally cultivate—crucial data talent.

“I think ultimately that would be good. The times and the world sort of change faster than the certification processes do, but I think it would help a lot of organizations to have more standard classifications.”

The future of data

What does Davenport expect to see in analytics 10 years from now? He predicts machine learning will become even more automated than it is today, freeing up data scientists to focus less on building ML models and more on tackling business problems.

He says a type of “business/technology hybrid” worker is already emerging in enterprise organizations, a trend that could one day produce more data/business chameleons than data science unicorns.

“These people understand the technology, they’ve been working with it for a long time, but they apply it to solving business problems,” he explains.

Before I bid Davenport goodbye, he offers a parting thought on the future of my own profession in this age of GPT-3, the AI-based program whose writing output (a movie screenplay and an academic research paper) has already outpaced mine.

“There are some journalism things that have already been somewhat automated but not feature stories of the kind that you write,” he grins. “So you’re probably safe for a while.”

Images: metamorworks/iStock; gremlin/iStock

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While we may not have missed queuing in airports and the hassle of travel, most of us have been missing in-person events—from networking with our peers to the energy of live keynotes.

Fortunately, many trade shows, conferences and events that were cancelled, postponed or moved entirely online since the start of the pandemic are back (or have plans to be back) in fall 2022—giving us a chance to reconnect with our peers, hear the latest thought leadership and discover cutting-edge technological innovations.

But for those who can’t travel—and those who prefer remote options—there are still hybrid events to look forward to. Here’s a sampling of what’s planned for the fall:

September

Big Data Expo
Sept. 14-15
Utrecht, The Netherlands
[in-person]
This event is dedicated to all aspects of data management—from collecting, generating and analyzing big data to rendering, optimizing and applying data.

IoT World
Sept. 28-29
Santa Clara, California
[in-person]
This year’s conference offers a jam-packed headline stage, a curated collection of vertical and technology-specific stages, and a free-to-explore technology showcase.

Mobile World Congress Americas
Sept. 28-30
Las Vegas
[in-person]
Decision-makers from across all sectors will learn how to navigate the transition from physical to digital, with summits and workshops from more than 200 industry experts.

SpiceWorld 2022
Sept. 28-30
Austin, Texas
[hybrid]
The must-attend conference for IT pros features three days packed with tech know-how, networking with peers and the latest IT products and solutions. 

October

Global Software Architecture Summit
Oct. 3-4
Barcelona, Spain
[in-person]
Software architecture experts from all over the world will come together at this two-day summit to learn about essential practices, innovation, working software and practical solutions.

Microsoft Ignite
Oct. 12-14
Seattle
[hybrid]
Explore the latest innovations, learn from product experts and partners, level up your skill sets, and create connections from around the world at this signature event.

Gartner IT Symposium/Xpo
Oct. 17-20
Orlando
[in-person]
This conference will explore the future direction of technology, best practices to define and validate IT strategies and real-world examples on how to execute on key initiatives.

DevOps Enterprise Summit
Oct. 18-20
Las Vegas
[in-person]
This summit is designed for technology and business leaders who are transforming the way large, complex organizations deliver software and implement DevOps principles and practices. 

RE•WORK Toronto AI Summit
Oct. 19-20
Toronto
[in-person]
This event brings together a unique mix of academia and industry to showcase AI pioneers at the forefront of research, as well as real-world case studies.

November

ODSC West
Nov. 1-3
San Francisco
[in-person]
Develop your skills with 50+ live hands-on virtual workshops and training sessions, and network with 6000+ data scientists to exchange ideas and collaborate.

Web Summit 2022
Nov. 1-4
Lisbon
[in-person]
This premiere tech event gather CEOs of technology companies, fast-growing startups, policymakers and heads of state to ask a simple question: Where to next?

Quantum World Congress
Nov. 29-Dec. 1
Washington, DC
[in-person]
The first-ever gathering of its kind will connect the world’s quantum ecosystem to accelerate the value of the growing quantum industry.

December

5G Expo Global
Dec. 1
London, UK
[in-person]
This Expo will showcase cutting-edge technologies from 125+ exhibitors and provide insight from 100+ speakers sharing their industry knowledge and real-life experiences.

Black Hat Europe
Dec. 5-8
London, UK
[in-person]
This cybersecurity event provides the security community with the latest cutting-edge research, developments and trends.

Image: gorodenkoff/iStock

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The telecommunications industry isn’t exactly renowned for stellar customer service. Customers have become accustomed to waiting on hold, just to talk to an entry-level call center employee who often isn’t empowered to properly resolve customer issues and complaints. Which means waiting yet again to speak with a manager.

As a result, many customers have low expectations from their telco and see it as more of a utility. Many don’t feel they’re important or relevant to the service provider; they feel like a number. As a result, they don’t feel particularly loyal to that telco, nor are they likely to recommend it to others.

What Allstream does differently

Allstream has made incremental improvements over the past three years, such as allocating more resources to the right areas, speeding up response and turnaround times, and adjusting to ensure they meet customers’ expectations, product- and service-wise.

Every customer response is shared with the entire company—from frontline team members to the president. And all negative responses are assigned to an “owner,” who will contact the customer and find a solution to the issue whenever possible.

This also helps to continually improve customer service, deliver an exceptional customer experience and promote customer advocacy throughout the organization.

What’s NPS and why should you care?

How do we know we’re doing a good job delivering on the customer experience? We use an industry standard metric called NPS (Net Promoter Score), which measures customer loyalty to a particular product, service or brand, based on how likely a customer is to recommend that product, service or brand.

It’s similar to the star ratings you find on Yelp for restaurants or retailers. But instead of stars, it’s a score based on a scale of -100 to +100, so it’s entirely possible to get a negative score! In fact, in our industry, a negative score is fairly common.

For telcos, it’s widely understood that a score of 0 is typical. It’s a neutral score—for every customer that likes you, another doesn’t. All telcos have a score, so it’s an easy way for customers to compare which company offers the best service. But in this industry, 0 or negative scores are standard.

Why NPS matters to Allstream

Allstream, however, has turned that upside-down. Three years ago, we set out to become a more customer-focused organization, aiming for a score of +10. This year we’ve received a score of +32, which in our industry is a huge deal.

NPS matters because our customers matter. While we’ve made tremendous progress in serving our customers, we are committed to continuously improving and evolving with our customers in this hyper-competitive environment.

We’re not done yet. When it comes to customer service, there’s no ‘finish line.’ We’ll keep working toward getting even better results. And we’ll constantly strive to maintain and improve our NPS as part of our commitment to ensuring we keep the customer front and center of our business model.

Find out more about what customer service means to us in our Q&A with a customer service manager at Allstream.

Image: PeopleImages/iStock

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The honeymoon period may be over for hybrid work, or at least the model most organizations have deployed so far.

A new poll of 2,000 office workers in the U.S, Australia and Europe suggests organizations are still grappling with how to deploy technology for hybrid work:

• 27% of workers say businesses aren’t investing in the right collaboration tools
• 25% say collaboration tools have “poor functionality”
• 22% say they aren’t using the tools at their disposal
• 21% say they haven’t been trained to use the tools
• 39% want collaboration tools that enable multiple team members to seamlessly work on the same project at the same time
• 32% favour collaboration tools that allow them to work and collaborate on any device

According to Gartner VP and analyst Adam Preset, enterprises must address this situation by realizing hybrid work is about much more than just remote work technology.

Shift in thinking

“We no longer necessarily think about work as somewhere we go, because we know we can do that from anywhere,” Preset said in a  webinar presentation of Gartner’s latest research on hybrid work.

He argued the evolution of hybrid work will require an even bigger philosophical shift by employers: from designing a work space to designing a work experience.

Since work is no longer defined by physical location, designing the ‘perfect’ office setup isn’t gonna cut it. Enterprises must now design a work experience that works for all employees in their organization, no matter where, when or how they do their jobs.

Here are the key things Preset urged enterprises to keep in mind when designing a hybrid work experience for their organizations.

EX is everything

Although the Great Resignation has made hiring and retaining workers extremely challenging, Preset said the upside is that it’s forcing organizations to focus on EX instead of just CX.

“It’s called Total Experience,” he explained. “It interlinks customer experience, the customer user experience, employee user experience and, ultimately, employee experience as well. More engaged, more satisfied employees create better experiences for customers.”

So, to provide great CX, you must first provide great EX. Preset said the key to great EX is designing an excellent hybrid work experience. That design inevitably includes technology. According to Preset, “technology is the touchpoint for employee experience.”

He listed a plethora of technologies as essential tools for crafting a hybrid work experience, including:

• visual collaboration
• collaborative work management
• desktop-as-a-service
• digital EX monitoring
• hybrid meeting solutions

He emphasized, however, that designing an exceptional hybrid work experience requires thinking beyond remote tech tools.

Hybrid isn’t just WFH

For one thing, Preset wants organizations to stop thinking of hybrid as merely ‘working in the office’ and ‘working from home.’ His spheres of hybrid work include:

• office work
• home office work
• mobile work
• frontline work

Organizations must re-examine how employees do their jobs in these different spheres and how their needs change across all of them, he said. For example, he believes frontline workers have been particularly underserved by hybrid work technology thus far.

“For frontline workers, maybe redesigning (work experiences) for hybrid means having a new look at these generalized collaboration tools that we typically give to workers in offices, and recognizing that they haven’t extended as much as we needed to match the new unique needs of the frontline.”

Hubs for harmony

Preset recommends breaking down your organization even further into hubs such as:

• employee engagement hub
• employee services hub
• technology services hub
• business role hubs (sales, HR, finance, supply chain, legal, etc.)

Preset said technologies like automation, analytics, AI and software development definitely play key roles in “harmonizing the digital employee experience” across all of these hubs.

His overriding point, however, is that technology is part of an integrated, holistic strategy that assesses the roles and needs of workers and managers in all departments to create an ideal hybrid work experience for each person, regardless of their location.

“One of the challenges we’ve seen up until this point,” Preset reflected, “has been around the dropping of the technology on workers and then hoping that they just do the right thing with it, without well-defined change management, without sharing best practices, without learning best practices from others who have gone down that hard path, and then learning that well enough to transmit it to others.”

Read more:

How UCaaS will empower the future of work
Future of work webinar: The Great Retention
Tips for a successful transition to hybrid work

Experiment with design

Designing a hybrid work experience requires experimentation, according to Preset. His advice:

• put intention, influence and investment (i.e., budget dollars) into designing your hybrid work experience
• assess your staff’s hybrid work pain points (office, home, mobile, frontline)
• pick one area of friction and experiment with new technology tools that might ease it
• collect data and feedback on the results
• continue the cycle of assessing, experimenting and implementing as your workforce changes

“Just turning on the technology is not enough,” Preset said. “It’s a question of implementation now. What I mean by this is that we’re asking you to move from just turning on the technology to designing an experience.”

Images: miniseries/iStock; FreshSplash/iStock

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The first thing that catches your attention when reading EMA’s Network Management Megatrends 2022 report—a biennial study the research firm has been producing since 2008—are the words: “Network Operations: Red Alert.”

Over the years, Enterprise Management Associates (EMA) has been benchmarking networking trends large and small, from cloud to IoT. But this year, the report is more ominous.

“EMA sees an alarming warning sign. The effectiveness of network operations teams is declining,” reads the report, with data showing a precipitous decline in the number of respondents who believe their network operations groups are completely successful—from 49 per cent in 2016 to a mere 27 per cent in 2022.

So what’s going on?

Based on survey results from more than 400 IT organizations in North America and Europe, EMA found that a double-whammy of network data quality and a shortage of skilled IT personnel are the biggest challenges to NetOps.

Some of the key findings from the report include:

• 31% of all IT service problems are reactive (caught by users, not NetOps)
• only 34% of alerts from network monitoring tools are actionable
• only 5% of IT organizations find it easy to hire and retain networking personnel

How NetOps is changing

EMA’s report indicates a fundamental shift in NetOps strategies. Back in 2008, the focus was on server virtualization. This year, virtualization ranks No. 14 on the list, with public cloud, SaaS applications and cloud-native application architectures now the most critical drivers of their enterprise networking strategies.

Almost all enterprises in the survey (nearly 99 per cent) have adopted public cloud, with 72 per cent moving into a multi-cloud strategy using at least two Infrastructure-as-a-Service (IaaS) providers. The shift to multi-cloud combined with the work-from-anywhere model means that data centre modernization is an increasingly urgent priority.

And this year, WAN transformation “now dominates the enterprise networking world,” with enterprises prioritizing network performance management tools, network automation and data centre SDN.

EMA found that larger enterprises are also more likely to invest in private 5G and Wi-Fi 6/6E. But across the board IoT is driving investments in network security, network performance monitoring and network automation.

New problems for a new era

NetOps teams are struggling because of increased complexity in IT infrastructure and services. While most companies are now multi-cloud—which introduces a host of complexity into their environment—only 18 per cent of respondents believe they are effective at cloud monitoring with network tools.

In part, this could be due to network management tool sprawl. The more tools, the more problems caused by manual errors—and EMA says most network teams use anywhere from four to 15 tools. One anonymous IT operations manager quoted in the report says their organization is using close to 20 tools from six to eight vendors.

Add to that the skills shortage, and it’s even more of a struggle—particularly for small and mid-sized enterprises. Respondents indicate they’re especially struggling to hire people with network security, network automation and network monitoring skills.

The good news

While this all sounds very dire, finding solutions means recognizing where the issues stem from. For example, hybrid work is here to stay, as is multi-cloud. It’s also likely that we’ll be facing an IT skills shortage for years to come. Areas where technology can be consolidated or even automated can help mitigate complexity and lack of IT resources.

“EMA research has often found that an effective network management toolset will make network operations teams more efficient and effective. To some degree, improved efficiency should help mitigate shortages in skilled networking personnel,” says the report.

There are other solutions, too. The EMA report indicates that NetOps teams are starting to collaborate with DevOps and, in some cases, fully integrating—which could help in areas like security policies, application optimization and network capacity planning. While this is easier said than done, collaboration could erase silos and create efficiencies.

Read more:

Transforming the network: SD-WAN and SASE
Will SD-WAN replace MPLS for hybrid work?
Build out your network with a ‘lit’ building

While the challenges are immense, they’re not going away. End-to-end network visibility is critical—from multi-cloud, SaaS and edge services, through to home wireless—to transform NetOps in the era of multi-cloud and work-from-anywhere.

Images: Maxiphoto

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The pandemic-fuelled boom in enterprise cloud adoption is still going gangbusters.

In its latest forecast, Gartner expects worldwide end-user spending on public cloud services to reach $494.7 billion this year (a significant increase of 20 per cent from 2021) and nearly $600 billion next year.

Gartner vice-president Paul Delory recently offered up a glimpse of the hot-button issues organizations may encounter as they boost their cloud budgets. Here are highlights from Delory’s webinar presentation on the top six trends in enterprise cloud.

1. Cloud teams will optimize for business outcomes, not technical implementation.

Delory said that while business value has always been the primary goal of cloud deployment, “in talking to clients, I do think a lot of them have lost sight of that.”

He issued a gentle reminder to cloud teams: focus on business outcomes to avoid getting swept away by the undertow of complicated IT minutiae.

“You can’t be a gatekeeper. Remember, your end-users are trying to create business value. They’re trying to innovate, they’re trying to do new things. You don’t want to get in the way of that.”

Here are some steps Delory suggested to ensure your cloud strategy stays aligned with business goals:

• map CIO-level priorities to cloud architecture initiatives
• build a reusable cloud adoption framework to onboard new services quickly with best practices learned over time
• create cloud advisory councils spanning IT and business
• set up cloud communities of practice (“clubs” of non-IT employees interested in cloud)

Delory said cloud advisory councils and cloud communities of practice help “make sure that users have a voice, (so) we as engineers are building what the users need.” 

2. Hybrid and multi-cloud adoption will increase operational complexity and cost.

“Multi-cloud is hard,” Delory acknowledged. “(It’s) making your architecture more complex and expensive.”

Delory pointed out that expanding beyond a single cloud also complicates matters such as data management and governance, data dispersion, IT integration, cybersecurity, asset tracking, vendor relationships and employee skill requirements.

“Multi-cloud means a lot of changes for people, policy and process(es) as well,” he said.

Here are Delory’s tips for managing the cost and complexity of hybrid and multi-cloud environments:

• prioritize a primary strategic cloud provider
• only add a second cloud provider when you have business needs that can’t be met by your primary provider
• place workloads based mainly on their integration and data affinities

3. Business resilience will be built into the application architecture.

Two factors are driving this push for more resilient IT architecture, according to Delory: ransomware and the rise of cloud-native apps.

To recover from ransomware, he suggested building “an immutable data vault” that is read-only and completely separate from production, development and testing. He said this area can act as “a secure, isolated recovery environment … where you can restore your data, where there’s no chance it can get re-infected.”

Similarly, he said, “cloud-native applications really need to be treated differently (than traditional apps) when it comes to backup and data recovery.”

There’s a movement afoot to design systems “where replication, redundancy, performance (and) management, those are features of the application code itself (so) we’re not needing to bolt that on at the infrastructure layer,” Delory said.

Delory’s recommendations for enterprise cloud IT resilience:

• start by building resilience into cloud-native applications
• prioritize ransomware defence and recovery, especially in secure, isolated recovery environments
• create KPIs/metrics for IT resilience

4. Distributed cloud will displace private and hybrid cloud initiatives.

Delory defined distributed cloud as “public cloud services that are running outside the provider,” either inside your data center (wait, what?) or pushed out to the edge.

“Essentially, you have a substation of a cloud provider in your data center. You’re going to have a little baby Azure, for example, that runs in your data center and is running the actual cloud provider services on-prem. It’s on-prem infrastructure but it’s tethered to a cloud provider in some way,” Delory said.

In what type of scenario would an enterprise deploy distributed cloud?

“If you have a workload that can’t move to public cloud but you still want cloud services,” he said. “AWS, Microsoft or Google, they’ve already built the (public cloud) service. Now they’re going to give you some hardware and a way to run the service on-prem. (Their) sales pitch is don’t try to build a private cloud, you can buy it from us.”

Delory’s suggestions for adopting this distributed cloud model:

• evaluate distributed cloud substations offered by major cloud providers
• compare these to hyperconverged infrastructure (HCI) products from major data centre vendors
• replace “homebrew” private and hybrid clouds with distributed cloud offerings and/or HCI

5. Containers and serverless will become a foundation for application platforms.

Delory clarified right away that it’s not really serverless technology, but more like containers-as-a-service (CaaS). In a nutshell, the cloud manages your servers so you don’t have to. As an example, he said Kubernetes could be used to orchestrate containers, making workloads portable and enabling them to work with hybrid or multi-cloud architectures.

“The idea behind a serverless container architecture is that you package up whatever code you want to run in a container, then you just feed it into this platform and that container just runs. You don’t need to worry about setting up the underlying infrastructure; you don’t manage that. This is something that the cloud provider can take care of for you,” Delory said.

Some of Gartner’s tips for CaaS and serverless architecture:

• optimize apps for cloud-native architectures, including CaaS and serverless
• introduce serverless container architectures into DevOps workflows, then expand other use cases from there
• use public cloud Kubernetes and CaaS services unless you have specific compliance or functional requirements they can’t meet

Read more:

6 best practices to ensure a smooth CCaaS migration
UC drives future growth of PBX market
Introducing Allstream’s Cloud Connect service for AWS

6. The crisis-level skills gap will compromise cloud innovation.

“I really do think this is a crisis,” Delory emphasized. “(The skills gap) is a barrier in a lot of cases to going cloud-native. It’s not the tools, it’s that you don’t have the people who know how to use the tools.”

His suggestions for coping with the skills shortage:

• budget time and money for staff to learn new skills
• use skills growth as a KPI for teams and individuals
• tie skills growth into each employee’s annual review and bonus pay
• prioritize Kubernetes and DevOps skills

Images: Maria Stavreva/iStock; IftodeIulian/iStock

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