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The State of the Union for IoT Intelligence

A digital transformation revolution in manufacturing is underway, and data is the primary currency paving the way for more efficient ways of doing business.

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By Frank Antonysamy

Frank Antonysamy is Vice President of Cognizant’s Global IoT and Engineering Services

A digital transformation revolution in manufacturing is underway, and data is the primary currency paving the way for more efficient ways of doing business. Gone are the days when data analysis was left to Monday night quarterbacking by poring over static results. Today, thanks to a central wireless ecosystem which links relevant mobile devices, Internet of Things (IoT) connected machines and connected employees, data gathering and analysis in a smart factory is immediate and real-time optimization drives significant efficiencies.

But not all smart factories are created equal.

Given that enterprises are all on different points on the path to complete digital maturity, it helps to take stock of the state of IoT intelligence — where we are now and where we are headed — and what industrial organizations need to be successful.

Laying the foundation for intelligence

One of the key advantages of Industry 4.0 is the promise of the Internet of Things (IoT) or Industrial Internet of Things (IIoT). Sensors connected to raw materials, factory floor equipment and final products can relay information, over a Wi-Fi connection, about their health and usage patterns to wider enterprise asset management software and enterprise resource planning systems.

Equally important, stakeholders can access this data in real-time and on-demand. Companies can leverage this data to deliver insights across three channels:

  • Product intelligence
  • Service intelligence
  • Operational intelligence

There is significant overlap across these three pillars but their power to deliver a smart factory with new avenues for monetization, is revolutionary.

Here’s an overview of the IoT landscape with respect to its three core pillars of intelligence.

Case Study: Fast-tracking innovation with a PLM platform

Product intelligence shakes up traditional PLM

The smart factory runs on smart products whose intelligence can be leveraged to read the tea leaves of market demand. At its core, product intelligence is defined as intelligence derived from an intelligent (read…IoT-enabled) product. In the IoT world, traditional rules of product lifecycle management (PLM) no longer apply. Gone are the rinse-and-repeat cycles of concept, design, manufacture, marketing and sales. In traditional manufacturing, the ideation-sale stage took years if not decades and slight changes in market demand had a whiplash effect on the process.

IoT has rebooted the PLM conversation to move it away from the product and make it more about the customer. IoT-enabled products can now deliver intelligence post sales about how the product is being used (or not), how it is being disposed of, and a whole host of other downstream information. Such product intelligence is useful in two primary ways: as a method of refining the product to make it more agile and responsive to consumer needs (thereby leading to potentially more sales) and as new avenues of monetizing such product intelligence.

The future of product intelligence is a complete “closed-loop” product development, with real-time customer feedback woven into the process. It bears stressing that while customer focus groups and behaviors have always been part of the design and manufacture process, IoT has effectively compressed that time cycle and expanded the scale of parameters that might be considered — and monetized.

Service intelligence delivers customer-focused monetization

Monetization in the new smart factory landscape need not be restricted to product intelligence alone. Service intelligence, for example, is about delivering aftermarket intelligence in the form of added services to an existing or expanding customer base. A customer who buys Widget A from a manufacturing company might also be interested in understanding how to optimize the use of that widget for their own tailored environments.

[Download]: Designing Manufacturing’s Digital Future

While aftermarket services are not entirely new, the addition of IoT has the capability of delivering service intelligence on steroids. In the future, service intelligence providers will use IoT to tailor measurements of key performance indicators (KPIs) and delivery of data insights depending on exactly what the end customer is looking for. Tailoring service intelligence to the customer potentially leads to greater client stickiness. What’s more, IoT is capable of slicing and dicing intelligence for each and every customer, making the net results that much more insightful and leading to more bountiful monetization opportunities.

Operations intelligence squeezes the most out of machines

Monetization also comes from picking the low-hanging fruit in production processes. Arguably one of the best ways to squeeze the most out of IoT is to use it to increase manufacturing uptime. IoT is also favorably impacting the ability to fine-tune production processes by being able to connect, visualize and analyze data from a whole host of new players such as machines on the plant floor. RFID and computer vision layers also add to such intelligence.

IoT-embedded devices on the plant floor can spit out data that measures machine health, which can be fed into machine learning algorithms for predictive maintenance. If a rotor heats up past a preset temperature setting, for example, it can trigger the algorithm to send an alert to a plant worker or even proactively shut the machine down. Machine learning capabilities derived from IoT enhance KPIs such as manufacturing uptime.

[Download]: Creating a Digital PLM Platform to Promote Collaboration and Increase Efficiency

In the future, expect a move toward increasingly segmented manufacturing, possibly sliced and diced into ever smaller batches. Operations intelligence will allow manufacturers to segment the production process — and fine-tune each — to fulfill a variety of specialty orders at the same time.

What it takes to deliver on the promise of IoT

While IoT intelligence in its various forms promises a truly smart factory with a wealth of monetization opportunities, it needs a robust infrastructure to truly deliver. Elements of this winning infrastructure include, among others: a C-suite willing to address negative attitudes of incumbency; standardization of data aggregation and analytics processes such as machine learning; and future-proofing technologies through increasing reliance on open-source models.

Since data is the lifeblood of IoT, enterprises need to ensure that they don’t get mired in the data lake — that the data they’re working with is clean and structured, relevant to the KPIs they want measured, and fed to algorithms in a consistent format. Once data is clean and uniform, smart factories can leverage IoT to feed machine learning algorithms that learn from the data and eventually deliver an almost lights-out production stream.

Since the future of intelligence also involves its monetization — vendors up and down the digital supply network will pay for insights — it will be important to connect stakeholders to the central nervous system of the smart factory in new ways. Customer service agents (or even customers themselves) for example should be able to see where product orders are in the production process and fine-tune their forecasts accordingly. IoT delivers transparency to all stakeholders — within reason, keeping intellectual property concerns in mind.

[Download]: Advancing Smart Manufacturing Operations Value with Industry 4.0

IoT in manufacturing is not limited to the production floor either. IoT sensors in warehouses can detect when supplies are going bad, when inventory is low and beef up accordingly. Remote weather events that can affect vendor delivery can trigger automated backups. The IoT-driven smart factory touches many processes and products much beyond the plant floor.

Until true digitization from start to finish is a total reality, companies are figuring out stop-gap measures that will leverage the promise of IoT. A “nerve center,” which serves as a central repository for data gathering and analytics can serve to overcome the problem of data connectivity across locations and devices.

The ripple effect from IoT intelligence is not limited to the manufacturing floor alone. By placing the digital core at the center, it reshapes processes up and down key constituencies such as supply chain and asset management.

How tomorrow’s tech might impact IoT intelligence

IoT is already being incorporated in the smart factory of today. Tomorrow, expect acceleration with respect to monetizing closed-loop product intelligence, an increased focus on the customer through service intelligence and using operations intelligence by improving businesses processes on the way to a truly smart factory.

The road is expected to get even smoother with the advent of 5G technology which will decrease latency of IoT for edge computing devices. 5G will deliver even faster access to data in real time which will make real-time analysis even more accurate. The technology has special ramifications for production processes where time is of the essence. Devastating machine shutdowns can be averted in split seconds by machine learning algorithms fed through 5G connections from IoT-enabled equipment. This means smart factories of faster computing speeds and greater agility. The state of the union for IoT intelligence is strong and only expected to grow stronger as new technologies such as 5G make data competencies that much more robust.

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The Northern Lights Technology & Innovation Forum navigates AI, economic concerns and upskilling in Alberta

Panelists dive into how innovation and collaboration may help navigate the changing industry landscapes

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While rapid advancements in AI are reshaping industries worldwide, they’ve sparked discussions about innovation and community resilience through ongoing economic challenges. At this year’s Northern Lights Technology and Innovation Forum, panelists explored how technology could drive positive adaptation.

​​Moderated by the Calgary Economic Development’s Geraldine Anderson, the panel featured:

  • Mark Little, co-founder and CEO Jotson Inc, and board member of General Fusion
  • Anna Baird, culture and innovation evangelist at Google
  • Dan Semmens, SVP and head of data and IT at ATB Financial
  • Arthur Kent, Canadian journalist and author
  • Joy Romero, executive advisor innovation at Canadian Natural Resources Limited (CNRL)

Approximately 250 attendees gathered for the forum at the Calgary Petroleum Club on Feb. 8. Filled with industry leaders and burgeoning entrepreneurs, the forum focused on collaboration and knowledge sharing in the tech sector.

Over the past five years, Calgary has seen a 22 per cent increase in tech talent and total tech jobs, emerging as one of North America’s top markets for young tech professionals.

“The talent pool here is amazing,” said ​​John Givens, vice president of sales at C3 AI and one of the event’s organizers. “So how do we leverage our talent here? How do we share that knowledge?”

In response, this year’s forum included the inaugural “Mentors and Makers” initiative, where a dozen industry experts pinned green buttons to their lapels, signaling to anyone in the crowd that they’re open to a conversation.

Shawn Mahoney, another event organizer and co-founder of Spare Parts & Gasoline, said in his opening remarks that the initiative speaks to “creating the new innovators that we need to solve tomorrow’s problems.”

And with that, the panel took the stage to dig into the big questions: What are the challenges and opportunities for Alberta as a growing tech market? How will AI continue to change industries across the board? And if it does, will that be a bad thing?

The Alberta advantage

The panel conversation was kicked off by the first question asked by moderator Geraldine Anderson: “What is the Alberta mindset, or the ‘Alberta advantage?’” 

Mark Little. Photo by DX Journal / Digital Journal

Mark Little, co-founder and CEO Jotson Inc, said Alberta has a lot going for it — including having the highest GDP in Canada, a younger population, and high education levels — but those aren’t the advantages that stand out to him.

“There’s a resilience and an entrepreneurial spirit here,” he said. “As a result of that, we’re seeing innovation … I think 10 to 15 years from now we’re going to lead this country in innovation and it’ll be every sector you could imagine.”

Hailing from Vancouver and the only panelist not based in Calgary, Google’s Anna Baird said she considers herself an honorary Albertan based on the “sheer grittiness and roll up your sleeves and work together” attitude she’s witnessed. 

“The grittiness takes us into innovation,” said Baird. “We’re willing to try new things, we’re willing to fail — hopefully fast and cheaply, as is Google’s ethos. But we’re also willing to borrow with pride and give kudos to the people we’re borrowing the pride from so we can have building blocks.” 

The panelists’ discussion kept coming back to the importance of adaptability, innovation, and collaboration. While the province faces significant hurdles, including global market fluctuations and environmental concerns, they spoke with optimism about the potential to emerge stronger by investing in the future.

Dan Semmens, SVP and head of data and IT at ATB Financial, calls it an “opportunity” for both the province and country to focus on investing in the next generation.

“I think the opportunity there is continuing to invest in our most precious resource, which is our young people,” he said. 

When it comes to AI, “it’s on all of us” to level up our own skills

Joy Romero. Photo by DX Journal / Digital Journal

AI is already impacting most industries globally, and it shows no signs of slowing down. But it’s not new either.

Joy Romero, executive advisor of innovation at Canadian Natural Resources Limited (CNRL), said she was using AI neural networks 20 years ago to take ecological data and process it through oil sands facilities. 

“Why?” she asked. “Because that would allow us to improve our processing and our productivity … So for me, digital is our world. That’s productivity.”

The day of the panel, Google announced that Gemini Ultra 1.0, the largest version of their large language model, is being released to the public. 

Baird was asked about the implications of the new AI model, and while she acknowledged there will be challenges, she maintained that “the train has left the station.”

“It’s on all of us here in the room to level up our own skills,” she says. “With an announcement like Gemini, like you have to get in there, you have to play, you have to try.”

Anna Baird. Photo by DX Journal / Digital Journal

Transitioning to the realm of media and journalism, Canadian journalist Arthur Kent highlighted the increasing role of AI in newsrooms. From assisting journalists in gathering and analyzing data to content creation, journalists are experimenting with AI for efficiency and detecting false information.

“We can become even better if we harness artificial intelligence to do that,” said Kent. “So we constantly have to be developing and pushing ourselves forward, to keep pace with this.”

However, he emphasized the critical role of journalists in maintaining integrity and discerning between fact and fiction in an era of AI-generated content. 

“Journalism is always going to be a human process, because journalism is based on their location, and verification, verifying leads, tips, and figuring out rumour from fact,” said Kent. “So far, none of the machines that I’ve seen associated with artificial intelligence, have those human characteristics. However, there is also that human aspect called temptation.”

Arthur Kent. Photo by DX Journal / Digital Journal

In the financial services industry, Semmens said the impact of generative AI “poses an existential risk” to the relationship banks have with their clients. 

Despite this, he says incorporating AI technology into banking is “an incredible opportunity” to personalize experiences for customers more effectively and efficiently, and he expects to see a lot of changes in open banking in the next three to five years. 

“With all the disinformation that is out there, a trusted source is going to be a high commodity,” he said. “And so I think in banking, being a heavily regulated industry, there is an opportunity for us to really show up from that standpoint.”

Dan Semmens. Photo by DX Journal / Digital Journal

An innovation forum’s charitable roots

The Northern Lights Technology and Innovation Forum’s story begins over a decade ago. The organizers, including Givens, first banded together for the Gordie Howe C.A.R.E.S. Hockey Pro-Am Tournament in support of Alzheimer’s research and education. 

As the cause drew more attention they opted to expand the tournament into the forum as a way to expand their reach. All of the event proceeds go to Gordie Howe C.A.R.E.S. Centre for the Alzheimer’s Research and Education Society — and this year they broke their record, raising a minimum of $40,000 thanks in part to a funding match made by Google. 

“It’s amazing,” Givens said at the end of the night. “I always knew the potential of our community. And I explained to people that the community is the draw … It’s about education. It’s about doing the right thing. It’s about just finding ways for other people to get involved in doing the same thing. There’s enough energy there. Now we just have to harness it.”


DX Journal is an official media partner of the Northern Lights Technology and Innovation Forum.

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Generative AI fascinates many, but how are businesses addressing the societal effects and talent gaps?

A look at Deloitte’s latest study of the state of AI in 2024

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Across the globe, 2023 was heralded as generative AI’s breakout year, and it hasn’t really slowed down since. So now experts are asking what AI trends will come this year and what the business impacts will be.

Tech and finance consulting giant Deloitte recently studied the state of generative AI in 2024, examining common use cases and goals, as well as broader societal implications. 

Here are some highlights from the report, as well as practical tips to leverage AI safely in your organization: 

Generative AI for more productivity and efficiency

The research surveyed more than 2,800 leaders across various organizations currently piloting or implementing generative AI. Most (62%) cited emotions of excitement, as well as fascination (46%), while 30% reported feeling uncertain around generative AI.

The majority saw the technology as a tool to gain more efficiency within their businesses, along with these cost benefits: 

  • Improve efficiency and productivity: 56%
  • Reduce costs: 35%
  • Improve existing products and services: 29%

From the respondents who sought more productivity, here’s where they plan to reinvest in that newfound efficiency: 

  • Encourage innovation and growth: 29%
  • Shift workers from lower-value to higher-value tasks: 26%
  • Uncover new ideas and insights: 19%

Talent still a barrier to successful generative AI adoption

Less than half of the respondents cited having sufficient employee expertise or education on generative AI, with about 55% planning to improve their learning and development strategy in the next one to two years. 

This is a consistent challenge that we’ve seen across multiple research studies, including IBM’s for the Canadian market

So how can an organization turn these plans into action? According to the respondents, the top three investments are being made in:

  • Generative AI fluency and education: 74%
  • AI recruitment and hiring: 74%
  • Reskilling: 73%

Global collaboration and governance needed for equity in generative AI

The IMF recently found a whopping 40% of jobs will be affected by AI globally, with more advanced economies seeing that number jump to 60%. The advanced economies see the tech as a compliment, while lower-income countries and emerging markets experience more job replacement. 

Will this disparity contribute to a wealth gap? Many of Deliotte’s respondents seem to think so, with 51% saying they expect generative AI to increase economic inequality.

The majority of respondents agreed that responsible AI development requires more global collaboration (72%) and governance (78%). 

Deloitte suggests these results reflect an understanding that generative AI could be too powerful for individual organizations to regulate themselves — but that doesn’t absolve them from behaving responsibly.

For individual businesses, this means paying close attention to government guidelines on responsible AI use and research on AI’s effects over time. Additionally, collaborating and sharing information across different businesses, industries, and even countries can help maintain responsible use of AI in society.

While companies are racing to keep up with these rapidly evolving AI solutions, “the key is to maintain a beginner’s mindset” reads the report. No matter how much of an expert you think you are, there’s always more to learn.

Read the full of the report here

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Legal storms loom over businesses as new US regulations mandate swift disclosure of cyberattacks

The new US regulations pose a legal and reputational minefield for businesses and experts say Canada may follow suit, highlighting the need for cybersecurity and crisis communication strategies

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In the case of new US regulations for businesses required to publicize that they were hacked, there may be an unpleasant price to pay. Observers in the industry say companies are increasingly facing legal consequences and public relations disasters.

The regulation requires businesses to report any cyberattack to the Securities and Exchange Commission (SEC). They must disclose the breach within four days, list various ways the data was compromised, and show how risks were mitigated. 

“The new rules are a part of a larger regulatory shift to hold businesses accountable for protecting their customers online, and to hold the companies liable for the losses they suffer because of these attacks,” notes Israel Mazin, co-founder and CEO of Memcyco, a website impersonation detection and protection solution.  

The drawbacks? 

“This puts businesses in a vulnerable position,” he adds. “Publicly disclosing attacks means potentially big reputational blowback — and it has yet to be shown to help solve the problem.” 

Though he won’t mention names, Mazin says he knows of several renowned businesses that lost revenue as a result of their willingness to announce a data breach.

The US regulations have already become a source of perverse games for hackers.

In one story, a hacker played “cop and robber” at the same time: after breaching a company, they then reported them to the SEC for not disclosing the breach. Essentially, this double attack was an unforeseen consequence of otherwise well-intentioned law.

What are the implications in Canada?

The legal problem is another challenge. 

Dave Oswald, founder of Forensic Restitution, which specializes in forensic accounting and computer forensics, says there’s already a proliferation of court cases filed against American breached entities. Expect the phenomena to soon inch north to Canada, he says. 

“I think over time there will be increased litigation,” he says. “Especially with companies who don’t have adequate cyber training.” Those organizations or businesses that do not have a cyber reaction team, or are not set up to protect against a cyber attack, “are the companies that, I think, will end up on the wrong side of lawsuits going forward.” 

There are already plenty of cybersecurity lawsuits being handled in Canada and the US, adds Andrew Buckles, cyber services owner at ISA Cybersecurity in Toronto. He points out five Ontario hospitals that recently faced a “major cyber attack” and are currently facing a close to half-billion dollar class action lawsuit.  

“If you’re being hit with a very large lawsuit, that can be extremely detrimental to your business,” Buckles says. “Chances are you weren’t managing that risk effectively. And you may not have even been aware of that risk.”

Canada has its own cybersecurity laws proposed in Bill C-26, also known as the Critical Cyber Systems Protection Act, which Buckles says is a “good example” of oversight. However, he adds that “Canada certainly needs to continue looking at what regulatory authority they have over different industries and how [they can] improve those requirements to a minimum standard.” 

“Lots of businesses collect data and information and digitize; if they experience a cybersecurity incident, the public is impacted in many cases,” he continues. “So there is a public interest in making sure that organizations do manage their risks effectively so that the public doesn’t have to ultimately pay the price.”

Guidelines for data security

When it comes to dealing with cyber breaches, the United States and Canada have different rules. In Canada, if a cyber breach is considered significant, companies only need to issue a press release. Other than this, most of the guidelines are more like suggestions than strict requirements. 

In February 2017, the guidelines for this in Canada were outlined in the Canadian Securities Administrators’ (CSA) notice for disclosure of cybersecurity risks and incidents. 

Canadian Securities Litigation reported that these were characterized as “guidelines,” including: risk governance and risk mitigation strategy, detailed disclosure of material cybersecurity risks, procedures designed to ensure that detected cybersecurity incidents are communicated to management for timely disclosure, disclosure of the anticipated impact, and costs of the incident.

The report said legal and protocol demands of companies are sure to follow. “Trends in the United States are often a harbinger of what may be coming to Canada,” the article states. And, while the trend in cybersecurity disclosure-related litigation hasn’t hit the Great White North to the same extent yet, the authors say that “Canadian companies should be watching.”

In Canada, the emphasis in proposed class actions regarding cyber attacks has mainly centered around individuals whose data might have been impacted by a cybersecurity event rather than securities class actions, according to the authors. 

In November 2022, Ontario Court of Appeal issued three decisions that held that companies who had been cyber attacked by unknown third parties, were not liable for the damages. The authors of the article, however, say this law “will continue to be tested.”

Mitigating risk

Ultimately, for any Canadian or American company, cyber damage control is key to mitigating legal issues or reputational issues. At the point of discovering a hack, an organization or company should know the right steps to curtail the threat and minimize damages. 

“Communication should include clear identification of the threat, steps the business is taking, and actionable advice for customers, such as verifying website URLs, avoiding clicking on suspicious links, and monitoring their accounts for unusual activity,” says Mazin.

By the time of discovery, attackers may have already harvested user data — which they can use or sell — leading to identity theft or further scams. 

As a result, it could shake customer confidence in the brand. 

“It’s vital to provide reassurance that customer protection is a priority, and to offer support services for those who may have been compromised,” Mazin adds.

In regards to the new US regulations, he says the government did the right thing by looking out for the consumer’s best interest in requiring data breach crises to be open and transparent. The next requirement should be legally-mandated up-to-date cybersecurity, he says, “to greatly minimize the overall risk of privacy breaches, and legal consequences.”

Something like this would require security professionals to work in tandem with the government so as not to make this kind of law onerous, “but also ensure a standard set for major companies.” 

As for the reputational damages after the fact, “it would pay for companies to have a pre-emptive plan to cope with public relations fallout,” says Mazin.

Here are some tips to on how to mitigate risk:

Implement robust cybersecurity measures:

  • Establish strong firewalls, encryption, and intrusion detection systems.
  • Regularly update and patch software to address vulnerabilities.

Prioritize employee training and awareness:

  • Provide comprehensive cybersecurity training to employees to avoid human error.

Develop and test an incident response plan:

  • Create a well-documented incident response plan for cybersecurity breaches.
  • Regularly conduct simulations and drills to ensure effectiveness.

Secure customer data and communication:

  • Encrypt customer data.
  • Develop clear communication protocols for timely and transparent disclosure of cyber incidents.

Regularly review and update policies:

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