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Looking to deliver IoT value? Don’t go it alone

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By: John Gonsalves

According to Gartner, more than $440 billion will be spent on Internet of Things initiatives by 2020. Yet networking company Cisco recently found that only 26% of organizations so far have completed an IoT initiative they consider a success. That percentage isn’t pretty. And companies don’t have much time to climb a steep learning curve and thus avoid costly failures.

So what is preventing companies from getting IoT right? Much of the challenge derives from focusing on implementing technologies without a comprehensive, holistic plan. Sensors? Smart devices? Data analytics? Cloud-based processing? All necessary and helpful. But how will they operate together? How will they collectively transform data into usable information – delivered in time to act in real time? That takes thought. And the thinking must be in the C-suite.

Related:  How manufacturers can unlock value with IOT analytics

Today’s IoT industry is maturing from stand-alone point applications to integrated systems that capture and process data to derive business insights and even quality of life outcomes. Smart parking solutions, for example, now leverage IoT to analyze parking inventory and guide drivers to available spaces, an outcome with great potential value projected to save hours, miles and even gallons of gas.

A more complex IoT “system of systems,” however, might integrate that parking platform with other IoT-enabled systems, exchanging data that leads to actionable insights. An owner/operator of parking structures could then optimize lighting use in different spaces, control climate for peak and off-peak times and temperatures, assess risks and security needs, respond to staffing shortfalls quickly, and even adjust prices for a particular facility based on volume, previous usage patterns, scheduled local events and consumers’ real-time needs.

An optimal pace to value

Companies have been slow to take their IoT solutions to this next level because they face genuine challenges. How to quantify the potential value to justify the investment? How to stay ahead of security risks? How to understand and leverage multiple complex technologies? Or identify physical installation and support services? Or aggregate, synthesize, store, analyze, act on and monetize their data?

To many, the feasibility of bringing partners and service providers together to create an end-to-end ecosystem is not yet clear. There is the pressure to anticipate integration points and ensure components and people work together. as well as understand and plan for the potential disruptive impact on the organization, customers and business models.

[Download]:  How manufacturers can unlock value with IOT analytics

Nevertheless, developing an integrated IoT constellation of devices, sensors, actuators, gateways and network and cloud service providers, a new breed of IoT platform providers, along with analytics, specialty visualization and integration with enterprise applications – all designed to work together – is the best way to optimize results.

The IoT Value Chain

Components of the IoT value chain should include:

  • Data capture. Data originates from sensors, actuators, controllers, devices and hardware in the field, but companies quickly learn that implementing a transformational IoT solution involves far more than adding sensors to their packaging, products and the machines that manufacture, deliver and service them. Sensors must collect data spatially (i.e., throughout a space) and temporally (i.e., across time), and be instrumented in such a way that vital signs can be signaled, collected and analyzed for downstream action. Such massive amounts of data must be cloud- and network-agnostic to ensure compatibility with various platforms.
  • Data communication and storage. To maximize their value, cloud and network services platforms need to deliver operational insights by working with devices at the edge – that is, where the data is gathered. They must be multilingual (able to talk to any sensors using any communications protocol) and hardware agnostic, so that data can be integrated, synthesized and stored, making it available for future context-aware analysis.
  • Data analysis and insights. Making sense of vast amounts of data and taking action is key to unleashing the power of IoT. Predictive analytics providers identify patterns, network effects or anomalies so undesirable outcomes can be anticipated and prevented. Such analytics prompt prescriptive action: Companies can course-correct on the fly – replacing a part or stopping an engine from overheating, for example – to optimize operational efficiency through improved asset performance and employee productivity. World-class algorithms must be domain-sensitive and industry-aware so they can be meaningfully applied to unique use cases; advanced visualization of data may be required in certain situations.
  • Infrastructure & security. Beyond cloud and network service providers, IoT solutions at scale need end-to-end security from device to edge to the cloud (and the apps), distributed device management and distributed data management.
  • Coordination between IoT components and systems of engagement. Systems of engagement may vary from mobile devices to advanced augmented/virtual reality (AR/VR), mixed-reality or other user interfaces. The focus of IoT solutions is now migrating beyond operations optimization to enable new business models (e.g., pay per use), imagine new products and services (e.g., software-based services), monetize data, etc. Indeed, the opportunities are massive as we develop and benefit from “system of systems.”
  • Partners. The variety and range of technologies for the IoT is enormous, yet still immature. Each participant would do well to understand its role in the IoT ecosystem and get to know adjacent players to partner with to deliver smart, connected IoT solutions at scale. Scale implementations need physical deployment of sensors (and device instrumentation), the operations technology and the digital value chain. And they require a skilled system integrator that also knows the associated IT and heritage systems, to develop and orchestrate the combined ecosystem and, thereby, realize business value.

How to get started

A good systems integrator will start by asking the question, “What business problem do you want to solve?” From there, the company can help to create the business case for an IoT solution by articulating its value, be it cost reduction, revenue enhancement, asset optimization, customer experience transformation or increased safety.

Then it’s on to the heart of the engagement: defining new operational processes, recommending IoT-enabling information and operational technologies, identifying and classifying the right ecosystem players in the IoT value chain, and assembling and integrating them based on who plays best where.

[Download]:  How manufacturers can unlock value with IOT analytics

Challenges certainly remain, but the opportunities for new revenue streams, increased operational efficiency and improved customer engagement have never been greater for companies that leverage end-to-end IoT solutions in consumer, commercial or industrial settings.

This article originally appeared on the Digitally Cognizant Blog

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How can the value of the cloud evolve between now and 2030?

According to McKinsey research, large enterprises aim to have about 60% of their environment in the cloud by 2025.

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Cloud technology has become an integral part of the digital transformation of today’s businesses. And that has executives asking themselves important questions — namely, how large is the value at stake in my sector? How quickly will this value be captured? Who will capture it? What can I do to ensure my organization gets its share? 

The answers are multifaceted, and were sought by researchers at McKinsey through a recent analysis. They conducted a thorough review of several key resources, including the McKinsey D2020 IT spending structure benchmarking study, and independent third-party surveys of more than 1,000 organizations that have adopted cloud technologies. Researchers addressed over 700 use cases across 20 different sub industries, ultimately to inform their conclusions, which we’ll cover more below.

Organizations That Maximize Cloud Value Do So In a Combined Approach

The first prominent finding of McKinsey’s review is a prominent trend among organizations that maximize cloud value. According to analysts, those that make the most of the technology do so in a three-pronged system:

Rejuvenate – IT cost optimization, resilience improvement, and core operations digitization

Innovate – innovation-driven growth, accelerated product development, and hyper scalability

Pioneer – early adoption of cloud technology

The Potential Value Waiting To Be Unlocked In Cloud Technology

Another important finding of the review, McKinsey researchers suggest that the potential value in cloud technology is substantial. After analyzing the value at stake for adoption in US Fortune 500 companies, they estimated that up to $1 trillion in annual value is waiting to be unlocked by 2030. Moreover, when applying those same drivers to Forbes Global 2000 companies, the potential value is estimated to be around $3 trillion in EBITDA (Earnings before interest, taxes, depreciation, and amortization) over the next decade.

Asia’s Potential for EBITDA Gains

The report noted that Asia is in line to reap the highest cloud value potential from adoption at about $1.3 trillion by 2030. The continent’s businesses make up the largest regional revenue share of the Forbes Global 2000 companies analyzed, many of which fall within the oil, gas and banking industries. These are sectors which McKinsey researchers have identified as having particularly high potential for value gains from cloud adoption.

The Americas aren’t far behind, coming in second with a potential cloud value of around $1.2 trillion, driven largely by retail and manufacturing sub industries. These specific domestic sectors stand to capture nearly $162 Billion in EBITDA growth by 2030 – more than three times the value potential for those in Asia and the European Union.

The Keys to Unlocking Value

McKinsey interviewed more than 50 CTOs, CIOs, and cloud program leaders from prominent North American enterprises to better understand their work and what success factors they had in common. The research concluded that the most successful cloud adopters leveraged three key levers:

1. Discovering the full value of the cloud.
2. Solving critical technical challenges.
3. Delivering fundamental, organizational change.

These organizations withstood the challenges of cloud adoption and emerged better-positioned to capture value. Their key takeaway was that creating an effective cloud program requires a combination of technical and organizational capabilities, as well as the right mindset. This means that even if an organization has the necessary tools, they may still need to make changes in areas such as strategy, culture, and processes in order to fully benefit from cloud technology.

Read the full report from McKinsey

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WeaveSphere: 5 conference highlights

The WeaveSphere tech conference wove together ideas about AI, FinTech, STEM education, innovation in Canada, and more.

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For three days this November, innovation, collaboration, and a whole lot of big ideas were shared among “Weavers” during the WeaveSphere tech conference in Toronto.

“Today is an opportunity for greater connection between the scientific and tech industry, and academia,” said Marcellus Mindel of IBM Canada, opening the conference. With innovation the event’s core, Mindel added: “let’s define innovation, thinking of it as reframing that implements better outcomes.”

While lots happened over three days, here are five highlights and takeaways from the event:

1. Thought-provoking keynotes had attendees thinking big

Each day of WeaveSphere kicked off with a keynote, where three speakers brought their insightful ideas to attendees.

Gillian Hadfield shared ideas about AI and regulation

On Day 1, Gillian Hadfield, Professor of Law and director of the Schwartz Reisman Institute for Technology and Society at the University of Toronto, explained where we are today when it comes to regulating artificial intelligence (AI) — and where we need to go next. 

While AI makes machines intelligent, Hadfield argued that it cannot, by definition, produce intelligent behaviour if it isn’t functioning appropriately and ethically. Machine learning is not the same as standard programming, since machines write the rules. As a result, machines can start solving problems in ways we don’t want them to, resulting in regulatory challenges. 

How to solve this? Hadfield presented two solutions:

  1. Establish compensation for harm
  2. Design incentives for meeting good and safe behaviour

Dr. William Barry discussed ethics with an AI co-presenter

On Day 2, professor, AI ethicist, and futurist Dr. William Barry talked about a particular problem: what ethical questions might arise when you program a robot? 

For starters, how do you determine what information to include or not? Where is the appropriate line? 

As a professor, Dr. Barry has been working with robots as teaching assistants in his classroom since 2015, and brought a digital version of Maria Bot (one of his AI assistants) to interact with the audience.

As Dr. Barry explained, he is very strategic when choosing the information from which his assistants learn. 

One place Maria won’t get access to? Twitter, says Dr. Barry, highlighting it’s too much of a risk for an “AI benign” to get access to misinformation. This would distort the ethical perspective that Maria is learning, he said. 

While he has programmed her to weed out and to not learn from toxic content — like racism and misogyny — Dr. Barry does work at exposing his AI beings to a wide range of diverse thought and lived experiences. In the end, how ethical an AI being is, is in the hands of the human controlling what they learn, he argued. As a result, they’ll ultimately be biased as a result of the specific data sets we provide for them. 

Marcel Mitran discussed technology for good

WeaveSphere’s Day 3 keynote took a slight turn away from AI. 

IBM Fellow, IBM Master Inventor, and CTO for Cloud Platform for zSystems and LinuxONE, Marcel Mitran took to the main stage for a keynote on responsible computing. At the heart of his talk was the argument that technologists need to take a step back and look at what’s being done to keep the world safe. 

For example, the opportunity for error and bias in the role of facial recognition in public safety, and the fact that our digital footprints — both on a personal level and for enterprise — have grown significantly even in the last year.

As Mitran explained, responsible computing is a systemic, holistic approach addressing current and future computing challenges like sustainability, ethics, and professionalism. It advances the “quadruple bottom line” of people, planet, prosperity, and participation. 

2. Insightful sessions had attendees thinking deep

Photo courtesy WeaveSphere

FinTech, cryptocurrency, AI, digital economies, Canada’s innovation landscape — there was a large cross-section of topics covered across a variety of workshops, paper presentation, and panel discussions. 

Some highlights include:

Chhavi Singh, co-founder of Flyte, asked the question: have you considered using AI to coach your sales staff? Elaborating on the opportunity AI presents to increase sales performance, Singh explained how AI can be used to help understand customer challenges and handle objections and concerns. 

COO of wealth management platform OneVest, Jakob Pizzera, outlined the three phases of FinTech. The first (1.0) was in-house sites for basic online banking. Version 2.0 was the “unbundling” of financial services, and the rise of standalone businesses. The last few years has brought FinTech 3.0, with embedded finance — for example making a purchase through Instagram.

WeaveSphere conference chair and R&D specialist Vio Onut answered the question of why we need to care about cyber security. For starters, the potentially very large costs to your organization, and because the massive skills gap of privacy and security experts has created vulnerabilities. 

Digital strategist Matt Everson explored what can go with emerging technologies like Web3 and the metaverse. Everson said developers should just start building and drawing on video game virtual markets as a model. He used popular online game EVE Online as an example of how virtual economy design can be translated to other markets.

Lijia Hou, Blockchain Systems Engineer with Draft Kings, explained that three key problems still exist when it comes to blockchain technology. First, investors want to understand how — in a volatile market — to mitigate risk. Second, developers from the traditional software side need a mindset shift when it comes to decentralization. And finally, the tools of decentralization are used differently, and this is not always evident for those unfamiliar with Web3.

3. There was a LOT of interest in STEM education

As part of WeaveSphere’s Education Day slate of programming, hundreds of high school and university students had the opportunity to workshop real-life problems from both school and work — all under the guidance of IBM’s Design Thinking experts

Photo courtesy WeaveSphere

This meeting of next-generation tech talent collaboratively explored Enterprise Design Thinking strategies like As-Is Scenario Mapping, Empathy Mapping, Hills (positioning statements), and Hopes and Fears. This approach to problem-solving works by framing the issue at hand in a human-centric way, centering the end-user in all decision-making. 

For Education Day, the problem at hand was helping fourth-year university students find their first job. 

Photo courtesy WeaveSphere

4. There were loads of networking and learning opportunities

One of the best parts of any conference is the opportunity to network and learn from fellow attendees.

In the conference’s Innovation Valley section, event sponsors were on-hand to discuss everything from their latest technologies to job opportunities, plus several graduate students were also there to present their research.

Since WeaveSphere is a “meeting of the minds” between tech professionals and students, many undergrads from schools like York University and Mohawk College came to the conference full of questions, ready to absorb everything. 

5. WeaveSphere celebrated top tech talent

A big part of WeaveSphere was a celebration of some of the best tech minds in Canada. 

During a gala evening at the end of Day 2, the 2022 Developer 30 Under 30 and Tech Titans were awarded to the best of the best among young developers and digital transformation leaders in Canada. 

The winners were:

Developer 30 Under 30 winners

Photo courtesy WeaveSphere
  • Alexander Newman
  • Anakha Chellakudam
  • Anthony Langford
  • Arshdeep Saini
  • Aryaman Rastogi
  • Bohdan Senyshyn
  • Charlie Mackie
  • Charmi Chokshi
  • Colin Lee
  • Daniel Marantz
  • Francisco Hodge 
  • Hassan Djirdeh
  • Jerry Fengwei Zhang
  • Julia Paglia
  • Karandeep Bhardwaj
  • Kathryn Kodama
  • Khushbu Patel
  • Lianne Lardizabal
  • Lucas Giancola
  • Mathew Mozaffari
  • Maz Mandi
  • Oleksandr Kostrikov
  • Rishab Kumar
  • Samantha Lauer
  • Sarah Syed
  • Stan Petley
  • Tanmay Bakshi
  • Tim Romanski
  • Xiaole Zeng
  • Yash Kapadia

Tech Titans winners

Photo courtesy WeaveSphere
  • Andrew Dolinski
  • Ashish Agrawal
  • Chhavi Singh
  • Chris Dolinski
  • Dean Skurka
  • Demetrius Tsafaridis
  • Fay Arjomandi
  • Harish Pandian
  • Harpreet Gill
  • Iman Bashir
  • James Stewart
  • Len Covello
  • Manav Gupta
  • Marcel Mitran
  • Michelle Joliat
  • Dr. Mohamad Sawwaf
  • Omar A. Butt
  • Peter Zwicker
  • Ryan McDonald
  • Dr. William Cherniak

Finally, as WeaveSphere came to a close, the Pitch Stadium opened, hearing from a wide variety of startups. 

They came, they pitched, and in the end, Iman Bashir and Nicole Lytle of Craftly.AI, a copywriting assistant that uses AI to generate original content, took home the $50,000 prize to help grow their business.

Photo courtesy WeaveSphere

WeaveSphere was a uniquely collaborative, innovation-focused conference filled with engaging workshops, presentations, and networking opportunities.


DX Journal is an official media partner for WeaveSphere. Check out our series of articles from the lead-up to WeaveSphere.

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7 Digital Transformation trends on the horizon for 2023

Salesforce’s MuleSoft reports seven trends that are key to balancing operational pressure and improved customer and employee experience.

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Efficiency and growth are at the heart of many a business plans right now, even though an economic downturn is widely predicted to be on the horizon.

In the face of these organizational pressures, Salesforce’s MuleSoft recently released a report detailing their predictions and insights for digital transformation in 2023. In the report, they outlined seven trends that are going to be crucial for organizations that want to overcome these pressures while keeping the gas on customer and employee experiences. 

As MuleSoft Global Field CTO Matt McLarty explained, “as companies gear up for the year ahead, businesses must recognize that effectively utilizing new digital techniques is the only way to ensure growth amidst economic pressures.” 

“Investing in cost efficient, employee- and customer-centric technologies will be critical for companies seeking to remain agile and break away from the competition in 2023.” 

Here are MuleSoft’s seven digital transformation trends-to-watch:

Increase in automation investment

MuleSoft’s research has validated what many in the industry have already predicted regarding the projected growth of automation tools. According to a previous survey, roughly 80% of organizations plan on incorporating hyperautomation into their technology roadmap within the next 24 months. This points to a paradigm shift in the way businesses operate, as they move away from reliance on manual processes to a more digitized and technology-enabled future.

Composability is key

MuleSoft and Salesforce predict that in lieu of the point mentioned above, companies will be inclined to implement strategies like low/no-code platforms and application programming interfaces (APIs) to make their automation efforts more composable.

The rise of low/no-code tools

The report from September found that 73% of leaders agree that acquiring IT talent is the hardest it’s ever been, which makes perfect sense given the global shortage of software developers. In order to free up resources and enable a wider range of employees to participate in digital transformation, low/no-code platforms will continue to grow in popularity.

Investment In total experience (TX) strategies

Amid findings that 86% of IT leaders believe that both employee and customer experience (EX and CX) are as important as a company’s products, MuleSoft’s research anticipates that organizations will increase their focus on delivering great experiences through loyalty and advocacy.

CX and EX initiatives will work in tandem to increase revenue and retain talent, focusing on integration and automation that connect the dots where these two meet.

Data-Driven Decision Making Should Be Technology’s Job

Salesforce research highlights that 83% of organizations consider data-driven decisions to be a top priority in their organization. This data, however, is often siloed. As a result, MuleSoft predicts, 2023 will see the rise of real-time analytics to bread down silos, to “create a data fabric that provides automated, intelligent, and real-time insights and reduces untimely decisions.”

Cybersecurity Is Set to Scale

Expect to see more organizations invest in a cybersecurity mesh approach in order to secure data as it moves between multiple cloud applications. This is in response to data from Gartner that claims doing so could reduce the financial impact of security incidents by 90%.

Sustainability Will Be a Priority

Organizations are likely to increase their adoption of data-driven insights and integration across supply chains as they seek to become more sustainable. 


Download the full Mulesoft report

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