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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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The importance of data access for digital initiatives

A new report from MuleSoft found that just 37% of organizations have the skills and technology to keep up with digital projects.

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In a global survey of over 1,700 line of business employees in organizations with at least 250 employees, MuleSoft found that just 37% of organizations have the skills and technology to keep up with digital projects.

The resulting report — The State of Business and IT Innovation — reveals four key ideas that IT leaders need to know in order to drive digital innovation forward.

These four key findings are:

  • Collaboration is key 
    • 68% of respondents believe IT and LoB users should jointly drive digital innovation.
  • Keep up the pace 
    • 51% expressed frustration with the speed at which IT can deliver projects.
  • Integration challenge
    • 37% cite security and compliance as the biggest challenge to delivering new digital services, followed by integration (i.e. connecting systems, data, and apps) at 37%.
  • Data access
    • 80% say that in order to deliver on project goals faster, employees need easy access to data and IT capabilities.  

“This research shows data is one of the most critical assets that businesses need to move fast and thrive into the future,” said MuleSoft CEO Brent Hayward

“Organizations need to empower every employee to unlock and integrate data — no matter where it resides — to deliver critical, time-sensitive projects and innovation at scale, while making products and services more connected than ever.”

Want to read through the whole report? Download it from MuleSoft

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Where is the financial value in AI? Employing multiple human-machine learning approaches, say experts

According to a new study, only 10% of organizations are achieving significant financial benefits with AI.

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AI is everywhere these days — especially as we work to fight the spread of COVID-19

Even in the “before times,” AI was a hot topic that always found itself in the center of most digital transformation conversations. A new study from MIT Sloan Management Review, BCG GAMMA, and BCG Henderson Institute, however, prompts a crucial question:

Are You Making the Most of Your Relationship with AI?

Finding value

Despite the proliferation of the technology and increased investment, according to the report, just 10% of organizations are achieving significant financial benefits with AI. The secret ingredient in these success stories? “Multiple types of interaction and feedback between humans and AI,” which translated into a six-times better chance of amplifying the organization’s success with AI.

“The single most critical driver of value from AI is not algorithms, nor technology — it is the human in the equation,” affirms report co-author Shervin Khodabandeh.

 

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From a survey of over 3,000 managers from 29 industries based in 112 countries — plus in-depth interviews with experts — the report outlined three investments organizations can make to maximize value:

  • The likelihood of achieving benefits increases by 19% with investment in AI infrastructure, talent, and strategy.
  • Scalability. When organizations think beyond automation as a use case, the likelihood of financial benefit increases by 18%.
  • “Achieving organizational learning with AI (drawing on multiple interaction modes between humans and machines) and building feedback loops between human and AI increases that likelihood by another 34%.”

According to report co-author Sam Ransbotham, at the core of successfully creating value from AI is continuous learning between human and machine:

“Isolated AI applications can be powerful. But we find that organizations leading with AI haven’t changed processes to use AI. Instead, they’ve learned with AI how to change processes. The key isn’t teaching the machines. Or even learning from the machines. The key is learning with the machines — systematically and continuously.” 

Continued growth

While just 1 in 10 organizations finds financial benefits with AI, 70% of respondents understand how it can generate value — up from 57% in 2017.

Additionally, 59% of respondents have an AI strategy, compared to 39% in 2017, the survey found. Finally, 57% of respondents say their organizations are “piloting or deploying” AI — not a huge increase from 2017 (46%). 

One of the biggest takeaways? According to co-author David Kiron, “companies need to calibrate their investments in technology, people, and learning processes.”

“Financial investments in technology and people are important, but investing social capital in learning is critical to creating significant value with AI.”

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Bringing DX to the food supply chain in a pandemic

In a new paper, supply chain stakeholders share how COVID-19 has affected the transformation of the sector.

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There’s little doubt that COVID-19 had a profound effect on the food supply chain.

As one example, just think back to roughly March of this year, when virus transmission was rapidly picking up speed. Remember the reports of food and beverage companies only producing their most popular or essential products? Or how it would take slightly longer than usual to restock certain products? What about the rush to integrate — or quickly improve the efficiency of — digital and e-commerce. 

Panning out a bit, think about food safety and quality professionals. The need to stay safe — and in many cases, stay at home — meant performing the very hands-on job of monitoring, auditing, inspecting at a distance, i.e. digitally. 

When the food supply chain was hit by storages, delays, breakdowns, and lockdowns, the end result was — like in so many sectors — a rapid digital transformation.

As The Food Safety Market — an SME-powered industrial data platform dedicated to boosting the competitiveness of European food certification — elaborates in a new discussion paper, “technology has played an important role in enabling business continuity in the new reality.”

The paper — Digital Transformation of Food Quality & Safety: How COVID-19 accelerates the adoption of digital technologies across the food supply chain — features industry experts from companies like Nestlé, Ferrero, PepsiCo, McCormick & Company, and more discussing the effects of the pandemic on the supply chain.

A few highlights from the paper:

  • John Carter, Area Europe Quality Director for Ferrero put the issue of food access into perspective at the start of his interview:

“The production of food defines our world. The effects of agriculture on our daily lives are so omnipresent that they can be easy to overlook; landscapes and societies are profoundly influenced by the need to feed our growing population. But much has been taken for granted. Only occasionally are we forced to consider: ‘where does our food come from?'”

  • Ellen de Brabander, Senior Vice President of R&D for PepsiCo provided insight on the cost benefits of digital transformation:

“The need for customization is a big driver for accelerating digital transformation and moving away from a ‘one size fits all’ approach. This means that the cost to develop and produce a product must be lower and digital technologies provide a clear opportunity here.” 

  • Clare Menezes, Director of Global Food Integrity for McCormick & Company brought up one area where digital tools need to go:

“There aren’t any areas where digital tools “fail”, but there is a need for tools that ‘prove out’ predictions around where the next integrity event will play out and how it could lead to quality or food safety failure. These tools are an obvious candidate for AI given the number of PESTLE factors that might come into play.” 

Want to read all of the interviews? Check out the paper here.

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