Experfy Insights

The convergence of IT and OT dramatically alters investing activities in corporate development. We’ve been seeing a new type of acquisition by large, vertical-specific OT players acquiring ventures focused on vertical industries. The new digital trajectory of OT affects the strategic investment considerations of a corporate development leader in OT or IT and the strategy of an entrepreneur. How do you align the new target’s investments with internal business unit’s goals? Is the new technology enabling multiple internal businesses? How should it be structured and measured internally if acquired?

The right go-to-market (GTM) strategy is needed to ensure you have product-pallet fit to reach your buyers. How your GTM adapts for a connected world is as important as reimagining your product strategy. We’ll look at how these IoT offerings are sold and bought. We will start by looking at channel partner structure in IT and OT worlds and then show them side-by-side to see the almost bewildering impact on GTM strategy when IT meets OT.

Although technology is quickly changing, your goals as a manufacturer likely haven’t. You still aim to please your customers by delivering quality products, while increasing productivity and profitability. Yet, new and unprecedented innovations will potentially impact all aspects of the execution of those goals at the operational level. Smarter connected devices that use open IoT protocols are rapidly penetrating factories. At the same time, the Industry 4.0 trend is showing how people, connected devices and artificial intelligence can work together to make factory automation more efficient and effective. To remain competitive, you must quickly adapt.

Before launching an IoT initiative, organizations need to have a comprehensive strategy in place. Otherwise, there’s a risk of overspending, exposing data to security and privacy threats, limiting the payback from IoT technologies, as well as other negative outcomes. Without three key elements — strong leadership, a sensible business plan, and a commitment to culture change — all the sensor, networking and data analytics technology in the world is not going to deliver optimum results. Your IoT initiative will likely face many challenges before you can proclaim it a success. Here are some important considerations to keep in mind.

If cybercrime were a country, it would have the 13th highest GDP in the world.  The global crime economy has become a self-perpetuating organism — an interlinked web of profit where the boundary between the legitimate and illegitimate is often unclear. Today, engaging in cybercrime is as simple as legitimate e-commerce. The dependency on the availability and performance of IT infrastructure among legitimate enterprises is increasing heavily, which makes them more vulnerable to breaches that can wreak havoc on business. Cybercriminals are clearly adept at leveraging existing platforms for commercial gain.

Industrial enterprises typically look to systems integrators to bridge the gaps with custom software development.  A few IoT vendors are now beginning to build more fully-integrated IoT service creation and enrichment platforms (SCEPs), designed to support an AFML IIoT architecture. SCEPs allow complex IoT architectures, applications and orchestrations to be efficiently created and evolved with minimal programming and administrative effort. These next-generation IoT platforms will help companies eliminate IoT data exhaust and harness IIoT data for use as a strategic business asset. 

Internet of Things is partly about value creation, using the ability to communicate and control things over connections and automating how we get work done. Products with embedded intelligence talking to the cloud bring the power of remote control to everyday things, much like the iPhone and iCloud has done. All this requires information technology (IT) to be embedded in our business systems that let us operate our businesses. In other words, it is operational technologies (OT) with IT inside. Ergo, IT + OT = IoT in a technological sense.

The Internet of Things remains one of the most revolutionary forces in today’s high-tech society. Along with its impressive growth rates and numerous deployments across different industries, IoT security remains the primary issue. 5 technological breakthroughs namely blockchain, PKI, IoT analytics, IoT authentication and IoT network security are making huge changes in terms of data privacy, seamless connectivity and manageability of IoT devices. This results in the emergence of innovative IoT security solutions which help global leaders embrace the digital trend without any risks.

The business landscape changes daily and with that comes new “buzzwords.” You know those ones that really bug you – those where you kind of know what they mean, but they can mean lots of things and different things to different people. One such word is “servitisation.” This term captures so many of the other current industry terms and buzzwords around Industry 4.0, digitisation, IoT, mobility and much more. What is needed is a focus on the data, the foundation of servitisation, and how to extract value from that data quickly through an “analytical life cycle.” 

The mobile app development domain is exciting and challenging at the same time. It is interesting to see how IoT impacts the mobile application development. The mobile domain always provides scope to access the IoT-enabled devices. Mobile apps are useful to access IoT ecosystems. Both IoT devices and mobile apps are two sides of a coin. They complement each other to create the third product, which is highly useful for the enterprises and enables entrepreneurs to stay ahead of the curve. Find a few ways in which IoT can affect the mobile app development.

IoT is rapidly emerging as the next giant technological leap towards global integration and interconnectivity. Combining the expansive geographic reach of Internet with the pervasiveness of everyday objects makes the Internet of Things a truly global network, where everything can communicate with everything else. The applications of this technology, or rather a phenomenon, though not fully realized, are already emerging everywhere around us.

Edge computing is a means of processing data physically close to where the data is being produced, i.e. where the things and humans are — in the field area, homes, and remote offices. Since they don’t live in the cloud, we need to complement cloud computing with many forms of computing at the edge to architect IoT solutions. Since we’re referring to computing close to the source of things, data, and action, a more generic term for this type of data processing is: proximity computing. In the next year, we will see reference architectures evolve to support new application patterns for IoT that incorporate proximity computing.

As enterprises delve more deeply into IoT, there will be a growing need for an operational intelligence-oriented data analyst as many IoT use-cases demand near real-time operational insight. So you can expect to see a huge uptick in demand for people who have technology and business skills related to the Internet of Things (IoT), as organizations continue to ramp up their IoT projects in a big way. As enterprises delve more deeply into IoT, there will be a growing need for an operational intelligence-oriented data analyst who is also an “AI/ML data engineer.”

The advent of IIoT (Industrial IoT) has completely changed the global IoT scenario. On one hand, IIoT drives the fourth wave of industrial revolution, and on the other hand, it contributes significantly to the unprecedented surge in the number of connected devices worldwide. Companies have started utilizing the IIoT to collect, aggregate, and analyze data to maximize efficiency and enhance productivity. The IIoT not only bring automation through machine learning but also establishes better synergy among machines to optimize output. However, implementation of IoT at your workplace requires utmost care and precision. 

Nearly half of cloud services in the enterprise are outside corporate IT’s domain, while around 47 percent of corporate data stored in cloud environments are not managed by the IT department. Cloud computing is attractive to enterprises for cost efficiency as well as its flexibility in allowing employees and customers 24/7 access to information and services. However, the security challenges can be significant. IT managers are often uncertain of which measures are meant to secure what data. Effective security for cloud data demands a holistic approach and recognizes that not all data is vital.

Today, all organizations are digital by default. Digital business inherently means utilizing new technology, connecting devices and operating platforms, embracing different ways of working, building large-scale data silos, and so on. The convergence of Internet of Things networks with what were once separate and self-contained — and therefore more manageable — systems represents a fundamental change. Coping with digital challenges and mitigating risks still represents a major burden for organizations across the board. The World Economic Forum now rates a large-scale cybersecurity breach as one of the five most serious risks facing the world today. 

Joining IoT and healthcare and leveraging connectivity to deliver care is not as easy as it seems. How can we ensure the successful marriage of IoT and healthcare? Let’s expand the notion of “pathways” to appreciate how IoT can be leveraged in healthcare delivery. The expansion includes the notion that data needs to flow across the players involved in care delivery and money needs to flow to compensate the right parties. We are on our way to professionally managed healthcare using IoT, not just consumer-grade wearables for the fitness-conscious.

Enterprises are moving cyber security and resiliency to the top of their priority lists (if they were not there already). This is especially true for enterprises building or managing IoT applications. Attacks which used IoT devices to launch distributed denial of service attacks (DDoS) are raising both consumer and business customers’ fears regarding the security of the IoT. When it comes to cybersecurity, IoT devices come with their own unique security challenges. Here are five key best practices enterprises can adopt to significantly lower the risk of a successful attack on their IoT infrastructure. 

Each year, Earth Day provides an opportunity for people around the world to consider how they can take action to protect our environment. For decades, it has encouraged people to undertake individual actions and advocate for policies. Digital technologies – in particular the IoT – can help us address the climate change challenge by accelerating the transition to a more sustainable, renewable-energy-powered economy. In particular, the IoT is a key enabling technology for an emerging concept called, “The Internet of Energy.” 

Most IoT ecosystem projects will involve multiple contributing application partners. They will also involve complex, evolving functional and non-functional requirements. To address these challenges and reduce complexity, IoT developers are now starting to embrace collaborative lifecycle management (CLM) technologies combined with the latest continuous engineering (CE) technologies. Organizations that want to ensure the success of complex IoT initiatives will need to mitigate the adverse potential of complexity-related development risk. Thankfully, these risks can be managed effectively using the latest CE/CLM tools to ensure that your IoT vision becomes a reality. Collaborative lifecycle management is a key to IoT success

IoT can be used not only to improve existing business operations but also to create new offerings and new business models. Business models require thinking through the consumption side of your offer — how it is bought and used, and the production side of the offer — how it is created and delivered. We need to think of the offer from the consumer’s lens, i.e. buyer, user, and operator. It is time to go beyond predictive maintenance and reimagining our offerings with IoT. Time to flip some tiles!

VPN evolution has transitioned the technology from point-to-point connectors that facilitate remote access to one that's based on sophisticated security multipoint connectivity. VPN evolution has taken place over the years, adapting to the networks that have been shaped by broadband connectivity, the cloud, and mobility, as well as the endpoint devices themselves. Reflecting back on the early days of VPNs and how far we have come, the evolution and the history of VPN technology can be broken down into four phases. Secure communication is one of the most important foundations for our future, and it is imperative to protect data in motion with VPN evolution.

Helping to fuel interest in data lakes are the digital transformation efforts underway at many enterprises, spurred by the emergence of the Internet of Things (IoT). The connected objects in the IoT will generate huge volumes of data. As more products, assets, vehicles and other “things” are instrumented and data ingested, it’s important that IoT data sets be aggregated in a single place, where they can be easily analyzed and correlated with other relevant data sets using big data processing capabilities. Doing so is critical to generating the most leverage and insight from IoT data.

Data clustering is the classification of data objects into different groups (clusters) such that data objects in one group are similar together and dissimilar from another group. Many of the real world data clustering problems arising in data mining applications are pair-wise heterogeneous in nature. Clustering problems of these kinds have two data types that need to be clustered together. In an industrial setting, despite collecting data from tens of thousands of sensors, less than 1% is actually utilized. We can move rapidly into Industry 4.0 by combining subject matter expertise, data collection methods and next-generation data science tools, beyond many of the "me too" products.