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Let's take a look at the top strategic Internet of Things (IoT) technology trends that Gartner, Inc. recently identified as driving digital business innovation from 2018 through 2023. “The IoT will continue to deliver new opportunities for digital business innovation for the next decade, many of which will be enabled by new or improved technologies,” said Nick Jones, research vice president at Gartner. “CIOs who master innovative IoT trends have the opportunity to lead digital innovation in their business.” In addition, CIOs should ensure they have the necessary skills and partners to support key emerging IoT trends and technologies, as, by 2023, the average CIO will be responsible for more than three times as many endpoints as this year. Analysts discussed how CIOs can lead their businesses to discover IoT opportunities and make IoT projects a success during Gartner Symposium/ITxpo. They shortlisted the 10 most strategic IoT technologies and trends that will enable new revenue streams and business models, as well as new experiences and relationships: Trend No. 1: Artificial Intelligence (AI) It's forecasted that 14.2 billion connected things will be in use in 2019, and that the total will reach 25 billion by 2021, producing immense volume of data. “Data is the fuel that powers the IoT and the organization’s ability to derive meaning from it will define their long term success,” said Jones. “AI will be applied to a wide range of IoT information, including video, still images, speech, network traffic activity, and sensor data.” The technology landscape for AI is complex and will remain so through 2023, with many IT vendors investing heavily in AI, variants of AI coexisting, and new AI-based tolls and services emerging. Despite this complexity, it will be possible to achieve good results with AI in a wide range of IoT situations. As a result, CIOs must build an organization with the tools and skills to exploit AI in their IoT strategy. Trend No. 2: Social, Legal, and Ethical IoT As the IoT matures and becomes more widely deployed, a wide range of social, legal, and ethical issues will grow in importance. These include ownership of data and the deductions made from it; algorithmic bias; privacy; and compliance with regulations such as the General Data Protection Regulation. “Successful deployment of an IoT solution demands that it’s not just technically effective but also socially acceptable,” said Jones. “CIOs must, therefore, educate themselves and their staff in this area, and consider forming groups, such as ethics councils, to review corporate strategy. CIOs should also consider having key algorithms and AI systems reviewed by external consultancies to identify potential bias.” Trend No. 3: Infonomics and Data Broking Last year’s Gartner survey of IoT projects showed 35 percent of respondents were selling or planning to sell data collected by their products and services. The theory of infonomics takes this monetization of data further by seeing it as a strategic business asset to be recorded in the company accounts. By 2023, the buying and selling of IoT data will become an essential part of many IoT systems. CIOs must educate their organizations on the risks and opportunities related to data broking in order to set the IT policies required in this area and to advise other parts of the organization. Trend No. 4: The Shift from Intelligent Edge to Intelligent Mesh The shift from centralized and cloud to edge architectures is well under way in the IoT space. However, this is not the end point because the neat set of layers associated with edge architecture will evolve to a more unstructured architecture comprising of a wide range of “things” and services connected in a dynamic mesh. These mesh architectures will enable more flexible, intelligent and responsive IoT systems — although often at the cost of additional complexities. CIOs must prepare for mesh architectures’ impact on IT infrastructure, skills, and sourcing. Trend No. 5: IoT Governance As the IoT continues to expand, the need for a governance framework that ensures appropriate behavior in the creation, storage, use and deletion of information related to IoT projects will become increasingly important. Governance ranges from simple technical tasks such as device audits and firmware updates to more complex issues such as the control of devices and the usage of the information they generate. CIOs must take on the role of educating their organizations on governance issues and in some cases invest in staff and technologies to tackle governance. Trend No. 6: Sensor Innovation The sensor market will evolve continuously through 2023. New sensors will enable a wider range of situations and events to be detected, current sensors will fall in price to become more affordable or will be packaged in new ways to support new applications, and new algorithms will emerge to deduce more information from current sensor technologies. CIOs should ensure their teams are monitoring sensor innovations to identify those that might assist new opportunities and business innovation. Trend No. 7: Trusted Hardware and Operating System Surveys invariably show that security is the most significant area of technical concern for organizations deploying IoT systems. This is because organizations often don’t have control over the source and nature of the software and hardware being utilised in IoT initiatives. “However, by 2023, we expect to see the deployment of hardware and software combinations that together create more trustworthy and secure IoT systems,” said Jones. “We advise CIOs to collaborate with chief information security officers to ensure the right staff are involved in reviewing any decisions that involve purchasing IoT devices and embedded operating systems.” Trend 8: Novel IoT User Experiences The IoT user experience (UX) covers a wide range of technologies and design techniques. It will be driven by four factors: new sensors, new algorithms, new experience architectures and context, and socially aware experiences. With an increasing number of interactions occurring with things that don’t have screens and keyboards, organizations’ UX designers will be required to use new technologies and adopt new perspectives if they want to create a superior UX that reduces friction, locks in users, and encourages usage and retention. Trend No. 9: Silicon Chip Innovation “Currently, most IoT endpoint devices use conventional processor chips, with low-power ARM architectures being particularly popular. However, traditional instruction sets and memory architectures aren’t well-suited to all the tasks that endpoints need to perform,” said Jones. “For example, the performance of deep neural networks (DNNs) is often limited by memory bandwidth, rather than processing power.” By 2023, it’s expected that new special-purpose chips will reduce the power consumption required to run a DNN, enabling new edge architectures and embedded DNN functions in low-power IoT endpoints. This will support new capabilities such as data analytics integrated with sensors, and speech recognition included in low cost battery-powered devices. CIOs are advised to take note of this trend as silicon chips enabling functions such as embedded AI will in turn enable organizations to create highly innovative products and services. Trend No. 10: New Wireless Networking Technologies for IoT IoT networking involves balancing a set of competing requirements, such as endpoint cost, power consumption, bandwidth, latency, connection density, operating cost, quality of service, and range. No single networking technology optimizes all of these, and new IoT networking technologies will provide CIOs with additional choice and flexibility. In particular, they should explore 5G, the forthcoming generation of low earth orbit satellites, and backscatter networks. Article published by Anna Hill Image credit by Getty Images, DigitalVision Vectors, miakievy Want more? 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We have seen a great deal of buzz surrounding HR analytics in the last couple of years. There have been publications across the globe covering lessons learned in HR analytics initiatives. After reading much of this content, a few observations stand out. First, getting from analyzing people data to achieving tangible results for your organization is a difficult thing to achieve. There are many initiatives in HR analytics, but when it comes to specific examples of results of this new business intelligence form, the same cases in point keep appearing. Especially, Google and its outstanding work that’s ahead of the rest. Second, highly intelligent, analytical people are active in this field of sport. But when it comes to being business savvy and adding real dollar value to your organization, the pool narrows noticeably. HR analytics are a means to an end, not the other way around. If you are passionate about data science and less about running a business, a career in science may be a better match. When reading about others’ experiences in this new field, a few basic pitfalls keep coming up. And these pitfalls I recognize from my own experience working on this subject. So here’s a look at the 5 most common mistakes when starting with HR analytics: 1. Putting the Cart before the Horse One of the first questions to ask yourself before beginning any HR analytics project is ‘why’? What is the goal of your efforts? How will your organization profit? Frequently, HR departments start working on HR analytics without a clear vision on the subject. There is so much hype that HR directors are afraid they’ll be left behind if they don’t start doing something analytical soon. In too many cases, working on analytics becomes a goal in itself. Often, new software, complex statistical techniques or new HR technology is the starting point for analytical ambitions, which is putting the cart before the horse. Business questions should always be leading, not technology. HR analytics only adds value if you can tackle a real, specific business problem. Don’t start your analytics journey working on a flashy analytics dashboard that no one needs. Work on something that will lead to real cost savings, or otherwise, better performance. Only then will you earn the trust of business leaders. 2. Ignoring Legal Risks This is simple. If your HR analytics project involves personal data about employees, serious risks concerning people’s privacy comes into play.There are rules and laws you need to comply to. You have to think of the legal consequences of what you are doing. You need to involve your colleagues from legal. Yes, this might take time and delay your initiative, but making mistakes in this area is lethal. Employees need to feel that their data is safe and handled with integrity. If you lose the trust of your colleagues, you will have a very challenging time earning it back. So get the information you need from legal, then collect and analyze data the right way without breaking any laws. 3. Lacking Balance in Your Team Meeting an expert data scientist that understands the role of HR and also convinces your CEO is a rare thing. HR analytics is a complicated field. To be successful, you need multiple types of people with varying skill sets in your talent analytics team. You need people who understand and are skilled in HR, IT, and data science. But you will also need people who understand the business side of things to bridge the traditional gap between HR and business. You can only be effective in HR analytics if you can make this assortment of people work together cohesively. This is tricky because everybody thinks their background or skills should be leading the way. In reality, you need a range of skills and ways of thinking during each phase of your project. You need razor sharp focus to keep moving ahead and not get stuck in the complex details. 4. Failing to Look Beyond the Borders of the HR Department If you are an HR enthusiast, you will be eager about the new possibilities HR analytics have to offer. For the rest of the world, your cherished HR analytics project is just another business intelligence pilot. Chances are, there have been more than 20 new projects across your organization involving data in this last year alone. Big data is red hot and not only in HR. So don’t expect your colleagues to be as over the moon as you are. Usually, I see HR professionals working on HR challenges nobody else really cares about. To get the attention of colleagues beyond the borders of HR, you have to address distinct business issues. You have to tell a convincing story about you adding value that everybody can directly understand. So always start with a real-life business concern that keeps your colleague’s up at night before you start thinking about an HR analytics approach. 5. Managing Expectations It is better to start small. You already believe in the huge potential of this thrilling new field of sports. Your colleagues from Finance or IT have yet to be convinced about the value of HR analytics. Don’t make the mistake to overpromise on your expected outcomes. HR analytics will not lead to millions of cost reductions in the first few months. In HR analytics, progress comes slowly. It is a complex and time-consuming ordeal. HR analytics project always take longer than you think, and the outcomes are not as overwhelmingly clear as you hope. So stay humble and keep a low profile. Keep your focus and work hard. Once the analytics train start to build up speed and you can show your first real results, you can start to make more noise. The Future of HR Analytics So where is this exciting new approach in HR taking us? Are HR analytics just a hype or more of the same? Considering everything that is written about this subject, I believe the real value of HR analytics is not so much in making HR more efficient or less costly. Reducing costs or risks is not the way to stand out in today’s modern age of business. Hiring and retaining the very best talent for key positions, having a highly engaged workforce, working on innovating in high-performance teams, that’s what the future holds. HR analytics gives an opportunity to finally understand the drivers behind high performance, motivation, and innovation. So I believe HR analytics should focus on improving the quality of human capital and less on cost efficiency. Article written by David Verhagen Image credit by Getty Images, DigitalVision Vectors, miakievy Want more? For Job Seekers | For Employers | For Influencers
A shrinking pool of qualified candidates surfaced as a top business risk for global executives in risk, audit, finance, and compliance, according to a recent survey by Gartner, Inc. In a time of historically low unemployment where the supply of available workers is much lower, organizations are struggling to find and retain the talent they need to meet their strategic objectives. At No. 3, behind accelerating privacy regulation and cloud computing, this is the first time talent shortage was named a top business risk in Gartner’s quarterly Emerging Risks Report . Cloud computing , which was ranked the No. 1 risk in 2Q18, remains a concern. Cybersecurity disclosure and the artificial intelligence (AI)/robotics skills gap round out the top five concerns among executives surveyed. “In this strong economic environment of significant business growth and record-low unemployment levels, the battle for talent is heating up as employees now have more bargaining power,” said Matthew Shinkman, practice leader at Gartner. “As a result, talent is harder to find and even more difficult to keep.” In the U.S. alone, the number of unfilled jobs rose by 117,000 to 6.94 million from June to July 2018, based on the most recent Job Openings and Labor Turnover Survey. And in the U.K., the unemployment rate is now at its lowest level in four decades, according to the Office of National Statistics.  As business leaders feel the squeeze, the pressure on recruiters continues to intensify. In a Gartner survey of 400 executives on their level of satisfaction with their organization’s ability to attract and retain high-performing talent in the current environment, only 26 percent reported being very satisfied or satisfied. Digital transformation initiatives have only increased this pressure by creating immense competition for workers who are skilled at navigating the increasingly digital environment. Moving From Needs-Driven to Market-Driven Sourcing To mitigate the risk of talent shortage as competition for workers continues to rise, leading organizations are shifting how they source talent. Most recruiting professionals have a needs-driven approach to finding talent, setting the sourcing strategy to fulfill the defined needs of the organization. Instead, Gartner recommends a market-driven approach that ensures the sourcing strategy adapts to evolving external labor market realities and organization needs. This approach includes the following hallmarks: 1. Confront brand weaknesses. Recognize (mis)perceptions that limit access to talent pools, and actively address them. 2. Coach prospects’ career decisions. Understand prospective candidates’ decision-making process, and act as a career coach. 3. Expand the labor market opportunity. Optimize the search criteria to redefine and expand the available talent pools. 4. Cultivate critical talent supply. Reorient learning and development to close skill gaps that exist because of digital transformation. “In today’s tight labor market, where employees have the upper hand, workers are more willing to look for a job with better pay, more generous benefits, and defined career development opportunities — or all three,” says Brian Kropp, Gartner HR practice group vice president. “To retain your best employees, companies need to better understand what matters most to them and help them see how they can advance in their careers with their current company, especially if wage growth continues to remain stagnate,” says Kropp. Article published by Anna Hill Image credit by Getty Images, Westend61 Want more? For Job Seekers | For Employers | For Influencer
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