8 items tagged "Internet of Things"

  • Big data vendors see the internet of things (IoT) opportunity, pivot tech and message to compete

    waterfall-stream-over-bouldersOpen source big data technologies like Hadoop have done much to begin the transformation of analytics. We're moving from expensive and specialist analytics teams towards an environment in which processes, workflows, and decision-making throughout an organisation can - in theory at least - become usefully data-driven. Established providers of analytics, BI and data warehouse technologies liberally sprinkle Hadoop, Spark and other cool project names throughout their products, delivering real advantages and real cost-savings, as well as grabbing some of the Hadoop glow for themselves. Startups, often closely associated with shepherding one of the newer open source projects, also compete for mindshare and custom.

    And the opportunity is big. Hortonworks, for example, has described the global big data market as a $50 billion opportunity. But that pales into insignificance next to what Hortonworks (again) describes as a $1.7 trillion opportunity. Other companies and analysts have their own numbers, which do differ, but the step-change is clear and significant. Hadoop, and the vendors gravitating to that community, mostly address 'data at rest'; data that has already been collected from some process or interaction or query. The bigger opportunity relates to 'data in motion,' and to the internet of things that will be responsible for generating so much of this.

    My latest report, Streaming Data From The Internet Of Things Will Be The Big Data World’s Bigger Second Act, explores some of the ways that big data vendors are acquiring new skills and new stories with which to chase this new opportunity.

    For CIOs embarking on their IoT journey, it may be time to take a fresh look at companies previously so easily dismissed as just 'doing the Hadoop thing.' 

    Source: Forrester.com, 

  • IBM vestigt 'Watson Internet of Things' hoofdkantoor in München

    IBM-Watson-IoT-HQ-300x179IBM investeert meer dan 3 miljard dollar in IoT-campus en innovatiecentrum.

    De campus zal naar verwachting duizend IBM ontwikkelaars, adviseurs, wetenschappers en ontwerpers gaan huisvesten. Met de opening gaat een investering gepaard van meer dan 3 miljard dollar: de grootste investering van IBM in Europa in 20 jaar.

    'Het Internet of Things vormt op korte termijn de grootste databron ter wereld, terwijl we momenteel met 90 procent van die data helemaal niets doen', zegt Harriet Green, general manager van IBM's nieuwe Watson IoT divisie. “Door deze data te koppelen aan IBM’s Watson technologie met haar unieke vaardigheden van op het gebied van waarneming, argumentatie en zelflerend vermogen, opent dit deuren voor bedrijven, overheden en individuen om verbanden uit hun data te halen die tot nieuwe inzichten leiden.'

    Naast het nieuwe hoofdkantoor lanceert IBM tevens vier nieuwe Watson API’s op de Watson IoT cloud:

    •Natural language processing (NLP) API. Stelt gebruikers in staat om te communiceren met toestellen en systemen via menselijke taal. Watson linkt taal aan andere databronnen die voor de juiste context zorgen. Zo kan een onderhoudsmonteur aan Watson vragen wat een bepaalde trilling in een toestel veroorzaakt. Watson zal automatisch de bedoeling achter de vraag herkennen en linken aan databronnen over bijvoorbeeld het onderhoud van het toestel en een aanbeveling doen om de trilling weg te werken.

    •Machine Learning Watson API. Automatiseert dataprocessen en monitort datasets op continue basis. Daardoor kan het systeem trends waarnemen en aanbevelingen doen wanneer een probleem zich voordoet.

    •Video and Image Analytics API. Doorzoekt ongestructureerde datasets van afbeeldingen en video’s en kan hieruit trends en patronen identificeren.

    •Text analytics API. Biedt de mogelijkheid om grote hoeveelheden tekst door te ploegen en patronen te herkennen. Denk bijvoorbeeld aan de transcripten van call centers, tweets en blogs.


    Source: Adformatie

  • Information Is Now The Core Of Your Business

    DataData is at the very core of the business models of the future – and this means wrenching change for some organizations.

    We tend to think of our information systems as a foundation layer that support the “real” business of the organization – for example, by providing the information executives need to steer the business and make the right decisions.

    But information is rapidly becoming much more than that: it’s turning into an essential component of the products and services we sell.

    Information-augmented products

    In an age of social media transparency, products “speak for themselves”– if you have a great product, your customers will tell their friends. If you have a terrible product, they’ll tell the world. Your marketing and sales teams have less room for maneuver, because prospects can easily ask existing customers if your product lives up to the promises.

    And customer expectations have risen. We all now expect to be treated as VIPs, with a “luxury” experience. When we make a purchase, we expect to be recognized. We expect our suppliers to know what we’ve bought in the past. And we expect personalized product recommendations, based on our profile, the purchases of other people like us, and the overall context of what’s happening right now.

    This type of customer experience doesn’t just require information systems; the information is an element of the experience itself, part of what we’re purchasing, and what differentiates products and services in the market.

    New ways of selling

    New technologies like 3D printing and the internet of things are allowing companies to rethink existing products.

    Products can be more easily customized and personalized for every customer. Pricing can be more variable to address new customer niches. And products can be turned into services, with customers paying on a per-usage basis.

    Again, information isn’t just supporting the manufacturing and sale of the product – it’s part of what makes it a “product” in the first place.

    Information as a product

    In many industries, the information collected by business is now more valuable than the products being sold – indeed, it’s the foundation for most of the free consumer internet. Traditional industries are now realizing that the data stored in their systems, once suitably augmented or anonymized, can be sold directly. See this article on the Digitalist magazine, The Hidden Treasure Inside Your Business, for more information about the four main information business models.

    A culture change for “traditional IT”

    Traditional IT systems were about efficiency, effectiveness, and integrity. These new context-based experiences and more sophisticated products use information to generate growth, innovation, and market differentiation. But these changes lead to a difficult cultural challenge inside the organization.

    Today’s customer-facing business and product teams don’t just need reliable information infrastructures. They need to be able to experiment, using information to test new product options and ways of selling. This requires not only much more flexibility and agility than in the past, but also new ways of working, new forms of IT organization, and new sharing of responsibilities.

    The majority of today’s CIOs grew up in an era of “IT industrialization,” with the implementation of company-wide ERP systems. But what made them successful in the past won’t necessarily help them win in the new digital era.

    Gartner believes that the role of the “CIO” has already split into two distinct functions: Chief Infrastructure Officers whose job is to “keep the lights on”; and Chief Innovation Offers, who collaborate closely with the business to build the business models of the future.

    IT has to help lead

    Today’s business leaders know that digital is the future, but typically only have a hazy idea of the possibilities. They know technology is important, but often don’t have a concrete plan for moving forward: 90% of CEOs believe the digital economy will have a major impact on their industry. But only 25% have a plan in place, and less than 15% are funding and executing a digital transformation plan.

    Business people want help from IT to explain what’s possible. Today, only 7% of executives say that IT leads their organization’s attempts to identify opportunities to innovate, 35% believe that it should. After decades of complaints from CIOs that businesses aren’t being strategic enough about technology, this is a fantastic new opportunity.

    Design Thinking and prototyping

    Today’s CIOs have to step up to digital innovation. The problem is that it can be very hard to understand — history is packed with examples of business leaders that just didn’t “get” the new big thing.  Instead of vague notions of “disruption,” IT can help by explaining to business people how to add information into a company’s future product experiences.

    The best way to do this is through methodologies such as Design Thinking, and agile prototyping using technologies should as Build.me, a cloud platform that allows pioneers to create and test the viability of new applications with staff and customers long before any actual coding.


    The bottom line is that digital innovation is less about the technology, and more about the transformation — but IT has an essential role to play in demonstrating what’s possible, and needs to step up to new leadership roles.


    Source: timoelliot.com, November 14, 2016

  • Insights from Dresner Advisory Services’ 2016 The Internet of Things and Business Intelligence Market Study

    • Sales and strategic planning teams see IoT as the most valuable.
    • IoT advocates are 3X as likely to consider big data critical to the success of their initiatives & programs.
    • Amazon and Cloudera are the highest ranked big data distributions followed by Hortonworks and Map/R.
    • Apache Spark MLib is the most known technology on the nascent machine learning landscape today.

    These and many other excellent insights are from Dresner Advisory Services’ 2016 The Internet of Things and Business Intelligence Market Study published last month. What makes this study noteworthy is the depth of analysis and insights the Dresner analyst team delivers regarding the intersection of big data and the Internet of Things (IoT), big data adoption, analytics, and big data distributions. The report also provides an analysis of Cloud Business Intelligence (BI) feature requirements, architecture, and security insights. IoT adoption is thoroughly covered in the study, with a key finding being that large organizations or enterprises are the strongest catalyst of IoT adoption and use. Mature BI programs are also strong advocates or adopters of IoT and as a result experience greater BI success. IoT advocates are defined as those respondents that rated IoT as either critical or very important to their initiatives and strategies.

    Key takeaways of the study include the following:

    • Sales and strategic planning see IoT as the most valuable today.The combined rankings of IoT as critical and very important are highest for sales, strategic planning and the Business Intelligence (BI) Competency Centers. Sales ranking IoT so highly is indicative of how a wide spectrum of companies, from start-ups to large-scale enterprises, is attempting to launch business models and derive revenue from IoT. Strategic planning’s prioritization of IoT is also driven by a long-term focus on how to capitalize on the technology’s inherent strengths in providing greater contextual intelligence, insight, and potential data-as-a-service business models.


    • Biotechnology, consulting, and advertising are the industries that believe IoT is the most important to their industries.Adoption of IoT across a wide variety of industries is happening today, with significant results being delivered in manufacturing, distribution including asset management, logistics, supply chain management, and marketing. The study found that the majority of industries see IoT as not important today, with the exception of biotechnology.


    • Location intelligence, mobile device support, in-memory analysis, and integration with operational systems are the four areas that most differentiate IoT advocates’ interests and focus.Compared to the overall sample of respondents, IoT advocates have significantly more in-depth areas of focus than the broader respondent base. The four areas of location intelligence, mobile device support, in-memory analysis, and integration with operational systems show they have a practical, pragmatic mindset regarding how IoT can contribute greater process efficiency, revenue and integrate with existing systems effectively.


    • An organization’s ability to manage big data analytics is critically important to their success or failure with IoT. IoT advocates are 3X as likely to consider big data critical, and 2X as likely to consider big data very important. The study also found that IoT advocates see IoT as a core justification for investing in and implementing big data analytics and architectures.


    • Data warehouse optimization, customer/social analysis, and IoT are the top three big data uses cases organizations are pursuing today according to the study. Data warehouse optimization is considered critical or very important to 50% of respondents, making this use case the most dominant in the study. Large-scale organizations are adopting big data to better aggregate, analyze and take action on the massive amount of data they generate daily to drive better decisions. One of the foundational findings of the study is that large-scale enterprises are driving the adoption of IoT, which is consistent with the use case analysis provided in the graphic below.


    • IoT advocates are significantly above average in their use of advanced and predictive analytics today. The group of IoT advocates identified in the survey is 50% more likely to be current users of advanced and predictive analytics apps as well. The study also found that advanced analytics users tend to be the most sophisticated and confident BI audience in an organization and see IoT data as ideal for interpretation using advanced analytics apps and techniques.


    • Business intelligence experts, business analysts and statisticians/data scientists are the greatest early adopters of advanced and predictive analytics. More than 60% of each of these three groups of professionals is using analytics often, which could be interpreted as more than 50% of their working time.


    • Relational database support, open client connectors (ODBC, JDBC) and automatic upgrades are the three most important architectural features for cloud BI apps today. Connectors and integration options for on-premises applications and data (ERP, CRM, and SCM) are considered more important than cloud application and database connection options. Multitenancy is considered unimportant to the majority of respondents. One factor contributing to the unimportance of multi-tenancy is the assumption that this is managed as part of the enterprise cloud platform.


    • MapReduce and Spark are the two most known and important big data infrastructure technologies according to respondents today. 48% believe that MapReduce is important and 42% believe Spark is. The study also found that all other categories of big data infrastructure are considered less important as the graphic below illustrates.


     Forbes, 4 oktober 2016

  • Integration Will Accelerate Internet Of Things, Industrial Analytics Growth In 2017

    • internet-of-things-cityscape-graphic-hqEnabling real-time integration across on-premise and cloud platforms often involves integrating SAP, Salesforce, third-party and legacy systems. 2017 will be a break-out year for real-time integration between SAP, Salesforce, and third party systems in support of Internet of Things and Industrial Analytics.
    • McKinsey Global Institute predicts that the Internet of Things (IoT) will generate up to $11T in value to the global economy by 2025
    • Predictive and prescriptive maintenance of machines (79%), customer/marketing related analytics (77%) and analysis of product usage in the field (76%) are the top three applications of Industrial Analytics in the next 1 to 3 years.

    Real-Time Integration Is the Cornerstone Of Industrial Analytics

    Industrial Analytics (IA) describes the collection, analysis and usage of data generated in industrial operations and throughout the entire product lifecycle, applicable to any company that is manufacturing and selling physical products. It involves traditional methods of data capture and statistical modeling. Enabling legacy, third-party and Salesforce, SAP integration is one of the most foundational technologies that Industrial Analytics relies on today and will in the future. Real-time integration is essential for enabling connectivity between Internet of Things (IoT) devices, in addition to enabling improved methods for analyzing and interpreting data. One of the most innovative companies in this area is enosiX, a leading global provider of Salesforce and SAP integration applications and solutions. They’re an interesting startup to watch and have successfully deployed their integration solutions at Bunn, Techtronic Industries, YETI Coolers and other leading companies globally.

    A study has recently been published that highlights just how foundational integration will be to Industrial Analytics and IoT. You can download the Industrial-Analytics-Report-2016-2017.pdf. This study was initiated and governed by the Digital Analytics Association e.V. Germany (DAAG), which runs a professional working group on the topic of Industrial Analytics. Research firm IoT Analytics GmbH was selected to conduct the study. Interviews with 151 analytics professionals and decision-makers in industrial companies were completed as part of the study. Hewlett-Packard Enterprise, data science service companies Comma Soft and Kiana Systems sponsored the research. All research and analysis related steps required for the study including interviewing respondents, data gathering, data analysis and interpretation, were conducted by IoT Analytics GmbH. Please see page 52 of the study for the methodology.

    Key Takeaways:

    • With real-time integration, organizations will be able to Increase revenue (33.1%), increase customer satisfaction (22.1%) and increase product quality (11%) using Industrial Analytics. The majority of industrial organizations see Industrial Analytics as a catalyst for future revenue growth, not primarily as a means of cost reduction. Upgrading existing products, changing the business model of existing products, and creating new business models are three typical approaches companies are taking to generate revenue from Industrial Analytics. Integration is the fuel that will drive Industrial Analytics in 2017 and beyond.


    • For many manufacturers, the more pervasive their real-time SAP integration is, the more effective their IoT and Industrial Analytics strategies will be. Manufacturers adopting this approach to integration and enabling Industrial Analytics through their operations will be able to attain predictive and prescriptive maintenance of their product machines (79%). This area of preventative maintenance is the most important application of Industrial Analytics in the next 1 – 3 years. Customer/marketing-related analytics (77%) and analysis of product usage in the field (76%) are the second- and third-most important. The following graphic provides an overview of the 13 most important applications of Industrial Analytics.


    • 68% of decision-makers have a company-wide data analytics strategy, 46% have a dedicated organizational unit and only 30% have completed actual projects, further underscoring the enabling role of integration in their analytics and IoT strategies. The study found that out of the remaining 70% of industrial organizations, the majority of firms have ongoing projects in the prototyping phase.
    • Business Intelligence (BI) tools, Predictive Analytics tools and Advanced Analytics Platforms will be pivotal to enabling industrial data analysis in the next five years. Business Intelligence Tools such as SAP Business Objects will increase in importance to industrial manufacturing leaders from 39% to 77% in the next five years. Predictive Analytics tools such as HPE Haven Predictive Analytics will increase from 32% to 69%. The role of spreadsheets used for industrial data analytics is expected to decline (i.e., 27% think it is important in 5 years vs. 54% today).


    • The Industrial Analytics technology stack is designed to scale based on the integration of legacy systems, industrial automation apps and systems, MES and SCADA systems integration combined with sensor-based data. IoT Analytics GmbH defines the technology stack based on four components inclouding data sources, necessary infrastructure, analytics tools, and applications. The following graphic illustrates the technology stack and underscores how essential integration is to the vision of Industrial Analytics being realized.


    • Industrial Internet of Things (IIoT) and Industry 4.0 will rely on real-time integration to enable an era of shop-floor smart sensors that can make autonomous decisions and trade-offs regarding manufacturing execution. IoT Analytics GmbH predicts this will lead to smart processes and smart products that communicate within production environments and learn from their decisions, improving performance over time. The study suggests that Manufacturing Execution System (MES) agents will be vertically integrated into higher level enterprise planning and product change management processes so that these organizations can synchronously orchestrate the flow of data, rather than go through each layer individually.


    Source: business2community.com, 19 december 2016

  • Internet of things (IoT) trends and realities: what to expect in 2017

    wat is iot of internet of things showcase 1472198180As part of our agenda of looking at the impact of technology and innovation on economic growth and development, we’ve written about the internet if things (IoT) for several years. In January 2013, we said:

    “‘Internet of things’ will have a huge impact on how businesses look at their business operations, efficiency and productivity – in the next few years it could actually help restore confidence after the global economic crisis, providing a leap forward in global productivity. Combine this with the need to interpret the huge number of data points that will be generated – the so-called ‘big-data – and automated business intelligence and reporting systems also become increasingly important. The next wave of innovation will therefore come around the internet of things, big data and business intelligence.”

    Fast forward to 2017, writing in the World Economic Forum blog, Dominic Gorecky and Detlef Zühlke of the German Research Centre for Artificial Intelligence (DFKI) say the internet of things (IoT) is already starting to affect environments of all kinds – homes, cities, travel, logistics, retail and medicine, to name just a few – and it will not stop at our factory gates, either.

    According to a recent estimation by McKinsey, the potential economic impact of IoT applications in 2025 is between US$ 3.9 and $11.1 trillion, of which $1.2 to $3.7 trillion is allotted to IoT applications within the factory environment. Also known as smart manufacturing, or Industrie 4.0 in Germany, these are fully networked manufacturing ecosystems driven by the IoT.

    Gorecky and Zühlke add that in smart manufacturing, where all ‘factory objects’ will be integrated into networks, traditional control hierarchy will be replaced by a decentralized self-organization of products, field devices and machines. Production processes have to become so flexible that even the smallest lot size can be produced cost-effectively and just in time to the customer’s individual demands. Customers are driving this development too, as they can design and order products at the click of a mouse. They can also expect products to be delivered within a few days – or even hours – and don’t want to wait weeks for goods to travel from far regions of the world where labor costs are lower.

    Despite this huge potential, the introduction of IoT technologies in the rather traditional domain of manufacturing will not happen abruptly: investment cycles are long, and robustness of processes and technologies outweigh the striving for innovation. Too many questions have to be answered first.

    As IoT technologies penetrate ever more deeply into our factories, down to the smallest piece of equipment, technology providers and factory planners must find solutions to four main problems:

    • How to assure the interoperability of systems
    • How to guarantee real-time control and predictability, when thousands of devices communicate at the same time
    • How to prevent disruptors, or competitors, taking control of highly networked production systems
    • How to determine the benefit or return on investment in IoT technologies.

    To compensate for technological uncertainty and financial risks, adequate pilot environments are needed. Here, smart manufacturing technologies and strategies can be implemented, evaluated and showcased for the first time. Smart manufacturing is a network paradigm affecting wide-ranging areas from automation to IT, from digital planning of a product to its recycling, and from smart sensors to business applications.

    There is no single-solution provider that can cover all of these aspects at once. So, for holistic solutions to emerge, there has to be a network of technology providers joining forces and competences to develop compatible solution blocks that fit the future requirements of technology users.

    As a result of all of this in a broader context beyond just manufacturing, Mike Krell, an analyst at Moor Insights & Strategy, says that 2017 will be another year of growth for the IoT — and potentially some contraction. IoT is still in its infancy in terms of dollars and deployments, and that can’t last much longer, before market frustration sets in. He says 2017 must become the year where the focus on real deployment and monetization of IoT systems, including both software and hardware.

    2017 will also be a year of contraction. There are way too many ‘platform’ and hardware providers trying to gain traction in the market. Small platform providers will either disappear or get swallowed up by ‘bigger fish’, and 2017 is likely to end with many fewer players than today. Hardware will continue to expand, but companies that only provide single or very narrow solutions will get swallowed up or disappear altogether, depending on the quality and security of their products.

    Writing in Forbes magazine, he says these are key things to watch for 2017 in IoT:

    • IoT semiconductor and sensor volumes will skyrocket. 2016 was a year of consolidation for IoT semiconductor makers. There was Broadcom and Avago (and then Broadcom jettisoning their IoT business to Cypress) and then Qualcomm swallowing up NXP (and the former Freescale in the process). Krells says that NXP is one of the best positioned IoT semi vendors, and if a deal with Qualcomm is completed, the combined company has the breadth of technologies and capacity to dominate the IoT market. ARM cores will continue to dominate IoT, and sensor manufacturers will continue to see volumes rise. He adds that 2017 may see more consolidation –Silicon Labs could grow bigger or be gobbled up.
    • The IoT platform shakeout will begin. The year started with lots of noise from new vendors with a definite slowing as 2016 came to a close. There are just too many vendors trying to push undifferentiated solutions.
    • Changes in ‘edge’ or ‘fog’ architectures will become critical to implement. The edge or the fog is the part of the network between the devices (where the data originates) and the cloud. Traditionally this had been a simple aggregation point or gateway, but that just won’t cut it for IoT. The massive amount of data generated by IoT devices will put strains on the network, requiring edge devices to get much smarter. Mainstream vendors such as Cisco Systems, Dell EMC and Hewlett Packard Enterprise recognize this and are pushing smarter IoT edge devices. These devices are, in simple terms, a combination of a server and gateway. With the increase in computation, storage and networking capabilities edge-based analytics will become a critical element in the success of IoT.
    • Telco and communication choices will continue to be messy. Telecom operators’ strategies and business models for generating revenues from IoT will continue to develop through 2017—and won’t be set by this time next year. For telcos, the battle will continue between NB-IoT and LTE-M based on region and monetization models through 2017. Infrastructure providers such as Ericsson and Huawei will increase in importance, with strong portfolios of IoT hardware and software solutions. Alternative LPWAN (lo power wide area network) technologies will become increasingly strong in niches where the bandwidth, capacity and security of 3GPP standards aren’t necessary (or cost affective). These include LoRa, Ingenu and Sigfox.
    • Regulation and standardization continue to come into focus but will evolve continuously. 2016 brought us a little closer to standards interoperability with the merger of OIC and the Allseen Alliance into the Open Connectivity Foundation. Other collaborations including ZigBee, Thread Group and Z-wave continue to move the market toward more cohesive and simpler solutions. However, there will still be a great amount of fragmentation and no clear-cut winners. Apple HomeKit and Google Weave will play a role, but how this fleshes out is anyone’s guess going into and coming out of 2017. On the regulatory front, expect to see more government interest in 2017, as IoT becomes more pervasive in smart cities, the public sector and energy.
    • Security gets its due. Security was finally taken seriously in 2016, largely because of real IoT hacks. The big denial-of-service attack in October, and the potential of a drone injecting a malicious virus via lights (from outside a building), caused great concern throughout the industry. With all the new vulnerable devices now being put into service, 2017 will see hackers continue to exploit IoT systems. Expect large scale breaches, as hackers look for newly connected devices in the energy and transportation areas.
    • Smart cities will lead the charge in IoT deployments. The awareness of what ‘smart city’ means has begun to come to the attention of residents. They value safety (smart lighting), convenience (transportation, parking) and potential cost savings (smart meters, on-demand trash pickup), and cities can deliver. Cities will continue to be strained by the need for money to support the deployment of sensors (to gather data) and the integration of citywide systems.
    • Smart home technology will become, smarter, more secure and easier to use. Amazon Echo and Google Home made great strides in 2016, both becoming more mainstream appliances in the home. However, networking bandwidth and connectivity between devices and systems is still a major problem for consumers. Networking continues to be painful. Streaming video rules the home entertainment market, and the need for increased bandwidth has put strains on home network bandwidth. Expect new announcements on mesh or mesh-like products with simpler network management in 2017. There continue to be too many applications and too many technologies to choose from to make it all work together seamlessly. Hopefully there will be some real advancements in interconnection in 2017.

    Source: thenextsiliconvalley.com, January 8, 2016

  • Nederland wordt innovatiever

    unnamedNederland wordt innovatiever. Gedurende het afgelopen jaar hebben bedrijven 2,9 procent meer radicale innovaties gerealiseerd, het hoogste niveau sinds jaren, zo blijkt uit de Erasmus Concurrentie en Innovatie Monitor in 2006 die vandaag wordt gepresenteerd.
    De sterk gestegen innovatie hangt samen met het feit dat bedrijven steeds meer worden geconfronteerd met disruptieve technologieën en nieuwe  zakelijke modellen. Hierbij valt te denken aan Big Data, Internet of things, 3D-printing, cloud technologie en robotisering. Ook de aantrekkende economie helpt een handje mee.
    Niet alle bedrijfstakken profiteren van de ontwikkelingen. De werkgelegenheid in de financiële sector en verzekeringen is relatief hard getroffen. Consumenten regelen steeds meer bankzaken online en daarvoor is minder personeel nodig. In de logistieke sector verwacht de helft van de ondervraagde bedrijven dat de vierde industriële revolutie leidt tot minder werkgelegenheid bij hun bedrijf.
    Startups zijn het meest positief over de ontwikkeling van de werkgelegenheid als gevolg van de die komende revolutie. Startups scoren in vergelijking met andere leeftijdsgroepen van bedrijven ook bovengemiddeld op tal van prestatie-indicatoren: disruptieve innovatie, medewerkerstevredenheid, enthousiasme, gevoel van geluk en lage stressniveaus.
    De regio Eindhoven voert de ranglijst aan van regio’s op radicale innovaties met een score van 9,8 procent boven het landelijk gemiddelde. De regio Twente scoort het meest positief op werkbeleving.
    De Erasmus Concurrentie en Innovatie Monitor wordt jaarlijks uitgevoerd door onderzoeksinstituut INSCOPE van Rotterdam School of Management, Erasmus University (RSM).
    Bron: Emerce, 24 november 2016
  • The mobile revolution is over. Get ready for the next big thing: Robots

    barbieThe computer industry moves in waves. We're at the tail end of one of those waves — the mobile revolution. What's next? Robots.

    But not the way you think.

    The robot revolution won't be characterized by white plastic desk lamps following you around asking questions in a creepy little-girl voice, like I saw at last week's Consumer Electronics Show in Las Vegas. That might be a part of it, but a small part. Rather, it'll be characterized by dozens of devices working on your behalf, invisibly, all the time, to make your life more convenient.

    Some people in the industry use the term "artificial intelligence" or "digital assistants." Others talk about "smart" devices. But none of these terms capture how widespread and groundbreaking this revolution will be. This isn't just about a coffee maker that knows to turn itself on when your alarm goes off, or a thermostat that adjusts to your presence.

    (And "Internet of Things" — please stop already.)

    This is about every piece of technology in your life working together to serve you. Robots everywhere, all the time. Not like the Roomba. More like the movie "Her."

    Where've we been?

    Every 10 or 15 years, a convergence of favorable economics and technical advances kicks off a revolution in computing. Mainstream culture changes dramatically. New habits are formed. Multibillion-dollar companies are created. Companies and entire industries are disrupted and die. I've lived through three of these revolutions.

    • The PC revolution. This kicked off in the 1980s with the early Apple computers and the quick-following IBM PC, followed by the PC clones. Microsoft and Intel were the biggest winners. IBM was most prominent among the big losers, but there were many others — basically, any company that thought computing would remain exclusively in the hands of a few huge computers stored in a data center somewhere. By the end, Microsoft's audacious dream of "a computer on every desk and in every home" was real.

    • The internet revolution. This kicked off in the mid 1990s with the standardization of various internet protocols, followed by the browser war and the dot-com boom and bust. Amazon and Google were the biggest winners. Industries that relied on physical media and a distribution monopoly, like recorded music and print media, were the biggest losers. By the end, everybody was online and the idea of a business not having a website was absurd.

    • The mobile revolution. This kicked off in 2007 with the launch of the iPhone. Apple and Samsung were the biggest winners. Microsoft was among the big losers, as its 20-year monopoly on personal computing finally broke.

    A couple of important points:

    First, when a revolution ends, that doesn't mean the revolutionary technology goes away. Everybody still has a PC. Everybody still uses the internet. It simply means that the technology is so common and widespread that it's no longer revolutionary. It's taken for granted.

    So: The mobile revolution is over.

    More than a billion smartphones ship every year. Apple will probably sell fewer iPhones this year than last year for the first time since the product came out. Huge new businesses have already been built on the idea that everybody will have an internet-connected computer in their pocket at all times — Uber wouldn't make sense without a smartphone, and Facebook could easily have become a historical curiosity like MySpace if it hadn't jumped into mobile so adeptly. This doesn't mean that smartphones are going away, or that Apple is doomed, or any of that nonsense. But the smartphone is normal now. Even boring. It's not revolutionary.

    The second thing to note is that each revolution decentralized power and distributed it to the individual.

    The PC brought computing power out of the bowels of the company and onto each desk and into each home. The internet took reams of information that had been locked up in libraries, private databases, and proprietary formats (like compact discs) and made it available to anybody with a computer and a phone line.

    The smartphone took those two things and put them in our pockets and purses.

    Tomorrow and how we get there

    This year's CES seemed like an "in-betweener." Everybody was looking for the next big thing. Nothing really exciting dominated the show.

    There were smart cars, smart homes, drones, virtual reality, wearable devices to track athletic performance, smart beds, smart luggage (really), and, yeah, weird little robots with anime faces and little-girl voices.

    But if you look at all these things in common, plus what the big tech companies are investing in right now, a picture starts to emerge.

    • Sensors and other components are dirt cheap. Thanks to the mobile revolution creating massive scale for the components that go into phones and tablets, sensors of every imaginable kind — GPS, motion trackers, cameras, microphones — are unimaginably cheap. So are the parts for sending bits of information over various wireless connections — Bluetooth LTE, Wi-Fi, LTE, whatever. These components will continue to get cheaper. This paves the way for previously inanimate objects to collect every kind of imaginable data and send simple signals to one another.

    • Every big tech company is obsessed with AI. Every single one of the big tech companies is working on virtual assistants and other artificial intelligence. Microsoft has Cortana and a bunch of interesting behind-the-scenes projects for businesses. Google has Google Now, Apple has Siri, Amazon has Echo, even Facebook is getting into the game with its Facebook M digital assistant. IBM and other big enterprise companies are also making huge investments here, as are dozens of venture-backed startups.

    • Society is ready. This is the most important point. Think about how busy we are compared with ten or twenty years ago. People work longer hours, or stitch together multiple part-time jobs to make a living. Parenting has become an insane procession of activities and playdates. The "on-demand" economy has gone from being a silly thing only business blogs write about to a mainstream part of life in big cities, and increasingly across the country — calling an Uber isn't just for Manhattan or San Francisco any more. This is the classic situation ahead of a computing revolution — everybody needs something, but they don't know they need it yet.

    So imagine this. In 10 years, you pay a couple-hundred bucks for a smart personal assistant, which you install on your phone as an app. It collects a bunch of information about your actions, activities, contacts, and more, and starts learning what you want. Then it communicates with dozens of other devices and services to make your life more convenient.

    Computing moves out of your pocket and into the entire environment that surrounds you.

    Your alarm is set automatically. You don't need to make a to-do list — it's already made. Mundane phone calls like the cable guy and the drugstore are done automatically for you. You don't summon an Uber — a car shows up exactly when you need it, and the driver already knows the chain of stops to make. (Eventually, there won't be a driver at all.)

    If you're hungry and in a hurry, you don't call for food — your assistant asks what you feel like for dinner or figures out you're meeting somebody and orders delivery or makes restaurant reservations. The music you like follows you not just from room to room, but from building to building. Your personal drone hovers over your shoulder, recording audio and video from any interaction you need it to (unless antidrone technology is jamming it).

    At first, only the wealthy and connected have this more automated lifestyle. "Have your assistant call my assistant." But over time, it trickles down to more people, and soon you can't remember what life was like without one. Did we really have to make lists to remember to do all this stuff ourselves?

    This sounds like science fiction, and there's still a ton of work ahead to get there. Nobody's invented the common way for all these devices to speak to each other, much less the AI that can control them and stitch them together. So this revolution is still years away. But not that far.

    If you try to draw a comparison with the mobile revolution, we're still a few years from the iPhone. We're not even in the BlackBerry days yet. We're in the Palm Pilot and flip-phone days. The basic necessary technology is there, but nobody's stitched it together yet.

    But when they do — once again — trillion-dollar companies and industries will rise and fall, habits will change, and everybody will be blown away for a few years. Then, we'll all take it for granted.

    Source: Business Insider

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