Businesses that move towards hyperconverged solutions are most likely to close the skills gap, release big data and drive innovation, according to a new research report by VCE, the converged platforms division of EMC.
Hyperconverged solutions represent the significant shift from companies laboriously buying and building servers to purchasing deployment-ready end-to-end systems that include all the aspects of a datacentre-ready server: connectivity, security, management, storage and virtualisation.
The move to converged infrastructure will help traditional IT departments to be re-purposed into business-savvy units that drive customer satisfaction, says Barry Cashman, EMEA VP for VCE.
VCE surveyed more than 2,700 business and IT professionals in Europe, the Middle East and Africa and came up with an extensive report detailing the current IT landscape. The report is entitled “Endangered IT: IT needs to reclaim technology or lose its voice forever.”
Cashman says the research clearly revealed what IT teams are worried about; what they are prioritising this year and where the opportunities are. It generally paints a picture of organisations where IT departments and the rest of the business are often not on the same page on a range of issues.
“The message of the report is simple: In a rapidly shifting IT landscape, businesses that manage to build cohesive digital systems that pull together all departments into rendering a single, customer-focused service, stand to benefit greatly. That is, if they stop building infrastructure as they always have, and instead invest in buying hyperconverged solutions that will ease their transition.”
Cashman says the fact that most businesses are increasingly focused on their ability to manage and extract value from the data generated in the process of selling products, rather than the products themselves, is a good thing.
“For example, 80% of those surveyed feel that implementing a more advanced and agile IT infrastructure would reduce risk and complexity and provide a solid platform for future growth. Nearly half are already training IT professionals in skills, including converged infrastructure, cloud computing and business skills.”
Cashman adds that IT needs to learn the language of business just as the rest of the business needs to learn the language of technology.
VCE suggests – and 80% of respondents agree – a scaleable, flexible, converged infrastructure would reduce risk by providing a solid foundation for business growth and innovation. “Of course, to maintain full control over the transition, CIOs need to stop spending so much time building and managing different infrastructure components.
“It’s no longer enough to just keep the lights on. Instead, they need to transform IT into an efficient, business-focused engine that can scale rapidly in response to changing business needs. This demands a modern datacentre, one that revolves around robust, software-defined, converged infrastructure. Convergence can power more agile development and increased speed to market, addressing directly some of the top IT challenges identified.”
To remain competitive in the future, the business needs to focus on developing and releasing new, value-added products and services. This means that IT needs to be free to focus on meeting business goals, and a converged infrastructure is what will enable it to do so.
The growing need for new tech
However, according to the report 68% of CIOs currently see IT in the traditional sense as a barrier to innovation. Almost two-thirds of CIOs felt that the IT team was losing its grip on the technology that is held and used across the business. The more technology is embedded, the more traditional IT becomes marginalised, a phenomenon the report calls ‘invisible IT’, not shadow IT. Cashman says power is shifting away from IT, in that ideas are being implemented there, rather than germinating there.
“They fear that this could lead to IT inhibiting, rather than enabling innovation if they do not have the right infrastructure or tools. This lack of preparation for current technological shifts could result in their businesses losing all relevance within the next three years, as their likely future competitors will be agile organisations that do not even exist yet. After all, it’s not surprising to feel out of your depth when you’re working against invisible competitors.”
In addition, many CIOs and business leaders voiced concern that they felt ill-prepared for the technological shifts taking place in the economy. Many are worried that business growth may expose their IT teams as under-prepared (68%) and may put excessive pressure on existing IT operations, damaging customer satisfaction and brand reputation (69%).
They agreed that a new infrastructure and a fresh skills set in their IT departments are needed to meet long-term needs, as technology becomes embedded across the business. But most felt they were not progressing sufficiently. This could be because all these divisions often don’t speak to each other, says Cashman.
“Even when they do, they talk in a completely different set of languages. The storage individual doesn’t understand the network perspective, and the network person doesn’t understand the server person’s problem. The languages they use are embedded in the technologies they have ownership of. CIOs are isolated both from their C-suite colleagues and from their own IT teams, sometimes lacking faith in the ability of IT professionals and infrastructure to meet emerging business needs.”
As challenging as it might be, businesses have to evolve their traditional IT infrastructure and culture to meet the challenges of big data, operational complexity and real-time business.
“Business leaders can help the IT function adapt, professionally and culturally, to the concept of IT infrastructure as an advanced, on-demand utility it can use rather than manage; something to buy rather than build. IT also needs to adapt to becoming a multi-disciplinary function, able to quickly respond to the challenges of releasing value from big data,” says Cashman.
“The time that a converged solution will save, will release IT professionals to share their expertise across the business; listening, understanding and enabling. This is the key to reclaiming IT relevance.” Cashman says IT tends to have a “build it yourself” mentality whereas business leaders “are more comfortable acquiring the building blocks for IT.”
Businesses need “cloud people”
Cashman says converged infrastructure would facilitate the re-positioning of staff in IT departments. “Before, you had a server team, a network team and a storage team. Ultimately, actually, instead of three people you need one cloud architect who is trained across all three. So there’s two jobs released.
“There are two ways of looking at this. You lay the two jobs off, or you retrain say the server administrator as the cloud administrator across the whole piece and the other two people you repurpose above the infrastructure line, up to the application line, to interact with the businesses, understand what they want and then move forward with the businesses. You need cloud people rather than siloed experts. At VCE we are increasingly asking our people to sit across various roles. For example, storage guys broadening around converged infrastructure and also software. We recognise the economics of retraining and we think our customers will too.”
Now IBM’s Watson joins IoT revolution in agriculture
Global expansion of the Watson Decision Platform taps into AI, weather and IoT data to boost production
IBM has announced the global expansion of Watson Decision Platform for Agriculture, with AI technology tailored for new crops and specific regions to help feed a growing population. For the first time, IBM is providing a global agriculture solution that combines predictive technology with data from The Weather Company, an IBM Business, and IoT data to help give farmers around the world greater insights about planning, ploughing, planting, spraying and harvesting.
By 2050, the world will need to feed two billion more people without an increase in arable land . IBM is combining power weather data – including historical, current and forecast data and weather prediction models from The Weather Company – with crop models to help improve yield forecast accuracy, generate value, and increase both farm production and profitability.
Roric Paulman, owner/operator of Paulman Farms in Southwest Nebraska, said: “As a farmer, the wild card is always weather. IBM overlays weather details with my own data and historical information to help me apply, verify, and make decisions. For example, our farm is in a highly restricted water basin, so the ability to better anticipate rain not only saves me money but also helps me save precious natural resources.”
New crop models include corn, wheat, soy, cotton, sorghum, barley, sugar cane and potato, with more coming soon. These models will now be available in the Africa, U.S. Canada, Mexico, and Brazil, as well as new markets across Europe and Australia.
Kristen Lauria, general manager of Watson Media and Weather Solutions at IBM, said: “These days farmers don’t just farm food, they also cultivate data – from drones flying over fields to smart irrigation systems, and IoT sensors affixed to combines, seeders, sprayers and other equipment. Most of the time, this data is left on the vine — never analysed or used to derive insights. Watson Decision Platform for Agriculture aims to change that by offering tools and solutions to help growers make more informed decisions about their crops.”
The average farm generates an estimated 500,000 data points per day, which will grow to 4 million data points by 2036 . Applying AI and analysis to aggregated field, machine and environmental data can help improve shared insights between growers and enterprises across the agriculture ecosystem. With a better view of the fields, growers can see what’s working on certain farms and share best practices with other farmers. The platform assesses data in an electronic field record to identify and communicate crop management patterns and insights. Enterprise businesses such as food companies, grain processors, or produce distributors can then work with farmers to leverage those insights. It helps track crop yield as well as the environmental, weather and plant biologic conditions that go into a good or bad yield, such as irrigation management, pest and disease risk analysis and cohort analysis for comparing similar subsets of fields.
The result isn’t just more productive farmers. Watson Decision Platform for Agriculture could help a livestock company eliminate a certain mold or fungus from feed supply grains or help identify the best crop irrigation practices for farmers to use in drought-stricken areas like California. It could help deliver the perfect French fry for a fast food chain that needs longer – not fatter – potatoes from its network of growers. Or it could help a beer distributor produce a more affordable premium beer by growing higher quality barley that meets the standard required to become malting barley.
Watson Decision Platform for Agriculture is built on IBM PAIRS Geoscope from IBM Research, which quickly processes massive, complex geospatial and time-based datasets collected by satellites, drones, aerial flights, millions of IoT sensors and weather models. It crunches large, complex data and creates insights quickly and easily so farmers and food companies can focus on growing crops for global communities.
IBM and The Weather Company help the agriculture industry find value in weather insights. IBM Research collaborates with start up Hello Tractor to integrate The Weather Company data, remote sensing data (e.g., satellite), and IoT data from tractors. IBM also works with crop nutrition leader Yara to include hyperlocal weather forecasts in its digital platform for real-time recommendations, tailored to specific fields or crops. IBM acquired The Weather Company in 2016 and has since been helping clients better understand and mitigate the cost of weather on their businesses. The global expansion of Watson Decision Platform for Agriculture is the latest innovation in IBM’s efforts to make weather a more predictable business consideration. Also just announced, Weather Signals is a new AI-based tool that merges The Weather Company data with a company’s own operations data to reveal how minor fluctuations in weather affects business.
The combination of rich weather forecast data from The Weather Company and IBM’s AI and Cloud technologies is designed to provide a unique capability, which is being leveraged by agriculture, energy and utility companies, airlines, retailers and many others to make informed business decisions.
 The UN Department of Economic and Social Affairs, “World Population Prospects: The 2017 Revision”
 Business Insider Intelligence, 2016 report: https://www.businessinsider.com/internet-of-things-smart-agriculture-2016-10
What if Amazon used AI to take on factories?
By ANTONY BOURNE, IFS Global Industry Director for Manufacturing
Amazon recently announced record profits of $3.03bn, breaking its own record for the third consecutive time. However, Amazon appears to be at a crossroads as to where it heads next. Beyond pouring additional energy into Amazon Prime, many have wondered whether the company may decide to enter an entirely new sector such as manufacturing to drive future growth, after all, it seems a logical step for the company with its finger in so many pies.
At this point, it is unclear whether Amazon would truly ‘get its hands dirty’ by manufacturing its own products on a grand scale. But what if it did? It’s worth exploring this reality. What if Amazon did decide to move into manufacturing, a sector dominated by traditional firms and one that is yet to see an explosive tech rival enter? After all, many similarly positioned tech giants have stuck to providing data analytics services or consulting to these firms rather than genuinely engaging with and analysing manufacturing techniques directly.
If Amazon did factories
If Amazon decided to take a step into manufacturing, it is likely that they could use the Echo range as a template of what AI can achieve. In recent years,Amazon gained expertise on the way to designing its Echo home speaker range that features Alexa, an artificial intelligence and IoT-based digital assistant.Amazon could replicate a similar form with the deployment of AI and Industrial IoT (IIoT) to create an autonomously-run smart manufacturing plant. Such a plant could feature IIoT sensors to enable the machinery to be run remotely and self-aware; managing external inputs and outputs such as supply deliveries and the shipping of finished goods. Just-in-time logistics would remove the need for warehousing while other machines could be placed in charge of maintenance using AI and remote access. Through this, Amazon could radically reduce the need for human labour and interaction in manufacturing as the use of AI, IIoT and data analytics will leave only the human role for monitoring and strategic evaluation. Amazon has been using autonomous robots in their logistics and distribution centres since 2017. As demonstrated with the Echo range, this technology is available now, with the full capabilities of Blockchain and 5G soon to be realised and allowing an exponentially-increased amount of data to be received, processed and communicated.
Manufacturing with knowledge
Theorising what Amazon’s manufacturing debut would look like provides a stark learning opportunity for traditional manufacturers. After all, wheneverAmazon has entered the fray in other traditional industries such as retail and logistics, the sector has never remained the same again. The key takeaway for manufacturers is that now is the time to start leveraging the sort of technologies and approaches to data management that Amazon is already doing in its current operations. When thinking about how to implement AI and new technologies in existing environments, specific end-business goals and targets must be considered, or else the end result will fail to live up to the most optimistic of expectations. As with any target and goal, the more targeted your objectives, the more competitive and transformative your results. Once specific targets and deliverables have been considered, the resources and methods of implementation must also be considered. As Amazon did with early automation of their distribution and logistics centres, manufacturers need to implement change gradually and be focused on achieving small and incremental results that will generate wider momentum and the appetite to lead more expansive changes.
In implementing newer technologies, manufacturers need to bear in mind two fundamental aspects of implementation: software and hardware solutions. Enterprise Resource Planning (ERP) software, which is increasingly bolstered by AI, will enable manufacturers to leverage the data from connected IoT devices, sensors, and automated systems from the factory floor and the wider business. ERP software will be the key to making strategic decisions and executing routine operational tasks more efficiently. This will allow manufacturers to keep on top of trends and deliver real-time forecasting and spot any potential problems before they impact the wider business.
As for the hardware, stock management drones and sensor-embedded hardware will be the eyes through which manufacturers view the impact emerging technologies bring to their operations. Unlike manual stock audits and counting, drones with AI capabilities can monitor stock intelligently around production so that operations are not disrupted or halted. Manufacturers will be able to see what is working, what is going wrong, and where there is potential for further improvement and change.
Knowledge for manufacturing
For many traditional manufacturers, they may see Amazon as a looming threat, and smart-factory technologies such as AI and Robotic Process Automation (RPA) as a far off utopia. However, 2019 presents a perfect opportunity for manufacturers themselves to really determine how the tech giants and emerging technologies will affect the industry. Technologies such as AI and IoT are available today; and the full benefits of these technologies will only deepen as they are implemented alongside the maturing of other emerging technologies such as 5G and Blockchain in the next 3-5 years. Manufacturers need to analyse the needs which these technologies can address and produce a proper plan on how to gradually implement these technologies to address specific targets and deliverables. AI-based software and hardware solutions will fundamentally revolutionise manufacturing, yet for 2019, manufacturers just have to be willing to make the first steps in modernisation.