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How digital skills boost economy

A recent study by Accenture has shown that the smarter use of digital skills and technology could boost the global economic output by up to $2 trillion by 2020.

Optimizing the use of digital skills and technologies could generate $2 trillion of additional global economic output by 2020, according to a new study by Accenture (NYSE: ACN).  The study also reveals the vast role digital plays in economic activity, with more than one-fifth of the world’s gross domestic product (GDP) attributed to some form of digital skills, capital and goods and services.

The Accenture Strategy report, Digital Disruption: the Growth Multiplier, provides a new and comprehensive measure of the scale of the digital economy in 11 major countries. It estimates the value added to GDP by hardware, software and related technologies and by workers who need these digital assets to do their jobs. It also calculates the value of intermediate digital goods and services used in production.

A little more than one-fifth (22 percent) of world output is linked to this digital economy of skills and capital. The US is the world’s most digital economy, with existing digital investments accounting for 33 percent of its output. Forty-three percent of the U.S. labour force and 26 percent of its accumulated capital are capable of supporting digital related activity. The digital economy in other markets varies from more than 30 percent in the UK and Australia to 13 percent in China.

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“Businesses and governments are turning to digital to secure faster growth amid an uncertain global economic outlook, but the size of the digital economy is no guarantee of growth,” said Mark Knickrehm, group chief executive, Accenture Strategy. “Organizations need to act aggressively in shifting the focus of their digital talent and technology from making efficiencies to creating entirely new business models. That requires not just greater digital investments, but broader organizational and cultural transformation in order to yield the greatest returns.”

The report states that in order to generate higher rates of growth, companies will need to improve their Accenture Strategy Digital Density score, which tracks the extent to which digital penetrates a country’s businesses and economy. This includes digital skills and technology, as well as broader enabling factors such as the ease of access to finance and the openness of a country’s regulatory environment.

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For example, a 10 point increase in the overall digital density of the U.S. economy would result in a $368 billion uplift to 2020 GDP, 1.8 percent higher than current forecasts. But Accenture Strategy calculates that an optimal combination of improvements to digital skills, capital and other accelerators could lift U.S. GDP by an even greater $421 billion by 2020, representing a 2.1 percent boost.   The countries with the greatest opportunity for improving their overall digital performance are Brazil (6.6 percent), Italy, (4.2 percent), China (3.7 percent) and Japan (3.3 percent).

The study shows how each national economy could best prioritize its extra efforts to achieve the greatest boost to revenues and economic output. For example, 70 percent of Brazil’s extra digital efforts should be focused on the improved application of technology, such as cloud and analytics, whereas greater efforts in digital skills would generate less of an economic return. In the US, however, just 10 percent of extra digital efforts need to be injected into technology, while a greater return will be gained from boosting digital skills and broader enabling factors.

Platform based models are the key to growth

According to the report, platform business models represent one of the greatest opportunities for digitally driven growth. These models allow organizations to create new markets and uncover value by bringing partners and customers together across a common digital platform. In many cases, platform players can enjoy strong growth without having to own or manage assets, helping them expand with low marginal costs.

While ‘born digital companies’ dominate the platform economy today, the Accenture Strategy report suggests  that traditional industry incumbents could be among the greatest beneficiaries of platform strategies by combining their customer reach and product portfolios with the networking power of the platform.

“The high growth rates experienced by many digital companies can now be enjoyed by traditional industry incumbents if they apply platform models to create an ecosystem of partners and customers in which they can offer new value added services,” said Bruno Berthon, managing director, Accenture Strategy.  “Companies need to shape their platform strategies and define their role as platform leaders or participants before aggressively forming partnerships that can deliver new value.”

The report recommends three broad actions that can improve the application of digital business models to drive higher levels of productivity and growth:

·         Prioritize digital investments based on value opportunities:  Assess carefully the balance of digital investments so that an optimal combination of improvements to skills and technology can maximize returns on digital investments

·         Compete using an industry-specific digital strategy: Be clear on which platform, what roles, and which data are fundamental to compete successfully in your industry.

·         Create the right environment for digital transformation: Improve your “digital IQ,” teaming with government to open up cross-industry relationships and change the rules of competition.

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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 [1]. 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 [2]. 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.

[1] The UN Department of Economic and Social Affairs, “World Population Prospects: The 2017 Revision”

[2] Business Insider Intelligence, 2016 report: https://www.businessinsider.com/internet-of-things-smart-agriculture-2016-10


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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.

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