It is well into 2017 and companies are coming up with trends that they forecast for the year. LEE NAIK, CEO of TransUnion Africa, discusses the tech trends that matter to local businesses.
It’s well into 2017 and you’ve been bombarded with more trends pieces than you know what to do with. From the many articles covering the CES and Davos to the analyses by the likes of Accenture, McKinsey, Deloitte and other major consultancies, there’s a lot to absorb.
I’d like to apply a more strategic viewpoint. Sound business decisions should not be made on a whim, adopted every time a new, innovative technology claims to be the future of enterprise. To make these decisions easier, I’ve closely researched the predictions of big analysts, cross-referenced it with TransUnion’s extensive bank of data, and put together a shortlist of the innovations that should be at the top of any South African executive’s priority list.
AI becomes part of our everyday lives
Artificial intelligence (AI) came of age in 2016 and will continue to steal the limelight this year. While you may not quite be able to visit an AI-powered theme park just yet, at least you’ll be able to order a pizza while you watch Westworld.
In 2017, Chatbots will dominate headlines, as companies like Starbucks and Domino’s roll out virtual baristas, with retail and banks leading the early adoption charge. Here at home, Mercedes Benz and Absa are just two of the companies that have already bought into this new technology. But before you go all in on chatbots for your organisation, just remember that the technology’s not quite yet at a level to deliver a seamless customer experience by itself.
Less discussed (though hugely significant) will be the enterprise and industry use of AI. Most common will be the use of messaging platforms like Slack and Microsoft Teams, incorporating some form of automation and chatbot functionality. And this is just the start: from reporting to research, the automation of knowledge work is already well under way. IBM’s Watson is streamlining cancer diagnosis and treatment, for example.
The Internet of Things comes home (but might bring a nasty surprise)
The advances in machine learning are set to have another big impact – on the mainstream realisation of the Internet of Things (IoT) in the home. The likes of Alexa, Siri and other virtual assistants are nothing new, but we saw a record number of companies at the recent Consumer Electronics Show (CES) – from Ford to Whirlpool – bring out compatible products. Smart home devices have always lacked a single unifying platform, but the number of Alexa-compatible devices set to come out this year suggests we might soon have one. The competition is not too far behind either: Google Assistant is already arriving pre-installed on the Google Pixel, and Microsoft’s Cortana is expected to be included in a variety of gadgets released in 2017.
The flipside of the IoT coin will be the challenge of securing intelligent devices from opportunistic cybercriminals. From automation to as-a-service models, hackers have embraced digital innovation as eagerly, if not more so, as legitimate businesses. And the IoT revolution doesn’t just offer a whole new army of hackable devices, but connected business processes that can be exploited as well.
Gartner believes the need for an adaptive security architecture will arise in 2017. What that architecture might look like will be the question that preoccupies many enterprises this year, but it’s likely that it will be powered by machine learning, gathering actionable intelligence in real-time from a variety of sources and adapting as threats evolve. Think next-gen authentication platforms that can tell who you are, simply by analysing behaviour patterns.
Blurring the lines between digital and physical
The PlayStation VR may be the latest virtual reality headset to hit the market, and a sensation at technology trading shows, but experts agree that it’s augmented reality you should be keeping an eye on in 2017. If IDC’s prediction that 3 out of every 10 consumer Fortune 5000 companies will experiment with Augmented Reality (AR) or Virtual Reality (VR) is anything to go by, it’s clear the greatest innovation will be found at the juncture between physical and digital.
Companies will find new ways to use digital technologies to enhance real-world experiences. Take Carnival Cruises, which is rolling out the same technology behind Disney’s MagicBand onto its cruise liners. Or BMW, who’s partnered with Google to allow buyers to check out any of its cars, even if it isn’t in stock, using a virtual showroom. We’ll also see the rise of enterprise IT, as businesses explore using AR tech to boost operational efficiency. With manufacturers such as Lenovo starting to create devices aimed at the enterprise market, we’ll see more and more businesses make use of AR and VR for scenarios such as training and remote stock-taking, and general collaboration.
Betting money on Africa’s FinTech market
It’s important not to focus so much on the headline-grabbing tech – the darlings of CES and Davos – that we ignore the disruptions outside of the American and European bubbles. McKinsey & Company predicts that up to 3 billion people will connect to the digital world – a large portion of that from emerging markets.
With many in these markets still unbanked, a need has arrived for solutions that can turn them into fully digital consumers. As a result, we’re likely to see a convergence of FinTech aimed at financial inclusion and convenience that could allow emerging markets to leapfrog the West.
Keep an eye out for money transfer, POS, microfinance, and mobile payment services to emerge out of Africa this year. As for Bitcoin and other cryptocurrencies, the continent will prove a fertile testing ground for alternatives to paper money. This year sees Senegal launch its own digital currency, for example.
Stop thinking big data, start thinking smart data
For years now, businesses have been acquiring more data than they know what to do with. But even with considerable investments in analytics, companies are failing to realise the true value of their data. And a shortage of data science capabilities means businesses are seeking alternate means of securing and using information.
Cue the rise of systems and partners designed around smarter, value-driven data analytics. More and more, businesses will use platforms like Hadoop and Spark to work around their lack of data science expertise. Business Intelligence applications like Power BI and QuickSight should also gain in popularity. At the same time, we’ll see more resources spent on high-level data strategy, as businesses work out ways to use their information as the basis for new services, experiences and models. In 2017, we will see more businesses partner with specialist service providers and original equipment manufacturers (OEM) in order to accelerate the extraction of value from vast data sets.
The reinvention of corporate culture
With all these new game-changing technologies hitting us, never has the task of digitisation been more urgent. In 2017, businesses must continue to find new ways to challenge their current operational models, or run the risk of lagging behind.
There is, of course, the task of adapting to a service-based economy. Not only are we going to see businesses continue to redefine their existing models, but we’ll also see largescale changes to what we think of as corporate culture. From the gig economy and on-demand enterprise to process automation and as-a-service models, these changes will support more elastic, people-centric cultures. Whatever form these changes take, they will all be centred around one thing: unlocking human potential and creativity to be able to innovate and thrive.
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.