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Forget millennials, think perennial

There’s a rapidly growing labour segment and it’s not millennials, writes SPENCER PITTS, chief technologist for VMware EMEA’s Digital Workspace

After years of hand wringing and think pieces about how we need to accommodate millennials, how they require a different approach to hiring, leading and developing, businesses now need to be aware of their perennial workforce. Whereas millennials are in their 20s and 30s, to be a perennial is to be over 55.

Why the new focus? Because perennials are now the fastest growing segment of workers in a number of industrialised countries. In Europe, countries like Spain, Ireland, Portugal and Italy are expected to see a significant increase in their over 55 workforces, while in the UK, over 50s now make up nearly one third of employees, up from around one in five in the early 1990s. In the US, they’re predicted to become the largest demographic in work by 2024, having been the smallest in 1994, while in the likes of Japan and South Korea it’s happening at an even faster rate. According to Statistics South Africa, the current skilled (managers, professionals, technicians) workforce in the perennial age group is higher than the skilled millennials.

The reasons for this are fairly straight forward. People are living and staying fitter for longer, pensions aren’t stretching as far, age is no longer a legal constraint in most countries, and the work we do isn’t perhaps as physically strenuous as it once was.

What that does mean, however, is that in the very near future we’re going to have workforces which range in age from 18 or 21 to late 60s and early 70s. So how do we go about accommodating these increasingly varied demographics, while contending with the changing dynamics of how people want to work, in order to get all employees as engaged and productive as possible?

The changing nature of the workforce

Increasingly diverse age ranges are just one macro factor having an impact on how we work. It’s coming at a time when expectations about how we interact with organisations, as both employee and customer, have evolved beyond all recognition. I want something now, I click a button and I get it, whether it’s a book, a car or a takeaway. Call it the Amazon/Uber effect or the consumerisation of IT – whichever we cut it, people want, and expect, to have the same level of experience, at home, at work or in a shop, irrespective of provider.

It’s a clash with the classic supply of IT equipment and services, where everyone has the same device, access to the same apps, and works in the same way.

This is no longer the experience employees want, and it doesn’t work for employers either. They want engaged and productive workforces to deliver better services to customers. Those organisations that empower employees with the apps and tools they want to do their jobs almost double the increase in service quality compared to those that don’t (17 per cent versus 9 per cent), according to a VMware study with Forbes.

Once enterprises understand that, they start to look at how they design their workplaces in ways that enable a less restrictive, but still controlled, approach to working. By doing so, they are able to deliver multiple working approaches to their staff – so the perennial can work in one way, the millennial in another if they chose, but the output and results remain the same.

They can also unlock new approaches to roles which can create a real differentiator – the smart colleague.

Why millennials and perennials don’t matter – but the smart colleague does

Consider a supermarket. It’s where many of us have our first experience of work, as sullen teenagers tasked with stacking shelves and managing checkouts. To be honest, while the labour might be cheap, the customer experience matches the lack of vision and thus investment in this role – perhaps one of blank stares and surly responses when asked if a certain product is in stock, or where something can be found. A few years ago, that might be acceptable, but with the retail landscape in constant flux, and consumers more generally more than twice as likely to recommend a company or brand based on the quality of service (66 per cent) than they are on price (31 per cent) according to one report, established players need new ways of differentiating..

To be honest, the experience we get is the result of years of not placing value in these roles. What if we started to? We’re talking about retail, but it could just as easily apply to travel, transport, healthcare, banking. What if we make these front-line roles aspirational, rather than something to endure?

How do we do that? By empowering employees. Give them the tools to know what’s happening at any given moment. That means technology, but not simply behind a till or workstation. On the floor, getting to customers rather than making the customer find them. How much better would a train cancellation, or stock issue, be for those wanting to use the service if employees were able to proactively engage with them, rather than be forced into queues. Using mobile devices with chatbots, for example, a worker can engage with the customer and provide guidance, see if something is in stock or on time, offer alternatives and act as a point of sale in the right circumstances. The customer receives a consistent, positive experience, delivered through a human touch enhanced by technology – in other words, a smart colleague.

Not only does this improve the customer experience, it stands out as a real employment differentiator. It upends the way we perceive certain roles. Suddenly it’s not about cheap labour, but about having the right skills, and the compensation to reflect that. It might be that rather than natural progression meaning moving away from the shop floor, it’s actually moving on to the shop floor and becoming a smart colleague.

It’s not a route that is only for perennials, or that millennials are barred from, but one that is designed with the customer in mind, and then asks who we have that fulfils that role’s criteria.

Employee, not platform, choice

It’s time for the worker to dictate how they work, not be dictated to by the platform. That could mean it’s perennials on the shop floor with a tablet, millennials in an office with a desktop. Whatever it looks like, every single person deserves the same consideration and access to the devices and apps they need to do their job. It’s the only way to ensure improvement in productivity and engagement and, most importantly, a better experience for the customer.


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:

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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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