In today’s era of global digitalization there are many examples that show that IT matters. Developments like cloud computing, the IoT and AI are proving that IT has again become a business driver, says WERNER VOGELS, CTO of Amazon.com.
How companies can use ideas from mass production to create business with data
Strategically, IT doesn’t matter. That was the provocative thesis of a much-talked-about article from 2003 in the Harvard Business Review by the US publicist Nicolas Carr. Back then, companies spent more than half of their entire investment for their IT, in a non-differentiating way. In a world in which tools are equally accessible for every company, they wouldn’t offer any competitive advantage – so went the argument. The author recommended steering investments toward strategically relevant resources instead. In the years that followed, many companies outsourced their IT activities because they no longer regarded them as being part of the core business.
A new age
Nearly 15 years later, the situation has changed. In today’s era of global digitalization there are many examples that show that IT does matter. Developments like cloud computing, the internet of things, artificial intelligence, and machine learning are proving that IT has (again) become a strategic business driver. This is transforming the way companies offer products and services to their customers today. Take the example of industrial manufacturing: in prototyping, drafts for technologically complex products are no longer physically produced; rather, their characteristics can be tested in a purely virtual fashion at every location across the globe by using simulations. The German startup SimScale makes use of this trend. The founders had noticed that in many companies, product designers worked in a very detached manner from the rest of production. The SimScale platform can be accessed through a normal web browser. In this way, designers are part of an ecosystem in which the functionalities of simulations, data and people come together, enabling them to develop better products faster.
Value-added services are also playing an increasingly important role for both companies and their customers. For example, Kärcher, the maker of cleaning technologies, manages its entire fleet through the cloud solution “Kärcher Fleet”. This transmits data from the company’s cleaning devices e.g. about the status of maintenance and loading, when the machines are used, and where the machines are located. The benefit for customers: Authorized users can view this data and therefore manage their inventories across different sites, making the maintenance processes much more efficient.
Kärcher benefits as well: By developing this service, the company gets exact insight into how the machines are actually used by its customers. By knowing this, Kärcher can generate new top-line revenue in the form of subscription models for its analysis portal.
More than mere support
These examples underline that the purpose of software today is not solely to support business processes, but that software solutions have broadly become an essential element in multiple business areas. This starts with integrated platforms that can manage all activities, from market research to production to logistics. Today, IT is the foundation of digital business models, and therefore has a value-added role in and of itself. That can be seen when sales people, for example, interact with their customers in online shops or via mobile apps. Marketers use big data and artificial intelligence to find out more about the future needs of their customers. Breuninger, a fashion department store chain steeped in tradition, has recognized this and relies on a self-developed e-commerce platform in the AWS Cloud. Breuninger uses modern templates for software development, such as Self-Contained Systems (SCS), so that it can increase the speed of software development with agile and autonomous teams and quickly test new features. Each team acts according to the principle: “You build it, you run it”. Hence, the teams are themselves responsible for the productive operation of the software. The advantage of this approach is that when designing new applications, there is already a focus on the operating aspects.
Value creation through data
In a digital economy, data are at the core of value creation, whereas physical assets are losing their significance in business models. Until 1992, the most highly valued companies in the S&P 500 Index were those that made or distributed things (for example the pharmaceutical industry, trade). Today, developers of technology (for example medical technology, software) and platform operators (social media enablers, credit card companies) are at the top. Also, trade with data contributes more to global growth than trade with goods. Therefore, IT has never been more important for strategy than it is now – not only for us, but for every company in the digital age. Anyone who wants to further develop his business digitally can’t do that today without at the same time thinking about which IT infrastructure, which software and which algorithms he needs in order to achieve his plans.
If data take center stage then companies must learn how to create added value out of it – namely by combining the data they own with external data sources and by using modern, automated analytics processes. This is done through software and IT services that are delivered through software APIs.
Companies that want to become successful and innovative digital players need to get better at building software solutions.We should ponder how we can organize the ‘production’ of data in such a way so that we ultimately come out with a competitive advantage. We need mechanisms that enable the mass production of data using software and hardware capabilities. These mechanisms need to be lean, seamless and effective. At the same time, we need to ensure that quality requirements can be met. Those are exactly the challenges that were solved for physical goods through the industrialization of manufacturing processes. A company that wants to industrialize ‘software production’ needs to find ideas on how to achieve the same kind of lean and qualitatively first-class mass production that has already occurred for industrial goods. And inevitably, the first place to look will be lean production approaches such as Kanban and Kaizen, or total quality management. In the 1980s, companies like Toyota revolutionized the production process by reengineering the entire organization and focusing the company on similar principles. Creating those conditions, both from an organizational and IT- standpoint, is one of the biggest challenges that companies face in the digital age.
Learn from lean
Can we transfer this success model to IT as well? The answer is yes. In the digital world, it is decisive to activate data-centric processes and continuously improve them. Thus, any obstacles that stand in the way of experimentation and the further development of new ideas should be removed as fast as possible. Every new IT project should be regarded as an idea that must go through a data factory – a fully equipped production site with common processes that can be easily maintained. The end-product is high-quality services or algorithms that support digital business models. Digital companies differentiate themselves through their ideas, data and customer relationships. Those that find a functioning digital business model the fastest will have a competitive edge. Above all, the barrier between software development and the operating business has to be overcome. The reason is that the success and speed and frequency of these experiments depend on the performance of IT development, and at the same time on the relevance of the solutions for business operations. Autoscout24 has gained an enormous amount of agility through its cloud solution. The company meanwhile has 15 autonomous interdisciplinary teams working constantly to test and explore new services. The main goal in all this is to have the possibility to quickly iterate experiments through the widest range of architectures, combine services with each other, and compare approaches.
In order to become as agile as Autoscout24, companies need a “machine” that produces ideas. Why not transfer the success formulas from industrial manufacturing and the principles of quality management to the creation of software?
German industrial companies in particular possess a manufacturing excellence that has been built up over many decades. Where applicable, they should do their best to transfer this knowledge to their IT, and in particular to their software development.
In many companies, internal IT knowhow has not developed fast enough in the last few years – quite contrary to the technological possibilities. Customers provide feedback online immediately after their purchase. Real-time analyses are possible through big data and software updates are generated daily through the cloud. Often, the IT organization and its associated processes couldn’t keep up. As a consequence, specialist departments with the structures of yesterday are supposed to fulfill customer requirements of tomorrow. Bringing innovative products and services quickly to market is not possible with long-term IT sourcing cycles. It’s no wonder that many of specialist departments try to circumvent their own IT department, for example by shifting activities to the cloud, which offers many powerful IT building blocks through easy-to-use APIs for which companies previously had to operate complicated software and infrastructure. Such a decentralized ‘shadow IT’ delivers no improvements. The end effect is that the complexity of the system increases, which is not efficient. This pattern should be broken. Development and Operations need to work hand in hand instead of working sequentially after each other, as in the old world. And ideally, this should be done in many projects running parallel. Under the heading of DevOps – the combination of “Development and Operations” – IT guru Gene Kim has described the core characteristics of this machinery.
Ensuring the flow
Kim argues that theorganization must be built around the customer benefit and that the flow of projects must be as smooth as possible. Hurdles that block the creation of client benefits should be identified and removed. At Amazon this starts by staffing projects with cross-functional and interdisciplinary teams as a rule. Furthermore, for the sake of agility the teams should not exceed a certain size. We have a rule that teams should be exactly the size that allows everyone to feel full after eating two (large!) pizzas. This approach reduces the number of necessary handovers, increases responsibility, and allows the team to provide customers with software faster.
The earlier client feedback flows back into the “production process”, the better. In addition, companies must ensure that every piece of feedback is applied to future projects. To avoid getting lost in endless feedback loops, this should be organized in a lean way: Obtaining the feedback of internal and external stakeholders must by no means hamper the development process.
Learning to take risks
“Good intentions never work, you need good mechanisms to make anything happen,” says Jeff Bezos. For that, you need a corporate culture that teaches employees to experiment constantly and deliver. With every new experiment, one should risk yet another small step forward behind the previous step. At the same time, from every team we need data based on predefined KPIs about the impact of the experiments. And we need to establish mechanisms that take effect immediately if we go too far or if something goes wrong, for example if the solution never reached the customer.
Anyone who has tried this knows it’s not easy to start your own digital revolution in the company and keep the momentum going. P3 advises cellular operators and offers its customers access to data that provide information about the quality of cellular networks (for example signal strength, broken connection and the data throughput) – worldwide and independent of the network operator and cellular provider. This allows the customers to come up with measures in order to expand their networks or new offerings for a more efficient utilization of their capacity. By introducing DevOps tools, P3 can define an automated process that implements the required compute infrastructure in the AWS Cloud and deploys project-specific software packages with the push of a button. Moreover, the process definition can be revised by developers, the business or data scientists at any time, for example in order to develop new regions, add analytics software or implement new AWS services. Now P3 can focus fully on its core competence, namely developing its proprietary software. Data scientists can use their freed-up resources to analyze in real time data that are collected from around the world and put insights from the analysis at the disposal of their clients
The cloud offers IT limitless possibilities on the technical side, from which new opportunities have been born. But it’s becoming ever clearer what is required in order to make use of these opportunities. Technologies change faster than people. And individuals faster than entire organizations. Tackling these challenges is a strategic necessity. Changing the organization is the next bottleneck on the way to becoming a digital champion.
Prepare your cam to capture the Blood Moon
On 27 July 2018, South Africans can witness a total lunar eclipse, as the earth’s shadow completely covers the moon.
Also known as a blood or red moon, a total lunar eclipse is the most dramatic of all lunar eclipses and presents an exciting photographic opportunity for any aspiring photographer or would-be astronomers.
“A lunar eclipse is a rare cosmic sight. For centuries these events have inspired wonder, interest and sometimes fear amongst observers. Of course, if you are lucky to be around when one occurs, you would want to capture it all on camera,” says Dana Eitzen, Corporate and Marketing Communications Executive at Canon South Africa.
Canon ambassador and acclaimed landscape photographer David Noton has provided his top tips to keep in mind when photographing this occasion. In South Africa, the eclipse will be visible from about 19h14 on Friday, 27 July until 01h28 on the Saturday morning. The lunar eclipse will see the light from the sun blocked by the earth as it passes in front of the moon. The moon will turn red because of an effect known as Rayleigh Scattering, where bands of green and violet light become filtered through the atmosphere.
A partial eclipse will begin at 20h24 when the moon will start to turn red. The total eclipse begins at about 21h30 when the moon is completely red. The eclipse reaches its maximum at 22h21 when the moon is closest to the centre of the shadow.
David Noton advises:
- Download the right apps to be in-the-know
The sun’s position in the sky at any given time of day varies massively with latitude and season. That is not the case with the moon as its passage through the heavens is governed by its complex elliptical orbit of the earth. That orbit results in monthly, rather than seasonal variations, as the moon moves through its lunar cycle. The result is big differences in the timing of its appearance and its trajectory through the sky. Luckily, we no longer need to rely on weight tables to consult the behaviour of the moon, we can simply download an app on to our phone. The Photographer’s Ephemeris is useful for giving moonrise and moonset times, bearings and phases; while the Photopills app gives comprehensive information on the position of the moon in our sky. Armed with these two apps, I’m planning to shoot the Blood Moon rising in Dorset, England. I’m aiming to capture the moon within the first fifteen minutes of moonrise so I can catch it low in the sky and juxtapose it against an object on the horizon line for scale – this could be as simple as a tree on a hill.
- Invest in a lens with optimal zoom
On the 27th July, one of the key challenges we’ll face is shooting the moon large in the frame so we can see every crater on the asteroid pockmarked surface. It’s a task normally reserved for astronomers with super powerful telescopes, but if you’ve got a long telephoto lens on a full frame DSLR with around 600 mm of focal length, it can be done, depending on the composition. I will be using the Canon EOS 5D Mark IV with an EF 200-400mm f/4L IS USM Ext. 1.4 x lens.
- Use a tripod to capture the intimate details
As you frame up your shot, one thing will become immediately apparent; lunar tracking is incredibly challenging as the moon moves through the sky surprisingly quickly. As you’ll be using a long lens for this shoot, it’s important to invest in a sturdy tripod to help capture the best possible image. Although it will be tempting to take the shot by hand, it’s important to remember that your subject is over 384,000km away from you and even with a high shutter speed, the slightest of movements will become exaggerated.
- Integrate the moon into your landscape
Whilst images of the moon large in the frame can be beautifully detailed, they are essentially astronomical in their appeal. Personally, I’m far more drawn to using the lunar allure as an element in my landscapes, or using the moonlight as a light source. The latter is difficult, as the amount of light the moon reflects is tiny, whilst the lunar surface is so bright by comparison. Up to now, night photography meant long, long exposures but with cameras such as the Canon EOS-1D X Mark II and the Canon EOS 5D Mark IV now capable of astonishing low light performance, a whole new nocturnal world of opportunities has been opened to photographers.
- Master the shutter speed for your subject
The most evocative and genuine use of the moon in landscape portraits results from situations when the light on the moon balances with the twilight in the surrounding sky. Such images have a subtle appeal, mood and believability. By definition, any scene incorporating a medium or wide-angle view is going to render the moon as a tiny pin prick of light, but its presence will still be felt. Our eyes naturally gravitate to it, however insignificant it may seem. Of course, the issue of shutter speed is always there; too slow an exposure and all we’ll see is an unsightly lunar streak, even with a wide-angle lens.
On a clear night, mastering the shutter speed of your camera is integral to capturing the moon – exposing at 1/250 sec @ f8 ISO 100 (depending on focal length) is what you’ll need to stop the motion from blurring and if you are to get the technique right, with the high quality of cameras such as the Canon EOS 5DS R, you might even be able to see the twelve cameras that were left up there by NASA in the 60’s!
How Africa can embrace AI
Currently, no African country is among the top 10 countries expected to benefit most from AI and automation. But, the continent has the potential to catch up with the rest of world if we act fast, says ZOAIB HOOSEN, Microsoft Managing Director.
To play catch up, we must take advantage of our best and most powerful resource – our human capital. According to a report by the World Economic Forum (WEF), more than 60 percent of the population in sub-Saharan Africa is under the age of 25.
These are the people who are poised to create a future where humans and AI can work together for the good of society. In fact, the most recent WEF Global Shapers survey found that almost 80 percent of youth believe technology like AI is creating jobs rather than destroying them.
Staying ahead of the trends to stay employed
AI developments are expected to impact existing jobs, as AI can replicate certain activities at greater speed and scale. In some areas, AI could learn faster than humans, if not yet as deeply.
According to Gartner, while AI will improve the productivity of many jobs and create millions more new positions, it could impact many others. The simpler and less creative the job, the earlier, a bot for example, could replace it.
It’s important to stay ahead of the trends and find opportunities to expand our knowledge and skills while learning how to work more closely and symbiotically with technology.
Another global study by Accenture, found that the adoption of AI will create several new job categories requiring important and yet surprising skills. These include trainers, who are tasked with teaching AI systems how to perform; explainers, who bridge the gap between technologist and business leader; and sustainers, who ensure that AI systems are operating as designed.
It’s clear that successfully integrating human intelligence with AI, so they co-exist in a two-way learning relationship, will become more critical than ever.
Combining STEM with the arts
Young people have a leg up on those already in the working world because they can easily develop the necessary skills for these new roles. It’s therefore essential that our education system constantly evolves to equip youth with the right skills and way of thinking to be successful in jobs that may not even exist yet.
As the division of tasks between man and machine changes, we must re-evaluate the type of knowledge and skills imparted to future generations.
For example, technical skills will be required to design and implement AI systems, but interpersonal skills, creativity and emotional intelligence will also become crucial in giving humans an advantage over machines.
“At one level, AI will require that even more people specialise in digital skills and data science. But skilling-up for an AI-powered world involves more than science, technology, engineering and math. As computers behave more like humans, the social sciences and humanities will become even more important. Languages, art, history, economics, ethics, philosophy, psychology and human development courses can teach critical, philosophical and ethics-based skills that will be instrumental in the development and management of AI solutions.” This is according to Microsoft president, Brad Smith, and EVP of AI and research, Harry Shum, who recently authored the book “The Future Computed”, which primarily deals with AI and its role in society.
Interestingly, institutions like Stanford University are already implementing this forward-thinking approach. The university offers a programme called CS+X, which integrates its computer science degree with humanities degrees, resulting in a Bachelor of Arts and Science qualification.
Revisiting laws and regulation
For this type of evolution to happen, the onus is on policy makers to revisit current laws and even bring in new regulations. Policy makers need to identify the groups most at risk of losing their jobs and create strategies to reintegrate them into the economy.
Simultaneously, though AI could be hugely beneficial in areas such as curbing poor access to healthcare and improving diagnoses for example, physicians may avoid using this technology for fear of malpractice. To avoid this, we need regulation that closes the gap between the pace of technological change and that of regulatory response. It will also become essential to develop a code of ethics for this new ecosystem.
Preparing for the future
With the recent convergence of a transformative set of technologies, economies are entering a period in which AI has the potential overcome physical limitations and open up new sources of value and growth.
To avoid missing out on this opportunity, policy makers and business leaders must prepare for, and work toward, a future with AI. We must do so not with the idea that AI is simply another productivity enhancer. Rather, we must see AI as the tool that can transform our thinking about how growth is created.
It comes down to a choice of our people and economies being part of the technological disruption, or being left behind.