Technology companies will usually start by focusing on just one thing. Apple and Microsoft made computers, Google made a search engine, Facebook made a social network. Doing one thing incredibly well is the reason they are where they are today, but there comes a point at which diversification is key.
In business, there are product companies and there are platform companies. Product companies create solutions for specific problems, package those solutions and sell them. Platform companies, on the other hand, provide solutions and products that look to transform industries. Platforms are often B2B as well as B2C, and products can be built on top of them. As companies become more digital-focused, the distinction between platform and product companies becomes less defined.
Product companies are beginning to realise the value potential of platforms and have successfully diversified to include them. Take Siemens, for instance. The German manufacturing giant offers everything from medical products to industrial-plant-related automated machines. In 2016, it added MindSphere – a cloud-based, open IoT operating system for the ‘Industrial Internet of Things’ – to its already considerable arsenal of products.
In January 2018, Mindsphere went live on Amazon Web Services (AWS), the cloud system of choice for industrial-software developers. What you have, then, is a Siemens platform operating on top of an Amazon platform – just one of the myriad partnerships between major tech companies that are driving industries such as the IoT forward.
Platforms Driving Collaboration
Amazon has an influence in just about every area of tech you could imagine, spending some $23 billion on R&D in 2017 to ensure it meets as many needs as possible. Like Siemens, it does both platform and product. Its consumer-facing products are backed by a number of platforms – solutions it hopes will position the company at the heart of future developments. As a consumer, you are all but unaware that other companies you use are underpinned by technology created by such an omnipresent giant.
At Slush 2018, held in Helsinki, Amazon’s CTO, Werner Vogels, took part in a fireside chat discussing the tech giant’s move into platform creation. He explained that, as many companies have done, it initially created platforms for its own developers to use and build products on. These then became the AWS Cloud – a “broad set of infrastructure services, such as computing power, storage options, networking and databases, delivered as a utility: on-demand, available in seconds, with pay-as-you-go pricing”.
Vogels explained that they “decided to build services and platforms, first internally, to make sure every engineer can become a data scientist or machine-learning engineer. Because, in the end, for most of these cases, it’s ‘pick an algorithm, do the training, build a model’, rather than figuring out the algorithm by itself.
“Anybody can now integrate machine-learning-based recommendation engines into their products”
“So, we’re giving multi-layer support now and we still have data scientists creating new algorithms. We then built something called Sagemaker, which allows every engineer in the world to become a data scientist. Then, we put another set of services on top of that, which are what I would call AI services – pre-built models out of the machine-learning world that help you do image recognition, video processing and automatic translations. And we’ve just launched Amazon Personalize – one of the new cloud services we’ve built that comes out of the Amazon retail world. Anybody can now integrate machine-learning-based recommendation engines into their products.”
The Shift to No-skill Development
Products such as Sagemaker could represent a new movement toward low-skill development. It’s a fully managed service that allows its users to essentially prepare and input data, pick an algorithm, train it, optimise it, then make predictions from it, which can lead to positive action. According to Vogels, Sagemaker is “quickly becoming the platform of choice for anyone who wants to do machine-learning”.
The future for Amazon’s platform-building seems to be mass scale. Already this year, reports have emerged that Amazon Web Services is expanding to cater for those with little or no development experience. According to a report from GeekWire, Amazon is building ‘low code/no code’ software-development tools that will enable anyone to create custom business applications.
“Amazon is building ‘low code/no code’ software-development tools that will enable anyone to create custom business applications”
Though some LinkedIn digging, GeekWire found that AWS engineers looking for work at other low-code/no-code companies referenced a project called AWS For Everyone as their relevant experience. AWS employees also reportedly referenced the project on their LinkedIn profiles before they began to remove that information. It is fair to speculate that Amazon is building a low-code/no-code platform, following in the footsteps of the likes of Microsoft, Google and Salesforce, which have all also offered their customers these kinds of tools. Making the platforms straightforward with no prerequisite of development experiences will open this arm of the company up to an incomparably wide audience.
If tech giants are building low-code/no-code solutions, this could change the skillset required for working with data and AI. Low-code/no-code software is a visual integrated development environment, in which users can hand-pick application components to create an app. Without writing a single piece of code, the user can design and build scalable applications for their companies.
This has potentially significant implications when it comes to the skills gap that currently exists in data science. Everyone wants to be running analytics or AI programs, but finding qualified data scientists and developers is difficult – Nesta found that four out of five data-intensive businesses are struggling to find the talent to meet growing demand. If employees no longer need extensive training to build effective applications, a company’s data programs can, in theory, be run by anyone. With that in mind, platforms such as AWS For Everyone can tap into an essentially limitless market.
“If employees no longer need extensive training to build effective applications, a company’s data programs can, in theory, be run by anyone”
What we can take from Vogels’ insight is that, for companies as big as Amazon, it’s not enough to do one or a few things very well. Giants need to consistently identify where the next big position of influence is going to be, and Amazon has pinpointed data solutions. The same can be said for the likes of Siemens, identifying IoT as a development too promising to miss out on. The average consumer will still associate Amazon with its online marketplace and Siemens with its home appliances but, behind the scenes, these companies are building for the very cutting edge of tech.
Not all diversification strategies are successful. Sometimes, tech companies try to branch out into areas they are entirely unfamiliar with and the results can vary wildly. Sony Corporation, for example, launched an insurance arm of its company in the 1980s, which today performs more profitably than its electronics arm, raking in some $9 billion between 2003 and 2013.
In 1989, Amar Bose, founder of Bose Corporation, became interested in cold fusion after witnessing scientists at a forum arguing over it rather than discussing it scientifically. He set about forming a group of scientists to investigate the claims made about cold fusion methodically. In two years they had disproved all of them, and Bose Corporation had affected the discourse around cold fusion. Microsoft also sold electronically fitted children's toys in the shape of characters like Barney the Dinosaur, but that was less well received.
Illustrations by Kseniya Forbender
To contact the editor responsible for this story:
Margarita Khartanovich at [email protected]
- How Blockchain Can Reshape Charitable Donations
- Blockchain’s Scaling Crises: Can Sidechains Be A Potential Solution?
- Hacking Blockchain: Is it Really Secure?
- Regional Strengths Are Shaping AI’s Evolution in Asia
- Credit Card vs. Bitcoin: How Do You Pay for Your Coffee?
- Do You Trust AI? This Is What You Must Understand to Do So