In the past, we have paid a lot of attention to technology and the ways in which it is changing the world.
From education to the way we communicate with each other, technology has become an important influencer and will continue to do so in the years to come. But what happens when technology harnesses the worlds biggest commodity? Big Data?
In the past, large corporations had an advantage over smaller ones in that they had significant human capital and the products to bulldozer over smaller companies. However, this is now a thing of the past because Big Data allows smaller companies to personalize their service to customers in a way that larger companies may not have the ability to.
I recently read an article on theglobeandmail.com which discusses this in detail.the article points out that today’s teeming tech environment has created a level playing field. As such, how you leverage technology is even more important to success than your ability to access capital.
The article adds that victory will belong to the enterprises that make the right investments and embrace what the digital age really means: mass personalization, creating exponential value, leveraging ecosystems and embracing risk. Using technology to satisfy these Business 4.0 demands will have more of an impact on a company’s long-term viability than any temporary infusion of cash.
The proliferation of interconnected data channels has enabled access to knowledge at a never-before-seen scale. This democratization of information, so to speak, has created unprecedented opportunities for entrepreneurs. Take the sensational success of the free messaging platform WhatsApp, which currently has more than 1.3 billion users – three times that of Twitter. Its co-founder, Jan Koum, certainly didn’t have much in the way of capital – and, for a brief period, lived off welfare. What he did have was an idea and self-taught technical skills that he gleaned from available sources. In 2014, he and his co-founder, Brian Acton, sold WhatsApp to Facebook for US$19-billion.
The article points out that the emergence of cloud computing is another example of how businesses today require less capital to compete. It has afforded them the opportunity to tap into a wealth of resources at a fraction of the cost. Everything from data storage to operational software can be accessed through the cloud. It also makes it far easier for organizations to scale up when – and not a moment before – they need to.
For software companies, the cloud has fundamentally changed the speed at which products are created. Leading organizations are using the cloud to develop and upgrade software in an agile and interactive manner. What once took at least six months to develop is being deployed to consumers in a matter of days or weeks.
The article adds that even physical products are being brought to market at expedited speeds. Cloud solutions allow companies to evaluate designs, test performance and prevent quality issues. They have also given companies without deep pockets the ability to experiment with simulations – once the exclusive territory of the biggest players. A competitor to a bank or retailer, for example, can run simulations that predict the adoption rates of a new product before ever introducing anything to the market. On the other hand, an institutional company planning a digital transformation can pre-emptively look at its impact on profitability via cloud simulations.
Relatively cheap tech solutions are making a real difference beyond commerce – they are aiding in research and development, as well as social responsibility. Harvard Medical School’s Laboratory for Personalized Medicine is speeding up research on the clinical value of new genetic tests through the use of a cloud-computing platform. Similarly, the pharma company Novartis accelerates its preclinical efforts for drug development on the public cloud.
This all makes sense. However, what happens when a big company has access to mountains of Big Data? This has been the major calls for regulation when it comes to data portability. This issue was discussed in detail in a recent article on forbes.com.
The article points out that facilitating development in Artificial Intelligence (AI) technologies forms a substantial part of the case for these kinds of regulatory interventions. As noted in a variety of reports by Accenture, the Council on Foreign Relations, the McKinsey Global Institute, the World Economic Forum, and President Obama’s Council of Economic Advisers, among others, AI has the potential to boost productivity and economic growth. However, the most dramatic advances in AI arise from a data-intensive technique known as machine learning, which requires lots of data to create, test, and “train” the algorithms underlying the AI.
The article adds that as AI-enabled technologies are becoming more important to the economy, so too are large datasets. A firm that lacks access to good data faces a substantial barrier to entering a market involving AI technologies. These potential obstacles have led some regulators to question the extent to which some firms control data; if barriers to entry are too high, entrants will be kept out, established firms will not face competitive pressure, and innovation may suffer.
Over the past several years, incumbents have made substantial investments in AI startups, including outright purchases. McKinsey Global Institute’s (“MGI”) analysis, as well as our own analysis using data from Crunchbase, indicates that venture-capital investment in AI startups grew by about 40 percent between 2013 and 2016. MGI estimates that established firms spent between $18 billion and $27 billion on internal corporate investment in AI-related projects in 2016 alone.
The article adds that in contrast, investments by AI startups appear to be heading in the opposite direction. For example, the number of seed-stage financing deals is apparently down 40 percent from a peak in the middle of 2015, and some of the decline is reportedly due to fear of established firms, particularly large, platform-oriented technology firms. However, Ian Hathaway shows that even as the number of deals has dropped, the capital invested in seed stage deals has increased.
Anecdotal evidence suggests that dominant tech platforms are aggressively assimilating apps from smaller providers, a practice that may discourage edge innovation. Some of the best evidence of the risks to innovation posed by large technology platforms comes from UT Austin’s Wen Wen and Harvard’s Feng Zhu. Wen and Zhu show that when a platform starts to appropriate features of its developers’ applications, the application developers cut back on innovations to those applications.
The article points out that despite mixed evidence on the need to introduce either new regulatory oversight of technology firms or intervention in technology markets, there have been multiple calls for such measures. For example, New York University’s Scott Galloway has called for the break-up of the “Big Four” (Amazon, Apple, Facebook, and Google), essentially arguing that they are capturing more value than they are creating, especially when considering employment and taxes. Similarly, Lina Khan of the Open Markets Institute and Yale Law School has advocated reconsidering and modifying current antitrust frameworks to address certain practices of Amazon. Others have called for the formation of a Net Tribunal, which would police discriminatory conduct by vertically integrated platform providers in favor of their own apps.
The article adds that any strategies that involve litigation and that are employed to broaden entrants’ access to large datasets—regardless of whether they adhere to a consumer-welfare antitrust standard or advocate for one that is broader—should be complemented by more forward-leaning regulatory approaches. These potentially include data portability requirements, the introduction of temporary data monopolies (followed by complete data availability), the use of trusted third parties, and blockchain-enabled technological solutions.
The debate continues.