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We believe technology-driven business transformations will continue to disrupt additional industries over the next decade. This disruption creates situations where SME enterprises will be best-suited to exploit opportunities for growth in serving customers with new conveniences, superior customer experience and creative business models. Simultaneously, Emergis believes that digital-driven high-tech innovations will create new start-ups in health, bio sciences, financial services, retail, CPG, and TMT (Technology, Media & Telecommunications).
We view the Internet-driven evolution of technology innovation as three distinct phases of IT infrastructure and applications driving new businesses and innovation in traditional industries. 1993-2006 was the era of Web 1.0. We define it as IT infrastructure (webware, middle-ware, servers, storage) and massively scalable architecture enabling Once-turn-on, Always-on services such as search, e-mail, chats, maps, e-commerce, online publishing & sharing. Web 1.0 further opened enterprise compute and communications (beyond client-server) and drove measurable productivity and operational efficiencies. It led to new business models that disrupted traditional industries in retail, publishing, media and travel. Consumers and businesses gained visibility to price comparisons and gained buyer power. On the flip side, it also opened personal and enterprise info to security and privacy breach.
In 2016, we are in the midst of Web 2.0. We define Web2.0 as digital business underpinned by CASM (Cloud, Analytics, Social, Mobile) and integrated with Web 1.0 era infrastructure. While Web 2.0 is accelerating further disruption of industries previously impacted by Web1.0, it is also creating new businesses, new business models, new and more intimate ways of customer engagement, new sources of revenues across all industries.
While Web 2.0 is playing out, simultaneously, we see the building blocks of Web 3.0 emerge. We define Web 3.0 as IT infrastructure and applications underpinned by CASM and further extending into biome through nano-technologies and into inanimate objects through IOT.
Web 3.0 is characterized by a massive evolution in:
We believe, privacy and information security will continue to be not fully solved in the Web 3.0 era. Regulators will demand more stringent requirements to safeguard their citizens, leading to massive needs for security and privacy management services..
Web 1.0, Web 2.0, Web 3.0 IT infrastructure will exist together with legacy IT infrastructure for the foreseeable future. It is not possible to totally migrate IT to Web 3.0 or Web 2.0 and re-write over 150 million enterprise apps from scratch on new architecture. Simply because the costs, complexity and business continuity considerations make this proposition impractical. However, there will be new businesses built entirely on Web 2.0 or Web 3.0 architecture. Thus we see significant opportunities in the broader technology industry and in businesses launched on Web 2.0 and Web 3.0 architecture.
You may not have known Dollar Shave Club (DSC), perhaps, until you probably heard of Unilever acquiring it. DSC is a great example of explosive growth in digital businesses, their impact on their own industry and on adjacent industries. Here it is:
In both digital and non-digital businesses, core business processes running on digital platforms, transforming the value proposition of the business, for example:
In today’s fast product cycle economy, product development requires efficient collaboration and information sharing among multiple teams, sometimes spread across global time zones. A new breed of communication, collaboration and project management tools – seamlessly working across smart phones, tablets, PCs – built on cloud infrastructure and social platform architecture are enabling order of magnitude faster product development. Companies such as Slack, Atlassian are enabling this, and in the process are challenging established players. Another example, Indigo Agriculture is a bio science start-up out of Cambridge, MA. It is using microbial isolation, gene sequencing and computational biology for millions of microbes that have evolved over hundreds of millions of years across a range of climates in thousands of plant species. Indigo product development requires working with billions of data points and millions of genomes. What Indigo is doing would not be possible without the technology and cost-economics of cloud computing, big data analytics and genome sequencing.
Facebook has four platforms with over 1B active users. Google has seven platforms with over 1B users. WeChat, Line, Kakao, Twitter, to name a few, are other social platforms with billions of users. About two billion smart phones are sold annually worldwide. Social media surpasses by a multiple factor the number of active visitors (users) compared to TV, shopping malls, neighborhood shops, print subscription. This is a big deal! What is even a bigger deal is that the people on average are spending over 20 hours a week on these platforms in very intimate ways. And thus the devices people use, behavior people are developing and expectations people are acquiring are so critical to acknowledge, understand and act on for any marketing professional.
The future brands are being formed as we read, old brands are deepening their attraction via social media. Web presence not only requires websites tailored to three screens (smart phones, tablets, PCs), but also substantial participation in social media. Netflix rode the Wave of Web 1.0 and Web 2.0; Blockbuster did not. Yahoo pioneered the Web 1.0 era, but failed to define its own identity as Web 1.0 grew and Web 2.0 emerged.
While social media giveth, social media also taketh. In March 2013, after an investigative story on CCTV about Apple’s discriminatory warranty practices, almost a billion users on the Weibo, WeChat and QQ platforms in China complained loudly. Within two weeks, Apple CEO Tim Cook had to issue an apology letter on April 1, 2013 to Chinese customers. China is Apple’s biggest market – ~$40B in rev – outside the US.
Sales organizations across a wide range of industries have been dealing with age-old problem: about 30% of sales staff brings over 2/3rd of sales. Improving sales effectiveness has been the most-daunting business challenge. Beginning with Web 1.0, a new category of software – CRM – emerged that revolutionized cost-effective solutions to improve sales effectiveness.
With Web 2.0, new and more powerful and still lower cost CRM applications emerged, further improving sales effectiveness and customer experience. Gainsight provides a 360 degree view of customers and reduces churn, Zuora is enabling subscription commerce and improving AR by a factor of multiple. Consumers are using social media platforms to make pre-sales inquiries, provide feedback on product and services, and make customer grievances – loudly and virally.
While a large portion of customer support is still done through outsourcing of processes, social platforms are rapidly emerging as alternatives for customers to seek support from vendors and peer users of products/ services. Companies such as Zendesk are pioneering customer support through their cloud services and social platforms.
Social platform companies are developing AI and machine learning bots, integrated with their messaging platforms, layered with big data analytics to provide support wherever customers are – smart device, phone, social media, e-mail, apps or any other channel.
F&A processes are rapidly being transformed to automation through machine learning and AI technologies. Additionally, Fintech is transforming trade settlement, payment processing. Companies such as Zuora are integrating order processing with invoice presentation and payment processing, AR/AP is being transformed by pioneers such as Taulia, C2FO. Blackline is leading end-to-end financial closing and reporting processes with its cloud platform and shaving time from weeks to a few hours and providing real-time visibility.
Traditional BI provided hind-sight view of the business and only answered “what happened?”. We call it descriptive analytics. Web 1.0 propagation led to mashing of structured and unstructured data, and predictive analytics emerged. It enabled answering “Now what?” and “So what?” questions and companies could take forward-looking action based on almost real-time data gathered from customer behavior, product data, sales data.
Software companies such as SAS, Cognos, Infor were pioneers in the early evolution of predictive analytics. Today in the Web 2.0 environment, predictive analytics is moving to “connecting the dots” in real time and allowing organizations to take action while their customers are interacting with them. Companies such as Qlik, Tableau are leading this evolution. Companies such as Palantir are further pushing the boundaries of predictive analytics by taking multiple formats of structured and unstructured data, including images, videos, machine learning, and answering with high specificity “what is likely to happen?”, “what caused an event or series of events?”
We believe, with Web 3.0 taking a more developed shape, data itself will have intelligence and would lead to massive automation of processes that today have friction due to human or compute limitations.
The digital milk man has arrived with digital businesses providing subscription-based delivery of daily or frequently purchased items. Same day groceries delivery is gaining rapid adoption in metropolitan areas around the world. Supply-chain processes transformation is playing out on two fronts: 1) massive global networks of makers, shippers, distributors, consumers with end-to-end transparency, enabled by software and cloud technologies, 2) expansion in bricks & mortar facilities of warehouses networked with distribution infrastructure.
E-commerce market is over $1T in size, globally. As each industry is picked apart across its value-chain by entrepreneurs through digital businesses, supply chain processes will become nimble and faster. Groceries and local same day or 4-hour delivery services are further driving automation in back-end supply chain processes. Ride hailing and ride sharing services are also simultaneously morphing into local delivery services. As autonomous vehicles evolve and IoT takes hold, we can expect to be living in a world, in not too distant future, that would be unrecognizable from that of 2016.