Trends Identified
Redefine winning: The new rules for sports brands
A new global generation of fans and customers has emerged, with new tastes and new expectations, shifting definitions of what sports brands actually are. From the rise of eSports to the transforming face of fandom, there are new rules and new winners. From fields to phones, all sports are increasingly digital. And digital distinctiveness is ever more important—to stand for something can mean everything to the next generation.
2019
The top trends for brands to watch in 2019
Landor
Every company is a wellness company
Every brand should provide appropriate solutions for supporting physical and/or mental wellness. All companies—from retail to real estate—should offer some degree of a wellness experience to maintain a competitive advantage. Wellness options include physical health programs as well as offerings that support mental health and balance, providing stress relief or even addressing issues such as social isolation.
2019
The top trends for brands to watch in 2019
Landor
Marketing and HR: unlikely allies
Brand marketers and HR join forces to drive greater value from the inside out, from employee to customer.As demand for more connectivity increases across all touchpoints in our lives, the push for end-to-end experience design will require closer relationships between people and product. Employee engagement, employee satisfaction, and employee retention are key to those relationships. Marketing and HR departments that partner together and blur traditional functional siloes are better positioned to attract, engage, and outperform their competition.With the rise in demand for innovative, creative, and branded employee experiences, leaders from HR and marketing will be 2019’s most critical power team. This new emphasis on the integration between customer experience and employee experience will require diversifying and attracting new types of talent to those roles.
2019
The top trends for brands to watch in 2019
Landor
Don’t get stuck in the middle
Brands must strategically commit to either a high-end or low-fidelity value proposition. We are seeing a new polarity in brands: companies offer either a low-cost, low-fidelity value or a high-end experience. Consumers will pay a premium for brands that provide a unique über-experience but they also want brands that provide what they want at a low cost. Even mainstream brands need to offer unique experiences in order to influence engagement and commitment and to drive repeat purchase. In 2019, brands that operate in the middle, offering utilitarian value without a distinct point of difference, will die.
2019
The top trends for brands to watch in 2019
Landor
Technologies are converging across multiple industries
"The financial services industry pioneered technology that enables very high speed marketplaces and machine-to-machine communications. Some of these technologies are now being applied in other industries as well as in non-financial markets everywhere. Take general-purpose time series databases and Field Programmable Gate Array (FPGA), software embedded on hardware to allow a much more deterministic speed, as examples. These technologies have been essential to financial services firms for some time. Now cloud providers are deploying both, and automakers are using FPGA within their vehicle systems. Simultaneously, the financial services industry is looking at how other industries are leveraging technology to increase efficiency, reduce risk, improve customer service and gain competitive advantage. To illustrate, the Internet of Things (IoT) is taking machine-to-machine communications to the next level in many areas including agriculture and supply chain management. GPUs used in gaming are enabling machine learning, which is being applied across all industries. Financial firms are moving away from technology islands and leveraging technology architectures and designs in their core infrastructure that are similar to those used in other industries. Examples include distributed global connectivity solutions used in telecommunications, and global networks and platforms that have been within the purview of Google and Facebook. Tech convergence is all about applying technology in creative ways to solve problems, accelerate innovation and meet customer needs. Nasdaq is working constantly to spot new trends and exploring opportunities to adopt new technologies where appropriate. "
2019
NASDAQ DECODES: TECH TRENDS 2019 -The technology trends that are driving the world of markets forward
Nasdaq
Open source is enabling community problem solving and differentiation
Often a problem is widely experienced by many different firms. Instead of solving it individually and sub-optimally, it makes sense to band together and solve it as a community. The open source model enables companies to tap into a community dedicated to building modern software, and to align with vibrant, active projects. As such, companies can accelerate innovation on the differentiating parts of their platform while leveraging the underlying foundational innovation of the broader open source community. The open source model lowers costs and in some cases achieves vendor independence. Notably, the cloud providers’ embrace of open source is leading to lower cost for additive cloud services as well as more robust competition. Open source also helps to attract the next generation of talent, who want to work on cutting-edge projects and have a positive impact on the world. Linux, an open source solution that modernized and replaced an outdated alternative, is a great success story. But not all projects achieve that level of success, and it is important to identify which ones are likely to remain vibrant and viable. One indicator is when the founders remain involved and the project is growing, as in the case of Confluent and Databricks with Apache Spark and Apache Kafka. Another positive sign is when open source projects are widely adopted across the major cloud providers, such as Docker and Apache Spark. Perhaps one misperception is that the acquisition risk is lower with open source technology. IBM bought Red Hat recently, and VMWare bought Heptio. As a result, companies that have decided to migrate toward an open source technology may find themselves bound to a large incumbent vendor once again. If this trend continues, the full benefits of tapping into open source may not be long-lasting. Moreover, some new license frameworks prohibit companies from reselling what they have built on open source. Given these trends, Nasdaq plans to contribute to a select group in the open source community. In particular, open source makes it easier for exchange customers to access data and derive insights from it in real time. If market participants handle data in a common way and with a common set of tools, individual firms do not have to devote resources to building those tools. Importantly, data can be shared in a way that does not compromise security and integrity to the benefit of all.
2019
NASDAQ DECODES: TECH TRENDS 2019 -The technology trends that are driving the world of markets forward
Nasdaq
Innovation in the cloud is prolific
Innovation in cloud product offerings has been prolific as cloud providers compete to gain market share. Two significant advances over the past year are the integration of time series databases and the introduction of parallel streaming in milliseconds, giving companies a comprehensive view of activity like never before. Specifically, Apache Spark is a fast, in-memory data processing engine with development APIs to allow data workers to efficiently execute streaming, machine learning or SQL workloads that require fast, iterative access to datasets. Apache Kafka is a community distributed streaming platform capable of handling trillions of events per day. Both technologies are available in the cloud, and will be foundational for next generation surveillance, risk management and generally keeping up with the high-speed information on trading and clearing systems. It is notable that the cloud providers are embracing and supporting open source alternatives in addition to the enterprise software and proprietary solutions that are available currently. Importantly, customers are benefitting in terms of better availability and cost effectiveness of product. Some cloud providers have conceived of products that extend their offering to the customer’s premises. Other offerings allow large customers with many accounts the ability to give their employees autonomy while still maintaining control. Regulatory compliance is a key consideration for companies, and concerns about data residency are driving some global players toward a true multi-cloud offering. One implication of GDPR, for example, is that companies may not be willing to cross borders with their products and data if a cloud provider has not built out in Europe and in the company’s region. In many firms, the multi-cloud strategy is still taking shape, and the fear of traditional vendor lock-in is ever present. That said, open source foundational technologies as well as emerging ones such as Apache Kafka may be adopted across all major cloud providers. For now, firms appear to be adopting the leading cloud provider in their region plus a second one, but the right cloud strategy is a matter of perspective. For technology providers, having a multi-cloud strategy is important for product distribution and customer reach. Many financial firms, however, are still operating in a hybrid cloud mode, focusing on connecting to one cloud provider as well as their own data centers. Nasdaq will continue to monitor progress in this area.
2019
NASDAQ DECODES: TECH TRENDS 2019 -The technology trends that are driving the world of markets forward
Nasdaq
Alternative data, machine learning and artificial intelligence are a powerful combination
Enterprises need to become data driven to succeed in the current business environment. The ability to make both structured, unstructured and alternative datasets actionable can be a significant differentiator. In some cases it is necessary just to stay relevant. This is true across all industries, including finance. Traditionally, investor analysis involved looking at a company’s 10Ks and 10Qs, market data and the technical analysis of the trading activity. Nowadays, investors see an opportunity to use alternative datasets from sources such as Quandl to make better decisions. For example, they might look at month-over-month sales and compare those figures to the company’s peer group, and track the company’s supply chain for insight into future production flows, sales and sources of risk. Clearly, alternative datasets, analytics, and machine learning/ artificial intelligence (AI) are a powerful combination. The advancements in AI are coming rapidly. New techniques such as reinforcement learning as well as generative adversarial networks (GANs), which are a type of deep learning neural network, are starting to attract attention. They are also extending capabilities beyond what was possible with standard machine learning and deep learning algorithms. GANs for instance will allow AI to compete with itself to come up with an optimal model in real time, resulting in greater accuracy. A potential application is in risk management. All these technology enhancements have not brought us much closer to having a generalized AI (capable of super-humanlike intelligence across any subject). However, companies are achieving success by focusing on narrow AI applications where an algorithm can be trained to do one thing extremely well, surpassing the capabilities of what a human could do on their own. Financial firms are doing this to detect spoofing behavior or risky trading activity. For example, they use these narrow AI algorithms to build applications that are much more sophisticated and accurate than their traditional counterparts. Generalized AI – the ability for a machine to successfully perform any intellectual task that a human being can – is still about a decade away. Yet it is becoming easier to interact with Siri, Alexa and Google Assistant, and every question people ask is another narrow AI application. Before long, it will be possible to put together millions of questions and answers, drawing us farther down the path to generalized AI – especially as the technology improves.Until then, the greatest opportunity and challenge is knowing the right narrow AI applications to develop. Commercial success is dependent on having a clear understanding of how, when and why people will use something new rather than relying on their tried and tested human intelligence. Behavioral science methods are becoming recognized as the differentiator to deliver this understanding, and the way forward could be through “collaborative intelligence”, involving a reimagining of people and machines working together. Achieving this requires behavioral scientists to do a new depth of analysis of clients’ cognitive and manual working processes. This ensures the best of human and machine capabilities can be leveraged to deliver this new way of working. In the meantime, Nasdaq’s strategy is to build a community of data suppliers and connect them with a community of data consumers, and then provide the services they need to make the data actionable. As we build up our data repositories, and we connect them to Nasdaq Financial Framework, those datasets and technologies will become available to an array of market participants.
2019
NASDAQ DECODES: TECH TRENDS 2019 -The technology trends that are driving the world of markets forward
Nasdaq
Blockchain projects produce early results
Many financial institutions and blockchain/ distributed ledger technology labs have been working on proof of concept (PoC) and pilot projects, and some are starting to produce early results. A goal of this work is for parties to form consortia and set up commercial networks on shared infrastructure based on the blockchain. Multiple blockchain technologies are now emerging with different implementations and consensus algorithms. As certain projects may require interoperability between these different implementations, Nasdaq recently completed a PoC with the Singapore Exchange (SGX) and the Monetary Authority of Singapore (MAS) demonstrating cross-blockchain settlement. This indicates that blockchain can provide a supporting role in the next generation CSD and the transfer of digital asset ownership. The emergence of different types of tokens is another trend. Some link directly to a fiat currency, while others are tokenized assets. In response, regulators worldwide are trying to build a legal framework for payment, security and utility tokens. Going forward, blockchain will likely be used as a solution for managing new types of financial and non-financial assets in markets everywhere – potentially including real estate, insurance and loyalty points. The token ecosystem will support the entire life cycle of the asset – from issuance and price discovery to execution and settlement, and perhaps corporate actions. Payments will either be done on the same network, via a link to an external payment network such as T2S or Swift, or via a utility settlement coin. Yet, some important questions remain unanswered. Who will take on the custodial aspects of dematerialized physical assets and digitized tokens on a blockchain, and manage know your customer and anti-money laundering compliance? The traditional custodians could assume that role, but disrupters could appear in markets that do not have custodians. Another question is who will be the arbitrator if and when a smart contract goes wrong? The smart contract hype cycle has nearly peaked, and the trough is about to begin. Technologists need to think about where smart contracts make sense and whether the programming languages should be Turing complete so they can run any program given enough time and memory. In the next few years, expect to see the major cloud providers supply the infrastructure for blockchain, and blockchain software companies consolidate as funding becomes more difficult.
2019
NASDAQ DECODES: TECH TRENDS 2019 -The technology trends that are driving the world of markets forward
Nasdaq
Cryptographic technologies are ensuring data integrity
Regulations such as GDPR in Europe and the misuse of personal information on social media highlight the importance of trust in a system where data is shared between different parties. Yet data needs to be protected in a way that adds value to the end user. Financial firms’ data is often shared internally and externally. Many workflows are regulated, and firms must follow a proof of process when it comes to the custody and provenance of data. They must demonstrate to auditors, regulators and customers that systems are functioning as prescribed, workflows are completely auditable, repeatable and immutable, and measures are established to prevent security breaches. Data lineage, a data lifecycle that includes the data’s origins and where it moves over time, is becoming more critical and can become a competitive advantage. A recent trend is to leverage cryptographic libraries, public key infrastructure, blockchain and zero knowledge proofs to record who did what, when and where in workflows in an immutable, persistent, auditable and impermeable fashion. These technologies ensure integrity starting with the first person who enters data through all its transfers and transformations. Potential applications include managing the publication of earnings reports, anti-money-laundering and know-yourcustomer compliance, risk and surveillance. The technologies could also help to improve customer service. For example, money that is held captive on margin could be freed up by allowing a prime broker and executing broker to contribute data to a secure multiparty compute service that calculates a credit score. That could help to reduce the margin requirement. The technologies could be used to create a certificate authority in the cloud, so users could verify that the service that they are about to run came from the correct source and was unmodified in transit. Together, they could also be used as a formative technology to create a data marketplace where the fidelity, integrity and lineage is guaranteed. A zero knowledge proof is a severable technology, allowing for secure multiparty computation to occur. Let’s say two people each have a dataset that neither wants to share. But they would like a mechanism so they can contribute those datasets into a piece of compute that would transform it privately into a result that both people would find mutually beneficial. This technology would prevent data sharing, and the result would redact all information that would prescribe the origin, who owned it, or any details of it. One can imagine valuable use cases in research and development work across many industries and functions including healthcare clinical trials and supply chain management.
2019
NASDAQ DECODES: TECH TRENDS 2019 -The technology trends that are driving the world of markets forward
Nasdaq