Cognizant Technology Labs identified seven trends that businesses need to exploit to open new digital horizons. Here’s a quick look at these trends, as well as a few of our field-proven recommendations for gaining an unfair advantage on the competition.
Leading businesses are adept at uncovering insights from digital data, which we call “Code Halo thinking.” New business models are being built around real-time, predictive awareness of customer needs and trends. Expect to see an increase in automated strategic decision-making as organizations embrace cognitive computing, machine learning, natural language processing, and predictive analytics. Real-time intelligence based on Internet of Things (IoT) data will also contribute to new business models.
# 1 Develop expertise in big data analytics, modeling and data visualization, such as in-memory computing or stream processing.
# 2 Master tools that enable self-serve and on-demand analytics.
# 3 Identify key processes that would greatly benefit from taking predictive action.
Businesses increasingly use big data analytics, geolocation and historical metadata to deliver personalized, contextualized products and experiences. With more customer access to technologies like smartphone cameras and 3-D printers, this trend will grow. On-the-fly customization will become the norm, as businesses adopt beacons and other tools to push highly personalized offers, based on customers’ locations and behaviors that reveal implicit needs and desires. Businesses will need to boost data quality, ensure their supply chain capabilities can meet customization demands, and lower costs for delivering hyper-personalization.
# 1 Enable “self-customization” of products and services.
# 2 Specify which customer actions are being tracked and allow “opt-out.”
# 3 Experiment with the medium and timing of personalized offers.
Security today requires a multi-layered approach in which pervasive layers of intelligent assets protect themselves. For example, machine learning and artificial intelligence technologies can help correlate multiple events from various systems to identify the source of a breach, and adaptively learn how to counter it. Businesses need to invest in assessing, monitoring and remediating an ever-changing mix of attack vectors, and ensure ongoing cooperation from and monitoring of business partners.
# 1 Assume it’s not a matter of if, but when, the business will be compromised.
# 2 Research new technologies, such as software-defined security, homo-morphic encryption and ephemeral systems.
# 3 Consider new processes, such as integrating development, security and operations teams.
Just-in-time intelligence, especially through the IoT, will be the next competitive battlefield, as businesses race to meet expectations for immediate delivery of information, entertainment, help and product delivery. Capabilities range from proactive problem resolution for manufacturers, to remote alerts and live help for healthcare patients. Data volumes will pose a challenge for businesses, as will customer privacy and security concerns.
# 1 Consider cloud-based platforms for storing and sharing data to enable a fail-fast-and-learn strategy.
# 2 Research machine learning, cognitive computing and other advanced analytics techniques to improve insight quality and speed.
#3 Share just-in-time insights with customer-facing employees to empower front-line decisions.
Virtualization and automation are changing the face of everything from IT infrastructure services, to business processes and interactive customer services. The common thread is the ability to replace human interactions with code for critical everyday functions. Over time, the increased use of machine learning and predictive analytics will allow software “robots” to perform more complex tasks.
# 1 Automate IT infrastructure provisioning and management first, todeliver short-term savings and business agility.
# 2 Automate steps like user interface creation, testing and code hand-offs from requirements through deployment.
#3 Take advantage of emerging tools, such as modeling languages that allow processes to be described in a way that is understandable to both people and computing systems.
APIs are becoming a core corporate resource. In addition to enabling easier application enhancements, businesses can also use APIs to create a “platform” — an ecosystem of partners that fuels innovation and generates revenue. Almost any business with data or expertise must master the disciplines required to develop, secure, share, use and monetize APIs.
# 1 Consider platforms that help companies develop, secure, share, monitor and monetize their APIs.
# 2 Design services to support specific business capabilities, such as price look-up or inventory check, rather than technical functions.
#3 A successful strategy requires DevOps, continuous integration, testing, logging and tracing, monitoring, messaging, service registration and discovery.
The digital economy is reshaping enterprise sourcing models, as businesses require low-cost, high-quality and agile delivery of IT capabilities. This is giving rise to increased cloud delivery of IT and business services, more use of open source software, global crowdsourcing and the “gig economy,” marked by just-in-time, short-term engagements.
# 1 Consider technologies such as semantic search and machine learning to help find and rank workers.
# 2 Work with business leaders to understand the skills and experience required for each potentially crowdsourced task.
#3 Use the gig economy as an opportunity to work with business, legal and project management offices to minimize the risk of working with new providers.
For more insights, see our white paper “Riding the Seven Waves of Change that Will Power, or Crush, Your Digital Business,” or visit the Digital Business section of our website.