Digital Platform Insights - Enterprise Perspective

The new digital platform consists of five domains: Traditional IT systems, Customer Experience, The Internet of Things (IoT), intelligence and the Ecosystem Foundation.

Each of these domains are interconnected and interdependent. CIOs will participate in the building of a new digital platform with intelligence at the center. Digital platform will enable ecosystems, connecting businesses and collapsing industries. It will change society itself, and the way people live.

The five elements of the new digital platform insights include:

Traditional Core IT Systems

Taking high performing traditional IT systems (such as the data centers and networks) and modernizing them to be part of the digital platform. It’s building on what’s already been built.

• Organizations are halfway through the transition to the cloud leaving traditional methods of hosting. It goes into every department soon or later.
• Organizations need to make cloud, mobile, social and data as core capabilities while investing in resilience, business continuity and disaster recovery, inside and outside in a hybrid approach.

Customer Experience

Organizations needs to connect and engage in new ways. The digital customer experience may be the only one that the customers have. This is how the business engages in the digital world. The pioneers are exploring how new experiences such as virtual and augmented reality will change the way customers engage.

• The new competitive differentiator is understanding the customer’s intent through advanced algorithms and artificial intelligence.
• Creating new experiences that solve problems customers didn’t realize they had. 

Internet of Things (IoT)

Two-third of organizations have had to rework their existing IT systems to accommodate IoT. Adding devices to the IoT domain is the easy part. Processes, workflows, and data integration are much harder.

IoT also changes how Organizations should invest in analytics because decisions must move from days to minutes to instant. Organizations should plan to shift their investments in analytics to real-time. Real-time analytics will outpace traditional analytics by a factor of three by 2020 to become 30 percent of the market.

Intelligence

The systems analyze, learn and decide independently. Organizations start with traditional data management, data science and data intelligence. Algorithms determine the action. The new type of intelligence, driven by machine learning is artificial intelligence.

• Machine learning and artificial intelligence move at the speed of data, not at the speed of code releases. Information is the new code base.

Ecosystem Foundation

The enterprise interacts as an institution in the digital world. Ecosystems go beyond the capability to decide, Organizations need to build the capability to interact with customers, partners, adjacent industries, even your competitors. The ecosystems allow for the transformation from traditional business with linear value supply chains to networked digital ecosystem businesses.

Worldwide IT Spending

Gartner forecasts worldwide IT spending to total $3.4 trillion in 2016, a 0.3 percent decline from last year. In 2017, global IT spending is projected to grow 2.9 percent and reach $3.5 trillion. This growth will be driven by the software and IT services segments. 

Worldwide spending on software is projected to grow 7.2 percent, and IT services 4.8 percent.

Source: Link

Top 10 Strategic Technology Trends: 2017

Gartner defines a strategic technology trend as one with substantial disruptive potential that is just beginning to break out of an emerging state into broader impact and use or which are rapidly growing trends with a high degree of volatility reaching tipping points over the next five years.

The top 10 strategic technology trends for 2017 are:

AI and Advanced Machine Learning

Artificial intelligence (AI) and advanced machine learning (ML) are composed of many technologies and techniques (e.g., deep learning, neural networks, natural-language processing [NLP]). The more advanced techniques move beyond traditional rule-based algorithms to create systems that understand, learn, predict, adapt and potentially operate autonomously. This is what makes smart machines appear "intelligent."

Intelligent Apps

Intelligent apps such as VPAs perform some of the functions of a human assistant making everyday tasks easier (by prioritizing emails, for example), and its users more effective (by highlighting the most important content and interactions). Other intelligent apps such as virtual customer assistants (VCAs) are more specialized for tasks in areas such as sales and customer service. As such, these intelligent apps have the potential to transform the nature of work and structure of the workplace.

Intelligent Things

Intelligent things refer to physical things that go beyond the execution of rigid programing models to exploit applied AI and machine learning to deliver advanced behaviors and interact more naturally with their surroundings and with people. As intelligent things, such as drones, autonomous vehicles and smart appliances, permeate the environment, Gartner anticipates a shift from stand-alone intelligent things to a collaborative intelligent things model.

Virtual and Augmented Reality

Immersive technologies, such as virtual reality (VR) and augmented reality (AR), transform the way individuals interact with one another and with software systems. VR and AR capabilities will merge with the digital mesh to form a more seamless system of devices capable of orchestrating a flow of information that comes to the user as hyperpersonalized and relevant apps and services. Integration across multiple mobile, wearable, Internet of Things (IoT) and sensor-rich environments will extend immersive applications beyond isolated and single-person experiences. Rooms and spaces will become active with things, and their connection through the mesh will appear and work in conjunction with immersive virtual worlds.

Digital Twin 

A digital twin is a dynamic software model of a physical thing or system that relies on sensor data to understand its state, respond to changes, improve operations and add value. Digital twins include a combination of metadata (for example, classification, composition and structure), condition or state (for example, location and temperature), event data (for example, time series), and analytics (for example, algorithms and rules).

Blockchain and Distributed Ledgers

Blockchain is a type of distributed ledger in which value exchange transactions (in bitcoin or other tokens) are sequentially grouped into blocks. Each block is chained to the previous block and recorded across a peer-to-peer network, using cryptographic trust and assurance mechanisms. Blockchain and distributed-ledger concepts are gaining traction because they hold the promise to transform industry operating models. While the current hype is around the financial services industry, there are many possible applications including music distribution, identity verification, title registry and supply chain.

Conversational System

The current focus for conversational interfaces is focused on chatbots and microphone-enabled devices (e.g., speakers smartphones, tablets, PCs, automobiles). However, the digital mesh encompasses an expanding set of endpoints people use to access applicatons and information, or interact with people, social communities, governments, and businesses. The device mesh moves beyond the traditional desktop computer and multiple devices to encompass the full range of endpoints with which humans might interact. As the device mesh evolves, connection models will expand and greater cooperative interaction between devices will emerge, creating the foundation for a new continuous and ambient digital experience.

Mesh App and Service Architecture

In the mesh app and service architecture (MASA), mobile apps, web apps, desktop apps and IoT apps link to a broad mesh of back-end services to create what users view as an "application." The architecture encapsulates services and exposes APIs at multiple levels and across organizational boundaries balancing the demand for agility and scalability of services with composition and reuse of services. The MASA enables users to have an optimized solution for targeted endpoints in the digital mesh (e.g., desktop, smartphone, automobile) as well as a continuous experience as they shift across these different channels.

Digital Technology Platforms

Digital technology platforms provide the basic building blocks for a digital business and are a critical enabler to become a digital business. Gartner has identified the five major focal points to enable the new capabilities and business models of digital business — information systems, customer experience, analytics and intelligence, the IoT, and business ecosystems. Every organization will have some mix of these five digital technology platforms. The platforms provide the basic building blocks for a digital business and are a critical enabler to become a digital business.

Adaptive Security Architecture

The intelligent digital mesh and related digital technology platforms and application architectures create an ever-more-complex world for security. "Established security technologies should be used as a baseline to secure Internet of Things platforms," said Mr. Cearley. "Monitoring user and entity behavior is a critical addition that is particularly needed in IoT scenarios. However, the IoT edge is a new frontier for many IT security professionals creating new vulnerability areas and often requiring new remediation tools and processes that must be factored into IoT platform efforts."

Source: Link 

Top 10 Technologies for Information Security in 2016

Gartner, Inc. has highlighted the top 10 technologies for information security and their implications for security organizations in 2016.

Cloud Access Security Brokers: Cloud access security brokers (CASBs) provide information security professionals with a critical control point for the secure and compliant use of cloud services across multiple cloud providers. Many software as a service (SaaS) apps have limited visibility and control options; however, SaaS adoption is becoming pervasive in enterprises, which exacerbates the frustration of security teams looking for visibility and control. CASB solutions fill many of the gaps in individual cloud services, and allow chief information security officers (CISOs) to do it simultaneously across a growing set of cloud services, including infrastructure as a service (IaaS) and platform as a service (PaaS) providers. As such, CASBs address a critical CISO requirement to set policy, monitor behavior and manage risk across the entire set of enterprise cloud services being consumed.

Endpoint Detection and Response: The market for endpoint detection and response (EDR) solutions is expanding quickly in response to the need for more effective endpoint protection and the emerging imperative to detect potential breaches and react faster. EDR tools typically record numerous endpoint and network events, and store this information either locally on the endpoint or in a centralized database. Databases of known indicators of compromise (IOC), behavior analytics and machine-learning techniques are then used to continuously search the data for the early identification of breaches (including insider threats), and to rapidly respond to those attacks.

Nonsignature Approaches for Endpoint Prevention: Purely signature-based approaches for malware prevention are ineffective against advanced and targeted attacks. Multiple techniques are emerging that augment traditional signature-based approaches, including memory protection and exploit prevention that prevent the common ways that malware gets onto systems, and machine learning-based malware prevention using mathematical models as an alternative to signatures for malware identification and blocking.

User and Entity Behavioral Analytics: User and entity behavioral analytics (UEBA) enables broad-scope security analytics, much like security information and event management (SIEM) enables broad-scope security monitoring. UEBA provides user-centric analytics around user behavior, but also around other entities such as endpoints, networks and applications. The correlation of the analyses across various entities makes the analytics' results more accurate and threat detection more effective.

Microsegmentation and Flow Visibility: Once attackers have gained a foothold in enterprise systems, they typically can move unimpeded laterally ("east/west") to other systems. To address this, there is an emerging requirement for "microsegmentation" (more granular segmentation) of east/west traffic in enterprise networks. In addition, several of the solutions provide visibility and monitoring of the communication flows. Visualization tools enable operations and security administrators to understand flow patterns, set segmentation policies and monitor for deviations. Finally, several vendors offer optional encryption of the network traffic (typically, point-to-point IPsec tunnels) between workloads for the protection of data in motion, and provide cryptographic isolation between workloads.

Security Testing for DevOps (DevSecOps): Security needs to become an integral part of DevOps style workflows — DevSecOps. DevSecOps operating models are emerging that use scripts, "recipes," blueprints and templates to drive the underlying configuration of security infrastructure — including security policies such as application testing during development or network connectivity at runtime. In addition, several solutions perform automatic security scanning for vulnerabilities during the development process looking for known vulnerabilities before the system is released into production. Whether security is driven from models, blueprints, templates or toolchains, the concept and the desired outcome are the same — an automated, transparent and compliant configuration of the underlying security infrastructure based on policy reflecting the currently deployed state of the workloads.

Intelligence-Driven Security Operations Center Orchestration Solutions: An intelligence-driven security operations center (SOC) goes beyond preventative technologies and the perimeter, and events-based monitoring. An intelligence-driven SOC has to be built for intelligence, and used to inform every aspect of security operations. To meet the challenges of the new "detection and response" paradigm, an intelligence-driven SOC also needs to move beyond traditional defenses, with an adaptive architecture and context-aware components. To support these required changes in information security programs, the traditional SOC must evolve to become the intelligence-driven SOC (ISOC) with automation and orchestration of SOC processes being a key enabler.

Remote Browser: Most attacks start by targeting end-users with malware delivered via email, URLs or malicious websites. An emerging approach to address this risk is to remotely present the browser session from a "browser server" (typically Linux based) running on-premises or delivered as a cloud-based service. By isolating the browsing function from the rest of the endpoint and corporate network, malware is kept off of the end-user's system and the enterprise has significantly reduced the surface area for attack by shifting the risk of attack to the server sessions, which can be reset to a known good state on every new browsing session, tab opened or URL accessed.

Deception: Deception technologies are defined by the use of deceits and/or tricks designed to thwart, or throw off, an attacker's cognitive processes, disrupt an attacker's automation tools, delay an attacker's activities or disrupt breach progression. For example, deception capabilities create fake vulnerabilities, systems, shares and cookies. If an attacker tries to attack these fake resources, it is a strong indicator that an attack is in progress, as a legitimate user should not see or try to access these resources. Deception technologies are emerging for network, application, endpoint and data, with the best systems combing multiple techniques. By 2018, Gartner predicts that 10 percent of enterprises will use deception tools and tactics, and actively participate in deception operations against attackers.

Pervasive Trust Services: As enterprise security departments are asked to extend their protection capabilities to operational technology and the Internet of Things, new security models must emerge to provision and manage trust at scale. Trust services are designed to scale and support the needs of billions of devices, many with limited processing capability. Enterprises looking for larger-scale, distributed trust or consensus-based services should focus on trust services that include secure provisioning, data integrity, confidentiality, device identity and authentication. Some leading-edge approaches use distributed trust and blockchain-like architectures to manage distributed trust and data integrity at a large scale.

Source: Gartner 2016

Digital Marketing in Healthcare

Care is on-line.

Patient’s knowledge in searching mobile and social channels for cost-effective healthcare information has increased. Combined with exhortation from qualified doctors, the web is helping patients in selecting more accomplished doctors and hospitals.

In other way, hospitals leveraging the opportunity by putting them first in place for reaching the growing number of consumers who look online for health-care information.

For Digital Marketing in Healthcare, SMAC is the key.

Social – Patients tend to refer experiences, expertise, success stories, and testimonial. Social channel with better content often engage more users and drives the possibilities.

Mobile – It’s in every hand. Healthcare has come in hand. Healthcare sites, mobile apps, online events (interactive sessions), etc.

Analytics – Measurement pays every time. Analytics tools gives great insights about patient behavior online.

Cloud – Everything on cloud! Cost effective, collaborative solutions made cloud as the preferred choice for healthcare. 

Enterprise Digital Analytics

Digital analytics play an important role in nearly each enterprise’s digital marketing strategy, not just for following and measurement web site traffic, but for following and measurement different digital channels, as well. With the explosive growth of social media, video, and mobile, the importance of understanding the contributions and relationships of those channels to web site traffic and conversions has increased significantly.

Key areas for digital marketers:

• Ensuring consistency of messaging across all channels
• Understanding how mobile users research/buy products
• Understanding where and when customers use different devices
• Using online data to optimize offline experience
• Using offline data to optimize online experience
• Attributing Big Data for more effective marketing

The benefits of digital analytics platforms:

• Developing actionable insights across the enterprise
• Harnessing powerful, real-time analytics
• A better understanding of user demographics.
• Improved tracking of on-site user behaviour
• Greater ability to monitor site performance and usability
• Increased measurability and marketing effectiveness 

Source: 2014 Third Door Media, Inc

Enterprise Digital Marketing Strategy

Digital marketing strategy uses the core values of an enterprise to make use of digital channels to promote or market products and services to consumers and businesses.

Components of Enterprise Digital Marketing Strategy: 

• Network Building Strategy
• Engagement strategy
• Content Marketing Strategy
• Recommendations
• Client Centric Strategy
• Employee Engagement Strategy
• Visibility Strategy
• Measurement and Follow-ups 

Digital Advantage:

Worldwide Business Analytics Software Revenue by Segment and Leading Vendors: 2009-2018

Business Analytics

Business analytics (BA) refers to the skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods.

The Business Analytics Software Market in 2013

In 2013, the worldwide business analytics software market grew 8.2% to reach $37.7 billion. The market is now forecast to grow at a 9.4% compound annual growth rate (CAGR) through 2018.

Within BA market, the business intelligence and analytics tools segment grew, at 8.6%, reversing the trend of the previous two years when the data warehousing platform segment had the leading growth rate. In fact, in 2013, the data warehousing market grew only 6.4%, the worst performance since the recession of 2008–2009. The analytic applications segment grew 9.4% in 2013.

For over a decade, IDC has defined the business analytics software market as the combination of the data warehouse (DW) platform software with performance management and analytic applications and business intelligence (BI) and analytic tools. Key observations about the business analytics software market include:

• 2013 market growth rate of 8.2% was essentially unchanged from the 8.6% growth rate in 2012. The overall market is in a period of steady growth, but there is variability in the expected growth rates of the individual market segments.
• In 2013, the market experienced a noticeable shift toward cloud-based solutions. Although these cloud-based solutions had been available for years, supply of cloud services from the largest vendors accelerated rapidly in 2013 and is expected to continue throughout the forecast period
• Increasingly, the distinction between business analytics and big data is blurring, and the hype about the latter phenomenon has subsided. As a result, more organizations are looking to develop comprehensive business analytics strategies that address all of their data access, analysis, and management requirements.
• There is a broad theme of "self-service" in the business analytics market that applies to all user groups. This trend is putting increasing pressure on IT departments to address end-user requirements faster and yet without increasing IT resources. Methods used by IT to address this demand include relying more on cloud services, outsourcing, consulting services, and technology automation, including appliances.
• At the same time, IDC estimates that about 60% of IT project funding is now controlled or significantly influenced by business units. This has resulted in many more "shadow" IT and analytics efforts to support analytics and business intelligence needs of end users. It is part of the reason for the rapid growth of the visual discovery sub-segment of the end-user query, reporting and analysis segment of the business analytics market.

Worldwide Business Analytics Software Revenue by Segment ($M): 2009–2018 

Worldwide Business Analytics Software Revenue by Leading Vendor: 2011–2013

Source: SAS, IDC 2014