Wednesday, 15 March 2017 07:40

Three Disruptive Macro Trends Shaping Enterprise Technology Featured

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Artificial Intelligence, Machine Learning, Intelligence Systems. These applications are transforming business, and the enterprise technology an platforms to support them. By Catherine Upton

The digital evolution is changing how business is done. This is the era of impassioned CEOs and technology leaders with creative ideas who can inspire their organizations and lead them in transforming into digital businesses.

"The learning ecosystem is going through a technical disruption to automation and autonomous learning programs in the corporate space. Reminiscent of the shift from contact management software to sales force automation software or email marketing to marketing automation, the learning stack is the laggard to be re-invented and adopted, says Rory Cameron, General Manager, Litmos by Callidus Cloud.

In a Gartner report titled, “Top 10 Strategic Technology Trends” authored by David W. Cearley, Brian Burke and Mike J. Walker, there are three macro trends leaders must embrace to enable a shift to the digital enterprise.

MACRO TREND 1:ALGORITHMIC BUSINESS  DRIVES TRANSFORMATION

Algorithmic business is an accelerator and extension of digital business, according to Gartner. It focuses on how increasingly intelligent algorithms enable smart machines and systems to become autonomous actors in the digital business as agents for human beings. Algorithms drive the connectedness among people, things, businesses and information that drive business value. Algorithms provide the “intelligence” to get the most out of the connections and interplay between people, things, processes and information. Algorithms also are critical to delivering a differentiated customer experience. Although big data remains a major concern for CEOs, big data generated as part of the digital business process is of no value in itself. It is only when the organization shifts from a focus on big data to “big answers” that value begins to emerge.

"Forward-thinking learning profes- sionals and learning technology providers have long recognized that we are amassing a significant amount of data on learners, reports Chip Ramsey, CEO, Intellum. “From the corporate perspective, the enterprise should already be drilling down to the individual employee to determine which learning asset positively altered which specific outcome. On the learning technology side, we should be leveraging the tremendous amount of anonymous user data within our reach to identify learning trends that impact performance. But these are still ‘fixed’ approaches by which learning technology providers, and our clients, are making decisions."

Analyzing big data to identify patterns and insights that drive business actions is the start of this shift, according to Gartner. Algorithmic business transformation occurs when organizations encapsulate these insights into algorithms tied tightly to real-time business processes and decision-makers, and when they use machine learning to allow increasingly autonomous algorithmic action. Algorithms are more essential to the business than data alone. Algorithms define action.

Algorithmic business extends beyond data and analytics to influence the evolution of applications, business models and future digital business solutions. This is ushering in a post-app era in which system and application vendors such as Microsoft, Google and Apple are likely to deliver platforms and applications with ever-more powerful agent- based interfaces.

Intellum’s Ramsey continues: “As business sectors across the board, including learning, continue to apply machine learning techniques, these traditionally fixed algorithmic approaches are themselves learning. At Intellum, we are already testing a solution that presents the exact information the user needs to consume at the moment in which that presentation has the highest likelihood of improving that employee’s performance. The algorithms that control this approach are not static equations but processes that learn from large numbers of prior successful outcomes to better determine who needs what, when.”

Algorithmic business builds on digital business, shifting the emphasis to the intelligence encoded in software, according to Gartner. Enterprise architects must add algorithmic business and related enabling technologies to their planning and future enterprise, data, security and application architectures.

IBM’s acquisition of The Weather Company is an example of algorithmic business. The Weather Company has a massive Internet of Things (IoT) implementation, with hundreds of thousands of weather sensors sending 28 billion transactions to its Cloud every day. Before the acquisition, IBM had an agreement to feed data to IBM Watson for weather prediction. With the acquisition, IBM brings together The Weather Company’s digital environment and associated data with IBM’s analytical and cognitive computing capabilities. This has created an algorithmic business that provides analytical services and results to a business ecosystem with more than 5,000 customers. These customers — in, for example, airlines, insurance companies and retailers — can use the algorithmic input to drive their own business operations.

Organizations must examine the potential impact of these macro trends, factor them into their strategic planning for 2017 and 2018, and adjust business models and operations appropriately. If they fail to do so, they will risk losing competitive advantage to organizations that do. {See Figure 1}

ELM March Disruptions 1

Ramsey concludes: “The algorithm that learns how to present the right information to the right person at the right time is beyond valuable. It will fundamentally transform the company that learns to harness it. Imagine the competitive advantage gained when the learning solution recognizes in real time an opportunity to intercede and present the user with information (a new sales technique) that turns an otherwise negative outcome (lost sale) into a positive one (closed sale). This is not an imagined future state. Companies like Intellum will be providing this competitive advantage to clients within the year.”

MACRO TREND 2:THE EMERGENCE OF THE DIGITAL MESH

Gartner defines the “economics of connections” as the creation of value through increased density of interactions among business, people and things. As an organization increases the density of its connections (among people, business and things), it increases the potential value it can realize from those connections.

Connections are at the core of digital and algorithmic business models. The digital mesh builds on the economics of connections, focusing on devices, services, applications and information. The digital mesh is a people-centered theme that refers to the collection of devices (including things), information, apps, services, businesses and other people that exist around the individual. As the mesh evolves, all devices, computers, information resources, businesses and individuals will be interconnected. The interconnections are dynamic and flexible, changing over time. Building business solutions and user experiences (UXs) for the digital mesh — while addressing the challenges they create — must be a priority for enterprise architects.

“This concept of a digital mesh that is made up of all the devices and digital applications that are tracking every aspect of our lives is very applicable to enterprise learning," claims Ramsey. “In a corporate environment, we use applications to manage projects and relationships, receive customer feedback, and control versions of critical documents and code. We interact with these applications across a number of devices from a number of locations. The things we rely on to get our jobs done are actually gathering data about how well we do our jobs.”

The digital mesh has emerged as a re- sult of the collision of the physical and virtual worlds, as computing capability becomes embedded in virtually everything around us. Additional advances allow the virtual world to enter the real world through advanced UI and virtual reality models, as well as physical items created with 3-D printers. This blending of both worlds delivers new insights into the physical world, allowing us to understand it in greater detail, and interact with it in new and intelligent ways. This will change how people experience the world in their daily lives. Opportunities for new business and operating models will abound.

Ramsey adds: “At Intellum, we can already mine this data from a range of devices (think Fitbit) and applications (think Salesforce) to determine employee performance levels. We can now experiment with how well specific inputs, like a mid-day walk or a two-minute video on how to become more persuasive, can alter an outcome or improve an employee’s performance. Once these feedback loops are in place, particularly at scale, we can apply the algorithms that will determine the exact learning asset an employee should encounter in a specific scenario. This will, of course, require even more data from even more sources, and the digital mesh will continue to grow.”

MACRO TREND 3:SMART MACHINES SET THE STAGE FOR ALGORITHMIC BUSINESS AND THE ALGORITHMIC ECONOMY

The smart machines theme describes how information of everything is developing to extract greater meaning from a rapidly expanding set of sources, reports Gartner. Advanced data analysis technologies and approaches are evolving to create physical and software-based machines that are programmed to learn and adapt, rather than programmed only for a finite set of prescribed actions.

The amount of big data collected by the many devices currently in place is staggering. However, the accelerating merger of the physical and virtual worlds will make the present volumes seem paltry. New kinds of data will continuously stream from new types of devices at record rates. This oversupply will overwhelm those who are ill-prepared. But for those who are prepared, the potential to gain new kinds of critical intelligence will be unprecedented. Leading senior executives will build a strong competency in turning this data into critical intelligence that will drive their organizations’ future direction. Additionally, leading organizations will significantly advance operational agility with near-real-time information, feeding business processes that can absorb it and react accordingly. Data coming from almost all directions provides the possibility for intelligence everywhere when combined with advanced artificial intelligence algorithms and other machine-learning techniques.

Three distinct trends are intimately linked in the smart machines theme. They represent an evolution in how systems deal with data, and the machines and people that create and consume this data, culminating in intelligence everywhere. {See Figure 2}

ELM March Disruptions 2

“These three macro trends are substantiated by what we have seen in the financial trading arena," says Apratim Purakayastha, CTO, Skillsoft. “For some years, sophisticated algorithms have taken over trading decisions. Those algorithms are connected in a mesh, taking decisions and automatically trading across firms — and those ‘smart machines’ — have set the stage for a mostly automated algorithmic business. There are other areas, such as supply chain management, where this trend is currently growing. In the area of digi-tal advertisement, we can also see this trend dominating. Overall, it is already a broad, cross-industry phenomenon.

Even everyday objects such as a stethoscope and enterprise software such as CRM systems or security tools increasingly have a smart and autonomous aspect. In “Top 10 Strategic Technology Trends: Autonomous Agents and Things,” Gartner looked at how information of everything and advanced machine-learning algorithms, supported by advanced system architectures, are leading to more intelligent software and hardware-based solutions. These are creating new market segments and enhancing existing ones.

“The pervasive nature of these trends demands that everyone understand what comprises a 100 percent digital workforce — a workforce that is fully trained and conversant with fundamental digital skills, along with its benefits and risks,” adds Purakayastha.

The key digital skills sets required include but are not limited to:

>> Broad digital skills such as productivity and collaborative tools.

>> Modern technological trends such as Big Data, Blockchain, etc.

>> A thorough understanding of fundamental cybersecurity issues such as phishing, ransomware and other risks

>> Best practices and laws relative to digital compliance and data privacy

>> Digital “presence, leadership and image in a virtually interconnected workforce.

—This article contains excerpts from the Gartner Research Report titled “Top 10 Strategic Technology Trends” by David W. Cearley, Brian Burke, Mike J. Walker. To access the complimentary Gartner report, download it at: http://gartnerevents.com/ Top_10_Strategic_EMEA?ls=ppcggle&gclid =CJiMlrSN184CFVAo0wodWdQNkQ

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