My take on Gartner’s Top 10 Strategic Trends for 2018 & beyond..

My vision for the future state of the digital economy – I see a movie. I see a story of everybody connected with very low latency, very high speed, ultra-dense connectivity available. Today you’re at the start of something amazing… I see the freeing up, not just of productivity and money, but also positive energy which can bring a more equal world.” -Vittorio Colao, CEO, Vodafone, Speaking at the World Economic Forum – Davos, Jan 2015

As is customary for this time of the year, Gartner Research rolled out their “Top 10 Strategic Technology Trends for 2018” report a few weeks ago –  https://www.gartner.com/newsroom/id/3812063. Rather than exclusively cover the IT technology landscape as in past years, Gartner has also incorporated some of the themes from the 2016 US Presidential election, namely fake news and content.My goal for this blogpost is to provide my frank take on these trends to the reader. Also, as always – to examine the potential impact of their recommendations from an enterprise standpoint.

Previous Gartner Reviews…

2016..

My take on Gartner’s Top 10 Strategic Technology Trends for 2016

2017..

My take on Gartner’s Top 10 Strategic Technology Trends for 2017

The predictions themselves can be organized in five specific clusters – Web-scale giants, Cryptocurrencies, Fake News & AI,  IT job markets & IoT/Security.

Let us consider  –

Prediction Cluster #1 -Of  Web Scale Giants, Bots & E-Commerce… 

This year, Gartner makes two key predictions from the standpoint of the webscale giants, namely the FANG (Facebook, Amazon, Netflix and Google/Alphabet) companies plus Apple. These companies now dominate whatever business areas they choose to operate in largely due to the general lack of traditional enterprise competition to their technology-infused business models. They have not only gained market leadership status in their core markets but are also branching into creating blue ocean business models. Gartner’s prediction is that by 2020, these giants – which will largely remain unchallenged –  will need to innovate via self-disruption to stay nimble and competitive.

This prediction is hard to disagree with and is fairly obvious to someone who has followed their growth over the years. Virtually every major advance in consumer technology, mobile business models, datacenter architectures, product development methodologies over the last ten years has originated at these companies. The question is how much of this forecasted organic disruption will happen due to their cannibalizing existing product lines or creating entirely new markets e.g. self-driving tech, VR/AR etc.

The critical reason these companies have such a wide business moat is that they’ve incubated the Digital Native customer category. Their users are highly comfortable with technology and use services offered (such as Google’s range of products, Facebook services such as the classical social media platform, Instagram,  Uber, Netflix, Amazon Prime etc) almost hourly in their daily lives. As I have noted before, these customers expect a similar seamless & contextual experience while engaging with the more mundane and traditional enterprises such as Banks, Telcos, Retailers, Insurance companies. They expect primarily expect a digital channel experience. These companies then have a dual fold challenge – not only to provide the best user expereince but also to store all this data as well as harness it for real-time insights in a way that is connected with internal marketing & sales.

As many studies have shown, companies that constantly harness data about their customers, internal operations and perform speedy analytics on this data often outshine their competition. Does that seem a bombastic statement? Not when you consider that almost half of all online dollars spent in the United States in 2016 were spent on Amazon and almost all digital advertising revenue growth in 2016 was accounted by two biggies –Google and Facebook.

Which leads us to the second prediction, that – by 2021 early adopter brands that redesign their websites to support visual and voice search will increase digital commerce revenue by 30%.

This prediction is also bolstered by the likes of comScore which notes that voice & visual search have rapidly become the second and third leg of online search. Every serious mobile app now supports both these modes. Further Amazon with their Alexa assistant is bringing this capability to bear in diverse areas such as home automation.

Virtual reality (VR) and augmented reality (AR) are technologies that will completely change the way humans interact with one another and with intelligent systems that make up the Digital Mesh.  Uses of these technologies will include gamification (to improve customer engagement with products and services), other customer & employee-facing applications etc.

Prediction Cluster #2 – By 2022, Cryptocurrencies create $1B of value in the Banking market…

We have discussed the subject of bitcoin and blockchain to some degree of depth over the last year and this prediction will seem safe and obvious to many. The explosion of market value in Bitcoin and other alt-currencies also supports the coming of age of cryptocurrencies. However, Gartner pegging cryptocurrency led business value at just $1B by 2022 seems way on the lower end. Cryptocurrencies are not only widely accepted in various forms of banking. E.g. Payments, Consumer Banking loans, Mortgages etc but they are on the verge of gaining Central Bank support. I expect an explosion in their usage and institutionalization over the next two-three year horizon. Every enterprise needs an Altcurrency and Blockchain strategy.

Blockchain For the Enterprise: Key Considerations..

Prediction Cluster #3 – Fake News and Counterfeit Reality run amok…

Keeping in line with the dominant theme of the US Presidential election of 2016, fake news has become a huge challenge across multiple social media platforms. This news is being manufactured by skilled writers working for foreign and often hostile governments as well as AI driven bots. Gartner forecasts that by 2022, the majority of news consumed in developed economies will be fake. This is a staggering indictment of the degree of criminality in creating a counterfeit reality. Germany has led the way in passing legislation that goes after criminals who sow racial discord by planting fake news on internet platforms which have more than 2 million users. [1] The law applies to online service providers who operate platforms that enable sharing and dissemination of data. If offending material is not removed from social network platforms within 24 hours, fines of upto  €50 million can be levied by the regulator.

Enterprises need to guard similarly against fake news being shared with a view to harming their corporate or product image. Putting in place strong cyber defenses and operational risk systems will be key.

Prediction Cluster #4 – IT jobs in the Digital Age…

We have spoken about the need for IT staff to retool themselves as Digital transformation & bimodal IT projects increasingly take a seat in the corporate agenda. Accordingly, IT needs to increasingly understand and communicate in the language of the business. Gartner increasingly forecasts that IT staff will become versatilists across the key disciplines of Infrastructure, Operations, and Architecture.

What Lines Of Business Want From IT..

Gartner also forecasts that AI related jobs will experience healthy growth staring in 2020. Until then AI will result in widespread time and effort savings with AI augmenting existing workers with time and productivity savings.

Prediction Cluster #6 – IoT and Security… 

There are two key predictions included this year from an IoT standpoint. The first is that by 2022, half of IoT security budgets will be spent towards remediation and device safety recalls rather than in providing protection. Clearly, as threat vectors increase into an enterprise by their adoption of IoT, it is key to put appropriate governance mechanisms to ensure perimeter defense and to ensure appropriate patching & security policies are followed. You are only as secure as the weakest devices inside your organizational perimeter.

Secondly, In three years or less, Gartner predicts that IoT capabilities will be included in 95% of new electronic designs. This is not a surprise given the proliferation of embedded devices and the improvements in operating systems such as embedded Linux. However, the key gains will be made in platforms that harness and make this data actionable.

A Digital Reference Architecture for the Industrial Internet Of Things (IIoT)..

The Numbers…

This year’s Gartner’s predictions have largely underwhelmed in three broad areas.

Firstly, the broad coverage of all leading tech trends that were evident in the earlier years is clearly missing. For instance, sensor technology enabling autonomous vehicles such as LIDAR (Light Detection and Ranging) being pioneered by the likes of Alphabet and Tesla is conspicuous by its absence on the list. Elon Musk has been on record saying that self-driven transportation is just two or three years away from being introduced by the car makers.  Next, any mention of 5G wireless capabilities which enable a range of IoT workloads is expected to be a reality in 2020. This is another obvious miss by Gartner.

Secondly, some of the most evident areas of enterprise innovation such as FinTechs, InsurTechs are conspicuous by their absence.

Thirdly, Gartner has included quantitative data such as percentages and dates that with each trend that can leave one scratching their head. It is unclear what methodology and logic were employed in arriving at such exact numbers.

References..

[1] “Germany’s Bold Gambit to Prevent Online Hate Crimes and Fake News Takes Effect” – Evelyn Douek, Lawfare
https://www.lawfareblog.com/germanys-bold-gambit-prevent-online-hate-crimes-and-fake-news-takes-effect

My take on Gartner’s Top 10 Strategic Technology Trends for 2017

We’re only at the very, very beginning of this next generation of computing and I think that every industry leader will be the ones that transforms first. I don’t care what industry you’re talking about” -Kim Stevenson, CIO, Intel, Feb 2016

Gartner Research rolled out their “Top 10 Strategic Technology Trends for 2017” report a few weeks ago. My goal for this blogpost is to introduce these trends to the reader and to examine the potential impact of their recommendations from an enterprise standpoint.

gartner_trends_2017

                                                              Gartner’s Strategic Trends for 2017 

# 1: AI & Advanced Machine Learning

Gartner rightly forecasts that AI (Artificial Intelligence) and Advanced Machine Learning will continue their march into daily applications run by the Fortune 1000. CIOs are coming to realize that most business problems are primarily data challenges. The rapid maturation of scalable processing techniques allows us to extract richer insights from data. What we commonly refer to as Machine Learning – a combination of econometrics, machine learning, statistics, visualization, and computer science – helps extracts valuable business insights hiding in data and builds operational systems to deliver that value.

Deep Machine Learning involves the art of discovering data insights in a human-like pattern. We are, thus, clearly witnessing the advent of modern data applications. These applications will leverage a range of advanced techniques such as Artificial Intelligence and Machine Learning (ML) encompassing techniques such as neural networks, natural language processing and deep learning.

Implications for industry CIOs – Modern data applications understand their environment (e.g customer preferences and other detailed data insights) to be able to predict business trends in real time & to take action based on them to drive revenues and decrease business risk. These techniques will enable applications and devices to operate in an even more smarter manner while saving companies enormous amounts of money on manual costs.

http://www.vamsitalkstech.com/?p=407

# 2: Intelligent Apps

Personal assistants, e.g Apple Siri, Microsoft Cortona in the category of virtual personal assistants (VPAs), have begun transforming everyday business processes easier for their users. VPAs represent the intersection of AI, conversational interfaces and integration into business processes. In 2017, these will begin improving customer experiences for the largest Fortune 100 enterprises. On the more personal front, Home VPAs will rapidly evolve & become even more smarter as their algorithms get more capable and understanding of their own environments.  We will see increased application of smart agents in diverse fields like financial services,healthcare, telecom and media.

Implications for industry CIOs – Get ready to invest in intelligent applications in the corporate intranet to start with.

# 3: Intelligent Things

The rise of the IoT has only been well documented but couple AI with massive data processing capabilities – that makes up Intelligent Things which can interact with humans in new ways. You can add a whole category of things around transportation (self driving cars, connected cars) and Robots that perform key processes in industrial manufacturing, drones etc.

Implications for industry CIOs – These intelligent devices will increasingly begin communicating with their environments in a manner that will encourage collaboration in a range of business scenarios. 2017 should begin the trend of these devices communicating with each other to form the eponymous ‘Digital Mesh’.

# 4: Virtual & Augmented Reality

Virtual reality (VR) and augmented reality (AR) are technologies that are beginning to completely change the way humans interact with one another and with intelligent systems that make up the Digital Mesh. Pokemon GO & Oculus Rift were the first hugely successful consumer facing AR applications – debuting in 2016. Uses of these technologies will include gamification (to improve customer engagement with products and services), other customer & employee facing applications etc. While both these technologies enable us to view the world in different ways – AR is remarkable in its ability to add to our current reality. BMW’s subsidiary Mini has actually developed a driving goggle with AR technology[1].

Implications for industry CIOs – This one is still on the drawing board for most verticals but it does make sense to invest in areas like gamification and in engaging with remote employees using AR.

# 5: Digital Twin

A Digital twin is a software personification of an Intelligent Thing or system. In the manufacturing industry, digital twins can be setup to function as proxies of things like sensors and gauges, Coordinate Measuring Machines, lasers, vision systems, and white light scanning [2]. The wealth of data being gathered on the shop floor will ensure that Digital twins will be used to reduce costs and increase innovation. Data science will soon make it’s way into the shop floor to enable the collection of insights from these software proxies.

Implications for industry CIOs – Invest in Digital capabilities that serve as proxies for physical things.

# 6: Blockchain

The term Blockchain is derived from a design pattern that describes a chain of data blocks that map to individual transactions. Each transaction that is conducted in the real world (e.g a Bitcoin wire transfer) results in the creation of new blocks in the chain. The new blocks so created are done so by calculating a cryptographic hash function of its previous block thus constructing a chain of blocks – hence the name.

Blockchain is a distributed ledger (DLT) which allows global participants to conduct secure transactions that could be of any type – banking, music purchases, legal contracts, supply chain transactions etc. Blockchain will transform multiple industries in the years to come. Bitcoin is the first application of Blockchain.

How the Blockchain will lead disruption across industry..(5/5)

Implications for industry CIOs – Begin expanding internal knowledge on Blockchain and as to how it can potentially augment or disrupt your vertical industry.

# 7: Conversational Systems

Mobile applications first begun forcing the need for enterprises to begin supporting multiple channels of interaction with their consumers. For example Banking now requires an ability to engage consumers in a seamless experience across an average of four to five channels – Mobile, eBanking, Call Center, Kiosk etc. Conversational Systems take these interactions to the next level and enable humans to communicate with a wide range of Intelligent Things using a range of channels – speech, touch, vision etc.

Implications for industry CIOs – Every touch point matters, and those leading the smart agent transformation should constantly be asking how organizations are removing friction and enhancing the experience for every customer regardless of where they are in the journey.

# 8: Mesh App and Service Architecture

This one is still from last year. The Digital Mesh leads to an interconnected information deluge which encompasses classical IoT endpoints along with audio, video & social data streams. The creation of these smart services will further depend on the vertical industries that these products serve as well as requirements for the platforms that host them. E.g industrial automation, remote healthcare, public transportation, connected cars, home automation etc.The micro services architecture approach which combines the notion of autonomous, cooperative yet loosely coupled applications built as a conglomeration of business focused services is a natural fit for the Digital Mesh.  The most important additive and consideration to micro services based architectures in the age of the Digital Mesh is what I’d like to term –  Analytics Everywhere.

Implications for industry CIOs -The mesh app will require a microservices based architecture which supports multichannel & multi device solutions.

# 9: Digital Technology Platforms

The onset of Digital Architectures in enterprise businesses implies the ability to drive continuous micro level interactions with global consumers/customers/clients/stockholders or patients depending on the vertical you operate in. More information on the core building blocks of Digital Technology Platforms at the below blogpost.

Implications for industry CIOs

http://www.vamsitalkstech.com/?m=201609

# 10: Adaptive Security Architecture

The evolution of the intelligent digital mesh and digital technology platforms and application architectures means that security has to become fluid and adaptive.Traditional solutions cannot handle this challenge which is exacerbated by the expectation that in an IoT & DM world, data flows will be multidirectional across a grid of application endpoints.

Implications for industry CIOs -Expect to find applications in 2016 and beyond incorporating Deep Learning and Real Time Analytics into their core security design with a view to analyzing large scale data at a very low latency. Security in the IoT environment is particularly challenging. Security teams need to work with application, solution and enterprise architects to build security into the overall DevOps process to create a DevSecOps model.

Conclusion..

In this year’s edition, Gartner are clearly forecasting the future ten years out from a mass market standpoint. As we cross this chasm slowly over the next ten years, we will see that IoT begin to emerge and take center stage in every industry vertical. Digital transformation will happen on apps created for and brought together for Smart Agents on the Device Mesh.

These apps will gradually become autonomous, data intensive,server-less, hopefully secure and location independent (data center or cloud). The app can be a sensor or a connected car or a digital twin for a manufacturing technician. So, it’s not just about a single app sitting in a data center or the cloud or on the machine itself. These smart agent apps will data driven, components of a larger mesh, interconnected connected using open interfaces, and resident at the places where it’s optimal for realtime analytics. This may seem like science fiction for the Fortune 1000 enterprise but it is manifest reality at the web scale innovators. The industry will have no choice but to follow.

References..

[1] Cramer – “A lesson in Augmented Realities” –  http://cramer.com/story/the-difference-between-ar-and-vr/

[2] Dr.Michael Grieves – “Digital Twin: Manufacturing Excellence through Virtual Factory Replication” – http://innovate.fit.edu/plm/documents/doc_mgr/912/1411.0_Digital_Twin_White_Paper_Dr_Grieves.pdf

My take on Gartner’s Top 10 Strategic Technology Trends for 2016

Gartner_top_2016

Dream no small dreams for they have no power to move the hearts of men.” — Goethe

It is that time of the year again when the mavens at Gartner make their annual predictions regarding the top Strategic trends for the upcoming year. The definition of ‘strategic’ as in an emerging technology trend that will impact Iong term business thus influencing plans & budgets. As before, I will be offering up my own take on these while solidifying the discussion in terms of the Social, Mobile, Big Data Analytics & Cloud (SMAC) stack that is driving ongoing industry revolution.
  1. The Digital Mesh
    The rise of the machines has been well documented but enterprises are waking up to the possibilities only recently.  Massive data volumes are now being reliably generated from diverse sources of telemetry as well as endpoints at corporate offices (as a consequence of BYOD). The former devices include sensors used in manufacturing, personal fitness devices like FitBit, Home and Office energy management sensors, Smart cars, Geo-location devices etc. Couple these with the ever growing social media feeds, web clicks, server logs and more – one sees a clear trend forming which Gartner terms the Digital Mesh.  The Digital Mesh leads to an interconnected information deluge which encompasses classical IoT endpoints along with audio, video & social data streams. This leads to huge security challenges and opportunity from a business perspective  for forward looking enterprises (including Governments). Applications will need to combine these into one holistic picture of an entity – whether individual or institution. 
  2. Information of Everything
    The IoT era brings an explosion of data that flows across organizational, system and application boundaries. Look for advances in technology especially in Big Data and Visualization to help consumers harness this information in the right form enriched with the right contextual information.In the Information of Everything era, massive amounts of efforts will thus be expended on data ingestion, quality and governance challenges.
  3. Ambient User Experiences
    Mobile applications first begun forcing the need for enterprise to begin supporting multiple channels of interaction with their consumers. For example Banking now requires an ability to engage consumers in a seamless experience across an average of four to five channels – Mobile, eBanking, Call Center, Kiosk etc. The average enterprise user is familiar with BYOD in the age of self service. The Digital Mesh only exacerbates this gap in user experiences as information consumers navigate applications as they consume services across a mesh that is both multi-channel as well as provides Customer 360 across all these engagement points.Applications developed in 2016 and beyond must take an approach to ensuring a smooth experience across the spectrum of endpoints and the platforms that span them from a Data Visualization standpoint.
  4. Autonomous Agents and Things

    Smart machines like robots,personal assistants like Apple Siri,automated home equipment will rapidly evolve & become even more smarter as their algorithms get more capable and understanding of their own environments. In addition, Big Data & Cloud computing will continue to mature and offer day to day capabilities around systems that employ machine learning to make predictions & decisions. We will see increased application of Smart Agents in diverse fields like financial services,healthcare, telecom and media.

  5. Advanced Machine Learning
    Most business problems are data challenges and an approach centered around data analysis helps extract meaningful insights from data thus helping the business It is a common capability now for many enterprises to possess the capability to acquire, store and process large volumes of data using a low cost approach leveraging Big Data and Cloud Computing.  At the same time the rapid maturation of scalable processing techniques allows us to extract richer insights from data. What we commonly refer to as Machine Learning – a combination of  of econometrics, machine learning, statistics, visualization, and computer science – extract valuable business insights hiding in data and builds operational systems to deliver that value. Data Science has evolved to a new branch called “Deep Neural Nets” (DNN). DNN Are what makes possible the ability of smart machines and agents to learn from data flows and to make products that use them even more automated & powerful. Deep Machine Learning involves the art of discovering data insights in a human-like pattern. The web scale world (led by Google and Facebook) have been vocal about their use of Advanced Data Science techniques and the move of Data Science into Advanced Machine Learning.
  6. 3D Printing Materials

    3D printing continues to evolve and advance across a wide variety of industries.2015 saw a wider range of materials including carbon fiber, glass, nickel alloys, electronics & other materials used in the 3D printing process . More and more industries continue to incorporate the print and assembly of composite parts constructed using such materials – prominent examples including Tesla and SpaceX. We are at the beginning of a 20 year revolution which will lead to sea changes in industrial automation.

  7. Adaptive Security
    A cursory study of the top data breaches in 2015 reads like a “Who’s Who”of actors in society across Governments, Banks, Retail establishments etc. The enterprise world now understands that an comprehensive & strategic approach to Cybersecurity has  now far progressed from being an IT challenge a few years ago to a business imperative. As Digital and IoT ecosystems evolve to loose federations of API accessible and cloud native applications, more and more assets are at danger of being targeted by extremely well funded and sophisticated adversaries. For instance – it is an obvious truth that data from millions of IoT endpoints requires data ingest & processing at scale. The challenge from a security perspective is multilayered and arises not just from malicious actors but also from a lack of a holistic approach that combines security with data governance, audit trails and quality attributes. Traditional solutions cannot handle this challenge which is exacerbated by the expectation that in an IoT & DM world, data flows will be multidirectional across a grid of application endpoints. Expect to find applications in 2016 and beyond incorporating Deep Learning and Real Time Analytics into their core security design with a view to analyzing large scale data at a very low latency.
  8. Advanced System Architecture
    The advent of the digital mesh and ecosystem technologies like autonomous agents (powered by Deep Neural Nets) will make increasing demands on computing architectures from a power consumption, system intelligence as well as a form factor perspective. The key is to provide increased performance while mimicking neuro biological architectures. The name given this style of building electronic circuits is neuromorphic computing. Systems designers will have increased choice in terms of using field programmable gate arrays (FPGAs) or graphics processing units (GPUs). While both FGPAs and GPUs have their pros and cons, devices & computing architectures using these as a foundation are both suited to deep learning and other pattern matching algorithms leveraged by advanced machine learning. Look for more reductions in form factors at less power consumption while allowing advanced intelligence in the IoT endpoint ecosystem.
  9. Mesh App and Service Architecture
    The micro services architecture approach which combines the notion of autonomous, cooperative yet loosely coupled applications built as a conglomeration of business focused services is a natural fit for the Digital Mesh.  The most important additive and consideration to micro services based architectures in the age of the Digital Mesh is what I’d like to term –  Analytics Everywhere. Applications in 2016 and beyond will need to recognize that Analytics are pervasive, relentless, realtime and thus embedded into our daily lives. Every interaction a user has with a micro services based application will need a predictive capability built into the application architecture itself. Thus, 2016 will be the year when Big Data techniques are no longer be the preserve of classical Information Management teams but move to the umbrella Application development area which encompasses the DevOps and Continuous Integration & Delivery (CI-CD) spheres.

  10. IoT Architecture and Platforms
    There is no doubt in anyone’s mind that IoT (Internet Of Things) is a technology megatrend that will reshape enterprises, government and citizens for years to come. IoT platforms will complement Mesh Apps and Service Architectures with a common set of platform capabilities built around open communication, security, scalability & performance requirements. These will form the basic components of IoT infrastructure including but not limited to machine to machine interfaces,location based technology, micro controllers , sensors, actuators and the communication protocols (based on an all IP standard).


The Final Word
– 

One feels strongly that  Open Source will drive the various layers that make up the Digital Mesh stack (Big Data, Operating Systems, Middleware, Advanced Machine Learning & BPM). IoT will be a key part of Digital Transformation initiatives.

However, the challenge for developing Vertical capabilities on these IoT platforms is three fold.  Specifically in areas of augmenting micro services based Digital Mesh applications- which are largely lacking at the time of writing:

  • Data Ingest in batch or near realtime (NRT) or realtime from dynamically changing, disparate and physically distributed sensors, machines, geo location devices, clickstreams, files, and social feeds via highly secure lightweight agents
  • Provide secure data transfer using point-to-point and bidirectional data flows in real time
  • Curate these flows with Simple Event Processing (SEP) capabilities via tracing, parsing, filtering, joining, transforming, forking or cloning of data flows while adding business context to these flows. As mobile clients, IoT applications, social media feeds etc are being brought onboard into existing applications from an analytics perspective, traditional IT operations face pressures from both business and development teams to provide new and innovative services.

The creation of these smart services will further depend on the vertical industries that these products serve as well as requirements for the platforms that host them. E.g industrial automation, remote healthcare, public transportation, connected cars, home automation etc.

Finally, 2016 also throws up some interesting questions around Cyber Security, namely –

a. Can an efficient Cybersecurity be a lasting source of competitive advantage;
b. Given that most breaches are long running in nature where systems are slowly compromised over months. How does one leverage Big Data and Predictive Modeling to rewire and re-architect creaky defenses?
c. Most importantly, how can applications implement security in a manner that they constantly adapt and learn;

If there were just a couple of sentences to sum up Gartner’s forecast for 2016 in a succinct manner, it would be “The emergence of the Digital Mesh & the rapid maturation of IoT will serve to accelerate business transformation across industry verticals. The winning enterprises will begin to make smart technology investments in Big Data, DevOps & Cloud practices  to harness these changes “.

My take on Gartner’s Top 10 Strategic Technology Trends for 2015

As open source vendors like Red Hat, OpenStack, Hortonworks etc as well as foundations (OpenStack etc) help customers achieve their key business transformation initiatives through open architectures and technologies, customers should place a close eye on emerging technologies and trends as they happen.

But what comes next and what is to be expected?

Gartner top 10 trends offers a compelling look at these very important potential shifts in the IT landscape and their seismic impact on customer organizations.

gartner-top-10-strategic-technology-trends-2016-4-638

http://www.gartner.com/newsroom/id/2867917

Here is an independent (and open source) & hopefully succinct take on each of these –

1.Computing Everywhere

It is not just about serving these transient visitors across a business context, we feel that business architectures built in support of Mobile devices should also support the building of relationships with them. We increasingly see a number of customers supporting a BYOD model where mobile apps now serve as a replacement for web applications. Security,User interface design & business workflow support will emerge as key drivers from a business side. IT will focus on the ability of such architectures to support multiple cloud deployment backends.

2.Internet of Things

From an enterprise perspective, IoT has the potential to turn any organization into an Enterprise Internet of Things. We recommend that customers not only think about IoT soley in the context of smart home appliances and wearable fitness devices etc buts also about the ramifications of the changes to existing and potentially new complex application architectures run by most enterprises.

If IoT isn’t already viewed as a “must-have” by business stakeholders, chances are it won’t be long before customer IT organizations are tasked with identifying and harnessing information and actionable insight from Internet-connected devices.

The true value of Internet-connected devices lies in harnessing all the data they produce to provide insights into how the business is working – so that existing business models can be fine-tuned or even new ones created. This is typically done by developing applications that can glean insights from the data and providing it to business stakeholders and customers through dashboards. As a first step to designing an IoT strategy for your enterprise, start by identifying the areas of your business that would be a natural fit from a revenue generation or customer engagement perspective.

3. 3D Printing

We forecast that will be an interesting space to watch as more financing and funding goes into players in the 3D printing market. We expect this to only mature, evolve into supporting many different kinds of manufacturing products as cost of materials falls & more diverse products produced.This eventually this will lead to sea changes in the manufacturing industry with impacts for industrial automation.

4. Advanced, Pervasive and Invisible Analytics

As mobile clients, IoT applications, social media feeds etc are being brought oboard into existing applications from an analytics perspective, traditional IT operations face pressures from both business and development teams to provide new and innovative services in response to rapidly changing business requirements and the need for real-time responsiveness.Data streams need to be filtered and acted in appropriate context from an analytical perspective. Analytics is the first killer app for Big Data. Be it the low hanging fruit of reporting & dashboards to forecasting and predictive modeling and even Data Science. One of the biggest trends for 2014, is the enhancement of analytic capabilities to incorporate real streams of data at a humongous scale. Existing applications can now incorporate such functionality to derive real time meaning from this data.

5. Context-Rich Systems

We feel that context will be the critical piece as enterprise architectures ingest, transform and analyse new age data streams whether they are IoT or mobile device or social media related. Cross cutting concerns like security,workflow and business policies will all need to be baked in and supplied as part of the overall context of the data-flow.

6.Smart Machines

Smart machines like robots,personal helpers,automated home equipment will rapidly evolve as algorithms get more capable and understanding of their own environments. In addition, Big Data & Cloud computing will continue to mature and offer day to day capabilities around systems that employ machine learning to make predictions & decisions. We will see increased application of smart machines in diverse fields like financial services,healthcare, telecom and media.

7.Cloud/Client Computing

Cloud Computing will play an increasing role in the life cycle of development, deployment and optimization of computing applications.As mobile clients proliferate,the trend will be in favor of applications that use robust MBaaS technologies to maximize application performance and provide an ability to synchronize data efficiently across between devices and cloud computing backends.

8.Software-Defined Applications and Infrastructure

Innovation in the industry is often shackled by the absence of a responsive, automated,efficient and agile infrastructure. It can take days to procure servers to host bursts of workloads that may not be feasible for existing IT departments to rapidly turn around. We will witness the further rise of application controlled compute,network and storage.Further, Cloud Management Platforms (CMP) which beginning to provide orchestration capabilities by means of workload portability around public and private clouds will find increased adoption.

9.Web-Scale IT

Web-scale IT has already proven its mettle at large cloud services providers such as Amazon, Google, Netflix, Facebook and others and is now making its way into enterprises. Webscale IT in the enterprise will find adoption via technologies like OpenStack, Platform As A Service(PaaS) and DevOps, a software development philosophy & methodology that emphasises communication, collaboration and integration between development and operations. This trend towards adopting web scale practices, is definitely taking hold in IT organizations that want to be nimble and effective, will be driven by Open Source.

10.Risk-Based Security and Self-Protection

As cybercrime attacks increase in scale, notoriety and sophistication, security will clearly emerge as a cross cutting concern in any technology implementation. Broadly identifying every potential attack vector, enforcing realtime intelligence & deep learning around these while keeping the overall business context in mind will be one of the key approaches in keeping data & systems secure.

All said and done, these are disruptive (and exciting times) for enterprise IT and open source in particular. In follow-on posts, we will examine how these trends are rippling across the financial services industry both from a business solution & technology platform perspective.