Corporate Executives continually scan the landscape to stay updated on trends in technology. In my role, that includes EA governance, I have a ringside view of new initiatives being rolled out at a multinational organization. Some of these involve emerging technologies, while most are integration of incremental capabilities; better mousetraps if you can call it that.
Some of these “trends” might indeed usher seismic innovation and changes, while many are just aggregation of existing technologies and techniques – better and incrementally effective mousetraps! Herein lies the risk of reviewing new capabilities, trends and technologies: the risk of being wowed by the buzzwords, and being able to see through The Emperor's New Clothes.
Here is an eclectic list of trends I have been scanning (trends not listed in order of significance):
Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate to deal with them.... The term "big data" often refers simply to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. – Wikipedia
Trends in leveraging Big Data and tools and techniques for visualization and Analytics are already being leveraged by mainstream corporate IT and business users. For an example case study, refer to my earlier post: Digitization in Agriculture: Enabling Data and Analytical Modeling.
Adoption of SR and STT in business contexts may include a mix of IVR technologies to enhance User Interfaces in ways we haven’t done before.
The field of AI and machine learning periodically receives media attention when platforms like Watson beats Chess grandmasters, Jeopardy and Go champions; and also when thinkers like Stephen Hawking warn about dangers of AI or machines going rogue.
Emerging technologies in the eCommerce space include enhanced payment gateways, supply chain and third party logistics management platforms, combined with social customer engagement (SMAC) and use of Big Data. Multi-channel customer engagement and a strong eCommerce framework is among the key enablers of a digital strategy. While technologies and skilled resources exist in the marketplace, integrating them into one's existing corporate ecosystem continues to be a challenge.
Note: I have not listed some of the more obvious technologies, including widespread adoption of SaaS, Cloud, virtualization, in-memory computing, SMAC etc as some of these are already appearing in implementation roadmaps.
* Analysts and consultants have already started publishing “predictions for 2017”
Repost from my Linkedin Pulse article
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Some of these “trends” might indeed usher seismic innovation and changes, while many are just aggregation of existing technologies and techniques – better and incrementally effective mousetraps! Herein lies the risk of reviewing new capabilities, trends and technologies: the risk of being wowed by the buzzwords, and being able to see through The Emperor's New Clothes.
Here is an eclectic list of trends I have been scanning (trends not listed in order of significance):
Trend: Digital and Digitization
Digitization has certainly come beyond buzzword, though there are several schools of thought when it comes to leveraging digital technologies. IT executives and leaders have been living through waves of automation, updates in usability, user self-service, web and mobile enablement and eCommerce. Some of us muse if Digitization is perhaps an uber term used as a combination of some of these: taking the view “Isn't "Digital" just IT done the right way?” Of course, "Digital" isn’t just IT done the right way ! (my earlier post) In many organizations, realizing the promise of digitization is really a challenge of system integration, and visualizing how technologies work in cohesion.Why should corporate executives pay attention?
- We need to continually explore opportunities to engage business stakeholders, and design “digital services” for our customers. Novel digital use cases include that of a medical Insurance company offering “virtual doctor visit” (to minimize cost of doctor visits), a bank enabling digital deposit tools to minimize the need for customers to visit a branch etc.
- Startups continue to innovate in domain specific areas, some of which can be leveraged by larger enterprises
- Need to continually evaluate the impact of new and emerging digital business models like the sharing economy – uber, airBnb etc - and what it could mean to your business
Trend: Big Data, visualization and Analytics
In a tongue and cheek way, Lisa Arthur wrote in a Forbes article (link)Big data is new and “ginormous” and scary –very, very scary. No, wait. Big data is just another name for the same old data marketers have always used, and it’s not all that big, and it’s something we should be embracing, not fearing. No, hold on. That’s not it, either. What I meant to say is that big data is as powerful as a tsunami, but it’s a deluge that can be controlled . . . in a positive way, to provide business insights and value. Yes, that’s right, isn’t it?
Why should corporate executives pay attention?
Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate to deal with them.... The term "big data" often refers simply to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. – Wikipedia
Trends in leveraging Big Data and tools and techniques for visualization and Analytics are already being leveraged by mainstream corporate IT and business users. For an example case study, refer to my earlier post: Digitization in Agriculture: Enabling Data and Analytical Modeling.
Trend: Speech and Voice recognition
“Speech recognition (SR) is the inter-disciplinary sub-field of computational linguistics which incorporates knowledge and research in the linguistics, computer science, and electrical engineering fields to develop methodologies and technologies that enables the recognition and translation of spoken language into text by computers and computerized devices such as those categorized as smart technologies and robotics. It is also known as "automatic speech recognition" (ASR), "computer speech recognition", or just "speech to text" (STT).” ( link)Speech recognition is an area that continues to make strides in both consumer-centric – Siri, Alexa et al – and in business. Call center applications have been at the forefront of speech recognition. When is the last time you were directly connected to a call-center agent of your credit card company or airline? You probably spend a few minutes patiently explaining the “reason for your call” and spelling your first/last-name and account number to a digital prompter before being put on hold for a “live” person to talk to you.
Why should corporate executives pay attention?
Advanced interactive voice response (IVR) technologies, SR and STT are at a very nascent stage of evolution. Consumer centric applications like Siri, Alexa and others continue to push the boundaries. Among the cool tools I continually use include online text-to-voice that I use for proofreading my articles. I find it easier to catch silly errors by having someone – even a digital voice read back my text.Adoption of SR and STT in business contexts may include a mix of IVR technologies to enhance User Interfaces in ways we haven’t done before.
Trend: Artificial Intelligence (AI), Machine Learning and cognitive technologies
An ideal "intelligent" machine (computer) is a flexible rational agent that perceives its environment and takes actions that maximize its chance of success at some goal. The authors of "State of Enterprise Machine Learning" defines it as "software that extracts high-value knowledge from data with little or no human supervision.”The field of AI and machine learning periodically receives media attention when platforms like Watson beats Chess grandmasters, Jeopardy and Go champions; and also when thinkers like Stephen Hawking warn about dangers of AI or machines going rogue.
Why should corporate executives pay attention?
The promise of Artificial Intelligence (AI) has been touted by computer scientists and researchers for the past few decades. While some of the prophecies are yet to come true, expert systems and deep-learning frameworks are already being leveraged for data and predictive analytics in Financial, medical research, chat-bots and other areas. Some of the AI and machine learning tools and techniques are also being leveraged to enhance corporate platforms like ERP (link) and CRM systems, which means these technologies are entering the corporate world without a lot of fanfare.Trend: Blockchain
At its core, blockchain is a globally distributed ledger of all the information pertaining to a digital transaction. Despite the wild swing of new-age currency – Bitcoin - blockchain and distributed databases pioneered by it has been receiving a lot of attention. It runs on millions of devices, is open to anyone and can be used to securely move and store anything of value, including money, art, intellectual property and even votes.As the Harvard Business Review put it, “it’s the first native digital medium for value, just as the internet was the first native digital medium for information.” - Forbes
Why should corporate executives pay attention?
Blockchain use-cases include smart contracts, secure medical records, secure sharing of intellectual property like music among others are already being pioneered. Organizations continue to evolve other scenarios using blockchain technologies to digitally authenticate users and to securely store measurable value.Trend: eCommerce
Electronic commerce, commonly written as e-commerce or eCommerce, is the trading or facilitation of trading in products or services using computer networks, such as the Internet or online social networks. - wikipediaWhy should corporate executives pay attention?
A corporate eCommerce initiative may feel like “a better mousetrap,” especially for those of us who have been engaged in corporate digitization, B2B or B2C initiatives. (link to my case study) However, eCommerce tools and technologies to enable consumer centric and business-to-business electronic commerce continue to mature.Emerging technologies in the eCommerce space include enhanced payment gateways, supply chain and third party logistics management platforms, combined with social customer engagement (SMAC) and use of Big Data. Multi-channel customer engagement and a strong eCommerce framework is among the key enablers of a digital strategy. While technologies and skilled resources exist in the marketplace, integrating them into one's existing corporate ecosystem continues to be a challenge.
Other trends to add to a watch-list:
- Virtual Reality and gaming
- Why? Advances in IOT, wearable devices, gaming, animation and other technologies have enterprise use cases too.
- Robotics, automation and Internet of Things (IOT)
- Why? Obvious uses in manufacturing, and consumer electronics and entertainment. Other scenarios continue to emerge
- 3-D printing
- Why? Use-cases include modelling, prototyping and visualization and in manufacturing and entertainment. Other scenarios continue to emerge
- Self-Driving Cars
- Why? Technologies - including robotics, sensors, AI - that are being integrated to enable self-driving cars may be applicable in other scenarios
Note: I have not listed some of the more obvious technologies, including widespread adoption of SaaS, Cloud, virtualization, in-memory computing, SMAC etc as some of these are already appearing in implementation roadmaps.
* Analysts and consultants have already started publishing “predictions for 2017”
- IDC Reveals Worldwide CIO Agenda 2017 Predictions
- Gartner: Top Strategic Predictions for 2017 and Beyond
- Forrester's 2017 Predictions For CIOs
- ZDNet : Predictions 2017: A year of action
Repost from my Linkedin Pulse article
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Thanks for reading! Please click on Like, Share or Comment below to continue this conversation and ping back with your forecasts.
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