A CIO’s DevOps approach to resolving the agility-stability paradox
Real process change to DevOps requires a break with the past.
The next stage in the evolution of the internet of things? Security.
It’s a whole new world—but only if businesses enact appropriate safeguards.
Are you keeping up with your tech-savvy customers?
Vala Afshar of Salesforce on the new rules for delighting—and keeping—your customers in the digital age.
Security at the level of key-value pairs in a NoSQL database
Adam Fuchs of Sqrrl describes the benefits of data-centric security analytics.
Augmented reality: A catalyst for the coming cognitive revolution
Augmented reality can extend humans’ cognitive potential, reduce cognitive burden, and provide a new view to business operations.
Chris is a principal and Chief Technologist for the US firm’s Advisory practice, where he is responsible for technology strategy, enterprise architecture and innovation, and the development of thought leadership reflective of PwC’s point of view on trends and innovations in technology. He works directly with senior executives on their most complex and strategic technology issues, helping to explore the opportunities presented by emerging technologies, define the IT function and organization, deploy IT governance and management practices, and develop business and technical architectures. Among his accomplishments, Chris has global experience helping CIOs be more innovative, and has helped design and lead the implementation of high-value technology initiatives for his clients, most recently in the property and casualty insurance, health insurance and consumer products industries. Chris is a leading technology blogger, and also leads the development and analysis of PwC’s annual Digital IQ Survey, which measures how well companies understand and capitalize on the value of technology and leverage it to meet their business and customer needs. Follow Chris on and
3 approaches to emerging technology experimentation
The key to effectively experimenting with emerging technology is to link innovations to specific business goals.
Industrial manufacturers should set sights on digital operations, not just products
Manufacturers that transform their operations with digital technologies can move faster and more efficiently—and cut costs.
Not quite ready for the (fourth industrial) revolution
With few businesses prepared for Industry 4.0, it’s time to hone your strategy for emerging technology.
Three big emerging technology themes from CES 2016
How will three major themes that prevailed at CES 2016 impact your organization’s technology strategy?
Garage university for emerging technologists: Quadcopters
What inspired makers tinkering in their garages can teach businesses about effectively experimenting with technology.
Demystifying machine learning part 2: Supervised, unsupervised, and reinforcement learning
What do all technology innovators have in common? These three guiding principles.
The capabilities and limitations of video analytics
Video analytics promise to help retailers better understand customers. Here are three issues to keep in mind.
The power of picking the right prototype
How to overcome some common challenges of using prototypes to test out product ideas.
Three key hurdles hampering the internet of things
We explore three big issues that are keeping the internet of things from truly taking off.
Field service workers could fix wearables’ PR problem
Why wearables are tailor-made for field service workers, who could become the technology’s biggest advocates.
Will data lake advocates repeat the mistakes of data warehousing?
A look at some of the challenges enterprises can face in implementing a shift to data lakes.
6 technology innovation sources for outside-in learning
How to stoke the flames of innovation in your company by bringing the outside in.
The FBI says you’ve been breached by a nation-state. Now what?
What to do if your company’s network falls victim to hacking by a nation-state.
The 5 Dimensions of the So-Called Data Scientist
What is “data science”? Is it really a new emerging discipline as some claim it to be; or is it the emperor in new clothes – data mining, statistics, business intelligence or analytics re-branded? Moreover, is it possible that one person can fulfil the role of a data scientist? Rather than answering this question directly, let’s review some of the skills required for someone to be a “data scientist.” First and foremost, a “data scientist” is a business or domain expert: Someone who has to have the ability to articulate how information, insights, and analytics can help business leadership answer key questions – and even determine which questions need answering – and make appropriate decisions. The data scientist will need a thorough understanding of the business across the value chain (from marketing, sales, distribution, operations, pricing, products, finance, risk, etc.) to do this well. Second, a “data scientist” is a statistics expert: Someone who has to have the ability to determine the most appropriate statistical techniques for addressing different classes of problems, apply the relevant techniques, and translate the results and generate insights in such a way that the businesses can understand the value. This will be predicated on a …
Common Misconceptions about Emerging Technologies: Gamification
Mining Customer Insights with Speech-to-Text Technology
From touch and gesture interfaces to advanced facial recognition, our computers are communicating with us on an increasingly human level. One technology that is showing particular promise is a computer’s ability to recognize human speech or Speech-to-Text (STT). Applications such as Apple’s Siri, Google Now, and Nuance’s Dragon have brought voice-activated commands to the masses while enterprise companies are employing the technology to discover new insights from previously untapped audio and video data sources. One of the greatest benefits of STT is the ability to bridge the gap between unstructured audio/video data and advanced analytics such as machine learning, natural language processing (NLP), and graph analysis. A company’s ability to understand their most vocal customers, whether within their call centers or on video sharing sites, can lead to a better view of customers and their experiences. Call center logs can reveal interesting patterns and trends in the quality of customer agent call handling and (when combined with other data) call center operational costs. These insights could then be used to retrain customer service agents, identify and stop a poorly conceived marketing campaign, or quickly understand the root cause for a spike in call center volume. For example, PwC’s Emerging Tech …
Espionage tradecraft targeting businesses
Defending against sophisticated cyber attacks starts with awareness training.