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Which division of a brand should own “data analytics”?

(TECH NEWS) Some say data analytics should be under the CMO’s control, others say the CFO, and so forth. So where does it fit today?

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We are entering a new data-driven age

As this new data revolution sweeps across corporate America, one of the most important questions businesses must start answering is who owns the organization’s data.

With the predictive power that comes from data analysis, an essential part of corporate strategy for companies is to become adept at anticipating where analytics is best placed.

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Why not in the finance division?

There are a few main ways an organization can structure their analytics to suit their needs. Typically, the first way is to place data analytics with the finance arm of the business.

Particularly for companies who are numbers- and finance-driven, it can make a lot of sense for the finance or CFO to oversee analytics. Companies such as Guthy-Renker, a leading direct response firm, place data analytics in the hands of finance because they are focused on numbers.

Maybe the IT department?

Information technology is another area of the organization that can successfully own the company’s data analytics. Capital One’s CIO, Rob Alexander, notes how the company leverages big data technologies to analyze customer spending patterns and demographic data to inform their building of mobile apps and other offers to members.

Placing data analytics directly in the hands of IT can be helpful to firms still trying to determine how to store, access, and even accurately analyze all of its data. This ensures all technology-related decisions are left in the realm of their tech department.

Marketing, sales, and customer service are generally the best at customer stewardship. For companies that are truly customer-focused, these areas of organizations are essential for reading data and distilling insights. In 2015, for example, T-Mobile reduced customer attrition rates by 50% by focusing on the key analytic of customer acquisition. Discovery of what repels, attracts, and retains customers can be crucial to fulfilling enterprise goals.

How about a good ol’ matrix?

Alternatively, other businesses adopt a matrix approach that focuses on allowing the data to determine the strategy around an organization.

In a matrix, each impacted department has some degree of analytics focusing on intent and action, with the chief strategy officer overseeing the larger picture. This scenario best suits firms that take an R&D approach to data analytics. In this way, they may not precisely know what they are going to get from the data, where it comes from, or where it’s going, but they are committed to letting the data speak for itself.

The takeaway

It is up to a business to determine how committed they are to data analytics, what resources they have to dedicate to it, and where it is best placed in their organization.

However large or small, at this point all companies should start learning how best to use data analysis in their decision-making.

#dataanalytics

Nichole earned a Master's in Sociology from Texas State University and has publications in peer-reviewed journals. She has spent her career in tech and advertising. Her writing interests include the intersection of tech and society. She is currently pursuing her PhD in Communication and Media Studies at Murdoch University.

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China no longer dependent on U.S. for smartphone components

(TECH NEWS) Trump’s trade war, more specifically, the ban on shipping phone components, to China has begun to take a toll on chip manufacturing.

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Once upon a time, the U.S. and China were buddies, exporting and importing from each other with ease. However, President Trump’s recent actions regarding trade with China is certainly putting a damper on things.

It seems that Chinese companies have moved past the need to import certain products, like smartphone chips, from the U.S. – something they previously relied heavily on by working with American companies like Qorvo, Inc. in North Carolina, Skyworks, Inc. in Massachusetts, Broadcom, Inc. in California, and Cirrus Logic in Texas.

Since the ban in May, Trump specifically barred shipments from the U.S. from companies like Qualcomm and Intel Corp to companies like Chinese tech conglomerate, Huawei Technologies Co. But much like the bans that came before the Trump administration, it didn’t last long. With tensions high, the U.S. actually recently started rolling back some aspects of the ban and started making exceptions that allow American tech companies to continue to work with Chinese companies like Huawei.

Of course, China’s lack of U.S. parts hasn’t stopped them from rolling out new and improved products. As a matter of fact, in September, Huawei unveiled its newest phone, the Mate 30, which boasts highly-desired features, such as a curved screen and a wide angle camera. This makes the phone a pretty solid competitor of Apple’s newest iPhone, the iPhone 11, of which China was sent 10 million of in September and October.

After Huawei’s announcement, investment and banking firm UBS, and Japanese technology lab Fomalhaut Techno Solutions, partnered up and took to their labs to analyze the phone’s components. Their analysis was simple and straightforward. They found that there were absolutely zero American components in the phone. In fact, the chips in the Mate 30 are actually from Huawei’s in-house chip design agency, HiSilicon. They also provided Huawei with WiFi and Bluetooth chips. With HiSilicon’s 20 + years experience in the industry, 200+ chipsets, and 8000+ patents, it’s no wonder U.S. chip companies are getting nervous. Qualcomm, for example, announced a 31-40% decrease in estimated chip shipments over the next year.

Although the chip ban has made a big impact on larger U.S. companies who make and supply chips to China, there are still many other businesses that have been affected in Trump’s trade war. As it happens, U.S. Commerce Secretary Wilbur Ross recently confessed that, since May, when the ban was put in place, the U.S. has received at least 260 requests, asking that they excuse them from the ban and be allowed to work with China as they previously had.

But really, at the end of the day, with so many American companies relying on China for both import and export, it’s probable that the ban will be short-lived and that exceptions won’t need to be made. As Americans, we can be hopeful that the end-result of this trade war will be a positive one, but only time will tell.

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AI cameras could cut down traffic deaths, but there may be flaws

(TECH NEWS) Traffic accidents have plagued humanity since motor vehicles were created, can AI help cut down on text and drive incidents?

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What if we told you Australian officials believe they have found a way to reduce driving deaths by almost 30% in just two years? It’s a pretty appealing concept. After all, Australia alone faces an average of over 3 deaths a day due to driving accidents. And Australia’s average death rate clocks in at just half of what we face in the United States.

There’s just one problem with Australia’s proposed solution: it’s basically Big Brother.

Basically, Australia plans to use AI cameras to catch people texting and driving. There are plenty of places that have outlawed texting and driving, but that rule is very hard to enforce – it basically means catching someone in the act. With AI cameras, hands free driving can be monitored and fined.

Australia has already started rolling out some of these systems in South Wales. Because this is a new initiative, first time offenses will be let off with a warning. The following offenses can add up quickly, though, with fines anywhere from $233 to $309 USD. After a six month trial period, this program is projected to expand significantly.

But there are real concerns with this project.

Surprisingly, privacy isn’t one of these worries. Sure, “AI cameras built to monitor individuals” sounds like a plot point from 1984, but it’s not quite as dire as it seems. First, many places already have traffic cameras in order to catch things like people running red lights. More importantly, though, is the fact these machines aren’t being trained to identify faces. Instead, the machine learning for the cameras will focus on aspects of distracted driving, like hands off the wheel.

The bigger concern is what will come from placing the burden of proof on drivers. Because machine learning isn’t perfect, it will be paired with humans who will review the tagged photographs in order to eliminate false positives. The problem is, humans aren’t perfect either. There’s bound to be false positives to fall through the cracks.

Some worry that the imperfect system will slow down the judicial system as more people go to court over traffic violations they believe are unfair. Others are concerned that some indicators for texting while driving (such as hands off the wheel) might not simply apply texting. What if, for instance, someone was passing a phone to the back seat? Changing the music? There are subtleties that might not be able to be captured in a photograph or identified by an AI.

No matter what you think of the system, however, only time can tell if the project will be effective.

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DeepComposer: AWS’ piano keyboard turns AI up to 11

(TECH NEWS) Amazon has been busy with machine learning, which includes a camera, a car, and now DeepComposer that’s able to add to classics on the fly

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Musicians, listen up, there’s a new kid in town, its name is DeepComposer and it’s coming to take your creativity and turn it up to 11.

Artificial Intelligence has taken a leap into what has long been considered the “pinnacle of human creativity”, as Amazon revealed what is said to be the world’s first machine learning-enabled keyboard capable of creating music.

Amazon unveiled its AWS DeepComposer keyboard Monday during AWS re:Invent, a learning conference Amazon Web Services hosted for the global cloud computing community in Las Vegas.

Demonstrating DeepComposer’s abilities, Dr. Matt Wood, Amazon’s VP of Artificial Intelligence, played a snippet of Beethoven’s “Ode to Joy” and then let the keyboard riff on it with drums, synthesizer, guitar, and bass, sharing a more rockin’ version of the masterpiece.

Generative AI, is considered by scientists at MIT to be one of the most promising advances in AI in the past decade, Wood told the crowd. Generative AI allows for a machine not only to learn from example, as a human would but to take it next level and connect the dots, making the next creative step to composing something completely new.

“It [Generative AI] opens the door to an entire world of possibilities for human and computer creativity, with practical applications emerging across industries, from turning sketches into images for accelerated product development, to improving computer-aided design of complex objects, Amazon said on its AWS re:Invent website.

How does it work? The Generative AI technique pits two different neural networks against each other to produce new and original digital works based on sample inputs, according to Amazon. The generator creates, the discriminator provides feedback for tweaks and together they create “exquisite music”, Wood explained.

A user inputs a melody on the keyboard, then using the console they choose the genre, rock, classical, pop, jazz or create your own and voila, you have a new piece of music. Then, if so desired users can share their creations with the world through SoundCloud.

This is the third machine learning teaching device Amazon has made available, according to TechCrunch. It introduced the DeepLens camera in 2017 and in 2018 the DeepRacer racing cars. DeepComposer isn’t available just yet, but AWS account holders can sign up for a preview once it is.

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