The Role of Technology in the Medical Devices Industry

which new technologies have the potential to impact medical devices in a big way?

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With almost everything under the sun being touched in one or another way by technology; medical devices are not exempt from this influence. Technology and medical devices have always had a strong bond with each other. Newer technologies that have sprung up over the past few years have accentuated their already strong linkage. So, which new technologies have the potential to impact medical devices in a big way? There are many, but let us consider these among them:

Artificial Intelligence: Undoubtedly, the real shaker for the medical devices industry is AI. AI has been around for a while now, but with the major impetus it received with the advent of the cloud, which makes its monstrous amounts of data manageable, AI’s prowess seems more capable of actualizing. Take IBM Watson for instance. It is being seen as a technology that can alter the landscape of the healthcare industry. Its uses in the medical devices industry too may become more prominent in the years to come.

IoT: The Internet of Things is another phenomenon that could impact medical devices strongly. The day is not far off where we will be able to get IoT to carry out all the manual tasks of the industry today. The most crucial element it could introduce into the industry is likely to be connectivity. Connectivity of medical devices could alter the game for the medical devices industry.

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You can offer them a solution that meets their needs

How should you engage them next, since customer engagement drives purchase decisions?

As marketers, we’re in the business of understanding behavior and what makes people buy things. But in the age of technology, when we can communicate seamlessly with anyone, anywhere with an internet connection, crucial elements still get lost in translation.

It’s somewhat absurd that with the rise of digital, we’ve actually masked a lot of the behavioral signals that help us piece together the person behind the action.

Sure, someone clicked, but do you know why? And how should you engage them next, since customer engagement drives purchase decisions?

Your prospective customers aren’t necessarily saying anything to you verbally the way you’d hear a loved one or a boss. So, we’re left to sift through click-through rates, time spent on web pages and drop-off times on videos. But it’s vital that we decipher what our customers are trying to tell us online, just as we would in an in-person conversation.

Despite their seeming silence, customers are continually giving off signals about their mindset through their behavior during their engagement with your assets — powerful signals I like to call “digital body language.”

How Best Buy is using its insights

In recent months, for example, Best Buy realized their special sauce was the in-person conversation — the interaction people have in-store with the “blue shirts,” the employees wearing the well-known bright blue polo shirts. So Best Buy exploited this point of differentiation in its most recent ad campaign.

Recently, Best Buy Chief Marketing Officer Whit Alexander said:
Telling the story of our people — and how we make a meaningful impact on customers’ lives — is at the heart of this work.” … “The core of what differentiates Best Buy vs. everyone else — and makes us awesome for customers — is that we understand your unique needs and how tech can enhance your life.

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There are nuances to the process of buying electronics, especially big-ticket items, and an online description frequently doesn’t meet shoppers’ needs. That’s why Best Buy has shifted its focus to make its business model all about reading and engaging their customers.

One 30-second spot, for example, shows an employee helping a customer choose a refrigerator — a purchase decision based specifically on fingerprint-resistance.

This is a powerful lesson for B2B companies to apply to our own marketing — we need to create an environment online that mirrors the showroom experience, where we can take cues from prospective customers.

Reading buyers’ digital body language

So you’ve got all these metrics on your prospective buyers, but the difficulty lies in deciphering what their actions actually mean. Your data should provide intelligence into how to approach each customer.

Here are some general guidelines about how to interpret and act on your prospect’s online behavior:

Multiple visits to your website or content

This is the equivalent of bumping into someone a few times and making small talk. You’re not quite friends, but you are acquaintances and know a few things about each other. These buyers are aware of your product and offerings but may not know much about them.

It’s best to engage them with introductory content, and not get too far into the weeds too fast. If you have a sense of what industry they work in, you should tailor your content based on those insights. Keep these pieces of content on the short side, so you don’t lose their attention.

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Authorities by transferring relatively small amounts over time

Can this information help diagnose important problems, or detect trends that might help the car company improve its products?

Natural language processing (NLP) has become popular in the past two years as more businesses processes implement this technology in different niches. In inviting our guest today, we want to know specifically which industries, businesses or processes NLP could be leveraged to learn from activity logs.

For instance, we aim to understand how car companies can extract insights from the incident reports they receive from individual users or dealerships, whether it is a report related to manufacturing, service or weather.

In the same manner, how can insights be gleaned from the banking or insurance industries based on activity logs? We speak with the University of Texas’s Dr. Bruce Porter to discover the current and future use-cases of NLP in customer feedback.

Expertise: Machine reading, natural language processing

Brief Recognition: As SparkCognition’s Chief Scientist, Dr. Bruce Porter leads the company’s research and development initiatives. He was a two-time chair of the University of Texas, Austin Computer Science department, recently returning to his role as a professor at the university to focus on teaching and research. In 2017, the Austin Chamber of Commerce recognized Dr. Porter, with the Economic Development Volunteer of the Year award for his work in recruiting technology companies to build and innovate throughout the economy across the Austin region.

Big Idea

Many companies and government agencies are deluged with incident reports, customer logs, and information coming in the form of text. To gather insight from these logs, Dr. Porter coined the term “macroreading”, which refers to the detection of patterns in huge masses of unstructured text.

Example 1: Improving Customer Experience in the Auto Industry

In the automobile industry, imagine that a car company receives incident reports on a daily basis car owners or car dealerships. These reports consist of a paragraph or two of text describing a problem that the customer has experienced with a particular car. These incident logs have unstructured information. They come in the form of text, diagrams or pictures. They can also include metadata such as the occasion and other incident details that are structured, Dr. Porter clarifies.

The question is: Can the car company mine the text reports to find patterns at the macrolevel and discover what is happening with the cars in a particular model and year? Can this information help diagnose important problems, or detect trends that might help the car company improve its products?

Data entry might vary widely across different parts of the automotive industry. Car incident reports could be typed if they are received by someone in the office. Technicians in the field could be using audio devices to report a problem. A business with the ability to find patterns and across all of these different data types would be better prepared to find and address problems and opportunities quickly.

Example 2: Preventing Financial Fraud and Money Laundering

Dr. Porter brings us to the financial sector for his second example. He explains that wire transfer reports come with meta information such as the certain amount of money being moved, as well as the source and destination of the wire transfer. The report also contains text information about the nature of the wire transfer and the relationship of the money sender to the bank. In this, a macroreading application has the potential to uncover fraud and money laundering activities.

Dr. Porter further explains that developing a banking application for the government can be challenging, primarily because such an application requires a large quantity of data. That the application could potentially be used as an investigative tool requires it to be a deep, robust system. The application must have the capability to show interrelated actions and participants over time, which when taken together reveal a pattern of suspicious behavior.

Citing money laundering as an example, Dr. Porter explains that one pattern shows a small business such as a car wash or a laundromat collecting cash, and then wire transferring large sums of money through accounts owned by these small businesses (with the intention of “flying under the radar” of authorities by transferring relatively small amounts over time).

Dr. Porter forecasts that industries that would need this kind of insight in the next five to 10 years would be those with significant investments in equipment that is distributed globally. The company would be receiving reports on a regular basis, either hourly or daily, of how that equipment is performing. The challenge for the company is detecting failures early before they get out of hand and meeting the regulatory obligations for large industries.

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Defense secretary did not take the phone into confidential or sensitive meetings

More serious incident occurred in May when Amazon’s Alexa assistant mistakenly recorded a couple’s private conversation and sent it to someone on their contact list.

Apple’s digital assistant left a leading member of the U.K. government red-faced on Tuesday after it unexpectedly piped up during a speech he was giving to lawmakers in the British parliament.

Perhaps a little too keen to offer help, Siri interrupted a statement that defense secretary Gavin Williamson was giving to the House of Commons about the situation in Syria.

Evidently keeping his phone in always-listening mode, Apple’s digital assistant should really only have responded upon hearing “Hey, Siri.” But, with his iPhone in his pocket, it seems the word “Syria” prompted the assistant to spring into action.

As Williamson addressed lawmakers, Siri got back to the defense secretary with its findings, with the response picked up by the Commons’ microphones: “I found something on the web for Syria, Syrian Democratic Forces supported by coalition … ”

Speaker John Bercow was quick to respond, describing the unusual happening as a “very rum business” (an archaic term for “odd”) as the defense secretary scrambled to switch off his iPhone.

“I do apologize for that,” a sheepish-looking Williamson said, adding, “It is very rare that you are heckled by your own mobile phone.”

He then asked the Speaker if could proceed, “without the help and support of Siri.”

Williamson later tweeted that the gaff was “one of the pitfalls of having a new iPhone … I must ask my 13-year-old daughter how to use it!”

But some people questioned whether it was wise for a defense secretary to be going around with a phone that had voice recognition software switched on all the time.

A source close to Williamson later insisted that having Siri switched on did not pose a security risk, adding that defense secretary did not take the phone into confidential or sensitive meetings.

A similar though more serious incident occurred in May when Amazon’s Alexa assistant mistakenly recorded a couple’s private conversation and sent it to someone on their contact list.

Always listening?

In a piece about whether our smartphones are indeed listening to us the all of the time, Digital Trends’ Simon Hill points out how “the internet is rife with anecdotal stories about digital eavesdropping,” noting that “many people feel that conversations they’ve had within earshot of their phones have been used to tailor advertising.”

Both Apple and Google keep recordings of users’ conversations with their respective digital assistants, though Apple deletes files after two years and says it only uses them to improve the product.

To see your Google history, log in to your account and type history.google.com/history into your browser’s address bar. You’ll see all of your activity on Google’s various services, among them Chrome, Search, and YouTube. Tap Filter by date & product at the top, choose Voice & Audio, and select Search. Any voice searches you’ve made on Google will be listed, and you can even play them back.

Want to prevent your phone from always listening for the keyword — whether “OK Google” or “Hey Siri” — that activates its assistant? On Android, go to Settings > Google > Search & Now > Voice and turn off “OK Google” detection. For iPhone, go to Settings > Siri & Search and toggle “Listen for Hey Siri” to off.

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