Coming Wave of Artificial Intelligence & RPA

A wave of Robotic Process Automation or RPA is coming and will take over corporate America faster than we think. Businesses will be forced to implement it to stay competitive and be able to do more with less resources.

There are many naysayers who dismiss RPA as a mere rebranding of simple automation that have existed in different industries for many years. I disagree with this sentiment because this time around the automation we have is capable of leveraging Artificial Intelligence. RPA is to Automation what Facebook was to Myspace, Stripe is to PayPal, Uber to Taxis or Google to Yahoo.

The time is right

As surprising as it may sound, we are going through a massive cultural shift around reducing the human interaction and increasing on-demand services. This is evident from the success of companies like Doordash, GrubHub, Amazon, Uber, Lyft and UberEats. The coming generation wants to drive less, order online and get their things delivered to them as fast as possible. A stark contrast to the time when American companies used to tout having a real person answering the phone as one of their competitive benefits.

In healthcare, faster claims processing, speedy payment delivery and immediate replies to customer inquiries are easily possible via RPA. These RPA solutions can be developed quickly because in today’s market, we have many niche softwares and tools that can act as ingredients in designing a large system. This availability of external tools is what has made the RPA highly valuable.

For example: to use OCR within RPA workflow, we can use Google Cloud Vision, Amazon’s AWS or free open source libraries. Google, Amazon, Microsoft and IBM alone are offering so many cloud based tools that there are very few processes left that could not be automated using the RPA.

Is RPA truly an AI? 

RPA is a sequence of events or flow manually designed by a developer to mimic a specific process. When people talk about AI, they generally mean machine learning, deep learning or neural networks. However, the Artificial Intelligence is a term that includes every algorithm that allows automation to happen irregardless of how smart it is.

If I had to describe AI and RPA to a beginner, here is how I would put it:

AI is an umbrella term that includes RPA, machine learning, deep learning and neural networks. Out of these, the RPA is like a limb in a human body while the rest act as brain. RPA is capable of clicking on things, entering data and mimicking movements on a computer similar to that of a human. Machine learning, deep learning and neural networks on the other hand are like a brain and are capable of thinking, recognizing patterns and learning from past experiences.

The true power of RPA comes in when it is combined with machine learning.

For example: you can train a machine learning algorithm on 5 years worth of claims data and connect it to a claims processing RPA flow. This system will eventually be capable of processing claims at a much higher and accurate rate than an employee who has been doing it for 5 straight years.

Difference between RPA and Classic Automation 

Classic automation have always existed in one shape or form but what makes the current RPA different is its ability to handle exceptions and being system agnostic. RPA can work with multiple systems while classic automation only lives within the bounds of a single system it was designed for. RPA can also take any standard manual process and automate it. It can also leverage machine learning and neural networks to learn and improve itself.

Take claims processing as an example. Automatic Claims Adjudication is an example of classic automation. In the current claims adjudication processes, any claim that produces an error or requires special handling like manual checking of a Prior Auth needs a human to look at it. RPA on the other hand can not only learn from the previously processed claims but can also use any third-party systems that could aid in completing the processing of a claim.

Why RPA will take over corporate America? 

RPA will take over quickly because it is easy to implement, has high ROI, decreases errors, increases quality, reduces the turnaround time. It enables employees to work on innovative things, deal with customers and focus on more complicated tasks. Businesses that want to grow and stay competitive will have no choice but to implement RPA.

Will RPA cause job losses? 

A common myth about RPA is that it will take over all jobs. The truth is that RPA will actually result in a net increase in the number of total jobs. It's just that the nature of jobs will change. As mundane repetitive tasks are automated with RPA, new opportunities will emerge and new technological roles will evolve. Even the jobs that may become obsolete will not cause layoffs. The majority of businesses will opt for attrition rather than going for massive layoffs.

Final Thoughts 

Whether we like it or not, AI is coming. Implementing it is not a matter of being cool, saving money or automating things. It is about survival!

All of us implementing AI are in the same boat because we are essentially going from human to a robot. The processes in our companies were designed with humans in mind. This single point is what makes us different from the new businesses coming to market. Majority of these newcomers are starting with AI first and humans later.

Any insurance startup which designs its business processes based on AI will instantly have an upper hand on any existing insurance company. Their processing capability and revenue will be higher while their workforce will be a third of the incumbents.

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Decentralized technologies have made a huge progress in the last decade. The first major decentralized application to go viral was BitTorrent in early 2000. It was a file sharing network that allowed its users to share files across the globe. Five years later, Satoshi Nakamoto came out with the idea of BlockChain (a distributed Database) and used it to built the Decentralized Currency, BitCoin. BitCoin was a huge success because it allowed users to send and receive payments to anyone in the world without the approval or involvement of the financial institutions.

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If you work with multiple tables at the same time, there is a high chance you will need to join then through queries. In relational databases, we do this by using Left Joins, Right Joins, Outer Joins and  Inner Joins. Since there are so many options, the question is, which join to use in what scenario. Because if used incorrectly, the queries from these joins can produce erroneous data.

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What the heck is Population Health Management?

Looking at the name "Population Health Management", we can at least tell that it has something to do with the overall health of a population. But the questions that still linger in the mind are what kind of population we are talking about? how does this model work? what are its benefits? and why is it important?

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Important initiatives for CIOs in 2015

The focus of healthcare accountability, quality outcomes and cost of care is driving a major shift in the healthcare industry. Whilst CIOs have always had their plate full, this year specifically will be a busier one. Each of the agenda items this year ties back to the transition from "Fee for Volume" to "Fee for Value" model. Strategically this means paying attention to how care is financed, delivered and managed. Here is my list of items that I consider to be important in 2015.

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2015 The year of Analytics

It was 2001 when I read "The Age of Spiritual Machines" written by Ray Kurzweil and subsequently fell in love with his exponential growth and coming age of singularity ideas. Back then, I thought of Ray's predictions more so as herculean if not utterly impossible; but now, looking at the advancements from the last couple of years, it is quite clear that the future is about to arrive at a much faster rate than we had originally anticipated. The year 2015 will be one of the most important years for disruptive trends and will take us closer to Ray's singularity dream. The most prominent trend throughout this year will be getting the value out of implemented technologies rather than the technologies themselves.

IT as a Solution Center

The IT departments will not be able to survive as a mere cost centers anymore. Their function has been evolving for some time and will continue to shift towards becoming solution centers. The CIOs will have to leverage technology to derive change across organizations. The new era of data will demand that CIOs change their roles from technology professionals to someone who understands the business strategy, company direction, business operations and most importantly how the organization makes money. Successful CIOs will be the enablers of change that companies need.

Crowdfunded Startups

It would not be a stretch to say that the 2014 was the year of crowdsourcing and crowdfunding. Wherever millennials saw a problem, they tackled it by turning and asking communities to fund their solutions.

Take "One Fast Cat" as an example; it's a company which makes exercise wheels similar to hamster wheels but for Bengal cats. For over five years low quality cat wheels were being sold at high prices with cheapest being $500 dollars. In 2014, California resident Sean Farley managed to design his own wheel using Solid Works software and a 3D printer. Thinking he could help others with his solution, he took his prototype to Kickstarter and raised more than $320,000 in initial funding and thus the "One Fast Cat" was born. Today, they have more orders coming in than they can fulfill and are taking reservation orders with shipping dates of more than two months in the future.

Stories like "One Fast Cat" will become the new norm in our society and 2015 will bring a new batch of fresh millionaires.

Internet of Things

A well-known statement by Mark Weiser published in Scientific American (1991) was "The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it." Today Mark's quote is true in every aspect of technology we look at. Facebook used to be a personal profile website meant for students to share pictures. Today, we use Facebook for many more purposes that just a mere profile. In 2011, it was used for revolutions in Egypt and Tunisia; something never been done before that.

IoT (Internet of things) will follow the same suit as Facebook. It will creep up slowly such that living without intelligent devices will be considered weird. Although we will not see a full scale implementation in 2015, it will however appear in larger frequency throughout the year.

At the moment notable advancements in IoT include Fuel Band by Nike, FitBit Bands, Nest's Thermostat, intelligent fridge and the majority of smart watches. IBM's "smart planet," Samsung's "smart things" and Google's acquisition of Nest indicates that big businesses are paying attention. So the question is not if Internet of Things will become reality but "when" will they integrate themselves into the fabric of everyday life.

Data Analytics

It is said that data engineers will be high in demand but short in supply in the coming years. We will see technology going in the background and the "value of technology" taking center stage. This is because the technology simply collects the data while the analytics conducted on that data provides the actual value. In 2015, the majority of the CIOs will try to acquire talent which will help them get the most value and insights out of their technologies.

The healthcare industry will utilize data analytics as part of their "Population Health" initiative. Physicians will be enabled to see a 360 degree view of their patients and receive suggestions from their analytical engines. Insurance companies will be able to provide better and appropriate care to their consumers. IT departments will mine healthcare data to help shift focus from treatment based models to value 7 prevention based care models.

Data Security Products

Given the increasing number of data breaches, security applications will be most prominent in 2015. Two prominent applications coming out this year are Illumio and SkyHigh Networks. Illumio is a visual security platform which operates with no dependencies on the infrastructure while SkyHigh is a security platform meant for clouds and gives a very fine level of control to system admins.

Bottom Line

For the past couple of years everyone have been collecting vast sums of data through various channels. This year the focus will shift from collection to utilization (analytics). Companies ahead of the curve will be able to successfully extract value from their data and strategize where they want to go. Aside from analytics, other prominent needs will be larger storage, data security and cloud. In a nutshell, it will not be about what technology one is implementing but what value one is trying to get out of it.

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Big Data as the New Currency

The holy grail of Big Data lies in the ability of identifying the right set of data and thereupon properly using it for greater insights. Asking for such capabilities may have been difficult in the past years, but the recent flood of applications and softwares have made such tasks much easier (if not trivial). It is suffice to say that we are entering into an era where the power of predicting things seems to be within grasp.

Data Value

The moment we have a tangible use (such as predictability and decision insights) associated with the data, it becomes valuable; equally valuable to companies, individuals and the bad guys. Back in 2013, the most popular trend among hackers was to steal credit card information and to sell that info to third parties internationally. Now that trend is shifting towards stealing personal data. From PHI (personal health information) to things like emails, the possibilities are endless. Look no further than what happened to Sony in the recent breach.

Data Breaches

The sad part is that it will still take some time for us to take data security seriously. There is a risk of additional breaches, hacks and leaks in 2015 which will give the governments and companies the "push" they need to make data security reforms.

Looking back at some of the breaches in 2014 we can see a trend starting to appear. It will only get worse if nothing is done about the security.

Data Breaches in 2014

Onsite Health Diagnostics

When: January  2014

Number affected: 60 thousand

Data Type: patient names, DOB, addresses, emails, phone numbers and gender

Method used: Unknown party inappropriately accessed online scheduler system

Michaels Store Chain

When: January 2014

Number affected: 3 million

Data Type: customer debit and credit information

Method used: Payment system was breached by hackers

Los Angeles County Department of Health Services

When: February 2014

Number affected: 170 thousand

Data Type: patient names, SSN, DOB, billing information and medical history

Method used: Eight computers containing the data were stolen from the billing company (Sutherland Healthcare Solutions)

American Express

When: March 2014

Number affected: 76 thousand

Data Type: California customer names, accounts numbers, expiration dates and four-digit CVS codes

Method used: Hacktivist group The Anonymous

Living Social

When: April 2014

Number affected: 50 million

Data Type: Customer names, emails, DOB and encrypted passwords

Method used: Hackers attacked the website

Community Health Systems, Inc.

When: April 2014

Number affected: 4.5 million

Data Type: patient names, addresses, DOB and SSN

Method used: Chinese hackers were believed to be behind the attack

Aventura Hospital and Medical Center

When: September 2014

Number affected: 82 thousand

Data Type: patient name, DOB and SSN

Method used: Vendor's employee stole the data

Home Depot

When: September 2014

Number affected: 56 million

Data Type: customer credit card information

Method used: Malware was installed on payment systems by a hacker group

New Jersey Doctor (Dr. Nisar A. Quraishi)

When: October 2014

Number affected: 40 thousand

Data Type: patient names, SSN, DOB and medical history

Method used: Break-in at the storage facility

JP Morgan Chase

When: October 2014

Number affected: 76 million

Data Type: patient phone numbers, DOB, addresses and SSN

Method used: Hackers gained root access to the secure servers

Bottom Line

Our discovery of the powers that data holds is turning it into a tradable commodity. We are entering into a world where stealing data is as lucrative (if not more) as stealing credit card information. Hackers have successfully demonstrated they can compromise governments, companies and law enforcement agencies. The large number of data breaches that occurred in 2014 proves the aforementioned points and demands that we pay equal attention to the security of the data.

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