This paper is designed to shed some light on the use cases that exploit the new world of technology with Machine Intelligence encompassing Cognitive, Artificial Intelligence, Artificial Intuition, Machine and Deep Learning. People ask us every day to explain the use cases organizations are using for MI/AI in their vertical. While there are many published use cases, one common denominator exists for each. If they are published, they are not competitive in nature. The organizations in these verticals are already aware of the use cases. They are considering applying and optimizing them if they have not done so already. Conversely, the use cases we see that are not disclosed are quite innovative in nature and are tied to a specific business problem. This paper will not talk about ‘self-driving cars’ or robotic process automation as these are specific fields of innovation. Instead, we will look at the biggest issue we see, which is how to benefit from this new technology and data with existing legacy corporate and government organizations. The use cases that will mean the most to your organization will be the ones developed around your business, making it better, more competitive, disruptive, or more profitable. The opportunities exist; they simply have to be identified. Instead, this paper will examine the objectives, goals, and innovation process around Critical Thinking, Design Thinking, and Use Case Think Tank Workshops and the understanding of personas in the organization involved in the process of change. We will also discuss disruptive use cases that ride the line of social responsibility. Finally, we will wrap up with some public examples to get everyone thinking of use cases that involve analytics.
Historical Transformation to Accelerated Transformation
There is a little acknowledged fact that some of us forget to take into consideration. The majority of large corporations that existed ten, twenty, or thirty years ago are not in existence today. Without naming specific ones, we should consider what happened to a few of them. We reference these because transformation and innovation is part of successful corporate life. We believe digital transformation will simply accelerate this process. The transformation of organizations fall into several categories; they were acquired by another firm, there was a roll up of many similar companies, they closed their doors, they dropped certain lines of business, they created or launched a new market, they innovated, and more.
I started my career writing a master’s paper on the pending breakup of AT&T in university. Over the next three decades, I watched how this organization transformed. There was a big disruption back then as the FCC said they were a monopoly in the telecommunications industry. The Baby Bells were born and National Exchange Carrier Association was established to support them. AT&T morphed into various divisions. AT&T Labs was a great place for innovation, but over time, the company did not innovate enough. Southern New England Telephone was born in the Northeast part of the U.S. It grew and became SBC Communications through acquisitions. SBC grew so strong that it eventually bought AT&T, but kept the AT&T name because it had more customer recognition. In 2015, DirecTV was bought by AT&T (SBC Communications). At the time of this writing, there is a pending merger with Time Warner.
We give these as examples to demonstrate how large companies through innovation (or a lack thereof), acquisition, merger, failure, or just a better competitor in the marketplace have all changed organizations over the years. While the major corporations, which are typically slow moving, have experienced this, something is very different now. Machine Intelligence and all of its disciplines will simply be an accelerant to this process of change spawned by innovation, competition, or even the little garage based idea funded with millions of dollars of venture capital to exploit its exponential and digital transformation capabilities. That accelerant is normally a combination of ideas, technology, money, and successful execution.
Make Your Business Better
Legacy Corporations all look to maintain and increase their bottom line, as many are publicly traded or have private interests. The critical concept is to determine how to take an organization to the next level, exploiting what it already does very well with new or modified ways of increasing revenue or reducing costs. The goal of any use case should be to somehow make the business the organization is already in better. This could come in the form of efficiency in operations, decreasing the cost of doing business, increasing revenues, or being more competitive in the industry. Successful legacy organizations finding use cases that exploit this technology often pair it with improved financial results or operational efficiency. Some organizations do this so well that they create a new market. Each use case should pass the litmus test. Organization leaders must ask the question ‘why should we do this and what happens if we do not?’
Understanding the Personas and Roles
Destiny Corporation has learned over many years and projects that there are a few key roles in an organization that drive or prevent this type of change. We believe it is important to understand them before going through the process of ideation and transformation.
The ‘identifier’ is typically an individual or set of folks who understand today’s state of the organization or the processes they are intimately involved with. They know it well enough to understand how it works today and the challenges they currently have. They also think about how it could be better. However, the identifier may never act upon their thoughts or beliefs of making a process better, but it makes for great water cooler conversation.
The ‘innovator’ is quite often the person who understands the current process and some of the technology, but is determined to find a better way. They typically come up with ideas and possibly another way of using technology to solve current problems or create new opportunities. Data Scientists are not necessarily business innovators, but they can usually perform the Machine Intelligence work.
The ‘sponsor’ is usually the one who believes in this new capability and is willing to stake their reputation on it. The sponsor is sometimes also the ‘Process Owner’ who is commonly a senior business leader.
The ‘champion’ is often the politically astute individual who understands how to navigate the organization and gain agreement in cross functional environments.
There are other driving factors that rarely seem to be published in this setting. For example, understanding executive pay strategies is also critical. The sponsor or champion may be in a hired position that is tied to corporate profits, innovation, or growth. It is not uncommon to find individuals in half million dollar compensation packages where the base pay is part of that with a potential bonus if they succeed in moving the needle of measurement in a positive direction. Some of these people can often be highly motivated. It is important to get ideas vetted well before engaging with these folks as they have the power to move things along or immediately squash an idea if it gets in their way.
Beware the Luddites
It is worth mentioning that a good idea that sparks change and innovation in an organization will always be met with Luddites. These are folks that do not want anything to change and can be quite resistant for a variety of reasons. Understanding these reasons is a fruitful exercise for those of us who look to drive innovation. Their concerns around change can be loss of a job, fear of the unknown, loss of control, exposing their lack of competence, poor timing, lack of reward, politics, no support, empathy, peer pressure, or lack of trust. These folks will rarely help find use cases. Instead, to move forward once a project is defined, change should be disseminated to them, possibly offering incentives and an open door policy for discussion. Finally, management needs to be clear that regardless, change will happen in support of any new project.
Be Disruptive and Socially Responsible
The use cases for each firm will affect the organization or the market in some way. The end result is the effect it will have on people that could be employees, clients, and some aspect of society. The result and social aspect of some use cases are very clear. For example, discovering actual additional fraud and money laundering practices in financial systems can only yield a positive result for the organization, its shareholders and its clients. Rolls Royce created a way to check airline engines every time a plane lands to see if maintenance is required. This can only be seen as positive as they reduce engine failure by helping maintenance workers use technology to assist them in spotting issues before planes fall out of the sky.
However, other disruptive technologies may displace employees, affect the environment, change an industry, or change a consumer’s opinion. Let’s consider the sharing economy businesses such as Uber. They think of themselves as a technology company, but they have completely changed the people transportation industry, displaced taxi drivers, driven down and driven up transportation costs using ‘surge pricing’ with machine learning optimization algorithms. All of this convenience comes at a cost; dealing with the driver/passenger behavior component, lack of driver vetting, assaults on passengers, assaults on Uber drivers, legal battles in countries where the cab association unions have gone to court to get them banned, and so on. Vacation Rentals by Owner (VRBO)/Airbnb is another one that has completely changed some markets with its offerings. The Housing Rights Committee of San Francisco allege a violation of the unfair competition law and local residents in a town in Spain have seen their long-term rental rates sky rocket, increasing their own, local cost of living.
The creation of social media platforms have created new advertising markets and allowed people to connect globally, form groups of like-minded thinkers and allow a dad to keep in touch with his daughter while she studies abroad. However, it has also allowed various terrorist organizations to radicalize individuals in other countries. It comes down to how the platforms are used. In many countries, government stepped in to regulate these firms. Machine Intelligence for Facebook, Twitter and others will play a key role in how these environments are managed. The organizations now staff full time moderators to identify and view the gruesome content constantly posted that must be removed on a daily basis. Some of these employees report experiencing secondary trauma, similar to a veteran with Post Traumatic Stress Disorder (PTSD).
It is important to mention what really goes on in Silicon Valley investment firms. While there is so much innovation that comes from specific pockets of the world, it is mostly driven by money and is a thriving investment industry. Some startups innovate and create great platforms and technologies for the world. However, digital transformation does change our lives. Startup investing is such a big business that there are investing firms such as Y Combinator that bring together venture capital investment with selected startups each year. The goal is to get the highest return on investment with mitigation of risk, where possible. But disruption with social responsibility is a challenging topic. It is so important to many investors that Bloomberg and Morningstar have tracked and published socially responsible U.S. mutual funds and ETFs for religious, environmental, social, governance, and Sharia compliant funds since 2008. There is a belief that there are long-term performance advantages in this type of investing.
Some Interesting Use Cases
As Destiny Corporation has been involved in analytics for over thirty years, it is interesting to see how traditional consumer segmentation targeting in the retail industry has moved into politics with the help of Google, Facebook and other technologies. One example was driven by a very astute analytics firm out of the U.K. Our current president’s election committee was able to target the mindset of consumers to get elected. It was very structured and organized.
Howard Moskowitz of MJI Research created the practice of ‘Addressable Minds’ many years ago. The practice uses advanced analytics to mind-type individuals and determine what combination of words, phrases, and images turn people on or off, creating segments. Once a person has been ‘typed’ on a particular topic, they can be addressed appropriately to get them to move toward or away from affinity to that topic. Destiny Corporation worked with MJI on the Stand Up to Cancer campaign. By using the correct combination of phrases and images, there was a $30 million uplift in pledges in a two hour television telethon in comparison to the previous year.
On the legacy corporate front, several multi-national corporations have outsourced their traditional American worker jobs to overseas firms in an effort to reduce costs. However, there is still a drive to reduce costs even further. AIG’s ARIES ‘virtual engineer’ is a machine learning, robotic process automation with built in algorithms that can make decisions about network incidents around the world. Today it assists its current staff and is dubbed ‘co-bots’. However, it will only get smarter and more efficient as time progresses, which means even the IT outsourced firms that fill repetitive process jobs will see a reduction in market demand for workers.
The First Step
At Destiny Corporation, we believe it is important to know the desired result before designing and starting the project. Use cases can be built using some of the latest analytics available, on great platforms such as IBM’s PowerAI, H2O, SAS, Anaconda, and others, but it is more important to know what your use case goal is before venturing down any path. It could be as simple as reducing customer churn or predicting system down time before it happens, or augmenting current staff capabilities with machine intelligence algorithms. Once the goal is documented, it can be sniff tested before any effort is made. For example, if we could reduce customer churn by 5%, what does that mean to the organization and the bottom line? Do we maintain a higher revenue stream? Are they customers we want to retain? Do we have to hire more employees to tend to these customers? If the answer is a resounding yes, then that could be identification of a viable use case.
The Critical Thinking Process
The Foundation for Critical Thinking, criticalthinking.org, is based upon objective analysis of facts to form judgment. As we apply this to finding our corporate or government use cases, we need to challenge the status quo, asking the question, are we doing the best we can or can we get better at what we do? For an Anti-Money Laundering department, questions such as ‘are we finding all money laundering activity as efficiently as possible? If we measure what we do today and could do 10% better, what would that mean in the reduction of financial losses or government fines?
The Design Thinking Process
The process of Design Thinking is a way of thinking and a particularly useful method for collaborating with team members to understand and define a problem or concept, perform out of the box brain storming through an ideation process, creation of inexpensive, scaled down prototypes, and testing. Through this entire process, feedback is used to adjust the elements of the various stages. This methodology can be traced back to Herbert A. Simon’s book The Sciences of the Artificial, published in 1969. The Interaction Design Foundation publishes the following chart for reference and clearly shows the process and the interaction between the steps.
The concepts are accepted, improved, modified, or rejected until the end result is something that makes sense for the business and senior management to support.
Destiny Corporation’s Use Case Think Tank Workshop
At Destiny Corporation, we quickly learned that while Machine Intelligence technology is promising, most major legacy corporations and government agencies are not the next Uber or Facebook. Instead, they have their own challenges with decades of hardened processes. We designed a Use Case Think Tank Workshop for clients that embed Critical and Design Thinking, matched with an organization’s financial and operational benefits that can be achieved through Machine Intelligence.
One of the critical factors in supporting better results with MI is an understanding of new and additional data that is now available. For example, a computer is able to read images to pinpoint cancer in patients faster than doctors can diagnose them. A property casualty insurance company is able to get field information through telematics or IoT devices or localized weather data feeds and forecasts from around the world to prevent losses. Better retail planning and design can make use of metro area data, which may include Footfall information collected from local cell phone users to predict customer traffic. Anonymized Credit card spend patterns are now available from credit card organizations such as MasterCard. These are all real examples of new types of data not available in previous years.
Automatic Pattern Recognition
Organically detecting previously unseen patterns in data is the Holy Grail for legacy corporations. It is one of the main benefits of Unsupervised Deep Learning. A neural model of understanding is built using weights and connections through several data points. Open Frameworks are designed to support this process on training data sets. For instance, in an Anti-Money Laundering example, various organizations build business rules based on their understanding of actual events in their data. This allows them to use pre-defined business logic to catch money laundering schemes. But what about the schemes they are not aware of? This is where automatic pattern recognition through these types of processes can help detect unseen patterns. At this point in the evolution of MI, however, knowledge workers are still required to validate many of the newly discovered patterns.
Finding the best use cases for your organization is a journey. Understanding what other legacy corporate firms have done is great for initial ideas, but identification of your own qualified use cases is the best way to apply this technology.