Get Real AI with Right-Brain Based Reasoning

AI is blossoming, but the real advantage of AI is yet to come. While organizations are mesmerized by the power of AI on left-brained activities of facts, rules, and logic, the big opportunity lies fallow. It's the right-brained activities that help with insight, interpretation, intuition, judgment, and reasoning where the big benefits can be gleaned. The leverage of general policies, creativity, and constraints is not natural in the world of AI today. Because it is difficult today, many pass reasoning and judgment by these days. What if there was a way to deliver right-brained behavior with left-brained activities? There is, but I'll get to that later.  

Jump-Starting Right-Brained Reasoning:

Since Left-brained analytic and approaches require precision, they are more pure text language-based and not open-ended. They require all possibilities to be covered and dealt-with ahead of time. Right-brained approaches are more open-ended and somewhat of "close fit" or "similar patterned".  Reasoning requires a more model-driven approach, but not a static model. Right-brained approaches require more fitting, approaching dynamic limits and inflight adjustments. To make judgments and to reason requires adjustments plus precision used in unison.

Setting Goals, Constraints, and Interaction:

In interactive and adjustable situations, often goals are set to direct behavior. In the case of multiple goals, sometimes in conflict, dynamic adjustments to find a balance that works for the moment until completion of the overall mission. Along the way, the behavior will also be guided by constraints (boundaries) that are not easily changeable. As activity attempts to reach a set of goals without violating any boundaries, new and unexpected outputs and behaviors can emerge. Thereby the result may be similar to creativity and imagination. This effect is emergence with goals and guidelines implying judgment.  

Acting in Real-Time Dynamically:

Real-time is a vital part of the right-brained approach in that there are some trial and error, some in-flight adjustment and looking at results in light of desired outcomes. Adjustments are made on the way to outcomes or when outcomes are not what fits the desired outcomes. It implies judgment or reasoning. I'm not sure it fits precisely with feelings like empathy, but it can be emulated.

Net; Net:

Judgment is a different kind of AI that is hard to cobble together by yourself. The good news is that I have stumbled upon technology from a company called Compsim that has the graphical language, KEEL Dynamic Graphical Language that is able to deliver much of the right-brained behavior for organizations. KEEL also delivers explainable and auditable judgment along with the reasoning in a way that humans cannot provide. This is a little known company that has significant experience in dealing with live interactive problems that are impossible to deliver with just left-brained AI solutions. Remember you heard it here first. Make sure you sample some of the videos as they are instructive and will give you a sense of delivery.

More about Compsim & KEEL http://www.compsim.com/

Got Customer Excellence?

It seems that we all are chasing down the dream of customer excellence, but if you ask someone what it is you probably will get a variety of answers. Some would say that customer excellence is a better customer experience, some would propose an optimized customer journey and others would suggest an outside-in approach to a customer journey as a customer interacts with your organization. We would say it is all three plus a journey that transcends your organization and others. Many are missing the whole point and are optimizing on goals from an organizational point of view. Pictured below is a typical myopic customer journey optimized for an organization to drive sales.

Better Customer Experience:

Having a more fluid and easy to use customer experience is never a bad thing unless organizations stop there and claim victory.  Yes, you have paved the well-worn paths that lead to organizational outcomes in a more fluid way with less friction with legacy processes and applications, but that does not guarantee customer loyalty in the short term or the elusive customer for life. You may be still inflicting pain on your customers unwittingly. See customer pain index by clicking here. Without considering the real customer journey organizations miss the whole idea of customer goals.

An Organizational Customer Journey:

The next step in maturity is to consider the customer journey that your customers take in dealing with your organization. This can be accomplished by mining the journeys from channels, website, and systems logs to put together a picture of what is actually happening. While this will point out additional friction points and areas of optimization for both the customer and the organization, this may be incomplete. For parts of the journey that are not fully automated or there may not be logs, so modeling capabilities can be used in combination to complete the journey maps. The automated logs only represent existing processes that might not be good enough. More mature customer excellence programs have the processes highly influenced by the target journey. To read more about the journey/process interaction, click here.

An Outside-in Customer Journey:

Looking realistically at the real customer journey with their goals overriding goals is the next level of maturity in customer excellence. Ideally, this journey would go beyond the four walls of your organization. Instead of the sun orbiting around the earth, this takes a look at how the earth (your organization) revolves around the sun (the customer). For instance, your company might handle mortgage loans, which is a small piece of the journey buying and comfortably occupying a new home with your family. Another example is that your organization finds the ideal hotel for your holiday, but the journey is a literally a complete trip with airlines, ground transport and recommended places to eat and stores nearby.

Net; Net:

Customer excellence is all about understanding the customer. the goals of the customers, the real journey and your organization's opportunity to optimize its touchpoints for both the customer and your organization. This means a change in your organization's culture, the skills of your people and the effectiveness of your processes/applications in the real customer journey while serving the balance of organizational and customer goals.


Co-authored by Jim Sinur, Gero Decker & Mark McGregor

Top 5 Facets of the AI Gem

AI will be the gem of digital going forward for a long time. It is a co-driver of smarts in both automation and customer excellence efforts along with static algorithms. AI can learn, handle fuzzy problems, and help with increasing the probability of success in decisions, assist humans in interacting with traditional rule-based organizational systems and reaching shifting goals. There are five facets of AI that are shining bright now and for the future. There could be more down the road as AI progresses over time, but these are the top five right now.

Machine Learning:

Right now, ML is the brightest facet of AI as organizations deal with ever-growing big and fast data sources. ML learns for the data to get better and speed up responses to interesting patterns. ML is good at handling rich and complex data for incremental learning and thus assisting decisions and actions. The machines do most of the heavy lifting here, but the quality and control of the data is a key factor for success. The learning can get better with the addition of facets of neural nets to create deep learning opportunities to speed up the evolution. Keep in mind that ML can learn from bad data too and the maintenance of data can be costly.

Artificial Neural Nets:

While neural nets are popular in the deep learning portions of ML, they also have an identity of their own. They are great at interpolating between several taught patterns for classification and categorization. They pay attention to differences and emerging patterns.  They are also strong at self-training and learning, particularly for unstructured data often found in natural language problems. Their strength is that no expert is needed, just training data. Keep in mind that ANN requires a significant number of patterns for better results and retention of patterns becomes a management issue. Retraining is also a factor to consider.  

Fuzzy Logic:

Fuzzy Logic is helpful when there is not a precise truth as it handles degrees of truth. It is good where there are grey situations. This is often the case with human and machine dialog where there might be linguistic uncertainties. FL is difficult to explain in some situations because it handles linguistic uncertainty. Because of this uncertainty, there will be situations that a subject to interpretation.

Bayesian Belief Networks:

Bayesian Networks are applicable to cause and effect problem domains. BBN's are aimed at probabilities of the relationship between symptoms and situations or outcomes. This is accomplished by mapping the casual probabilistic relationship among a set of random variables, the conditional dependencies, and joint probability distribution. This is mapping is often represented in a visual model that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). Keep in mind BBNs are dependent on having good statistics to drive results.

AI Reverse Chaining:

Reverse chaining is good at moving towards goals where all the underlying data may not be complete, but there are available inputs to leverage. Also, ARC can be sued to figure out the typical paths that brought an organization to their existing state. The inherent strength is that it handles missing information and data. Keep in mind that since there is a lot of trial and error, ARC is not the best at real-time control.

Net; Net:

While AI is still an evolving gem in terms of application to an organizations problems, there are some bright spots that can deliver benefits. It is important to match the AI approach to the problem at hand even if there is a combination of AI facets used in the solution set.  As more case studies emerge, the clarity of the application of these facets will increase and reduce the amount of pioneering. Vendors and solution providers will a real source of wisdom here over time.

It's Time to Stop the "CPA Insanity"

Most organizations are cost-conscious to a fault. In fact, a goodly number of organizations are working against their customers and parts of their own organizations. CFOs state that "costs must be controlled or cut back". This creates a culture of suboptimization where individuals focus on their own span of control to cut costs thus negatively affects others. Management sets cost savings goals without guidance on how to do it intelligently. For instance, a servicing portion of a company cuts proactive customer service to save costs thus negatively impacting customer satisfaction and the sale of new products or services.  It is true insanity to manage costs to the point to impact revenues.  What are the symptoms or results of unguided or constrained cost-cutting efforts?

Slave to Metrics:

While it is important to measure, some organizations measure too much and expect all the numbers to move in a direction set by management. This creates a mentality that forgets common sense. Let's look at the Boeing 737 Max. Management set an impossible schedule and forced reuse of an existing airframe. While bigger engines were added, the software that compensated for the effect of these engines and placement were short-changed. The software development was completed by the lowest cost resources that were not great at excellent testing practices. Boeing also cut redundant measuring devices making it a higher cost option for the airlines. Suboptimal cost-cutting had tragic results.  The metrics of Boeing and the airlines came first.

Culture of Lower Quality:

Boeing also did not develop simulators or require airlines to do so. Instead, some light training was put in tablets for pilots. Boeing sold the idea that real simulation and training was not necessary as the 737 Max so similar to existing 737 fight behavior. Additionally, many airlines are configuring this new 737s in a way to cut customer comfort from seats to bathroom sizes. There is plenty of this kind of quality reduction in every industry to the point of inflicting pain on customers and employees.

Customer Neglect/Bad Experiences:

Most organizations are optimized for organizational outcomes and business processes that benefit the organization at the expense of the customer. Smart organizations are now additionally focusing on customer journeys and customer goals. Brilliant organizations are looking at their organization's role in the complete customer journey. Organizations, wrongly so, think that they are the center of the customer's journey or experience. An example would be mortgage companies believing that the loan process is the center of buying and settling into a new home. While one can appreciate a faster and easier loan process is good, it is only one piece of the real journey.

Immediate Gratification:

The mistake that most CPAs commit is to think short term cost-cutting is always a good thing. While the effect might please the existing management and help stock values in the short term, there could be long term impacts. Some times looking at the long term impacts and balancing customer outcomes with automation results is really the good thing. Obviously, there will be role and goal conflicts that include costs, but the CPAs should not have the last say.

Missed Opportunities: 

The focus on cost containment and short term result run headlong into the need for investments necessary to be future-ready. In this day and age of digital transformation, investments are needed now. Certainly, automation investments seem like a good deal for the CPA, but other investments are necessary to keep ahead or up to competitive levels. If the economy heads in another direction, then the window for digital investments that are not automation focused will be closing quickly. Invest in digital separation while the time is right.

Net; Net: 

Cost micromanagement without regard to long term or important investments ruins organizational cultures and beats down innovation. It also loses business as exhibited by recent cancelled orders for the 737 Max. It's time to move from "CPA Insanity" to organizations that are crazy smart by creating customer excellence while automating.

Low Code: Have it Your Way

While low-code is a better approach to delivering software in a rapid fashion through visual approaches, there are various forms of low code that can be used separately or in combination to deliver outcomes. Each low-code vendor will try to convince you that they have the best offering, but we all know that one vendor can't really do it all. It is important to understand the forms of low-code and which ones appeal to your organization. Click here to read about low-code benefits.

Model Focused:

This form of low code uses highly visual approaches to describe the intentions of the software. Often these model focused capabilities can describe how work can flow from one step to another as well as the basic step activities, data used and outcomes. The types of models that are being leveraged today are broad deep and rich. Click here for an explanation of the use of models in digital efforts. Suffice it to say tha models are quite convenient and show a visual connection to interrelated activities. The weakness sometimes is to understand the underlying details during the execution of these models when testing or debugging software.

Composition Focused:

When there is an inventory of pre-built code, process snippets, services or micro-services, a composition environment can be used to reuse these together or with new components to create either a loosely or tightly coupled package of software components. These new combinations will need to be tested as a group in the various contexts to make sure the outcomes are satisfactory. The weakness of this approach is to search and find just the right service to aggregate in a new group for new uses. Also changing these components might add extra overhead is they are reused in many contexts.

Configuration Focused:

This approach has code that is ready to execute, but the features and options will need to be selected. This is also called parameter or data-driven software. Most of the possibilities have been pre-designed into the software ahead of time and the developers can turn on or features on or off. In highly generalized approaches all the combinations may or may not be built-in. This is especially true of bootstrapped general software packages that leverage metadata. The weakness of this approach is that there is a lower level of customization. 

Framework/Template Focused:

Frameworks and templates are general outlines of known and tested in a simplistic way. They can be easily extended and customized for each use. This is a looser form of software package that allows for high levels of customization or extension. Often there are forms of configuration here as well and sometimes there are some lower-level services to compose. Frameworks appeal to those who want jump starts over the custom/ bespoke code approach. The weakness of this approach is that it requires that the user fill in a goodly number of details that need to be tested.

Graphical / Menu Focused: 

This approach is very popular and it is usually leveraged in the above approaches. There are often pull down visual menus that are utilized to build or configure the software. This is a highly useful "pick and chose" solution that delivers solid software in a productive fashion. There is a significant amount of visual creativity leveraged in this approach.

Net; Net: 

All of these approaches have proven to work in any number of combinations and in any number of organizations. It is truly a "have it your way" combination of options for developers of all kinds. Low-code fits well with digital transformation especially when migrating away from existing applications and packages.