Monday, August 19, 2019

Giants Will Fall

There is a strong belief that the gap between the large and small companies is growing and the small organizations are doomed to taking a second seat forever. The numbers and history are on the side of the giants. They are large and strong financially, so they can spend more financially on research and development (R&D). The reality is that they won't because they are too busy boosting their stock price or lining the executive's pockets. Even if they were committed to spending a goodly amount on R&D, will they invest in the right research? Like the David of the bible facing Goliath, SMBs can count on 5 smooth digital stones that they can launch at the giants.


Customer Journeys: 

Most organizations are self-delusional thinking their products and services are just plain excellent. They create surveys that increase scores for bonuses for such delusion. Customers are not wanting standard and time-consuming customer journeys aimed at corporate outcomes and results. Customers have choices and are taking them these days. Newer generations are not brand loyal forever. They measure and switch. Better customer journeys are the most lethal stone that SMBs have to close the size gap.

AI & Analytics:

Most of the interactions that people have with organizations make organizations look dumb. By making the interactions smart by optimizing each touchpoint a business moment of for winning them again over an over. This means that AI should be assisting customers to get their outcomes easily. This may mean focusing on the relationship over short term profitability. AI and the leverage of data in a real-time fashion in a historical context aiming towards a "win-win" set of outcomes in the future.

Process & Emergence:

Processes need to be intelligent and able to adapt as it progresses toward goals. This means processes emerge instead of being a fixed set of sequences. While some task sequences make sense, they don't always apply to every situation and customer. Processes, workflows and task sequences(snippets) are important, but they need to be smart in their behavior in context. The best way is to sequence them synchronizing the emerging to the journey, be it customer, product, service or partner.

Robotic Automation:

Let's get rid of the dumb work for both clients and associates. Nobody wants to do mindless work or be irritated by systems limitations and fractures. Why make people take care of integration and translation? This is why RPA is taking off in a rapid fashion. Intelligently automate to beat the competition. Give those bots intelligence, so they can adapt along with journeys and processes.

Low Code:

The software just takes too long to create. While you can make it cheaper by outsourcing it to cheaper resources, that only solves the cost part of the equation. Often the quality isn't there because the emphasis costs not great outcomes. Recent headlines about software failures make this point with emphasis. Just ask Boeing. What about easy to code techniques such as reuse, drop-down code creation or code generation?

Net; Net: 

David only needed one stone to get his giant down, but SMBs might not be that fortunate. If I was a betting man, I'd pick the combination of customer journeys, AI and processes. I look forward to watching the battle and hoping someone will be popping me some popcorn soon. I'm rooting for the underdogs as the giants have beat me up in the past with experiences that don't match my desired journey and outcomes.  Some Giants will fall. Some SMBs will become as powerful as giants.

Wednesday, August 14, 2019

A Seriously Salty Service Story

Everyone has their sad stories of poor service and I love to hear them in order to learn what doesn't work. Also, I love to hear stories of great service, but that channel is full of the sound of crickets. Well, I have one myself. I have lived in my home for over 20 years now and it came equipped with a water softener that filters out minerals through a filter that needs to be washed out with saltwater through an automated backwash process.  The original softener broke, thanks to pre-designed obsolescence principles. This put me in the market for a new one. Then the fun began.



My neighbor recommended a saltless softener that used a special fluid to clean the filter in the backwash process. It was triple the normal price of the salt versions, but I wanted something that would last. Well, so much for that thought. It turns out that the one dealer that supplied the fluid went out of business, so I was backed into a corner. Just before I ran out of my reserve of fluid, we had a power surge related to our monster monsoon storms here in the desert. The surge knocked out the electronics and fried the unit. Back to the drawing board after a short three years.

Next, I went to a national chain to buy a sturdier salt version. The chain said that the electronics were bulletproof and that they would stand behind the unit. Guess what, 6 months down the road and another power surge knocked this unit out too. The national chain said that they didn't sell that unit anymore, so they couldn't or wouldn't help. Back to the drawing board after a three-year bout with hard water.

Then I went to a competitive national chain and they had an inexpensive unit ($500) that they admitted would not survive a surge even with a GFI enabled electrical socket. They promised a seamless install and I would have to pay the installer for their service and the product. Well, guess what?  The installer called and said I had to lug the softner home myself (pretty clumsy size and pretty heavy). The other option was to buy the softner by standing in line and storing it in "will call" The installer would charge $75 dollars to pick it up and $300 for the install. Well, I had enough with national chain stores as I backed out of that deal.

I went to a regional appliance store who sold a product that would only require a $12 replacement transformer if I had another surge issue. They would have the installer pick up the unit and install it for less than $200 dollars. Smooth sailing until another surge hits. While the softner was more expensive, the end to end customer journey was seamless and easy. I will now do more business with my new source that considers the customer journey first.

Net; Net:

Besides buyer beware, I will always look for the easiest customer journey. Something that I have learned the hard way. I need to watch the millennials more as they figured this out earlier in life. Thanks for listening to me if you made it this far :)





Thursday, August 8, 2019

Top 5 Techs to Budget for This Season

Let's make this part of the budgeting process a breeze. I always hated the budgeting process as a manager, so If I can help one person with this post, I'm pleased :)  Many folks will be asked to identify areas to spend the remaining 2019 budget and plan for 2020 in August. I have identified "TheTop 5 Techs" to invest in for the next 12 months. My rationale for picking these five amongst many digital technologies to invest in for the near future is the time to payback without sacrificing strategy. These five deliver quickly and can participate in strategic efforts for the medium and long term. The top techs for budgeting purposes in 2019 & 2020 are as follows:



Artificial Intelligence:

AI allows you to start small and grow successes into strategic wins. Most organizations have tried small machine learning projects that focus on data-oriented problem domains. It is time for those organizations to up their investment to create more momentum for AI to augment human activity while replacing error-prone of drudgery work. Most of the short term benefits are around automation, but better customer experiences are emerging too. The leaders will be looking to leverage AI for competitive advantage and reasoning applications of AI to assist human resources. Fast followers will deepen investments in more data-focused applications. Followers will now jump into the fray and try some form of AI soon as the window for early advantage is closing. Please click here for the typical types of AI or click here for AI problem domains explained.


Customer Journey Mapping:

Knowing the customer's real journey is essential and customer journey technologies are getting significant investment today. Most are related to monitoring and mining the real experience with today's web pages, processes or systems, but that is just the tip of the iceberg. While this gives some ideas where the friction points can be improved for a better experience, this is not enough to declare victory. Real journey mapping considers the journey from a customers perspective that may go beyond the four walls of your organization. Mapping capabilities that go beyond mined data for owned processes and applications to touchpoints necessary for understanding, documenting and training all the resources that touch customers during their real journey. Leaders are going for total customer excellence that considers the customer experiences in context. Fast followers are going beyond mining to include modeling. Followers will jump into mining. Please click here to understand CJM approaches or click here to understand CJM technology.

Low Code:

Low code approaches generally allow for faster development and testing of code. Low code can be applied to testing out business or technological solutions in a "time to market" fashion that is consistent with digital results. It can also be applied to quickly converting code from existing burning platforms, applications and processes to speed up digital transformations. Leaders are trying new business models plus approaches with low code tech. Fast followers are leveraging low code for productivity mostly. Followers are fast being enticed to deliver with low code tech. Please click here for leveraging low code for creative solutions or click here for successful low code approaches.

Robotic Process Automation(RPA):

RPA is being actively used to automate eliminate drudgery work like keying, logging onto multiple systems, integrating data from diverse systems, and creating straight-through processes. Today bots are created to eliminate tasks or drive sequences of activity while reducing human intervention. This allows workers to focus on delivering results like better customer interactions. Leaders are combining process with RPA, RPA with AI or low code with RPA to extend the benefits of RPA. Fast followers are inspecting their current processes and applications with mining tools to look for more automation opportunities. Followers are jumping on the bandwagon for task automation. Please click here for the power of RPA and process or click here to find the future of RPA.

Workflow / BPM:

Processes often orchestrate the work sequences of work tasks, resources and the tapping of content/data. Managing work in processes sequences, small or large has been a large contributor for decades for large scoped industrial processes. Today organizations are discovering that these kind of processes are less than 20% of the hidden processes through their departments and organizational groups. Thus workflow has taken off fast to create form-driven, case collaboration or small departmental flows. Leading organizations will reach for larger scoped processes that follow the real customer journeys even if they are following multiple supply or value chains. Fast followers are leveraging processes everywhere. Followers are just discovering the power of workflow. Please click here to learn the role of processes in the digital age or click here to understand the interaction of process and IoT.

Net; Net:

These are my top five amongst many others including blockchain, content/collaboration, IoT, analytics, unified communications, process mining, chat-bots, architecture tools, digital twins, cloud computing, augmented reality, big/fast data, 3D printing, and nanotech. You can run with these five and deliver short term benefits to build upon. You can even combine these into powerful combinations. Please click here for some potential combinations.






Monday, July 22, 2019

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/




Monday, July 15, 2019

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

Thursday, July 11, 2019

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.



Sunday, July 7, 2019

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.





Tuesday, July 2, 2019

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. 


Tuesday, June 25, 2019

Low Code is Really About Effectiveness

While the low-code vendors would stress productivity and cost savings, the real winning organizations are more aimed at effectiveness. We all know low-code methods and technologies provide environments that increase speed and agility in and around the creation of software, unlike traditional computer programming. While this a big win in itself, the real benefit of low-code is the ability to focus on doing the right thing as well. Going fast to the wrong destination is not a great idea. So how is low-code assisting effectiveness as well? 




Try New Ideas Quickly:

The problem with traditional programming is that the specifications have to be pretty well tied down before you start. This creates an environment where new ideas and approaches are an impediment to getting results. Low-code turns this idea on its head and allows folks at all levels to try ideas and enhance them quickly if they are considered "good" or more easily throw away those that look to not deliver the end goals. While low-code is not a simulation approach, it can be used in a "do it, try it, fix it" fashion without the guilt of wasting a lot of time and energy. This reduces IT having to say "NO" so much and from business, folks having to have perfect specifications. 

Expand the Developer Pool:

Programming skills are a choke point to getting results, so why not make more programmers by giving business professionals a shot at modeling, configuring and even developing business applications. Some like to call this "citizen development" where many folks can create processes, programs and, reusable programming services. This allows for putting more hands to developing software solutions that achieve desired business outcomes. 

Accelerating Digital Transformation:

The problem with digital transformation is that it is a big job. Also, the platforms that are being left behind can be on fire and considered burning platforms for the long term. Because of low-codes ability to accelerate ideation and the programming tasks, it becomes strategic to race away from and leverage key legacy components. Once a digital target is identified, low-code can get you there faster with more resources aimed at the set of solutions. 

Net; Net: 

Yes, low-code is fast code, but finding the right destination is another side benefit of low code, Yes, low-code cuts cost by increasing productivity, but it also enables effective use of more resources to reach the right destination. Low-code can help noodle out the right destination through iteration or leveraging trial and error approaches. It's hard to lose with low-code if you understand how much it can really help. 





Wednesday, June 19, 2019

AI Case Study, Gaining Traction in Auto Sales


One can't go anywhere today without hearing about AI, but I would say that half of it is around projecting how AI will be affecting our future and the other half is about data focused approaches. While there is nothing wrong about these discussions and articles, most of us are more interested in the results of AI which represents a family of approaches and algorithms in action to apply to business and everyday problems. Even though there are three major approaches to AI with data-driven, algorithm-driven, and process-driven (click here to read more), this case study is all about the algorithms in action in the highly competitive field of vehicle sales.



The Challenge:

Most dealerships rely on a variety of different internal tools, outdated systems and virtually no predictive technologies to mine their customer profiles leading to limited insights and frustrating sales initiatives. There are both algorithm and data issues implied in this challenge, but the predictive nature of this case study stood out.

This Solution:

There was a two-pronged approach employed to uncover hot prospects and close deals that were not intuitively obvious. First, a dashboard was installed to suggest specific talk tracks to personalize the potential buyer's situation when a prospect was being engaged. This is a sensitive approach that made the prospect feel cared for when discussions happened by design in an outbound manner or in response to incoming calls. For outbound prospecting customers were sorted according to their Behavior Prediction Score (BPS) which armed sales folks with the right marketing approach at the right time to elicit action. Dealer employees were aided and more prepared for calls or visits building confidence in the sales process.

The Result:

The obvious result is a better relationship with clients, but on the whole, sales were up for several dealerships. The typical numbers are a 15% increase in retention sales, a 3% increase in service-to-sold related sales and a 3% increase in new customers, varying on brand and dealer size. The hidden benefits were around cost savings during these efforts to deliver these impressive increases. The ROI was 15 times better and the costs of campaigns were 20% of previous efforts. 

Net; Net:

While there was a dynamic interaction of algorithms and data, the prediction characteristics were the secret sauce here. As organizations compete on algorithms and AI in the future we will see more algorithm driven success. Data is important, but it will be the co-pilot of success.

This Case Study was implemented using automotive Mastermind 

Monday, June 17, 2019

Is Automation the Tip of the AI Spear?

AI has a lot of opportunities to flourish, but what will be the major thrust to put AI into action?  Will it be the study of data to find interesting and essential patterns for organizations to act on?  WIll it be to assist organizations to make better decisions? Will it be the demand to make processes smart enough to adapt to customer expectation? My assertion is that automation will be the thrust that many will get behind. It's the one thrust that executives can get behind because they can get benefits early thus obviating risk. Let's look at the two sides of this assertion.



Automation Will Be the Key Driver of AI:

If you look at the traditional use of technology, it has always been about automating manual tasks or making resources more productive. Why would it be any different now? Organizations are always looking for cost advantages. Right now the economies are clicking despite all of the rumors of wars (trade or otherwise). This means that AI can contribute to many channels of benefit without any significant impact on the bottom line. In fact, more attention can be given to things like better customer experiences and more effective decisions. Just watch what happens when the economy cools off.  Automation will take a strong march across the organization. The MBAs and CPAs will unite to drive costs into a corner. Executive management might give a nod to other efforts with a wink, but you can count on automation under all scenarios.

Automation is Just One of Many Drivers for AI:

Sure automation is a no brainer for investment, but narrowly focused executives will be blind-sided by the customer excellence movement. This time the movement will also be active during any economic down coming our way. The notion that business can dictate a clunky experience and expect a positive response is sorely wrong. There will be those organizations that will stand in the breach of balancing customer wants and goals with organizational goals. These organizations will also value adding AI to customer journeys that even span beyond their four walls. The key touchpoints and moments of truth will need AI to stay adaptable in real time. These savvy organizations will be looking for patterns of success, even in down economic times.

Net; Net:

While I believe that a balanced approach is the better approach, cost-saving automation will always go ahead of everything else initially. The key is to make sure automation does not dominate to the point of stealing the future of good customer relationships sowing the seeds of the ultimate destruction of some organizations. Convenience and customer excellence will win the war over time. Let's not inflict pain to our customers, but let's combine smart journeys with the power of process automation.  Let's keep organizational and customer goals in balance folks and remember that smarts are necessary everywhere!



Thursday, June 13, 2019

The Top 5 Helpful Improvements for Sales Engagement Software

While most front line sales professionals would say that they are getting much less out of Sales Engagement Software than they put in terms of time and effort. See my previous post on the problems that sales professionals have with Sales Engagement Sofware by clicking here  The good news is that there are some efforts that can improve the experience for front line Sales Folks. Here are my "Top 5" improvements that I have researched to date. These ideas will require some skin in the game from executive management, but the investments will pay off large.




Key Personnel Information:

Every prospect or customer that salespeople have to deal will have specific needs, likes, dislikes, and attitudes. Why not share this information if known. Some organizations build a contact database with key pertinent information and places to write comments like "This contact is totally cost focused" or "This person is a strategic operation focused person" or "This person hates to be smoozed". The corporate knowledge about your prospects or customers needs to be captured and shared. Sales professionals need to be armed with contact information even if it is unstructured information and they appreciate insightful tips.

Market Segmentation Information:

Every organization that exists lives within a context. How does the target organization compete within its market?  What are the management philosophies, culture, and corporate charter? Who are the likely competitors that might be circling to sell to competitive products and services? What's the history with this account over the last ten years? What are their planning and budget cycle seasons? Is this a learning institution and who do they feed trained people to? Information about the targets competition would also add value to sales efforts.

Product/Service Utilization Information:

For existing customers that you want to sell more to has used your organization's products or services. How often do they reorder? Is there a way to view the inventory to suggest that they might be getting low. What are the consumption and spin down rates of inventory? What are the organizations planning horizon for readiness? What are the real satisfaction scores (not just answers on rigged surveys)? What products are a real hit and where are the hotspots around lagging results with your products or services?

Integrated Sales Playbooks:

Your organization has some proven methods or playbooks that are representative of best practice for selling. If playbooks are even available, are they available through the sales engagement system? If not, can they be linked to in a convenient way? Are there patterns to these plays and how they might apply to the prospect or client? Are there success stories documented in the playbooks to encourage the sales staff, particularly when their managers are pegged for time and they are unavailable to coach in a timely manner.

Next Best Action Suggestions: 

Having smart software (AI / algorithms) to assist sales folks is a great help particularly if there are large amounts of data/information or the data is changing in near real-time from multiple sources. Can a sales professional decision assistant be built to take in the data and information to suggest some alternative next steps? These can be large scoped or spot advisors taking into account recent prospect/customer activity or emerging product/service offerings/features. These kind of decision advisors are starting to emerge out of the digital assistant movement.

Net; Net: 

Powering salespeople with Sales Enablement Software takes much more than buying software and demanding that sales just fill in data for management control. Sales folks want something back and assists to help them close new deals or expand existing footprints in customer organizations. I'm sure there are more ideas that would make sales professionals feel like they are getting something back from sales engagement software.













Monday, June 10, 2019

Sales Enablement Software Doesn't Help Sales Much

I hear it from all the sales representatives I know. They hate their organization's sales enablement (aka sales engagement) software. All they do is put lots of data into the software and they only get micromanagement from their sales managers in return. It's a real burden. Why should companies keep investing in building data stores instead of real customer relationships?  Why are sales and upper management so detached from reality? What's wrong with this picture?  There are at least three things really wrong here.



The Illusion of Control:

The Sales Department is one of the most expensive organizations in an organization and it drives bean counters and top management crazy. "This needs to be controlled," they say. By making the sales professional more responsible, they will get better and management will have a better handle on the real situation in the field. I hate to be the bearer of bad news, but your sales folks are more interested in the relationship with the customer and how their own organization is going to help them close sales. Sales folks will reluctantly fill in your data, but you will not have more control because they put in just enough to appease management. Sales enablement software doesn't help sell, but it can help train green sales folks.

The Illusion of  More Data:

There is a falsehood around collecting as much data as possible so that the big picture folks can make better decisions and direct sales. While some subtle data hints and senior experience can help in certain situations, most sales managers use the data against the sales representatives. You're most successful sales representatives do not need to be over-managed with data. Collecting data that would help the sales professionals would be better than collecting data for data's sake. Sales folks put in a lot of data and virtually get nothing back. When will the data be used to help the salesperson close?  It's pretty much a one-way street right now.

The Illusion of Understanding Customers:

Managers, equipped with masses of data, think they understand the customer. They like to insert themselves into getting results when the data collected rarely tells the relationship story. Managers would rather listen to the data entered rather than trusting their seasoned sales folks. I hear my sales buddies tell me that they keep telling management what the customer wants and make resonable requests for deaf ears to ignore or reject. When the account is lost, the sale person is rotated elsewhere, at best, and the mangers then come up with the very ideas the sales person was trying to communicate.

Net; Net:

Let's leverage the data in sales enablement software to give the front line sales folks an advantage instead of feeding the insecurities of management. The worm has to turn with the advent of smarter sales enablement software that builds trust with sale folks and management. Le'ts stop the illusions, sub-optimizing, and micromanagement and turn the sales data into a useful sales tool for the people that are on our sides and represent our customers to create customer excellence.






Wednesday, June 5, 2019

PegaWorld 2019, Day 2: Pega Demonstrates Empathetic AI Solutions

This is big news! Organizations have been viewed, rightly so, as cold-hearted and only after their own goals. Now organizations can dial in empathy as needed with the addition of Empathetic AI. There was an actual demonstration by Dr. Rob Walker from the stage of variable warmth of customer service actions and offers considering the past history of individual clients. This is groundbreaking, but won't be released until 4Q 2019. If I ran a company that wanted to balance customer and organizational goals in a dynamic fashion, I'd be standing in line to get a chance to see if my organization could benefit from Empathetic AI. While organizations will have to learn how to tune the empathy switches over time, just having this feature should be a boon to organizations trying to balance great customer journeys with hardcore processes.


While there were presentations on leveraging innovation to become really digital and more digital heroes, Empathetic AI stole the show. Click here for Day 1 highlights of  Pegaworld Day 1. Lost in the shuffle was some proof points that organizations need to look themselves in the mirror when it comes to the reality of their customer service. Pega commissioned a survey of companies and clients to find out that 89% of executives think the customer is great while only 50% of their customer think so. This is a huge gap that can be closed by Empathetic AI embedded in a customer-focused solution like Pega has done. Get in line for a solution focused and embedded dial a heart. 


FROM COLD TO WARM by EMBEDDING EMPATHETIC AI




To watch this highly recommended session, click here

Tuesday, June 4, 2019

Pegaworld 2019: To Infinity and Beyond with Digital Super Heroes

PegaWorld, here in Vegas, has great numbers again with over 5000 attendees from over 700 brands. So what's new this year? Actually quite a bit. The biggest announcement was around Pega Infinity. Alan Treflor excitedly described their new name for and the functionality of their digital platform. The strong claim was that Infinity could equally apply intelligence to the Customer Engagement and Digital Automation sides of any business. The secret to winning on both sides of the equation, that typically are at odds with each other, was to balance goals and suggest next best actions leveraging tunable and reusable micro journeys. These micro journeys can be used to overlay and differentiate both organizational and individual customers goals leveraging omnichannel capabilities.



Alan then went on to explain that Infinity was going to add empathy and highly contribute to true design thinking. I'm not quite sure I was able to grok how that was going to happen, but I think there are more announcements coming on the second day around how the customer is feeling at moments of truth or touchpoints.


As always Pega is always demonstrating it's potential through case studies on stage and at breakout sessions. Pega is now calling the outstanding organizations Digital Super Heroes. This is an effective way of getting clients to share a little of their digital success on stage. Don Schuerman announced the DX Heros and introduced Nicole Verburg of VodafoneZiggo who explained how they were using better customer experiences and intelligence to cross-sell products.



Next on stage was the ever-entertaining Karim Akgonul who introduced Moshe Pridan from Sirius XM who went on to explain how they were leveraging omnichannel and customer service to increase revenue. I still don't understand, as a former customer, how Sirius only knows my car and my billing address and not my household and how many cars I have for potential package deals. Anyways Karim went on to further explain Pegas new low code with guardrails approach for citizen developers and summarized the technical pieces that were being advanced or improved.




Lost in the shuffle was a small announcement of the recent "In Chat" acquisition which adds significant Digital Messaging (DM) capabilities. What was obvious was Pegas support for "Girls in Tech" with a fundraising effort of over 400K. The first day was a big hit for me with some compelling breakout sessions with more DX heroes. I am expecting big things on day 2.

Monday, May 20, 2019

Gaining Advantage by Combining Journeys and Processes

Processes have been a key contributor to operational excellence for decades and continue to progress with the addition of more automation, but the real secret to business success is to employ customer journey practices. This yields a balanced set of outcomes between the customer and organizational outcomes. Let's look at the advantages of aiming for customer excellence as a means of organizational progress in the digital age and beyond.  If you want to register for one of the first 300 copies of a new book on customer excellence click here.



The Progress of Processes for Operational Excellence: 

The use of processes for operational excellence is well known, documented and continues to progress with the addition of additional automation leveraging technologies like RPA, Process Mining, and AI. This allows organizations to visualize results and continually optimize for cost savings or efficiency purposes. The complaint of this approach has been that these processes are not friendly and are quite often too complex. To that end, organizations have been trying to make processes friendlier and less onerous. All of this is good but will be limited over time as your competition heats up with even more enticing approaches that appeal to customers.

The Progress of Customer Journeys for Satisfaction and Loyalty:

The use of customer journeys has been emerging for the past several years because of new models in industries that have tried to put the customer first. The assumption here is that a great customer journey that takes penalization into account and puts the pressure on the business and business systems will deliver better loyalty and new customers. This desire for customer excellence first will make the customer outcomes as important or more important than the business goals at critical points in the journey. In fact, the journey disciplines are even reaching to employee and partner journeys in the most enlightened organizations.


The Power of Combining Both:

While most organizations are not willing to change their business models to be completely customer driven, the gap between ugly system processes and personalized a pleasing customer journey is starting to narrow. Many organizations are starting to measure existing journeys and model target journeys figure out a way to bridge a great journey with existing processes. Adding chatbots and digital assistants in one approach for customer ease, but if your organizational silos still have to be managed by your customers, there is little gain. Taking your journey customer beyond the walls of your specific organization is the real way to come up with appealing journeys.               

Net; Net: 

There are real-world examples of combining process and journeys. There the pragmatic front ending efforts like you see with "Rocket Mortgage" and Amazon. There are examples of a complete rethinking of the journeys as exhibited by Uber and Lyft.  We even see big banks rethinking their experiences for attracting new customers. When many companies are able to personalize experiences while still keeping operational excellence goals intact, we know we have arrived. When new and innovative journeys that span multiple organizations become the norm, we will finally relax.

If you want to register for one of the first 300 copies of a new book on customer excellence click here.

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


Tuesday, May 14, 2019

Is AI Data Driven, Algorithm Driven, or Process Driven?


There are those that think that data is the oil of AI and the focus should be clean data, data science and deep understanding of what the data means. There are those that say data is meaningless without context that can be with other data, models/algorithms or processes. Let’s explore the arguments in a concise fashion to discover the advantage of each view.





The Case for Data Driven:

Data is the starting point as it is a very useful asset. True or not, it is assumed that data carries knowledge and that tapping that knowledge will give advantage to those that study data well. It just makes sense for AI to start with data and leverage an advantage can be had by learning from it. This is especially true in the age of big and fast data. It seems especially true when sensing signals and patterns that are occurring in emergent situations. Businesses have had a long history with business intelligence and a great deal of the effort surrounds data. Why would it be any different with AI?

The Case for Algorithm Driven:

Understanding the advantage that algorithms have over static data in the wild is important. In fact, organizations can gain the upper hand by having an algorithm that optimizes their business. In fact, finding the right formula, statistical model or projection that is appropriate for the situation is the real art of business. These algorithms are guarded by organizations and are often considered the secret sauce for success. While they are dependent on clean data, the rules implied in the math or the logic are the real differentiators for many industries. Where would the insurance industry be without actuaries and their prized algorithms? AI will be no different.

The Case for Process Driven:

The importance of sequence and president is crucial in doing the right steps or tasks in the proper order to obtain results. It makes no difference, if the process is static and repeatable or dynamic and emergent. Knowing the next best action is the key to getting the best business results. Bringing to bear the right data and algorithms at the right time is what process is all about. With the precision of process, business outcomes are sure to be on point and appropriate adjustments can be made with a transparent feedback cycle that employs various forms of monitoring.

Net; Net:

The real story here is that you need all three for long term success. You may start with one and add the other. AI is truly starting with data this time as machine learning ramps up to its power curve.  As AI progresses, it will have to cooperate with both algorithms and processes. Data based AI is working well today and it will likely lead to rule based AI again as the sophistication and scope of the problems expand.  A triangle needs all three sides.


Thursday, May 9, 2019

Combining Digital Technologies for Success

We have enough experience in leveraging digital technologies to be able to add value with a great chance for success. While nobody can guarantee results, there is enough evidence in organizations that have emerged to say what digital technologies deliver and what combinations are particularly potent. This post will take identify these potent combinations, but I would suggest understanding the ingredients first by clicking here for a helpful blog post on the most common successful digital technologies employed today. Teaming technologies together is a secret that many have been using to their advantage.


Putting Powerful Pairs to Work:

There are some common pairings that have led to some interesting case studies and tangible or intangible benefits for several organizations. I expect these combinations to deliver for the organizations that pursue them.

    •CJM & BPM Delivers a balance of customer satisfaction & efficiency
    •BPM AI Delivers processes that enable smart resources and actions
    •BPM & RPA Delivers automation of boring or time-consuming tasks
    •BPM & PM Delivers reality-based incremental improvements
    •IoT & AI Delivers IoT management and recognition of actionable patterns from big and fast data


Teaming Up Teriffic Triplets:

There are some common triples of digital technologies that have proven to work well together and have delivered business outcomes consistently. Again, I expect these combinations to accelerate their collaboration.
    •BPM / PM / RPA Delivers targeted automation
    •BPM / IoT / AI Delivers intelligent actions at the edge
    •Arch / Low Code RPA Delivers incremental transformation of legacy
    •Workflow / Content / Collaboration Delivers team outcomes on cases
    •Unified Communication AI / BPM Delivers Improved Customer Sat

Net: Net:

While these combinations have proven to deliver, there will be more combinations that will emerge for a strong delivery. Eventually, these powerful combinations will aggregate to even larger digital platforms that may specialize. Examples of specialty platforms include Automation, Sales Engagement, Data Science, Digital Twin Transformation, Infrastructure Management and more


Tuesday, May 7, 2019

So How Goes that AI Spring?

While AI hasn’t reached its full potential or its eventual impact yet, AI is making good progress in many directions simultaneously. Let’s examine some of the progress to date. While I’m sure that AI is adding value, I’m also sure there is more progress that is not visible yet as it is in the labs or being pioneered in several scientific avenues. Let’s look at the value add of AI to date.


Copyright Jim Sinur


Turning Data into Knowledge: 

AI is contributing to digesting large amounts of fast or slow data to create information or knowledge to assist the contextual situation, and resources accomplishing work. Work resources are only as useful as the knowledge they are provided to make decisions and take action. AI is playing a substantial role in assisting and can accelerate learning to suggest where to direct current and future actions.

Problem Recognition:

AI can sense various signals at the edge, or not, and recognize patterns. These patterns can represent emerging issues or problems. These patterns can be associated with well understood and prepared scenarios ahead of time so that AI can recognize the presence of threats or opportunities. Also, AI can find new and emerging scenarios and bring them to the attention of the right resources for decisions and possible actions.  

Taking Actions:

Once appropriate actions are selected, AI can help with appropriate responses by human, software or physical bots. By leveraging natural language, humans can kick off actions that are either pre-packaged and sequenced or parallel and emergent.  Sophisticated AI Agents or Bots will bid on tasks that are necessary to complete organizational outcomes within governance constraints.

Net; Net:

Because AI is showing progress, it will not likely fall into another AI Winter (see https://jimsinur.blogspot.com/2018/02/no-more-ai-winters-really.html).  Keep in mind that it is still early, and AI has a long way to go before it can reason, solve complex problems alone or learn enough to plan by itself. To end, AI is likely to partner up with other non-AI algorithms to take these areas of need down the road. AI will partner with data science platforms, automation platforms, and customer-centric platforms to help with next best actions. Spring will eventually lead to a full bloom summer and the fruits of a full AI harvest.