Wednesday, July 18, 2018

What's the Future of RPA?

Robotic Process Automation (RPA) has been a sector on fire. In order to carry momentum in the coming months and years some things need to change and unfold while delivering on tactical benefits. The will be a shift from a reduction of labor exclusively to more of a business outcome driven approach. Listed below are the changes I see coming in RPAs future. Make no mistake that automation will continue to be a big theme, but additional factors are needed to keep the momentum at a fever pitch.




RPA Must Target Multiple Business Outcomes: 

Traditionally RPA has made a great living reducing labor costs while adding accuracy and moving dull labor to automated bots. Mimicking human actions will continue, but there are other business outcomes that need servicing by RPA.  As Bots grow in capability, it can act as a listening post for patterns of interest, bid on available work and assist as a digital assistant to customers. Bots need to be goal driven as well to adjust to changing business needs.

RPA Market Places Must Emerge:

Today bots are built and will continue to be, but businesses will want to buy or rent bots to shorten time to results. This will probably happen vendor by vendor, but eventually these bots will have to be supportive across vendor lines as standards and universal catalogs emerge.

RPA Must Get Smarter:

Bots today are rather simple and single function in orientation. Over time these bots will leverage algorithms, statistical models, and multiple forms of AI and extend their functional impact and reach. As they get smarter they will become more autonomous and start to bid on tasks.

RPA Has to be Governed on the Edge:

Autonomous bots will live on the edge and act with high levels of freedom. This brings the challenge of setting up governance boundaries and constraints. Swarming agents/bots will likely be goal driven and bidding to win business, so dynamic governance will rise in importance

RPA Must Increase its Scope of Impact:

While RPA can replace humans on happy paths to create straight through processes, but there is much more to address. Bots must grow from structured screens and data to knowledge rich cases or dynamic processes that are emergent in nature.  Bots should be able to sense events and recognize patterns,  assist decisions and suggest or take actions.

RPA Must Assist the Human Experience:

Bots should not only assist employees and other labor focused resources, bots should assist customers. These bots should sense the personas and behave in context to assist people on either their work or consumer journeys.

RPA Needs to Embrace Adjacent Technologies:

RPA vendors should seek to partner with process vendors, process mining vendors and digital assistant providers at a minimum. Additionally RPA providers should leverage and partner AI and algorithm providers to expand their future.

Net; Net:

RPA is great, but it needs to set it's sights on a broader and deeper set of impacts. To keep this roaring fire of momentum going, I expect many of the seven categories above to be leveraged. It is a big set of tasks for these vendors, but the outcomes will be valuable to all.

Read More Here:

The Four Dimensions of RPA
Process Automation
Unleash The Bots
Bots n BPM
The Elastic Workforce








Monday, July 9, 2018

Art for 2Q 2018

After moving away from people portraits and creature paintings for a bit, I'm back at it this quarter with my frog painting. This is a commission job. I've also included last quarters turtle portrait, now that is has been scanned in for my website. This time trying something very detailed with acrylics (I usually use oil paint for these kinds of paintings).  I have no name for the frog yet, so I would like some suggestions please :)  www.james-sinur.com


                                                                 Night  Frog




                                                                     Island Sunset




                                                                    Mr Turtle 



                                                        
                                             

Tuesday, June 12, 2018

Process Automation vs Process Management

There is a lot of buzz around Robotic Process Automation (RPA) and there are those that would try to convince you that RPA replaces Business Process Management (BPM). There are others that would have you believe that BPM can be leveraged to do what RPA does in most cases. Let's examine this issue. Right now RPA works on specific tasks and BPM works on orchestrating all kinds of tasks that involve RPA or not while dynamically delivering changing business outcomes. Over time they will have more overlap as both leverage more intelligence through AI and Algorithms.





What Does BPM Do?

BPM manages tasks and the sequences in an end to end style while monitoring results and making necessary adaptations to keep goals and business outcomes on point. BPM is a task or event coordination/orchestration capability that makes sure the best sequencing (flows), even in parallel streams, are chosen at any point in time. BPM applies to simple or complex system and human tasks intermixed and dynamically optimized for SLAs.  Processes are great at exception handling and are often supported by decisioning capabilities (usually visual rules). Processes and process snippets (smaller sequences of tasks) are great a delivering best practises and emerging better practises recognized in cases.

What Does RPA Do?

RPA is great at automating manual tasks and stream lining some parts of an overall process. RPA, today is very task focused and operates with the boundaries of a existing process. As processes flex, this relationship may change. The scope of RPA today are much more focused and limited to single tasks. Though there may be a large number of specialized bots, their power is leveraged by the sequencing that process give them today. This may change over time.

What Can They Both Do?

They both help streamline processes for better efficiency and cost savings. They both support rapid deployment and ability to implement change in an incremental fashion. They both can start out with a low cost approach and grow to value over time. They share many of the operational improvement benefits. Over time as processes and bots increase in intelligence through AI they will both increase the customer, employee and partner experiences to create better journeys. Imagine a bot or a process Cog (AI) assisting you with your job!!

Net; Net:

BPM and RPA are better together for sure and they both will get better as they add smarts. As control moves to the edge, those tasks sequences will likely be short running and smaller in scope putting the advantage to RPA over time. Task sequencing is important in a great number of cases, so process will be there, but not as the BPM of old that many know today. In the future as the bots become more intelligent and are able to anticipate and negotiate, then maybe there will be less pre-built processes.

Thursday, June 7, 2018

Is Digital Transformation Reengineering in Sheep's Clothing?

There seems to be an awful lot of parallels between business reengineering, which focused on helping companies radially restructure their organizations by focusing on the ground-up design of their business models, and the way Digital Transformation is being touted by some. There are some "Chicken Little's" out there saying the sky will fall in on you. There are some visible examples in some industries, but radical business model change won't happen all at once in every industry simultaneously. On the other hand, nobody should ignore opportunities to leverage digital opportunities. This is a bit of a tightrope walk, but a necessary one with a safety line whenever possible 





Industries Under Siege:

When your industry is being attacked by better business models that are digitally enabled, then you may forgo the safety line and play it a bit riskier. Make no mistake digital will influence most industries by providing a better customer experience that includes faster, better, cheaper with more visibility. However, rarely is it a situation that requires turn key solutions yesterday. Yes, digital will increase the pressure, but organizations do not have to get out of the business model they have successfully rode for years.  They will, however,  have to pick up the pace of change and innovation. Whenever possible industries under siege should be working with parallel solutions to keep the lights on while trying new ways of doing business (better customer journeys, dynamic value chains or new markets). 

Most Everyone Else:

If your industry is not under siege, organizations should be taking steps to leverage digital in the best way possible to enhance and leverage the strength of your existing business model. If you are in the mortgage business, you better underwrite easily in the context of what the buyer complete journey might entail. You might start with a better data collection, but might end up guiding buyers and sellers through their whole experience, not just the loan process. Incrementally adding crucial and customer pleasing capabilities while being operationally effective and efficient on top a proven business model is a beautiful and profitable thing. If your organization is not working with several proven digital methods and technologies, there is lost opportunity. If your organization is not experimenting with a digital approach that could leap-frog themselves over the competition, there is also opportunity loss .

Net; Net:

There are some who are hiding radical change under the cover of digital transformations, but it isn't always necessary at the speed they demand. It's in their best interest to scare you into working with them to guide your through the dangerous territory of digital. While it's true there are dangers, risk can be lowered and incremental can work with digital. This is why there are many paths to the top of the mountain that can be taken one base camp at a time. 




Wednesday, May 30, 2018

Timing of Customer Journey Mapping

When should organizations practice customer journey mapping? Should it be done before the customer experience is built? There is a case for mapping the actual experiences after the fact and using the lessons learned to adjust the customer experience is strong. There is an emerging possibility of using real time emotional measures to adjust the customer experience based on the customer's reaction to the customer experience so far, which may include multiple touch points over time.



The Planning Approach:

Organizations that want to understand their customer experience and plan a better approach will use customer journey methods and technologies to actively create a better customer experience. This approach really works well with new systems and planned augmentations. The trick here is not to over-analyze, but to practically involve real customers, organizational representatives with a good dose of independent thinking.

The Audit Approach:

Organizations that want their analysis of the customer experience to be reality based, will use a measurement approach that gleans data from systems and people to create a near realistic view of the customer experience in context of the customers goals and persona. The challenge here is to think out of the box and imagine situations beyond the expected "happy paths" when designing a better customer experience. 

The Real Time Approach:

Organizations that want to adapt inflight, will gravitate to use technologies and techniques to measure the real time moods of the customers. This "on the fly" approach requires some newer emerging technologies such as AI enabled by emotion detection embedded in voice inflection, real time images and gestures or natural language understanding. This allows organizations to customize responses to individual customer situations in context. The challenge here is that the costs could get out of hand without creating some common responses over time.

Net; Net: 

The obvious answer is to use all three approaches, but that is easier said than done. The real time approach is still emerging and maturing. The planning approach might be too late if an organization has a legacy base that requires significant augmentation or change. Measuring what's going on might require significant instrumentation to gather the data. The answer depends on the situation at hand, but doing nothing is not an option. A customized mix is probably a solution, but this is not a "one and done" circumstance. We can't depend on getting lucky like the squirrel pictured above as we will all get wet with customer experience issues.

Wednesday, May 23, 2018

Dawning of Digital Disappointment

We have been seeing one article after another about how organizations are getting frustrated with Digital. It boils down to setting expectations. If you fell for the "digital will change your business model overnight", then I can understand why. Not every industry can expect a wholesale business model change overnight at this point in time. If your organization took an incremental benefits and learn approach as you progress digitally, you probably are still pretty happy even though you are not quite sure what the actual end game will be with digital. It may not matter because your organization is growing skills and competencies that will bode well for better customer experiences while creating greater effectiveness.



Let's Look at Rocket Mortgage:

Did Quicken Loans expect their product name to become more popular than their organization? Do they mind laughing all the way to the bank as they drew in more business even though they didn't really transform the mortgage business model while legacy applications of old still churn away under the covers? They added a very customer compelling front end leverage the best that digital offered at that time and put their muscle behind it. Customers received speedier and more visible results, but Quicken still does loans baby. This is practical application of digital in a focused way.

Let's Look at Taxi Service:

Many of  the taxi companies inspected themselves after the dawn of Uber & Lyft. They couldn't understand why customers would take a chance with unlicensed drivers just because there was an easy and visible app that linked you with drivers where you were. Once the traditional organizations realized they were in the transportation business that needed to wrap themselves around a better customer service model, many launched successful car services. Will it be enough to survive the jump start lead that Uber and Lyft have gotten? Time will tell

Let's Look at Industry 4.0: 

While the appeal of dynamic and customer adaptable supply chains whose complexity is buffered from the customer is great, there are incremental steps for new kinds of automation that do not require redesigning it all at once. More humanity laced automation in any piece of the supply or value chain will deliver benefits. Imagine a production line that watches workers and coaches them to better performance even if they are deep in the linked Industry 4.0 adaptable supply chain. While an end to end flexible supply chain that delivers custom product to the customer in the best way possible is still the goal

Net; Net:

Let's still keep our eyes and ears open for opportunities to disrupt with digital, but let's not forget that is not all "Turn Key". There is incremental value to mini-digital journeys that deliver benefit while making progress towards the ultimate digital destination. Maybe expectations need to be changed to match emerging reality.

Read more about incremental mini journeys and digital on ramps by clicking here



Wednesday, May 9, 2018

The Value of a Decision Management Framework


An organization’s ability to make excellent decisions will be a huge differentiator in today’s ever changing business environment. The days of leisurely decisions are numbered because of the speed and momentum of business. Also the amount of data, information that is available for any one decision is multiplying in an exponential fashion. More and more decisions will require the assistance from data science and combinations of algorithms with AI assistance. Aragon Research introduces it's Decision Management Framework(DMF). Click Here for the Research note. The basic dimensions are below. Click here for a free webinar on May 11th, 2018 with more details. 








While organizations will depend on people to leverage their experience and intuition in the best possible decisions, more and more decisions will be leveraging automated assists for human decision making. In the new digital world more decisions will be made in an automated fashion with significant consequences. In fact some decisions will be made at the edge without central control, so learning to manage these kinds of decisions that may be happening in an instant is essential.


Another factor being introduced in the much faster and smarter digital world is the ability to decide on making changes in the operational reaction. These changes could be implemented in procedures/processes, which in turn will help humans change. The ramifications of decisions and their downstream effects require a higher level of decision management.

Decision Management is an emerging discipline that needs a common base architecture, a shared methodology and a set of technologies. This research will seek to define a DMF that works for the large majority of decisions that will occur today and the foreseeable future. The resulting DMF will likely be used as a shared communication device for both business and IT professionals to describe the decision context, the decision components and the potential actions. The big reason is for better decisions consistently. 

Net; Net: 

Decision Management is an important emerging discipline so learning how to leverage a decision management framework will be well worth the effort. While decisions can’t always be purely methodological and scientific, having an organized approach is not only helpful in many situations and necessary in areas where there are lot of unknowns. This Decision Management Framework is important to keep in mind when making decisions and used as a communication device minimally. Technology markets are emerging to support these very frameworks and will be gain significant attention in the near future. 










Tuesday, May 1, 2018

Priority on AI Transparency?

Should we back off on AI to make sure it is transparent? Is there a way to balance exciting progress enabled by AI with the visibility necessary to make sure AI is not doing something wrong or immoral? AI is kind of a black box and what's happening inside is not only mystery to those using, but it is to the developers as it gets more sophisticated. Let's look at the some of the aspects of this issue.



The Case for More AI Visibility: 

How can we allow a black box to make important decisions? Can we really trust AI to make ethical decisions in a fair way? With programs, we can look at the coded logic and see the paths that can be chosen and watch the outcomes. With Decision Modeling Notation (DMN), we can see the decision and the results like programming. With AI we can't see the possible paths, reasoning and alternatives chosen from. Who can make sense of the inner workings of AI? Who do we hold responsible for the outcomes and ethics of AI? Would you trust AI with your life? AI is not flawless, so let's watch it closely.

The Case for Full Speed Ahead on AI:

Why should we slow down the benefits of AI while we wait for complete transparency? By a long shot AI algorithms are more accurate, by far, than human counter parts. AI can detect illnesses faster and can assist doctors with treatment plans. While some decisions are life impacting, there are a goodly number of decisions that are not life critical. Many AI investigations and actions can be logged and leveraged. AI should be tested like any other computer programming for a large number of possibilities. While the test beds for AI are difficult and sometimes near impossible, over time near perfection can be approached.

Net; Net:

Since AI will be involved with many decisions going forward, transparency will grow as an issue. If you want to hear more about decision management, AI driven or not, please sign up for a free webinar by clicking here  I believe that we can strike the balance by using AI to mine the audit the logs and actions generated AI activity. Let AI watch AI.

Monday, April 23, 2018

bpmNEXT 2018 Demonstrates Next Gen Processes

bpmNEXT aims to the definitive showcase of next generation processes (BPM) and it certainly did that this year. There were some interesting and intense demos of how process would change over time. We all saw process linking with decision management, customer journeys, IoT, process mining, advanced analytics, AI, RPA, Robots, Blockchain, voice and image recognition. There were many dimensions of process evolution practically demonstrated in 30 minute segments.



It was clear that process will be involved with significant innovation in the evolving digital world and that transformation is doable in increments. While most of the participants were vendors, there were notable visionary end users like Quicken Loans (the designers of customer journey called "Rocket Mortgage"). The hot topics were around decision management with DMN, linking with emerging technologies and automation of various kinds including AI, RPA, Mining and Robots. While one would expect a collegial environment surrounding the love of process, there was significant controversy with the powerful audience that bpmNEXT attracts. One was around DMN versus AI around transparency. Another was around Digital Business Platforms DBP being a market versus an architectural construct. I will take the blame for the later and will be creating a post for both controversies down the line.

The Digital Business Platform is a Destination for Digital Transformation:










Highlights:

The highlight demonstrations, for me, were the demos that showed the promise of voice and video based digital assistants tied to BPM. The best one in this category was given by Francois Bonnet of ITESOFT where he demonstrated the interaction of a Robot, BPM, Voice and Video Recognition working together somewhat seamlessly.

Another significant highlight came from Denis Gagne, from Trisotech, who not only demonstrated Decision Model and Notation (DMN) in modeling mode, but showed decisions in action with their associated test beds. This demo showed the full range of DMN in action. For a free webinar on Decision Management and DMN on May 11th, click here

The last, but not least, of my top three demos came from Pieter Van Schalkwyk of XMPRO where Pieter showed us process at work at the edge of an IoT network in place today. The demo focused on finding that important event or pattern at the edge with a critical part of a critical piece of safety equipment. The piece of equipment was crying out that it was at the end of it's life and needed an intervention. This involved looking through tremendous volume of events, most noise events, to find the key action trigger.

Bottom Line:

If you want to see the latest and greatest that process has to offer as it plays a key role as a digital choreographer, bpmNEXT is the place. bpmNEXT is not for beginners, but maybe it should open it's offer to show process as the true collaborator for digital transformation.









Wednesday, April 11, 2018

Mounting Pressure for Better Decisons

We are in a perfect storm for making great decisions and nothing less. There are converging forces that put a premium on better decisions in that organizations are being asked for more in a changing world. At the same time the number of assists that are available to boost better decision making are also emerging quickly. What are these forces and boosts to increase an organization's ability to make better at the minimum and great decisions at a maximum? The coming decision wars will be at the forefront of success going forward for organizations and individuals.

For a FREE WEBINAR on DECISION MANAGEMENT CLICK HERE





Forces Affecting Decisions:

Business Contexts Shifting Faster

Organizations are being swamped by the increasing number of factors that can affect them. While operational pressure persist and are intensifying, other factors such as governance, shortages, political storms and economic shifts are increasing simultaneously. This puts a premium on scenario planning like never before.

More Data Available Than Ever

The amount of data available for organizations to leverage is mind boggling and increasing by the second. All organizations are now information dependent and the amount of  data/information swamping them is larger than ever. This puts a premium on data mining and matching productive decision journeys with the proper data sources.

Increasing Speed of Business 

Organizational speed is increasing significantly. The idea of pondering operational adjustments is just not as feasible as it was just a few years ago. Tactical decisions have to be done quicker than ever because of customer demands and competitive pressures. The number and speed of opportunities and threats is accelerating faster than ever, so measured responses have to be done quickly.


Forces That Boost Decisions:

Increasing Intelligence

The number of intelligent coping mechanisms is growing rapidly. Traditionally algorithms have been the bastion of intelligence applied to data and this source continues to grow. Now we have miriad Machine Learning (ML) capabilities that can be used in conjunction with Deep Learning (DL) and eventually Cognitive Components (COGs) that can be assembled in combination with the aforementioned intelligent components.

Agility Features in New Software Platforms

Recently the spotlight has been on low code approaches that leverage model driven, menu driven and parameter driven code. While this is good, there are also other forms of explicit forms of rule and policy change that do not require changing of any code. A new promising form of rule agility is driven by a decision standard known as Decision Modeling and Notation (DMN).

Better Decision Reference Information

Catalogs of available helpful decision components (ML, DL. COGs, DMN, PMML, etc)  can be searched and leveraged during any decision journey. These reference catalogs also contain data sources that describe available data resources. These are one of the main ingredients in a Decision Management Platform (DMP)

Better Real Time Collaboration Work Spaces

Work Spaces have been in the headlines for a number of years now, but they have not been aimed at the decision management problem in a consistent fashion. The potential of work management spaces of decision collaboration is largely untapped

Net; Net:

The forces need to be matched by the proper boosts combined in innovative ways. This matching process should be guided by Decision Management Framework (DMF) that explains the nature of the decision(s) in a collaborative fashion. The DMF communicates both the business and technical attributes of a decision so that a good Decision Management Journey (DMJ) can be mapped out and supported by a Decision Management Platform (DMP). I will be writing more about the DMF, DMJ and the DMP in future posts, but you can attend the following free webinar.


For a FREE WEBINAR on DECISION MANAGEMENT CLICK HERE

Additional Reading:

Better Decisions with Decision Management
Decision or Data First Post
Beware of the Data
Intelligence










Monday, April 9, 2018

Art for 1Q 2018

After moving away from people portraits and creature paintings for a bit, I'm back at it this quarter with my turtle painting. This time trying something very detailed with acrylics (I usually use oil paint for these kinds of paintings).  I have no name for the turtle yet, so I would like some suggestions please :)  I have a couple of new fractals for your viewing pleasure as well. www.james-sinur.com

                                                             Mr  Turtle 


Glass Star 


                                                     
Spiral Crazy 


Throwing Star Convention 



Ice Necklace 


Loopy Monday



Thursday, April 5, 2018

Decision or Data First?

There is a debate brewing about how the best decisions are actually made and executed. With the birth of Decision Management as a discipline recently, this debate is starting to emerge. There are many technical platform vendors that are pushing "data first" approaches to decisions and digital efforts. It turns out that business professionals are pushing decisions first based on business outcomes. The question is "What approach will dominate?"


The Case for Decision First:

Decisions link the an organization's metrics and objectives to its operational processes, applications and systems. This is particularly true of known operational goals, targets and SLAs. Decisions are a forgotten first class business object, just like processes and data. Often decisions are not modeled first in order to select analytics, AI Services to create a decision management journey. This needs to change. Even decisions that are related to discovery of opportunities or threats can be better planned than we do today. Decisions should be explicit and not buried or subsumed with processes, applications or program code to support the agility required to manage organizations. Decisions need to be documented and shared amongst business and IT professionals alike. Build and model the decision and then link to the necessary data.

The Case for Data First: 

Data offers enormous and growing opportunities to create competitive advantage and operational advantage. Most organizations do not know what data they really have or how important the data they have in their possession. In fact most organizations do not have a significant or complete strategy defining how data really contributes to their organization. There is a lot of dark data in organizations and the amount is expanding and coming at speeds not seen before. Studying pools of accumulated data or kinetic moving data can point out opportunities and threats for organizations. Quite often these are discovery treks that can lead to opportunities at best and dead ends at worst. Many feel that the best opportunities for organic growth lie in data. Look at the data in new ways and take advantage of discoveries.

Net: Net: 

The nature of the decision context will dictate Data or Decision first.  Known operational contexts that have specific goals will likely dictate Decision First. Tactical or strategic situations where management is exploring options or where operational processes and applications are throwing off unknown signals and patterns will require a Data First. It boils down to known or unknown situations. There are situations that will cause both approaches operate interactively.


Additional Reading:

Introducing Decision Management
Data Issues







Tuesday, April 3, 2018

Beware of the Data !!

It used to be that data was this nice little contained resource that was on the leash of our own applications and processes. Once in while we would let it off the lease and let it roam for a little extra intelligence that organizations could use to gain a slight operational advantage. No Longer Data is now off the hook and can be plain ferocious at times. We can't ignore it's new properties and forms in this dangerous digital world. Let's explore the issues.


The First Issue is that there are new forms of data with opportunities and dangers. Besides the normal structured and docile data, the new forms need to be mastered while they are still evolving. There are new varieties that need attention.

Unstructured Data that really has no model or in some cases even a form are growing in importance. We see that text, voice, image, or video sources are growing in size and importance. There are hidden recognition issues for finding the usable data, facts, sound patterns and image objects to leverage in context. 

Big Data is accumulating faster than organizations can deal with it and quite often sits in static pools and is elusive in it's value to an organization. Often there is loads of dark data that lurks beneath the surface that could be valuable or dangerous if mined, known and leveraged.  

Fast Data is moving rapidly and usually contains, signals events and patterns that lose their importance or value quickly. This data works best when it is analyzed in real time or saved temporarily to be associated with other data. It can be mined in retrospect, but the value has usually waned. 

Knowledge Rich Data is data that is captured or available in context and it generally has value in context and links. Knowledge rich data is often stored in ontologies or graph data formats to link to multiple contexts or taxonomies. 

The Second Issue is that decisions and actions tend to use more than one kind of of data when they are most effective. This means that organizations have to become more multidisciplinary in dealing with data. 

The Third Issue is that the data that can hurt you might not be evident or visible to you until it is too late. This means that your data radar has to be searching for data sources of threat and opportunity. 

Net: Net: 

Data can be ferocious, particularly when you turn you back on it. Make sure you are doing everything to handle your data safely. This may mean being more proactive than in the past. Be safe out there !!!


Thursday, March 29, 2018

For Those Who Celebrate Easter

Peace to All !!  If you don't celebrate Good Friday or Easter, please do not be offended. Good Friday brings to mind the mercy that God is offering to us, if we just humble ourselves to accept it. The cross is a symbol of that mercy and the cost to my savior as he suffered, bled and died for all of us.

None of us would pass for perfect or able to work to attain anything acceptable to God. This is why God intervened by providing the perfect and suffering Messiah, Jesus Christ. My painting below shows a humble flower bowing in repentance with God watching through the shaft of light. The gift of mercy and grace is free to those who humble themselves before God. This allows us to experience eternity with a Holy God. Jesus is the first risen from death like we will be, if we believe. The second painting represents resurrection.




Monday, March 26, 2018

Better Decisions with Decision Management

Most organizations have experienced the benefits of  Business Intelligence (BI) and Data Science. With AI decisions are about to get better and faster. These are all great leverage points for better decisions, but there is another discipline that will help consistently deliver better decisions.  Decision Management is a growing field that helps add some structure to decisions that will enable many to deliver great decisions with consistency.


An organization’s ability to make excellent decisions will be a huge differentiator in today’s ever changing business environment. The days of leisurely decisions are numbered because of the speed and momentum of business. Also the amount of data, information that is available for any one decision is multiplying in an exponential fashion. More and more decisions will require the assistance from data science and combinations of algorithms with AI assistance. 

While organizations will depend on people to leverage their experience and intuition in the best possible decisions, more and more decisions will be leveraging automated assists for human decision making. In the new digital world more decisions will be made in an automated fashion with significant consequences. In fact some decisions will be made at the edge without central control, so learning to manage these kinds of decisions that may be happening in an instant is essential.

Another factor being introduced in the much faster and smarter digital world is the ability to decide on making changes in the operational reaction. These changes could be implemented in procedures/processes, which in turn will help humans change. The ramifications of decisions and their downstream effects require a higher level of decision management.

Net; Net:

Decision Management is a new discipline that is growing with importance. Decision Management helps optimize Decisions, Business Intelligence and Data Science. As I write more about this topic in the future, I will rollout a Decisions Management Framework and a Decision Management Platform that will be used together for better decisions. Watch this space. 

Monday, March 19, 2018

Intelligence is the New Currency

We all have heard it in the past, "data is the oil for the economic machine". While there is still a strong thread of truth in that statement, the new innovative digital economies will be aimed at the intelligence applied towards data and any number of people or machine resources including the software that orchestrates it all. Some would claim that it is just the addition of AI that creates the intelligence, but it is a broader effect as it includes algorithms, scenarios, policies, rules and constraints as well. It will take a cooperative and orchestrated set of capabilities to deliver innovative intelligence that will drive the new economy. Let's explore opportunities to apply intelligence in innovative ways




Intelligent Identity for People & Machines: 

While there is a great need for secure identity, there is more to identity than just pure essential security and assured identity.  Intelligent identity should also be able to understand and represent the preferences, goals and desired customizations of the person or machine. These all can be shifted in context for advanced identity capabilities. 

Intelligent Channels: 

Leveraging channel focused and cross channel intelligence will give organizations and advantage in creating satisfying customer journeys and touch points to make them pleasant. Factoring in location, contexts, moods and needs intelligently will lead to a competitive advantage and repeat interactions and eventually loyalty. 

Intelligent Communications:

Leveraging persona based digital workspaces aimed at intelligent and dynamic collaboration with other workers and supporting knowledge assistants. These intelligent workspaces can be extended to customers, partners and vendors to engage new audiences upon successes with employees. 

Intelligent People:

All the people that interact with an organization should be given assistance and maybe even augmented to higher levels of intelligence. While certain tasks that people do should be automated at best, various levels of assistance and augmentation should be sought with persistence, 

Intelligent Data & Content:

Data has been the focus of algorithms and now AI for a long time and will continue to deliver benefits. This will be accelerated by a larger amount of speedy data about events occuring on the edge and the dark data that needs to be teased out with intelligence. 

Intelligent Infrastructure:

More intelligence will be pushed to the edge with algorithms, statistics and AI residing there with the freedom to sense decide and act with new levels of freedom over time. The infrastructure of linked hardware of machines, controllers, sensors will be able to adjust to different loads and event patterns. 

Intelligent Agile Software:  

All software processes, applications, microservices, bots and cogs can benefit from intelligence. Speedy and dynamic assembly of pretested software can infuse great agility, but even untested components and combinations can speed the delivery of low and high code combinations. Explicit, changeable rules can also contribute to intelligent agility. 

Intelligent Feedback: 

Feedback that intelligently considers the contexts it affects can speed adjustment to changing conditions. In addition feedback can feed into adjusting existing guardrails and constraints to support many forms of overlapping governance. 

Net; Net: 

Intelligence gives momentum to all of an organization's resources and any people or machines it interacts with in an ongoing or temporary basis. Data that just sits there for discovery is not enough to transform it into knowledge and appropriate actions with wisdom. Intelligence is the new economic multiplier and will be the currency of digital. 

Find Out the Role of Process in Digital at bpmNEXT 2018

Process is about to overcome the stigma of being only useful in saving costs and optimizing rigid work patterns in and around organizations. While business process management (BPM) is not considered one of the flashy technologies in and around digital business, it will become an essential enabler of digital businesses. Tomorrow's Digital Business Platforms (DBP) will have a strong thread of BPM for work management and the development of resource and task management. With the emphasis in digital business on incremental transformation, dynamic process / case behavior, rapid iterative development, visual business and better customer experiences, BPM is an obvious enabler for 2018 and beyond. The trends in digital business are unstoppable, so emergent and growing BPM will be dragged along as the invisible enabler. 

Listen to a podcast about my presentation on the growing role of process in digital efforts by clicking this link





Listen to a podcast about my presentation on the growing role of process in digital efforts by clicking this link  See You at bpmNext !!!

Wednesday, February 28, 2018

Nintex Xchange 2018: Democratizing Process for Digital

There are 500+ attendees at this years Xchange and they seemed very engaged with the idea that the world needs more process. While this audience might not have a digital destination in mind or even an architecture to implement, they sure are implementing processes and sneaking up on digital. I'll talk about the customer experience with Nintex at the end of this blog.



Change in Management:

It brought both joy and sorrow to see the current CEO John Burton say his goodbyes to his customers and employees as he moves on to another challenge he has yet to find. While John exits, Eric Johnson enters with a steady hand and no change in direction, even with the acquisition of Nintex by Thoma Bravo. This makes sense as Thoma Bravo does not like interfering with their companies, unlike other private equity firms who make it a habit. This is a good thing for Nintex and their clients.





Becoming Digital Glue:

While Nintex has grown rapidly by taking process to the business user as well as IT, they have another plan they are rolling out. They want to orchestrate, via process, many of the different components of end to end processes. While they propose growing incrementally in a lateral and wide fashion, I found no apparent limits on how deep their process capabilities by leveraging services, microservices and eventually autonomous agents (because of polling capabilities). I talked to several clients that had implemented large volume solutions with no performance issues, much to my surprise. Go wide and then go deep seems the strategy.



Getting More Intelligent:

Right now Nintex allows intelligence by tapping into other vendors cognitive and analytic components that can be easily snapped into a process flow. This push was to leverage intelligence in Microsoft, Google, Salesforce and IBM for more intelligence, but there were subtle hints that their analytic and dashboard capability, called Hawkeye, could be leveraged over time to provide a level of intelligence.



Getting No Code Process to Business Professionals:

The strong and driving current for Nintex is getting process to everyone, particularly business types. This is a two edged sword. It really drive the benefit of process to results in a speedy fashion, but managing the productivity storm creates its own challenges. One organization I talked with said that had so many processes, they didn't know all of them or where they were rolling out. This means that implementing best practice or even emerging better practice was hard. Another organization said that demand was so high that they had to create a prioritization process for getting the most important business benefit consistently. Another organization documented best practice and guardrails and just let the feeding frenzy commence.

Net; Net:

The productivity empowered Nintex processes is certainly worth the management headaches. Innovation and sandbox experimentation is another high level benefit. Now business users can initiate and try innovation while eliminating productivity and cost issues. There are however risks of duplication without some sort of mechanism to identify reusable process snippets, smart services and integration adapters. A little forethought and architecture wouldn't hurt and already positive situation. Long live process.






Thursday, February 22, 2018

No More AI Winters: Really !!

History teaches us that there were two large AI Winters in the past. One starting in the mid 1970s and another in the late 1980's There were very clear reasons for the last two AI Winters, but most of the technical and cost issues are gone. The wild card is how humans accept AI this time around. My bet is against another brutal winter. This does not mean there won't be cold snaps, but a 15-20 year freeze out doesn't seem likely now.




The First AI Winter:

It was caused by a couple of major factors. The first and foremost was the lack of computer power. The examples that were put forward were "toy" solutions that really did not appeal to the investors at all. This set off a period of infighting about Natural Language Processing (NLP) in the AI community which scared off the investors for a long time.

The Second AI Winter:

It was caused by the fact that the AI portion of an application had to run on a detached expensive LISP machine that really wasn't that much more powerful that newer computers. To compound the situation, the AI systems were brittle and expensive to create and maintain. The isolation and expense was too much for users and investor alike kicking off an even longer AI winter.

What's Different Now?

  • AI now has a great NLP base to leverage and we will soon be seeing NLP services for front ending legacy transactions and systems.
  • AI is data focused now; not as rule and algorithm focused. This means as the data changes, the AI can change right long with the data. This reduces costs of maintenance. 
  • Computing capability is strong enough and getting stronger to take on even more ambitious uses. We see much parallelism coming on soon in Quantum Computing that is necessary for more ambitious uses of AI.
  • AI is working hard to assist people instead of displacing them except for dangerous and low level boring work. 
  • AI can consume large amounts of data from vastly different location and give advice to people 

Net: Net:

There is no sure thing with this generation of AI, but if we all make AI easy and helpful as it takes on more challenging tasks, I think we can avoid another AI winter. The economic and computing power issues seem to be under control. It is now our job to make AI interface well with people to make them feel secure. All that stuff about AI taking the world over and turning on people sounds good for a fiction book. Do no harm otherwise ethics and law will likely have to change.





Wednesday, February 14, 2018

Customer Service in a Closing Vice

Never before is there more pressure on customer service. All of this while organizations have to compete for well informed customers. The platitude creators just say all it takes is a better attitude by the front line. Workers should be aimed at "Customer Loyalty " to deliver "A Customer for Life". While I believe in these sayings and they are good goals, the reality is that most of the front line workers have their hands tied and are being squeezed in a  ever  closing vice. There are three reasons that there is little relief in just pursuing platitudes and tightening measures/goals. 


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The Pressure from Increased Customer Demands:

Customers expect great service and they do not want to deal with functional specialties of your organization. They have specific goals that may run counter to an organizations goals to close a call in a limited time frame. The expectation is that you know them, their goals and their history. In fact they want you to know their mood and respond accordingly. They want convenience as they have little time themselves. They want a pleasing experience as the pressure cooker they live in is difficult, They want you to understand the multiple outcomes they are expecting or they will pick up a go elsewhere. Loyalty is a lost concept theses days.

The Pressure from Not Understanding the Real Customer Journey:

The customers journey is usually larger or different than what your organization and systems are built to serve. Just look at what has happened in the mortgage and account opening journeys for proof of the effect of a better journey. While applying for a mortgage can be easier and more effective, the real journey is finding a new home. The end to end journey here is far more inclusive than getting a mortgage or opening accounts.  If an organization really works on understanding the real journey and the customers goals, this adds great credibility to that organization and contributes to loyalty.

The Pressure from Old and Patched Systems:

Systems have come up from a functional perspective and usually have weak interfaces for service workers of customers. While newly patched interfaces can help, systems that are built around the customers journey and normal variations would go far in helping customers and organizations service representatives. Better systems take some of the pressure and pain away from both. Digital transformation will give organizations a new opportunity to do just that. Make sure all of your constituents  (customers, employees, partners, vendors and stake holders) are well represented in the redesign.

Bottom Line: 

Customer loyalty will come from understanding the real customer journey the customer is on and the goals they have. This means that your organization is usually only one or two steps in their overall journey and set of goals  Expanding an organizations contribution to the overall journey will likely be effective along with fixing the arcane systems that support customers and customer service representatives. Organizations need to fix their system issues and increase their journey coverage to match customers goals and desires.


Wednesday, February 7, 2018

Predictions for Digital Business Platforms 2018

As the race to digital continues, the benefits to organizations will continue to accumulate. Businesses have the incentive and the opportunity with a new tax structure encouraging organizations to invest in digital efforts that have proven to deliver. Automation will accelerate as a theme in 2018 and will carry itself out in a number of ways—with the support of the digital business platform. Improving the customer experience will also be a major area of improvement. Both of these themes will need the application of AI to extend the continuous return on investment. This research note reviews five key Digital Business Platforms predictions for 2018 and beyond.



Click Here for Getting Started with a Digital Business Platform
Click here for a 2017 Vendor Rating for Digital Business Platforms  
Click here for the 2018 Digital Business Platform Notes




Tuesday, February 6, 2018

Can Designer AI Be Far Away?

We know that AI will be assisting us at work in a more influential way over time and will help us reach organizational goals. What do you think of AI influencing your every day life beyond super charging searches, playing your favorite music and controlling individual devices.  AI will help us look better, act better and participate better in social interactions. As we are successful at work with AI, we will trust it more in our personal lives.



AI will Help Us Look Better:

Well most of us won't leverage robotic plastic surgery or genetic supercharging for better looks, we might ask AI to help us with our looks. AI could know our tastes, looks and body types and suggest a target outfit and even buy the components for us. I think most of us still will want to shop for price and quality. Today you can try on make up with an AI assisted mirror. Imagine a full length mirror displaying your final outfit on you before a Saturday Night outing? I always need help at Halloween, so that will be my test run :)

AI will Help Us Hobby Better:

Have you ever had the aspiration to dive into a hobby, but were timid? Have you ever been knee deep in a hobby and run into a perplexing situation. Wouldn't an AI assist come in handy for those situations. My gear head friends who still tinker with cars are always running into situations that require help. In fact racers are always collecting data and leveraging technology to analyze performance. In my case I like to try new forms of art expression and spend hours looking at videos or going to classes. Imagine AI searching for an answer for your situation and suggesting approaches.

AI will Help US Socialize Better:

Have you ever felt uncomfortable in a social situation?  Wouldn't you like to contribute to a conversation in a meaningful and polite way? Wouldn't you like to have the right thing to say in the right situation without embarrassing yourself or others? Even if we are inviting guests over for a meal, wouldn't some suggestions come in handy? I think we all find ourselves in want of assistance in social situations. If you desire to interact with others, assistance could really be helpful for most of us. This might come in form of a voice in a ear piece or a image in our glasses / eye piece.

Net; Net: 

While it might seem intrusive or silly to some of us, others of us will embrace designer AI. For rugged individuals that don't want help, designer AI is probably not your thing. However, for those of us that are always looking to get better or look better, designer AI will be appealing. For me designer AI would help with confidence in new situations that I tend to want to put myself in from time to time. How about you?





Wednesday, January 24, 2018

CORE Roles & AI

There is a lot of hype and fear surrounding AI, but the truth is that AI is here to assist you. If you take chat bots as an example, they seem pretty dumb and just a super charger to search or manage simple devices one at a time. Add some machine learning to these natural language capable devices or software and the game moves up to something more interesting. Add deep learning on top of them both and now the possibilities expand. Add cognitive capabilities to add knowledge and wisdom to information and data, and the game can be changed. AI can have a significant impact on our CORE roles. This blog scratches the surface on how AI helps in our basic roles.




Consumer:

We all play the role of consumer on a pretty frequent basis. Often we have to interact with organizations to deal with their products or services. Often these interactions leave us numb at best and upset at the worst. We have to deal with organizations in generalized way with some pretty antique systems and have to sort through the artificial boundaries created by specialties. Imagine if an organization creates a seamless experience that takes your history and needs into account. AI can help create just this kind of engagement model. Organizations need stop using chat bots to find the right department in replacement audio response units and start using compound AI to treat as you expect and will require. This means that call centers need to boost the knowledge and context intelligence to service you with excellence leveraging AI.

Organizational:

Most of us play roles inside of organizations as employees, management or not. Today we are as good as our skills and experience. Imagine if AI can act as an assist of sorts that handles basic administrative tasks for you like managing your calendar, sorting through your inbox and giving typical responses leveraging machine learning. Imagine if AI could act as a knowledge assistant that could give you expert knowledge, options and actions that consider a balance of dynamic and conflicting goals. AI can make you stronger than your base skills and knowledge which will, in turn add to your experience base. AI helps your role as you act on behalf of an organizations and interact with your peers, partners, prospects and patrons.

Relationships:

We all have a goodly number of relationships that we participate in on a daily basis. Imagine if you had a personal assistant that could guide you through relational and social situations with important knowledge to guide your behavior. Wouldn't we all benefit from becoming a better partner. In social situations, AI could give you options in your ear piece for potential etiquette and suggestions for good topics of discussion in the context you are in at the moment. Even the loner could be given advice on how to develop relationships where it is not a comfortable set of circumstances. This will put people on more equal footing in social situations.


Example:

We all want to be the best at what we view ourselves to be. You might want to be the kindest human on the planet with serving others as your big contribution of your time on this sphere. Service to others can be done on an experimental basis; learning as you go. You can now go to the web and find lots of opportunities to volunteer or even earn a living helping others. AI could help you sort through thousands of readings to net out potential outcome paths to give you alternative plans to reach your goal; done your way. You could have an AI guru and mentor at your side.

Net; Net: 

AI has the real opportunity to assist you in ways that are quite desirable and obtainable in the near future. Let's not fear AI; Let us embrace AI. This is said in the context of being aware and testing AI at all corners. Will AI ever violate it's base rule of doing no harm to humans?  In the wrong hands, it's possible. I believe that level heads will win the day for the near future.