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.

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

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

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

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 !!!