Advanced Complex Adaptive
Advanced Complex Adaptive
Organizational Systems
Organizational Systems
Embedded Files
Business Process Management & Workflow Design
Business Process Management & Workflow Design
chapter by Mark Casey, Miyian.com 2015
A new theoretical model and software design based on recent CAOS (complex adaptive organization systems) science research has been developed, integrating business management, workflow optimization, and operational and scientific systems.
With federated big data and supercomputer support, self-organizing dynamic software dynamically rebuilds and optimizes itself in real and near real time to integrate and optimize the hundreds of current simultaneous BPM, Workflow, Learning, and engineering/technology CAS systems that make up an organizational system.
The new model and software design integrates existing software, informational, and process frameworks to encompass all the changing states within an organization. Longitudinal, temporal, and hierarchical process and workflow layers are auto-dynamically defined and modeled to produce optimal outcome and states using coordinated goal seeking strategies.
Embedded 2D and 3D virtual reality interfaces based on natural human audio, video, and data interface patterns are ubiquitous throughout the design. Healthcare is one of the first target industries.
INTRODUCTION
Models, Communication, & Decision-making
This Introduction is divided into discussions of how systems worked in the past ("then"),
and how they could work in the future ("now")
Current BPM/Workflow systems, communication architectures, and other software designs encompass only a small fraction of the thousands of processes, actors, and cases active at any one time in a large organization (such as a hospital).
Trying to model and manage this huge, complex adaptive interwoven mesh of systems, processes, and goals requires new designs and architectures that more accurately reflect the way humans naturally understand and model our surroundings, communicate with each other, and make good decisions.
We must make our systems reflect this optimized way, then aggregate their capabilities so the organization acts like a million smart, wise, aware people at once.
There is a new approach and infrastructure called Complex Adaptive Systems – Organization (CASO) to understand and run organizations. It is possible to create designs and architectures to monitor, manage, and optimize ALL the processes, actors, and cases, and successfully adapt the recent huge advances in Models, Communication, and Decision-making.
We have, over thousands of years, evolved a fairly optimized way of finding success in our world. We make mental models of different kinds, keeping track of all the near and far threats and opportunities, understanding the relationships between them, and focusing dynamically on only the important ones at hand.
Yet we have problems making accurate models of what a group of people are doing together and cannot hold in our collective heads more than a small fraction of the information or processes that are generated by an organization.
We have evolved better and better communications abilities, from gestures to speech to drawings to writing. We are now quite adapt at communicating locally, with our highly developed eyes, ears, mouths, and brains.
Note that we most frequently used gestures and speech and pictures to communicate, until writing came along. Since then, we have stubbornly stuck with only the old ways of communicating that technology provided, talking on a few phones on a desk and writing voluminous amounts of paper that few people read or remember or can even find.
Decisions are a little different: inside our own heads, we are experts at understand how to make things better, with less effort, more consistently. We efficiently gain information, turn it into insight and knowledge, and convert it to wisdom. To a point.
When we move out of our heads into the world with other people, we many times cannot correctly spread the decision-making power to those not at the top, or let them even understand what is happening enough to make good decisions.
Leaders cannot keep track of the thousands of decision points or options, much less know what technology is becoming costeffective and thus should be implemented.
As an organization we forget the lessons we has learned in the past and many times never know what others in our industry is doing well. This severely hurts organizations at all levels.
Current BPM systems only encompass part of an organization's business activities.
The biggest business drivers are:
Improved process productivity
More effective internal collaboration
Faster case resolution
Higher quality customer experience
Stronger compliance/reduced risk
Better management visibility and control
Faster customer response
(AIIM - IBM, 2012)
Figure 1 – CASO Models, Communication, Decision-making
COMMUNICATION
COMMUNICATION
Then
Then
When working with others, we almost exclusively use words to paint a “picture” of the process we are focusing on. Trying to include all the side and intersecting processes while we “paint”, as well as the variations the current case presents compared to a commonly agreed upon template, causes most people at some point to lose the mental “picture”, especially how one process impacts another. Writing this down or even using rectangles and arrows in a diagram can only capture a small fraction of the entire living, intersecting, and moving process milieu we are trying to commonly understand. Making a video is very useful, but takes too much time. Visualizing the state of a patient or process is very difficult at best, and electronic communications within the organization are usually confined to faxes and phone calls, with “advanced” organizations merely sharing static webpages when conferencing. We still use mostly our fingers to interact with technology and software, and it only interacts with us via words, and rarely, pictures.
Now
Now
Smart, aware mobile phones and tablets which will soon have 2D and 3D projection capabilities are now cost effective, potentially allowing all members of an organization – including its customers – to participate quickly and efficiently in advancing and optimizing the work and business. Large, high definition wall displays are now cheap enough to cover almost every wall, vastly increasing the amount of information and knowledge available to all.
Audio/video recognition and understanding is now at the level where we can interact with technology by merely speaking, listening, watching, and moving our bodies. All these technologies are now cost-effective and must become ubiquitous within the organization.
DECISION-MAKING
DECISION-MAKING
Then
Then
As we get more experienced and skilled at our level in an organization, we gather information, intelligence, insight, knowledge, and wisdom of how to make our area – and sometimes the whole organization - run better or smoother. Some of this we can impart to others or put down in print or pictures, but the amount soon increases way beyond our – or even the whole organization’s – ability to use it effectively, or even just keep track of it all.
This usually results in three things: we forget about many of the important processes or cases when they fall out of our focus; we constantly miss some things that are very important (or even critical); and we repetitively and manually adjust, change, tweak, and intervene in processes to make them come out right. There is no way for an average employee to easily automate or integrate the “easier” or “lower level” interventions we do every day, which would let us concentrate on more important or bigger issues.
There is also no way to easily orchestrate or coordinate multiple, remote, or higher processes via technology, so we still do most of that in our heads or in static documents that are hard to locate and understand when needed. This manual approach means we also have to wait for a higher authority to make crucial decisions rather than fixing or optimizing a situation on the spot. We also let insight, knowledge, and wisdom walk out the door each time a person quits. This lack of institutional memory and wisdom keeps us from evolving to a more optimized organization.
Education and learning is part of decision-making, and the complex organization of today contains many points where an employee needs to learn something right away, something that is not learned in a university degree program. Learning how to deal with a complex case, how to operate a piece of technology, or how to understand a new concept or practice demands just-in-time learning and education. Tracking and monitoring talent levels, skill development, and education achievements is necessary to ensure employees can do what is required of them, and are justly rewarded.
Now
Now
CASO decision-making includes the concept of a virtual agent (VA). There will be one VA for each process step, actor (including humans), model part, and decision-making component. The VA will act in the best interest of the real process step/actor/model part/decision-making component, making its life and work easier thru AI and automation.
Decision-making systems should initially focus on the primary or most important processes first, making or aiding decisions that affect the overall progress of the process or goal. In surgical services in a hospital, that would be the overall movement of the patient (aka surgical case). Certain states (criteria, milestones and artifacts) are critical to the case moving forward. These should be initially focused on by the decision-making system. As each state is successful, the case can move one more step forward in the process, moving through surgical candidate evaluation, pre-op (registration, imaging, anesthesia evaluation, trauma management, timing, financing, etc.), intra-op, postop, and rehab.
The next process that should get decision-making services is the physician flow. The next one should be the nurse flow. These flow processes are supported and constrained by sub processes, such as availability, resources management, cost/profitability, timing, etc. Those subsystems should come next. Farther down the line, processes supporting systems such as education, physical facilities, sterility, product and service mix, and scheduling come next. It can then expand to include sub processes and other more distant issues in the organization.
As the number of subsystems (processes) increases, layers of decision-making must be added, to handle coordination, choreography, orchestration, and multi-level process intelligence. Larger tactical and strategic goals such as organizational intelligence and business intelligence will be added at a higher level, as they exist as both a basic process for the top of the organizational hierarchy and a more distant process for line level processes.
CASO decision-making (as well as models and communication) includes the concept of federation. This means that each position in an organization’s org chart (CEO, CFO, Directors, Managers, etc.) will contain its own separate decision-making system/service with all the components – rule engines, evaluation engines, big data at their level, analytics, intelligence, automation, orchestration, etc. It will be fed not only by data and processes at its own level, but from levels below and beside it. It will feed up into higher organization chart positions.
This is analogous to the way organizations are run today. A worker has a certain number of primary processes, and mentally models and manages them (with the help of some written policies, etc.). The worker’s manager aggregates responsibility for and accepts data from the workers, and models and manages their own primary processes, feeding data and other things up to their director. To understand what decision-making systems or processes should be developed first, just look at the way the humans are doing it now. Of course reengineering can always make it better, but the decision to either forklift a new process model, or just tweak the existing one is part of the optimization process.
As an organization is transformed using the CASO concept, more and more complex decision-making will become useful. More and more process, both large and small, will be optimized, adding to the complexity of the whole system. This includes interlinking more and more subsystems so they can share data and collaborate; and increased use and complexity of human-facing systems to facilitate communications and collaboration and innovation. It also includes larger process sets, such as public health, medical population management, and skill set authorization.
Decision-making systems are starting to take hold in organizations, usually in helping people move from one step in a customer-facing process to another. Some systems are helping employees move through very simple processes. Tools and technologies are becoming available recently that allow organizations to use systems that act the way we think. Decision-making today is moving more and more from people to computer systems, starting with tasks and situations such as self-provisioning logic, automatic data distribution, automatic cross linking in sales, process step management, data, image, and sound understanding and semantical correlation.
Figure 1 – CASO Models, Communication, Decision-making
LEARNING AND EDUCATION
LEARNING AND EDUCATION
As smart as we make our hardware and software, if the people in an organization are not able to understand or use them properly, the system will fail or be disoptimized. Every day, all people come upon a situation where they need to learn about something right away. They also have some things they need to learn about in the short term, and some things they need to learn in the long run.
The current system of college degrees and industry certifications have their place, but must be supplanted by just-in-time learning systems that pervade the organization. A robust learning and education system is critical for an organization to become truly optimized. This system has several parts, federated like all CASO components. There should be a role/skills/certification tracking system that keeps records on every employee, a correlation system that matches needed skills/roles to that tracking system, and a learning/education planning systems that produces roadmaps to meeting the organization’s needs. At a lower level, every corner of an organization should have an on-the-spot, just-in-time learning system for use by employees and customers. It would provide short learning modules on the use of machines, processes, scientific activities (e.g., assessing a postpartum mother, inserting an IV), upcoming meeting agenda items, CASO principles, etc.
The learning and education system will of course use audio, video, images, text, simulations, and other media types. A media management system that manages all the media in an organization is a must, so both prepared media (learning videos, etc.) and meeting media (audio/video recording and transcriptions of all meetings) will be managed and available when needed. Both the learning/education and media systems will have their own modeling and decision-making subsystems, federated, of course.
COMPLEX ADAPTIVE SYSTEMS – ORGANIZATIONS (CASO)
COMPLEX ADAPTIVE SYSTEMS – ORGANIZATIONS (CASO)
CASO is a subset of the general science of Complex Adaptive Systems (CAS), In addition to organizations, Miyian also conducts CAS R&D in the domains of Complex Adaptive engineering, technology, learning, media, and humans. These have been identified as the core domains that all CAS contain.
CASO is different from most modern definitions of organizations, as it seeks to define, understand, and optimize all the parts of an organization, big and small, organizing them into processes, models, and communications.
CASO has the concept of scoping, in which (just as in real life), allows one to view the world at different levels. There is the organization CAS as a whole, which is composed of smaller CAS (e.g., divisions), which are composed of even smaller CAS (e.g., departments), which are made up of even smaller CAS (e.g., rooms). CAS can also consist of similar things distributed across the organization (e.g., all things sterile, all things pediatric). All these CAS, big and small, are interlocked together in a kind of fog or ball. Pieces of one CAS make up parts of another CAS, either larger or smaller.
CASO and all Complex Adaptive Systems (CAS) represent a new paradigm, a new way of looking at the world. Most of you possibly have mastered a CAS, such as your body, your marriage, a science, a hobby, etc. These are CAS also, so if you know how to successfully optimize one, you can learn to map over the knowledge and skills to other CAS. To better understand CASO, look at parts of an organization that have already been optimized – in a hospital, the operating room is an example. Attention to minute details within the OR in processes, models, materials, and communications have been worked out to produce the best possible outcome.
Scoping examples
Scoping examples
Each level will have its own federated Processes/Workflows/Cases, and its own Intelligence/Knowledge/Decision-making services, and its own Communications/Input/Display services
Business Capabilities (using Healthcare as an example)
Belong to Business Domain (Hospital) o Governed by Business Principles (Provide Quality, Efficient,
Effective Healthcare, Profitable, etc.)
§ realized by Business Processes (methods) (Patient passing through system)
Performed by Business Role (people, teams)
(Surgeon, Nurse, Manager, Director, etc.) o Business Functions are roles individuals and units play to meet business objectives (PreOp, IntraOP, PostOp, etc.)
§ Business Services is the realization of the Business Capability (Diagnostic Capabilities, Critical Care level Phase I and II services, Medical / Surgical level services, Rehab services, etc.), also IPSO - Input, Storage, Processing Output, etc.
• Vision o Goal
§ Objective Strategy o Tactic
§ Policy
• Case (defined as agent/environment within a process)
o Event separation o Rule / Decision
The Information Chain
§ Data
Information o Reasoning
§ Evaluation (cost/benefit, risk/reward)
Insight o Knowledge
§ Wisdom
OPTIMIZATION OF BPM MODELING, DECISION-MAKING, COMMUNICATIONS
OPTIMIZATION OF BPM MODELING, DECISION-MAKING, COMMUNICATIONS
Optimizing BPM/CM modeling
Optimizing BPM/CM modeling
CASO Approach to Process/Workflow/Case Management
• On The Fly Process/Workflow/Case modeling
• Deterministic evolving to Dynamic/Relative/Probabilistic
• Start with Static (“most probable”) Workflow, move towards Dynamic
Template/Roadmap/Tree
• Move Unpredictable Input towards Predictable Output
• Probabilistic Evaluation & Decision making
• Reuse of previously constructed P/W/C components that did not change, or as a starting point for reconstruction
• Processes/Workflows cross each other and interlock, can be incomplete, mature, etc.
Optimizing Decision-making
Optimizing Decision-making
• Goal oriented, adaptive case management based on state / approach
/ outcome probabilities (Pucher, 2014)
• The AI subsystem will maintain an internal content and state management system to manage decisions and artifacts
• manage decisions and artifacts
• Federated & Orchestrated BI / BPM / AI / Data / Analytics
• Use of HPC cloud distributed components and supercomputers to manage the thousands of an organization’s processes, agents, and evaluation / decision engines / predictive modeling / real-time state modeling / big data analytics (IBM Watson Analytics)
• Repositories of data marts / cubes, of goal seeking knowledge / experience cubes are dynamically created / updated / modified according to current states / goals of system at each level of scoping
Optimizing Communications
Optimizing Communications
• Automated semantic understanding of data / documents / audio / video into AI analytic systems (Web 2.0) (O'Reilly, 2005)
• Model communication goals on natural human interfaces (“The Mirror”)
• Voice input / output – natural language recognition, automatic advanced audio dictation
• 2D and 3D displays that display current states / outcomes in near real time (MIT MediaLab doppelab)
• Visualizing just the group of CAS and goals/processes you are interested in at any one time
• Ubiquitous videoconferencing / collaborations / meetings, automatic advanced video recognition
• Use of augmented reality systems (Google Glasses) (Augmedix.com)
CASO optimization
To be optimized, a CASO must have several conditions. It must be set up the right way; it must be allowed to quickly modify its organizational structure and activities; it must be able to self-organize at certain levels, within a firmly determined structure. It must actively seek to identify and recognize the abilities and talents of its members, allowing them to move within the organization to their most useful and productive role. Decision-making must be moved as close to the decision spot as possible, pushing authority down to match responsibility.
The three critical CASO optimization areas discussed above are also identified as “The Mirror (communications), the Org Chart (decision-making), and the Factory Hotel (models)” (Casey, 2014MUSE, 2014)
All current technologies and BPM concepts will be integrated into a CASO design and architecture. (Casey, ConceptsInCASO, 2014)
CASO design and architecture combines and integrates newly successful advanced technologies and capabilities from different industries into an organization, such as:
• Automated multi-level process management and supply chain / fulfillment systems (Amazon.com)
• Automated AI Deep Learning (IBM Watson Analytics) (Google
Voice) (Cognitive Science & Design)
• Advanced semantic voice recognition (Google Voice) (Apple Siri)
(Google Knowledge Graph)
• Advanced 2D and 3D (virtual reality) dashboards and simulations
(Breakaway Games, Healthcare) (Rockwell Automation)
(SSIH.ORG) (PharmaTimes)
• Machine learning and risk prediction (Etiometry 2013)
• Constraint optimization and risk allocation in scheduling planning (MIT CSAIL laboratory)
• Mobile tablets, smartphones, and targeted Apps
• Augmented Reality systems (Atheer Medical) (AR Healthcare - YouTube)
There are four pillars of CASO optimization: (FourPillars, 2009)
• Process (BPM/WM/CM)
• Technology (computing, communications, I/O)
• Learning (knowledge bases, education)
• People (openness, collaboration, support, interfaces, interactions, talent)
CASO User Modification
CASO User Modification
Because CASO change so quickly and have so many variations in processes and cases, it is critical that users and superusers (as opposed to IT people) be able to modify models, communications, and decisions, on the fly and in a structured way. Primary functions will be produced by programmers, but users must be able to modify the system both to modify the model or decisionmaking logic and design the communications the way that works best for them.
Sciences and Technologies
Sciences and Technologies
All CASO theory, design, and architecture for machines or people depends on a number of underlying systems, sciences and technologies:
Systems
• Business Process / Adaptive Case / Workflow management
• Complex Event processing
• Process improvement / optimization
• Process orchestration/choreography
• Business intelligence
• Activity monitoring
• Systems C3i (command, control, communications, intelligence) science
• Supply Chain Management
• Machine and Human Interaction Management
• Complex Finance Management
Modeling
• Near-real-time state modeling
• Processes - Long duration vs medium vs short
• Loosely coupled models
• Federated model architecture and positioning
• Distributed components
• Layered applications
• Internet of Things, aka IofT (Internet of Things, n.d.)
Communication
• Image and sound Storage/Processing/Retrieval
• Security, Cryptography, and Privacy
• Speech recognition
• Sensor / control management (IofT) (Internet of Things, n.d.)
• Cognitive robotics
• Federated Communication Strategy
• Human-computer interaction and visualization
• Advanced mobile systems
Decision-making
• Artificial Intelligence
• Neural networks
• Business intelligence (strategic) Decision engines
• Goal seeking management
• Machine learning
• Deep learning
• Federated AI/DM goal-oriented design
• Intelligent agent activities
• State management
• Rule matching and execution (if/then)
• Risk management
• Resource management
• Logistics management
• Operational intelligence (tactical)
• Probability
• Predictive modelling
• Planning
• Pattern recognition, matching and correlation
• Cognitive computing
• Model activity analytics
• Federated Automation
Data
• Federated Big Data analytics, both single and complex sets
• Repositories of data marts/cubes
• Goal seeking knowledge experience cubes dynamically created / updated / modified according to current states / goals of system at each level of scoping
• Data mining and management
Education and Learning
• Just-in-time education
• Skill management and optimization
• Microdegrees and complex skill set certification
CONCLUSION
CONCLUSION
CASO is a new way of looking at organizations, one that more closely matches the way humans look at the world. It uses the natural human experience, thought processes, and interfaces as a guide to designing organizational systems and processes. CASO seeks to identify and manage all the parts of an organization, from the largest primary value process to the smallest detail of the smallest process. BPM/WM/ACM are a critical part of CASO, taking a much bigger role in the organization by eventually expanding beyond business to managing all processes. CASO focuses on modeling, communication, and decision-making within the organization, providing a dynamic and configurable framework that can integrate all existing systems within an organization, both physical and conceptual. A primary concept of CASO is using advanced technologies that have already been successful in other domains and industries.
CASO is also future-proof in being able to absorb any new technologies or connections with other external systems. Common characteristics of all complex adaptive systems, which CASO inherits, are only touched upon briefly in this paper, which focuses primarily on BPM.
REFERENCES
REFERENCES
AIIM - IBM. (2012). Broadening the Scope for Advanced Case Management. IBM. Retrieved from http://public.dhe.ibm.com/software/data/swlibrary/ecm-programs/IBM-AdvancedCaseManagement-2013Final.pdf
(Amazon.com. Retrieved from http://www.amazon.com
Apple Siri. Retrieved from http://www.apple.com/ios/siri/
AR Healthcare - YouTube. Retrieved from https://www.youtube.com/results?search_query=augmented+reality +for+healthcare
Atheer Medical. Retrieved from https://www.youtube.com/watch?v=Vwshf8jXMh4
Augmedix.com. Retrieved from http://www.augmedix.com/index
Breakaway Games, Healthcare. Retrieved from http://www.breakawaygames.com/seriousgames/solutions/healthcare/
Casey, M. (2014). 2014MUSE. miyian.com. Retrieved from http://www.markboulder.com/origin/originportal/MARKATMIYIAND OTCOM2014MUSE.pptx
Casey, M. (2014). ConceptsInCASO. Retrieved from http://www.markboulder.com/origin/originportal/TechnologiesAndB PMConceptsInCASO.doc
Cognitive Science & Design. Retrieved from https://developers.google.com/events/io/sessions/326460111
Etiometry 2013. Retrieved from http://www.technologyreview.com/news/515461/machine-learningand-risk-prediction-in-the-icu/
(2009). FourPillars. research paper by Mark Casey.
Google Glasses. Retrieved from https://developers.google.com/glass/distribute/glass-at-work
Google Knowledge Graph. Retrieved from https://developers.google.com/events/io/sessions/351343657
Google Voice. Retrieved from http://www.google.com/insidesearch/features/search/knowledge.ht ml
IBM Watson Analytics. IBM.COM. Retrieved from http://www.ibm.com/analytics/watson-analytics/
Internet of Things. (n.d.). Retrieved from http://en.wikipedia.org/wiki/Internet_of_Things (n.d.). mark@miyian.com.
MIT CSAIL laboratory. Retrieved from http://www.gizmag.com/mit-bettersiri/35725/
MIT MediaLab doppelab. Retrieved from http://doppellab.media.mit.edu/
O'Reilly, T. (2005). CEO. www.oreilly.com. Retrieved from http://www.oreilly.com/pub/a/web2/archive/what-is-web-20.html
PharmaTimes. Retrieved from http://www.pharmatimes.com/Article/15-0220/Healthcare_is_about_to_go_virtual.aspx
Pucher, M. J. (2014). Adaptive Case Management Blog. http://www.isispapyrus.com/. ACMISIS. Retrieved from
https://acmisis.wordpress.com/
Rockwell Automation. Retrieved from https://www.arenasimulation.com/industry-solutions/healthcaresimulation-software?gclid=COyN3u2x-sMCFZGIaQodUVIAMw
SSIH.ORG. Retrieved from http://www.ssih.org/
A new theoretical model and software design based on recent CAOS (complex adaptive organization systems) science research has been developed, integrating business management, workflow optimization, and operational and scientific systems.
With federated big data and supercomputer support, self-organizing dynamic software dynamically rebuilds and optimizes itself in real and near real time to integrate and optimize the hundreds of current simultaneous BPM, Workflow, Learning, and engineering/technology CAS systems that make up an organizational system.
The new model and software design integrates existing software, informational, and process frameworks to encompass all the changing states within an organization. Longitudinal, temporal, and hierarchical process and workflow layers are auto-dynamically defined and modeled to produce optimal outcome and states using coordinated goal seeking strategies.
Embedded 2D and 3D virtual reality interfaces based on natural human audio, video, and data interface patterns are ubiquitous throughout the design. Healthcare is one of the first target industries.
Advanced Complex Adaptive
Organizational Systems
Business Process Management
&
Workflow Design
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