Smart Medical Process Rated on the CPIQ

I promised to rate some innovative processes on the cumulative process intelligence quotient(CPIQ). See http://jimsinur.blogspot.com/2013/05/measuring-cumulative-intelligence-of.html  This is one of my favorite smart processes that manages an outpatient surgical center.

The Challenge:

This organization wanted to find a balanced optimization that leveraged resource utilization with the best patient care. Quite often one suffers at the expense of the other. In fact this organization defined an extended patient care that included the people accompanying the patient, in that, they were given visibility into progress in near real time.

The Solution:

Each resource was tagged with sensors that were readable through out the facility. This included patients, relatives/friends, medical personnel and equipment. A visual simulation is run to show optimal throughput and positive outcomes. Once a goal, amongst many, is sensed to be in jeopardy, a re simulation with adjusted goals is run with a new visual dash board representing the new goal balance. There are many reasons for optimal goal balances to be in jeopardy including medical personal getting interruptions, equipment not being ready, late patients, slower than expected recoveries etc., but this process is smart enough to deal with re-balancing and real time visibility

How Smart is this Process Measured by the CPIQ?

 













Net; Net:
You can visually see where the intelligence of this process is more advanced.

This is a highly summarized and anonymous case study provided by Bosch



First Test Drive of the Cumulative Process Inteligence Quotient (CPIQ)

I thought about using the CPIQ (see http://jimsinur.blogspot.com/2013/05/measuring-cumulative-intelligence-of.html  ) on the most intelligent processes I could find first, but I changed my mind to start with processes and applications that I had experience with in the past. Only then would I branch out into the new and emerging intelligent processes. This way I could contrast what happened in the
past and what is happening more frequently with BPM today. To that end, I selected to rate the following to test the CPIQ:

A traditional application
A traditional process done via traditional BPM capabilities
A hybrid traditional process/rule enabled application

Traditional Application:

Traditional applications, whether they be hand crafted legacy applications or best practice application packages, do not show the kind of process intelligence that will be required to meet the changing business needs that face us today and the foreseeable future. It was not a great surprise that these applications did not fare well on the CPIQ spider chart. Applications, augmented with additional technologies, like rules engines, would fare better.





Traditional Process:

Early process efforts with BPM did not exercise the kind of intelligence that would be necessary in the business environments evolving today. While there were significant improvements in visualization and dynamic navigation with simple rule/event engines, this would not be enough to compete in a change prone world.

Hybrid Process Charged Application:

Before BPM became a software catagory, I had the opportunity to write a workbench based process and rule driven underwriters work bench. We had to create a dynamic work list / workbench and provide a high end collaboration environment for work specialites to share an emerging life insurace policy. High risk cases were shared amongst speciality roles within the organization with rule driven services applied as needed. It was ahead of it's day, but still not intelligent enough for today's world.

Net; Net:

I found the CPIQ spider useful in determining the intelligence level of sonme of the past applications and processes that I had the pleasure to work on in my career. Next I turn my attention to some of the more intelligent processes emerging today.

Measuring the Cumulative Intelligence of a Process

Up until now there has been no way to measure the cumulative intelligence of a process. I am proposing a way to do that based on five continuum lines that seem to fit the bill very well. We are definitely moving away from purely structured and low IQ processes to more intelligent processes.
I believe the only way we will make progress is by watching and measuring several measures to create a shape that represents the intelligence of a process. This way we can watch the cumulative IQ of our processes and have a common language

                   Cumulative Process Intelligence Quotient

Going forward I will be taking some intelligent processes and rating them on this cumulative intelligence diagram to show the applicability to some of the intelligent processes already up and running in the real world today. I will be giving the CPIQ a test drive :)

More details behind each measure:

Raw Intelligence (I):  http://jimsinur.blogspot.com/2013/05/measuring-levels-of-raw-intelligence-in.html

Social Intelligence (S):  http://jimsinur.blogspot.com/2013/05/measuring-social-intelligence-of-your.html

Agility (A): http://jimsinur.blogspot.com/2013/05/measuring-real-time-intelligence-of.html
Autonomy(A): http://jimsinur.blogspot.com/2013/05/measuring-autonomous-intelligence-of.html
Visual (V): http://jimsinur.blogspot.com/2013/05/visually-measuring-cumulative.html

Visually Measuring the Cumulative Intelligence of Your Processes

In my latest blog series, I have been enumerating the ways to measure the intelligence of your processes. While ISAA is a good way to rate the cumulative intelligence of your processes, none of this means anything without a visual way of grokking that intelligence. You can't harness and guide this intelligence without some great ways of visualizing the business outcomes, alternatives towards creating better alternatives proactively, and the results of changes. In other words "You can't manage what you can measure and visualize"

I propose the following five levels of visualization that build on each other:

Push Visualization:

Many of the visualizations are designed by others for specific roles. These are generally in the from of multi-panel dashboards and with some minor personalization  and viewing options. These are good for "keeping your eye on the ball" for desired and known business outcomes. There are usually specific views for process owners, process managers and the humans that are supporting the process. This is a typical visualization approach for a process.

Custom Subscribed Visualization:

When individuals are able assemble dashboard components/snippets and feeds to meet their specific needs within an architecture and visualization pallet that they chose themselves, this is a more of subscription model. This allows for optimum performance as an individual process resource/operator considering both local and end to end business outcomes. This approach also allows for dynamic changes and alternative views of a custom workers workbench.

Warning and Notification:

Even when events or exceptions occur, there are mechanisms for capturing the attention of crucial resources and process managers. It may be a simple as winking lights.When important preplanned events or business patterns occur these mechanisms aimed at asking for a human intervention of an operator or a decision maker. Notification of unplanned patterns or events must also employ unique attention capturing techniques and mechanisms.

Simulated Driven Visualization:

Moving up to proactive visualization will require ways of showing the effect of changes in process  action and decisions surrounding possible actions. This where scenario planning and visualizing outcome differences becomes essential for either manually or auto adjustments in process behavior. This can be a separate sandbox with safe test data or real data under new scenarios without actual implementation. Scenarios can actively be preplanned and dynamically switch in and out, depending on process conditions and outcomes. Visualization of such actions need be quite interactice and dynamic.

Gamification:

The ultimate in interactive and dynamic business direction would be combining human resources, machine resources, multiple roles, multiple organizational units, multiple partners in social interactions in a massively multiple online (MMO)  gaming fashion to reach desired outcomes in either a "training simulator" mode or in an actional real time mode.

Net; Net:

There are definite levels of visualization that processes can exercise reactively or proactively. We will need learn to utilize various levels and layers of visualization over the coming years

Measuring the Autonomous Intelligence of Your Process Via Freedom Levels

As processes become more intelligent, we will likely like to measure the level of intelligence http://jimsinur.blogspot.com/2013/05/how-smart-is-your-business-only-as_9.html This will give organizations an idea where they are in a continuum in trying to becoming a smarter business over time. This posting will cover the second "A" portion "ISAA" http://jimsinur.blogspot.com/2013/05/should-we-measure-how-smart-processes.html

I propose the following five levels of process autonomy that build on each other:


Programmed Behavior:

A process can be completely prescribed with some levels of agility, but the permutations and combinations are preplanned. This way control is exercised by the process managers and operators and there is a high dependence on a command and control approach. This is very proactive approach, but quite rigid.

Permitted Actions:

A process can suggest alternative actions for process managers or ask permission to act in a way that was not expected. This requires a level intelligence to point out emerging patterns and suggest proper responses. Nothing happens without some level of permission.

Act First, Then Notify:

A process can watch and learn and take action based on some proactive anticipation. In this case the process manager is notified in a timely manner of the processes decision and action. A process manager can then make appropriate actions, if the process is wrong or lower the level of freedom for this kind of process instance or case

Act with Constraints and Goals:

A process can be goal seeking in nature on it's own and call in the proper analytics to self adjust goals to reach optimum outcomes based on static or dynamic weightings of goals. Processes or appropriate process snippets can be kept away from out of bounds conditions through constraints. This creates a balance between freedom and negative boundary conditions.

Interactive Independent Action:

Processes or process snippets can interact with other process snippets or the Internet of things to create a dynamic response that requires automated collaboration of automation and measures. These snippets can systematically flock temporarily or permanently to deal with emerging patterns.

Net; Net:

There are definite levels of autonomous intelligence that processes can exercise. We will need learn to utilize various levels of autonomy over the coming years

Measuring the Real Time Intelligence of Your Process Via Agility

As processes become more intelligent, we will likely like to measure the level of intelligence http://jimsinur.blogspot.com/2013/05/how-smart-is-your-business-only-as_9.html This will give organizations an idea where they are in a continuum in trying to becoming a smarter business over time. This posting will cover the first "A" portion "ISAA" http://jimsinur.blogspot.com/2013/05/should-we-measure-how-smart-processes.html

I propose the following five levels of process agility that build on each other:

Explicit Parameters:

Where process/logic volatility can be planned ahead of time and represented by external data, explicit parameters can be leveraged. The parameters are usually bound into the logic at the very last second allowing for up to the last second change(explicit). This allows for a basic level of agility and can be made handed over to business professionals for change (usually via forms/screens).

Explicit Policies/Rules:

Where process/logic volatility can be planned ahead of time and be represented by decision tables, decision trees, visual logic flows or linguistics form, business rules can be leveraged. The rules are bound into the logic at the very last second. In some instances the rules can be used to not only induce, but to deduce logic.  This is a higher level of intelligence and agility that generally leverages a business friendly development environment.

Dynamic Sequencing of Services(logic):

While adding agility within a fixed process model is a good start, not all processes paths can be modeled. In this situation, sequences work and process activity can be dynamically arranged and completed. While common patterns can be identified and modeled over time, this approach is aimed at variable work sequences. This can be accomplished by aggregating fixed process snippets (small -modeled sub-processes) guided by rules or case management guided by milestones(mini completion points).

Dynamic Milestones:

In completely unstructured processes that are milestone driven, changes in priorities can be accomplished by changing the milestones, in flight.  This approach is particularly useful for cases that have emerging new outcomes to handle where the work sequences are highly variable. This is often leveraged by adaptable case management technologies.

Goal Directed:

The ultimate in agility is where processes reconfigure themselves around new set of goals or goal weightings. This can be accomplished by having goal models that can change through a business friendly development environment or the dynamic/real time setting of goals/weightings leveraging analytics. These kind of processes generally are getting real time feedback from the Internet of things or other real time sensors.

Net; Net:

There are definite levels of change intelligence that processes can enable. We will need learn to utilize various levels of change agility over the coming years

Measuring the Social Intelligence of Your Processes

As processes become more intelligent, we will likely like to measure the level of intelligence http://jimsinur.blogspot.com/2013/05/how-smart-is-your-business-only-as_9.html This will give organizations an idea where they are in a continuum in trying to becoming a smarter business over time. This posting will cover the "S" portion "ISAA" http://jimsinur.blogspot.com/2013/05/should-we-measure-how-smart-processes.html

I propose the following five levels of social intelligence that build on each other:

Basic Collaboration:

Leveraging the leverage of multiple knowledge workers on difficult cases/process instances is quite necessary when there a specialized skills, high levels knowledge gaps and complex decisions that require a team effort. Quite often there is shared content such as forms, images and video to work with and collaborate and comment on in completing such a case/process instance.

Skills Driven Collaboration:

Collaboration can become smarter when the best available resources are assigned dynamically to cases at certain milestones/steps. This approach generally leverages a skills / knowledge inventory and analytics that can measure the work load of a resource for the best outcome of a case. This means that there is a fine balance between skills and availability that needs to be sorted out in the context of an overall existing or anticipated workload.

Crowd Sourcing:

When all of the resources may not be under the command of the process manager, then the notion of dynamically finding and putting activities up for bid is an intelligent way of managing dynamic and difficult work streams. This may mean some of the resources may even work outside of your organization in organizations that may be in your value/supply chain, but can contribute. This may require certain levels of certification over time, but in a pinch crowd sourcing allows for better results in terms of timing and quality. This requires more intelligence to measure and manage.

Social Network Analysis:

When social interactions are wide a varied, analysis of these interactions are invaluable especially when tied to goals and outcomes. Interactions can be analyzed for compliance, efficiency, customer satisfaction and various other desired business outcomes. These can be analyzed in-flight or after the fact.

Ranked Better Practices:

When social interactions are analyzed for best airings and sequencing, additional intelligence can be applied to ranking best collaboration/interaction patterns. This way in flight case/process instances can be guided through choices between multiple successful best practices. This way participants can pick from successful patterns and even evolve new approaches. This is a great paring of machine and human intelligence to maintaining excellent outcomes is a rapidly changing environment.

Net; Net:

There are definite levels of social intelligence that processes can enable. We will need learn to utilize various levels of social interactions over the coming years.