When comparing bank processes (HOT and SOS), I prefer to use analogies.
I use Michael Lewis’ systems analogy because it’s one of my favorites and it uses our underlying comparison of the automotive industry.
Let’s start with car keys. They’re a simple system: you put the key in the ignition, turn and the car starts. If it doesn’t start, you know something is wrong.
On the other hand, cars are a complicated system utilizing thousands of parts and materials designed and engineered to perform one primary function and many secondary functions. If the car doesn’t start, it will take specialists and time to fix.
Now let’s move on to traffic…
Daily Miami traffic is a complex system. Many independent actors with different goals, motivators and decisions interact with each other on the same infrastructure. We know that a traffic jam on one street relates to a bottleneck on another street.
Let’s amp it up a bit: Miami traffic during a hurricane evacuation is a chaotic system. Everyone is using the same infrastructure with one goal in mind: to get out fast. This causes the complex system to transition into a chaotic system.
Utilizing these simple comparisons, let’s study SOS and HOT bank processes, comparing complex and complicated systems.
The Two Bank Processes: SOS and HOT
Banks typically manage two types of processes in reaction to complex and complicated systems:
- Self-Organizing Systems (SOS) processes are designed for complex systems. For example, commercial loans are complex with negotiated syndications, unique collateral, heightened risks, and profits. This is a SOS process, requiring human interactions.
- Highly Optimized Tolerance (HOT) processes are designed for complicated systems. For example, consumer loans are complicated but repetitive, so we “productize” the process within a set of choice parameters. This is considered a HOT process with very little human interaction.
In our efforts to achieve quality and efficiency, our first impulse may be to make all processes HOT processes. This is a mistake.
The goal is to make sure the right process type is being used to manage the right system type:
- SOS for complex systems
- HOT for complicated systems
Banks Want to Know: What System for What Process?
Self-Organizing Systems (SOS) exist to manage risk from complex dynamic systems. It’s nature’s way to survival in a predatory environment.
When an organization (or organism) faces a choice (threat, challenge, reward), it typically creates a process to make the choice easier next time it’s encountered. All organizations operate in a complex dynamic environment just like organisms in nature.
SOS processes are resilient, adaptive, and costly.
When employees interface with customers, executives, and authorities, they will create processes that make it easier for them to act next time. These are called Self-Organizing Systems (SOS).
All small banks start with SOS processes; many large banks still operate using manual SOS processes. In many cases, SOS processes are the only way to interact in a complex dynamic environment.
Highly Optimized Tolerance (HOT) processes exist to make complicated organizational systems better, faster, and cheaper.
When an organization controls its environment and parameters, then HOT processes are the right choice. A complicated system can be mapped, designed, engineered, and controlled with some anticipation for outside forces.
HOT processes are efficient, predictable, and fragile.
For example, when customers interact with a consumer loan origination system, they are being guided through a HOT process utilizing choice parameters with question-and-answer driven paths to a yet undetermined outcome.
If customer circumstances become too complex, there is an off ramp to customer service which is an SOS process. Similarly, a SOS process may lead a customer into a HOT process.
HOT Processes & Complex Systems Don’t Play Well Together
When a bank uses a HOT process to manage a complex system, it fails every time because HOT processes are fragile. Here’s an example:
Many banks want to productize small business loans to make the process better, faster, and cheaper. However, small business needs tend to be complex, forcing some users to opt out of the process. That means some small businesses opt out and call a loan officer, or worse, opt out completely and go to a competitor.
I would recommend a value stream mapping analysis of the whole process to determine which parts provide value to customers (complex) and which can be automated (complicated).
What About an SOS Process to Manage a Complicated System?
When a bank uses an SOS process to manage a complicated system, it is exhausting for the customers and employees. Here’s an example:
Some banks still require higher value checks be deposited at a branch rather than remote capture, making the process inconvenient for small businesses and expensive for the bank. Check deposits are complicated, not complex.
I recommend a risk/cost/value analysis be performed to convert this process from SOS to HOT.
Next up I will discuss how to optimize both SOS and HOT processes, as well as how to integrate them into extremely efficient processes.
The Fine Points About HOT & SOS Processes
HOT Processes: Here is an example taken from French researcher Didier Sornette’s book:
Consider a random variable X that takes on values xi with probability pi. Let’s assume for another parameter some fixed k.
We then want to minimize subject to the constraint. Using Lagrange multipliers, this gives us a power law. The global optimization of minimizing the energy along with the power law dependence between X and k gives us a power law distribution in probability 2.
HOT has been used to generate and describe internet-like graphs, forest fire models, and it may also apply to biological systems. Another example is the use of HOT in epidemic models incorporating local optimization and regrowth.
SOS Processes: They typically follow the Pareto Principle, also known as the 80/20 rule, which states that for many outcomes, roughly 80% of consequences come from 20% of causes (the “vital few”).
Basically, it’s an observation that most things in life are not distributed evenly. A few things are vital; many are trivial.
An SOS process may exhibit 20% of its steps and deliver 80% of the process value. However, the 80% represents an adaptive capability when circumstances change. In other words, the 20% vital steps get swapped in and out of the 80% trivial when circumstances demand. SOS processes reserve adaptive capabilities.
How Did the 80/20 Rule Come About?
Vilfredo Pareto, was an Italian economist and discovered the Pareto Principle in the late 19th century.
He observed that 80% of the land in Italy was owned by just 20% of the population. Pareto found that this principle applied to other areas as well. For example, he found that 80% of the peas in his garden came from 20% of the pea pods.
Joseph M. Juran, a Romanian-born American engineer, read about Pareto’s discovery and thought it could be applied beyond land ownership, including in the manufacturing industry. In 1951, Juran wrote a management manual called the Quality Control Handbook, in which he referred to Pareto’s discovery as the “Pareto Principle.”
Did you know this about HOT?
In applied mathematics, Highly Optimized Tolerance (HOT) is a method of generating power law behavior in systems by including a global optimization principle. It was developed by Jean M. Carlson and John Doyle in the early 2000s.
It is a mechanism for power laws which blends the perspective of statistical physics with engineering methods for developing robust, highly interconnected systems.
If you’ve read this far, you might have guessed that I thrive on deciphering the elements that work collectively towards progress. I love figuring out all the components that go into building a roadmap for successful execution.
If you need a partner in developing & leading transformational initiatives at your organization, reach out to me today.