Solution State Modeling (SSM)
Here's how you can extend & apply the state model equation (control systems) you learnt in your engineering to help you get better in working with scenarios, situations & teams.
State-space Modeling (Differential Equations)
Do you remember state-space model / state modeling equation and its solution using Differential Equations, Laplace Transforms, Inverse Laplace Transforms from your days of engineering?
Alright, alright! I know!
If you’re an engineer, you’re most probably cursing me for bringing this dreaded topic up, aren’t you?
But, hang on! Just stay with me here right through the end
I promise you this is going to be fun
But let’s first get into a bit of an introduction to the model, which so rightly is also “a blast from the past” for some of us.
For those of you who are new to it - in a very broad sense, a state-space model is simply used to predict the future states & their outputs using the current state as an input over a some really complex mathematical modeling.
Now, what’s a state-space, you ask?
A state is a representative of all the possible configurations of a given system.
And naturally, any state could be considered as governed by a few of constants & groups of variables, which could be a representative of the current / historical values of the system.
Here’s a representation of a the model over a Linear Time-Invariant (LTI) system:
X˙ = AX + BU - State Equation
Y = CX + DU - Output
where:
X & X˙ - state vector & differential state vector respectively
U & Y - input vector & output vector respectively
A - system matrix
B & C - input & output matrices
D - feed-forward matrix
The reason we look at a time-variant system is because both the inputs & obviously the outputs do change over time & one could closely associate linearity over any real-world system.
So, that’s enough to breed some familiarity. Now, onto the real work!
Pragmatic & Complex
Think of any real-world scenario with any degree of complexity and it doesn’t have to necessarily do with individuals stuck with some work-related situation alone, one could also think of complex situations that bring global teams under the net and put them all into a tizzy over some odd cases.
And you’d agree hands down, it could be a nightmare really!
“Life often becomes hard due to complicated situations we have created ourselves. Don’t blame life, just change situations.”
– Jerry Corstens
Getting down to the subject of problem solving, one has to first make it feasible & easy to identify a problem over estimating the deviation from a normal state, which more often than not is considered very simple given the application to say product teams at MNCs, the organizations boasting of 100+ teams members working towards a common goal / outcome. But whether that’s really feasible, could be a million-dollar question.
The identification of the state could also be thought of as really very messy, at times very time consuming & inaccurate if it has to be done over a single trial sometimes as the variables governing the changes in the state don’t really seem to be very clear on the face of it on the first glance.
So, it could often take multiple trials before one gets to zero-in on the exact hyperlocal region that’s a representative of the problem or it’s root.
One way out of it might as well be the SSM (Solution State Model).
Solution State Model
The Solution State Model (SSM) could help one sail through all the chaos and confusion moving stage-wise to make sense of the entire situation so as to get to a stage to total comfort thus making things all simple and doable.
It could also be thought of as indicative of how every human ought to approach problems in general establishing a method to the madness.
NOTE: The visual modelling here is inspired by the CYNEFIN Framework proposed in 1999 by Dave Snowden @ IBM Global Services which has been popularly accepted as a "sense-making device”.
So, any real-world situation / system could be thought of as being totally constrained and perhaps CHAOTIC when one steps right into it at the beginning or what could be confusion that’s driven by the presence of many unknown variables making it overwhelming.
The usual course of the journey ought to be over how a person uses a brand of intuition, logic, rationale, abductive reasoning to move over each of those phases thereof – CHAOS, COMPLICATED, MANAGEABLE & SIMPLE and all that could take its natural course of time.
One doesn’t need to look too far to understand this.
Let’s say you’ve taken to a new role as a product manager in a banking firm which is bound to have tons of legacy applications and platforms supporting the modern-day app development / meddling with the presentation layer.
And, all of a sudden, your devices start buzzing with notifications carrying the “CRITICAL” label painting your screen in RED with all the reports / e-mails / notifications which has something todo with the legacy platform being broken and how it’d take quite a long time to mend, (FYI: 3 hours could be considered quite a long time in such applications & if it’s during business hours, you’re done for) and all hell breaks loose.
You’d have to coordinate with the platform team (which may be difficult if that’s been syndicated and reduced to a select few people who are just appointed there for periodic scheduled maintenance activities) & try and get into the impact assessment & resort to reports coming in from there to accordingly update the concerned teams & stakeholders internally & externally.
Now, that’s a perfect representation of a state of CHAOS which obviously requires you work in order, following those steps depicted in the canvas above taking it stage-wise over making it all MANAGEABLE & then getting it down to a SIMPLE state - back to working condition, restoring all the peace upon the world.
NOTE: The SSM canvas could also be extrapolated and used to help quantify & build an estimation of the time cycles it would take to get the situation down to a MANAGEABLE / SIMPLE state from a CHAOS / COMPLICATED state, the information could prove to be GOLD for customer-facing teams as they’d be the ones getting bombarded with user queries / complaints.
Zoom-out & Zoom-in
Zoom-out
Let’s now take a look at the bigger picture to see how the Solution State Model fits in and also some of those nuances / complications and how that ought to be tamed before it goes totally out of hand, turning into utter pandemonium.
Usually as one finds oneself stuck in a certain situation, one of the first things he does is to scope it well & lead to some kind of categorization which is based on the confidence levels over solving it & removing the problem completely as far as it can be envisioned. It could be thought of as a stepwise process.
Here’s a list of such steps:
NOTE 1: Please beware, the number of variables governing all these parameters listed in the table above could be so many in number, one would certainly need to work his way through the MATH, the State-space equation depicted in the beginning of this article.
NOTE 2: Supposing the current state of the system is identified with “CHAOS”, the variables governing the classification could be used to predict not only the penultimate solution but also the path one ought to take towards getting to a resolution quick.
Zoom-in
Taking a closer look at the Solution State Model (SSM) you’d see how there is a need to categorize the state even before you start. But, real life situations / scenarios could really be more dynamic than that which obviously demands a lot of meticulous attention so as to be able to cover all possible nuances.
It has happened many times before & continues to happen as we speak as much as there is no guarantee that it would be eradicated in the near future.
Consider this (and this is quite possible):
supposing the solution state is determined to be MANAGEABLE
once an individual / a team starts putting in their quantum of work towards it, the clout begins to clear up leading to a much brighter understanding of the situation which leads them towards a belief that the current problem whose solution is applied and working seems to be linked to a much bigger and chaotic situation (findings)
which then gets declared an IMBALANCED STATE &
runs into another silo of IDENTIFICATION & SCOPING
leading to determining that the sub-STATE isn’t MANAGEABLE anymore but is indeed CHAOTIC
Now, how does one go about representing that complex situation over the Solution State Model (SSM)?
Just take a look at this figure below.
So, as is evident, when the so-called major quadrants 1 – 4 represent the states transitioning stage-wise from Chaos – Simple, the Sub-States bearing the respective numbers could be thought of being indicative of the respective problems found thereof which intern could go stage-wise from Chaos-Simple. Unless all sub-states get totally cleared up & get to SIMPLE / MANAGEABLE as decided by the teams owing to internal protocols, one could say that the system is in unrest / hostile.
NOTE 1: When those Sub-States seem to be an ordered list from 1 to 8 here in the illustration above, it could just be in a random order really fitting into those major quadrants as they are found and relevant.
NOTE 2: Proper highlighting could be used so as to indicate the overall state of a system / situation at present. It’s useful specifically when one is working with many teams & this could be a way to align all those team members as well.
Like here in the figure below. as for this depiction the overall state is COMPLICATED:
Conclusion
The Solution State Model (SSM) could be a great way to help individuals / teams wade through situations of turmoil / chaos by helping them plug things into a canvas which no doubt & obviously is useful to build a shared understanding, but could be a great platform to gain a much deeper insight of the problems and assist in building step-wise action plans over scoping / categorizing each of those problem subsets, variables governing the situations so as to tame the entire ship, whilst also being able to quantify the quantum of work against each minor / major headers arriving at row-totals, column-totals, team-totals, sub-totals, grand-total.