10 March, 2014

This is just the start

We have finished the course, but never done learning about the business. We just have learned about the crust of how to run a business and all of this is aimed at making you confident enough to open the door with confidence and start digging your own way
We are never done learning about anything in this information-bursting age. Information and sciences are always changing, overlapping, specializing, branching and accumulating more info from themselves of from other realms

I hope you enjoyed the ride as I did. Go make a checklist of what you have to read or study after this 

3-3-18 improving systems: Experimental mindset

So, how you can find this middle path?
You are an entrepreneur. You are making your own way. There are no instructions of anyone who has taken the same path before you are digging your own way
And you can't know for sure what is the right thing to do before you actually take a risk, jump in and give it a try; "experiment it" I mean
-          All things that you are doing are kind of experimentation: putting a prototype, testing, trying …etc. You just do it intelligently enough; come up with the idea and see how to try it without risking everything  
Those skills, if you put yourself into the experimental mindset of “There’s really no such thing in business as failure, there are things that work and there are things that don’t work, and the things that don’t work give you more information or point you in the direction of the things that do.” That’s pretty much it.
As long as you experiment smartly, even the things that don’t work for you can provide valuable input to the next round of iterations, the next prototype, the next product, and that’s the cool part.
You have all of these things that you could *possibly* do, and collecting all of this information, and a lot of business really comes down to trying stuff.
If you take away the pressure that everything that you need to do has to be perfect… and the more you got away from that and started just thinking, “I’m just going to try something, and see what happens.” The more wonderful things started happening, because the more you try, the more information you collect about what works and what doesn’t.

So one of the very best things, and I hope you take this away very clearly from the course, even though the future is uncertain and you don’t know exactly what exactly will work, nobody does, just the mindset of experimenting with things to try it and see what works and collect information and then try it again and keep doing it and have fun with it. And that’s what effective business really is all about. And the more you do that, the more successful you’ll be. That’s The Experimental Mindset.  

3-3-17 improving systems: The middle path

Throughout the course it seems like there isn't anything that you can optimize, things always move between too much and too little and this changes always with time
This makes BUSINESS as much of an art as it is a science. There is a sense in it; How much you should produce? What do personally think of this? What do you think the most probable scenario to happen? Etc.   
There is an old quote by Aristotle that says, “A master in any art avoids what is too much, and what is too little. They search for the mean and choose it.”

You will find yourself always searching for this middle ground

3-3-16 improving systems: Scenario planning

All the things we do based on some predictions of the future … you say hi to someone expecting that he will reply the same. If you are sure that he will reply by hitting you, you will never say anything to him
But the one and only sure thing about the future is that you can't be 100% sure of anything
-          The best way to deal with the unknowability of the future is to assume that you can only put some assumptions of what may happen. Of course some assumptions are more probable than others, but all of them has a chance of happening

-          So for anything you try to predict don't be satisfied with one scenario. Write down the best case and worst case scenario and the in-between ones and take measures to be prepared for all of them 

3-3-15 improving systems: Stress testing

Stress testing is one of the best ways to discover weaknesses in your system

You just sit in front of your system and ask yourself this question:
Here is the system, how can I break it?
Then you try every way to break your own system (of course without making permanent damage to it). Then you study what you did actually and see how you can prevent this from happening

-          Stress testing is just about knowing the maximum capacity of the system to do ______  that it breaks if things go beyond this capacity (or the quality becomes too bad)

3-3-14 improving systems: The backup system

For any show there is some backup actors than memorize he role of one or more actor so that they can step in if anything bad happens and the main actor can't perform for any reason. This is the fail-safe system

The point of this is summarized in one sentence:

Your business also needs a backup system that can step in and save the situation in case of any failure in the main system

-          It must be separated from the main system; so that a failure or shortage in one of them doesn't affect the other one
-          It will not be the same efficient as the main system, but it will save the situation for a while till the main system is fixed again

-          The best way for a backup system is to be versatile; do as may rules as possible  

3-3-13 improving systems: Resilience

Resilience is equal to "defensive measures":
Some massively underrated and critically important qualities for businesses to protect themselves out in the world (among competitors, in the environment, in the market, in the financial world)
There are some bad and good things about resilience

-          It makes your business live longer
-          It makes the business withstand rough conditions, disasters and situations
-          They are designed to make you need them less with time
-          The better the system is, the less you need them
So resilience is important but has a price: it is not efficient; the resources used in them aren't always used and are intended to use them less. Also resilience makes you less and slower responsive to the environment

Think of resilience as it resembles a turtle; slow and not efficient creature but it consumes less energy, live longer, has it is own cave … etc.

3-3-12 improving systems: Normal accidents

Problems can (and will inevitably) happen at any step in the system especially when the system is tightly-coupled and interdependent

The longer any system runs; the more risks accumulate and the more probable that problems happen

-          Things go wrong all the time, and will go wrong
-          The best strategy towards this is
-          Be prepared psychologically to accidents
-          Always run quality tests
-          Have experts prepared and ready to prevent and deal with accidents
-          Watch and learn from previous accidents to prevent more accidents
-          Analyze close calls to figure out what may cause problems
-            Stress testing (simulate failure in the system to learn from it)

Notice that you don't want to add more to the system in order to make it better; the simpler the system is, the less complicated it is the better 

3-3-11 improving systems: Cessation

All the time we think of improving, introducing, developing, fixing….… always DOING something to the system.

One of the best approaches successful people always do is one of the most radical ideas ever > NOT doing = cessation

Cessation: stopping doing things that aren’t working anymore, or don’t serve you, or are causing problems that you have to fix later, or wasting your time, or you think they are urging but they actually aren't, or unimportant things…. etc.-  is a subtle but probably the most important way to understand to fix an issue.
For example: If a customer is abusive, stop calling them. If they’re a pain in the butt, stop selling to them. If an employee is causing more problems than they’re actually providing value, fire them. All of these things – you don’t have to continue doing all the things that you’re doing. You can stop. And if you stop doing the right things, you can actually make the entire system run much better.

You don't need to fix something broke by something else that stopped because a third thing …….. One thing you have to do; look at the root of the problem and cut it and you are finally free 

3-3-10 improving systems: Checklisting

For the best SOP to occur, you need to get this pattern out of your brain to the papers. Moreover, you need to put it in clear numbered/bulleted points. Bulleting make it impossible to miss a thing hidden between the lines

There is no need to make stupid, unnecessary mistakes just because you didn't put your tasks in neat, organized points

And you don't just apply this concept to SOP. Make a checklist every  morning with the tasks you should do during the day and you will find this very productive and efficient 

09 March, 2014

3-3-9 improving systems: Standard Operating Procedure

There is no system that can be fully automated. There will always be something fuzzy, ambiguous that can't be systemized and a human factor must be there to carry it out; for example development, research, response to unexpected changes in the environment, some sort of decisions

But in good systems you will find these things repeat themselves over and over and over … and they have a pattern that you can put it on paper, make a checklist or a kind of a flowchart, a diagram, this is what is meant by "SOP"

"SOP" let you define standards easily, qualify it, improve it. It makes it easier for you to get other people to learn these SOPs easily and be trained much faster

So, try to make SOPs for the stuff you can't automate... This will be a great help to you 

3-3-8 improving systems: The paradox of automation

The paradox goes like this: the more efficient is the system, the more automated it is, the more important it is for an expert to be there, the less he has to do; or else the system wouldn't be that efficient

And what happens when a guy just sets there without anything to do? He gets board, he gets less efficient with time and he loses his skills with time

And the funniest yet most dangerous thing is that people tend to forget why they hire him in the first place and keep asking why we are paying him if he is doing nothing, and then they fire him. They will discover how stupid they are as soon as the system makes an error

Don't ever forget why people are so important to be there even if they are doing nothing most of the time, keep them always busy by making them go through quality training, tests … etc. and you will overcome the disadvantage of losing their skill with time 

3-3-7 improving systems: Exponentiation of error

Despite that "automation" is a great strategy; there are some drawbacks of it. One of the major drawbacks is what I called "exponentiation of error"

We know that the more efficient automation is, the less human intervention is. But imagine that for some reason an error has happened within a system lacking a human factor; imagine how many faulty products would it produce till someone discover it and shut the system down or fix it

And imagine if one error would lead to a bigger one … and etc. How big and devastating the end error will be?

So the more complex and automated the system is, the more probable it is for an error to happen, and the more important it is for a human expert to intervene to stop the error and fix it

  That's why there will ever be a pilot and a co-pilot in every plane carrying people no matter how automated and efficient it is 

3-3-6 improving systems: Automation

One of the best ways to reduce friction is automation

-          Human factor are great and essential for certain professions and businesses, but they have a lot of disadvantages:
-          They make a lot of errors
-          They are slow
-          Their work quality is not consistent
-          Their overall quality over time gets worse with time and exhaustion …etc.
Meanwhile, automation overcomes all these mistakes, but it has one restriction >> you must have a pattern, a system (process) to apply "automation". If you have to make different decisions every time in the process; you can't apply "automation"

So, each time you think of reducing "friction", think of "automation"  

06 March, 2014

3-3-5 improving systems: Friction

For any system to continue running you have to keep adding input into it. Without input the system slows down with time till it finally stops.

Why we need to add input all the time? For the same reason we have to hit the ball more than once to across the field to reach the goal: Friction

Friction is another universal concept that applies to the business like anything around us

Most of the time friction is a bad thing and hinders you from reaching your goal, so you have to do 2 things

1-     And the most important thing: is to get rid of this friction as possible as you can. Pave the way to your goal so that you spend less energy, time, power to get to your goal
2-     Keep pushing and adding input, increase the power of your shots to get faster and to add more inertia to every input before it loses its effectiveness

-          The more energy you have to expend to do your work, the less efficient is the system
-          The less energy, time and the better design of the system; the more efficient the system is
Lessen friction is most important with things you do on a regular basis in the system

Notice that friction is not always a bad thing. Think of it like a tool; it can be used to make some good to your business. How?

-          Confirmation and tasks review are made to decrease errors
-          A lot of papers and operations to go through when returning goods
-          Processes you through when you apply to a scholarship or a good job- are used to decrease and filter out some of the enormous number of applicants

Always keep in your mind the friction theory, and use it in your favor all the time to either slow down process or removing it to make things go smoother and faster with less energy and time 

3-3-4 improving systems:Diminishing effectiveness

Imagine that you have 1$ …then you earn another one … that would be great looking at the initial input you have ...but with time when you have like 600 dollars and you keep increasing them by one dollar; that wouldn't give you the same feeling

This is called "Diminishing Returns": with time and incremental increase in the output, the input no longer has the same effect as before

 You have to understand this universal concept; that everything even the 100% perfect static system will eventually come to satisfaction and the challenge is to be responding to the ever-changing environment and to figure out new ways to keep gaining money 

And you will use this concept a lot, everything lose its effectiveness with time 

3-3-3 improving systems: The critical view

A pattern noticed in every system we have, especially the complex systems:

Most of the output depends on a small number of inputs, and the rest of input is in charge of the smaller number of the output

Most of your costs come from a few things, and the rest come from various small things

Most of the sales come from a specific area/s of a few number of customers, and the major part of the customers give you the rest ... and so on

You will find this concept applicable to most of the systems in life. This will help you greatly in identifying priorities and provide most of the positive results with the least efforts and least percentage of input 

3-3-2 improving systems: Optimization

The wrong thing that people tend to do when they try to "optimize" a system is to make everything better at once

While optimization is really about taking one step at a time
-          Take a variable
-          Minimize its input, maximize its output … or vice versa
-          Go to the nest variable … do the same … and so on
What to choose first? The constraint has the first priority to be optimized

One of the benefits of optimizing one variable at a time is to be perceptive and understanding to the changes that a variable is making to the rest of the system parts 

3-3-1 improving systems: Refactoring

It is a term for ungrouping/grouping various system parts
Refactoring goal is to make the system run as efficient as possible. That is done by analyzing the system; deconstructing it, then look at it in different ways trying to figure out how to group things in a way that make it so efficient

This needs a very deep understanding of the system components and what it is supposed to do …. Then the keen eye to figure out different patterns and solutions to make the system better and an execution plan to actually apply the suggested changes 

22 February, 2014

3-2-12 analyzing systems: Humanization

Humanization is the ultimate skill of analysis, the gift that sooo few of us are capable of doing and maintaining it with long times of dealing with abstract numbers

That is most impotent with systems that affect people. Humanization is the skill of translating the numbers to actual human beings, understanding how these numbers stand out in a world full of humans with feelings and emotions

People with this skill need to be around people all the time, not just setting on front of their laptops … as it is kind of skill that fades with time if you keep out of the customers and people for some time.
This empathy part is where A LOT of the best data analysts miss. It is easier for them to control numbers. The more they understand what these numbers really are in the real world, the more useful the data becomes and the better they can use it to improve the system

3-2-11 analyzing systems: Segmentation

A very useful way of adding context to a measurement is to segment it: take a measurement and split it up into groups

For example: segment customer data by age, social level, location, how long they stay in the store, how they know about us …etc.

Segmentation is how you add meanings to the number by looking into details. It is adding new dimensions to the data to help you understand what is actually changing in detail

The more data you can collect, the more ways of segmentation you can figure out, the more ways you can interpret, understand and get insights in the data

Raw, unorganized and un-segmented data are very low-value data 

3-2-10 analyzing systems: Context

There is no such thing as "The awesomeness factor" or something; the one number that if you look at it you will understand if your business is doing good or bad and what needs to be worked on to improve things …ect.

You actually can come up with one, but the toooo much abstracting you will do to get that one number will actually take out any possibility to learn anything from this number or get any details from it

You have to look at more than one measurement, interrelated pieces of information to understand what these number actually mean and what is going in the right direction and what is not and what needs to be done to improve your business 

3-2-9 analyzing systems: Proxy

Is the method you use when you have some important to measure but you can't measure it directly e.g. Customer Satisfaction

So what you do? You look for things that are directly correlated to this thing and measure them. The more tightly they are connected to the original thing and the ore they are, the more accurate representation you will have

For example; you can measure the customers' satisfaction by measuring the number of returns/refunds, the number of complaint calls etc.

Know that this won't give you a 100% perfect measurement, but if you do it right it will give you pretty good representative numbers 

3-2-8 analyzing systems: Norming

It is "comparing your business now with itself earlier" to see if you are improving or not.
-          It needs a significant amount of historical records
-          For your Norms to be valid, you have to have the same measurements. If the measurements changed, you can't compare

-          One important benefit of this is to compare the same period/season over the years to get a better understanding of the seasonality of your business 

3-2-7 analyzing systems: Ratio

At certain point you have to compare two results (numbers) with the same nature
Ratio is the relationship of two numbers of the same nature. It gives us a sense of direction; where thing are going and a sense of comparison between stuff
Ratio can be a single number, a percentage, a fraction

So when you need to compare, to have a wider look or just want fewer numbers to look at; think of using ratios 

3-2-6 analyzing systems: Counterparty risk

People staring highly-interdependent businesses - where they have to participate with other companies of have partners that they don't have control/influence over – usually are the most ones that will deal with this term

"Counterparty Risk" is the risk of someone you're working with not doing what he is supposed to do & how does that impact the system as a whole

What makes this so important is that you don't have control over him, and people tend not to expect or consider any delay or problems happen with these partners  

You have to keep that in mind all the time, watch and keep track of their progress and assess that risk and keep a B-plan in your pocket just in case

3-2-5 analyzing systems: Sampling

If the system you are trying to analyze is not very simple and small, you will find that it is impossible to collect all the data, so you need to take a sample

Sample is: a subsection of a whole that can be representative of that whole the best way possible; so that you don't need to collect the whole data pool

How to select a sample, and how much sample you need to get, etc….. this is a whole other realm of science labelled "Statistics", "Sampling", "Data warehousing"

One last thing, "Confidence Level" is the certainty of how accurately the sample represents the whole system … and "Principle Of Statistics" let you answer this question and other questions of sampling 

3-2-4 analyzing systems: Garbage in – Garbage out

So you are collecting data to feed into your measurements systems to get results. If you enter crappy data, your measurements will be crappy and you will get crappy results 

When you are collecting data/info; beware of any human error, data entry error, outdated data, process errors, biases, spams and malicious data. Also keep your measurements equations and processes updated all the time with all important factors included 

The quality of your measurements depends on the quality of the data fed into the measurements processes and how good are your measurements' processes

-          Sometimes you will find that you or the people working with you knowing that there is something wrong with the data they are entering of with the measurements but they are ignoring them because correcting the error will make them look worse; for example lowering the number of website visits, cut the sales numbers in half …etc.). A very basic human nature is that we want to look good, and looking worse puts us out of our comfortable zone.

However, know that "Honest Systems" don't give a damn about your feelings! All they care about is getting true numbers and giving you true, objective results. 

3-2-3 analyzing systems: KPIs

"Key Performance Indicators" are the things that you can count that are actually count for something, things that can make great difference if you make use of them

If you can't use a measurement, then it is not a KPI

-          Some measurements are more important than others.
-          There are things that are easy to measure, and things that are important to measure :) .Sometimes they intersect but most of the time they don't
KPIs are the things that help you measure what the system is actually trying to do

You can figure out what your business's KPIs are. KPIs are numbers describing:

-          How much you put in
-          How much you are getting out
-          What is the speed of the process
The previous three numbers or measurements are for the 5 core business processes: value creation, sales, marketing, value delivery and financial stuff

Notice that not all of these 15 measurements are the KPIs of your business. You will find that one or two numbers (maximum 4 numbers) are the real indicators of how you are doing; if they are rising up then you are right, if they are going down then there is something wrong 

3-2-2 analyzing systems: Measurement

To understand anything you must analyze it

To analyze anything you must measure it

A very important part of analyzing a system is to figure out whether if its parts are doing what they are supposed to do or not, and the only way to do this is to look at different parts of the system and asking that question
-          You must keep track of your business all the time, especially of you are starting a new business and don't have a complete analytical system; as it is very easy to ignore stuff
-          This works as a verification of quality and progress … you compare what you are doing against competitors, standard reference … and the only thing you can compare them with is numbers. That's why you need to measure

Notice that:
-          A lot of things that are easy to measure aren't the important things to measure
-          As Albert Einstein said: "Not all the things that counts can be counted, and not everything that can be counted counts"
-          The hardest things to measure is the qualitative stuff, but there are ways to do it

Measurement is a critical part of understanding your business. "What gets measured gets managed" … and if you can't measure things you are then completely blind; you can't figure out if you are doing right 

3-2-1 analyzing systems: Deconstruction

The skill we use when we want to analyze any system is called "Deconstruction":
Taking a complex system and break it down to its simpler systems, studying them as if they stand alone

-          Any system consists of smaller simpler systems that are connected to each other
-          You take the small, easy-to-understand part and:
-          Examine it
-          Know its inflows and outflows
-          Know the connection between it and other parts
-          Know its order in the process
-          Whether it is a slack, constraint or not … etc.

You keep doing that with any system you want to analyze till you are finished with analyzing all its parts, and then you make a diagram/ flowchart of the system to get a whole eagle-eye look at it 

13 February, 2014

3-1-10 understanding systems: Second order effect

What is the relation between uncertainty, change, and interdependence?

-          What makes a complex system a very hard thing to understand and predict is that it has a unique and unpredictable interdependencies that we don't figure out yet. So, there is still uncertainty about a lot of stuff in it
That's best explained by a term called (Second order effect):

We can make a change to a very complex system, and we may predict what is the direct consequence of that move. But there are consequences to this consequence and there are effects to this … which is known by (second and third and fourth order effects) … that in the end; the final effect of this may result in things COMPLETELY opposite to what you intend to get by taking this course of action in the first place

-          The smallest change in a complex system results in huge consequences, mostly unpredictable
-          The basic rule of a complex system is: you DON'T mess with a system that you don't fully understand. You will do more harm by messing with it than if you let it by itself

-          Internalizing these concepts and understanding them is the best way to begin dealing with such systems 

3-1-9 understanding systems: Critical path

A set of steps that if happen in order with no problem will get you the finished product in the least time possible with the most possible efficiency and least slack of any type [resources, time, effort, labor ….. etc.]

-          A tightly-coupled system has mostly one path that is the critical path. And there are no other paths or any other alternative paths are much lower in efficiency and quality than the critical path
-          However, in a loosely-coupled system; there are many alternative paths with very close efficacy and quality to the critical path
Pay attention to how your system is designed;

-          Is it a tightly or loosely coupled system?
-          Is there any way to make it more loosely-coupled?

-          How to enhance the alternative paths to make it as close as possible to the critical path regarding the performance of the system and quality of the end-product?

3-1-8 understanding systems: Interdependence

In order for a system to work some of the factors or elements in it have to interact with each other in a certain way … depend on each other in order for the system to work
There are two types of systems that exist

-          Tightly-coupled system
-          Loosely-coupled system

-          Tightly-coupled system:
-          Highly dependent system
-          Time dependent: things happen before and after things
-          Ordered: A has to happen before B and then C …. Etc.
-          There is only one path to a successful outcome
-          There is very little slack
-          Failure in one part of the system cascades to the depending parts and the whole system fails to give the desired outcome
-          Example: [Domino trick]

-          Loosely-coupled system:
-          Low-dependent system
-          Parallel system: things happen at the same time
-          Not ordered: in most parts of it
-          There are many paths to a successful outcome
-          There is significant slack
-          Failure in one part of the system may be not noticed. It affects the system as a whole but only the one failing part and the few depending parts shut down for a while
-          Example: [Orchestra]

 Know that no system is 100% tightly or loosely coupled. It depends on the number of dependencies it has and the how they affect the final product 

3-1-7 understanding systems: Uncertainty and change

We can't see the future, we can just simulate what is most likely going to happen depending on what is happening now and extrapolate the most likely predictions of what may happen after certain period/s of time.

 That's how predictions and risks are assessed and calculated

But we know also that any complex system is never static. The environment is one of the most complex systems we know of. Our predictability and extrapolating abilities are very limited with such very complex systems. The environment always surprises us with what we don't expect … either with a fortunate or unfortunate event/s 

Do differentiate quickly between these three terms:
-          Chance: a predictable good event
-          Risk: a predictable bad event
-          Uncertainty: something we can't be prepared for because it is not predictable     
The best quote I heard that explains uncertainty is:
"You never step in the same river twice"

So, if something is unknown and I can't predict it … what am I supposed to do about it?

1-     Don't underestimate how RANDOM things are on the fortunate and unfortunate side
2-     Plan always a step or two steps ahead for any chances or risks you can think of
3-      Be prepared mentally for any unexpected change. Prepare and train yourself not to panic when you face unexpected twist

4-     Add a factor of resilience in your system and don't build your system in a way that it will collapse if anything unexpected happen to it … don't make so stiff and rigid 

12 February, 2014

3-1-6 understanding systems: Feedback loops

It means that you input something in the system, get an output and re-input it I the system ….. and so on
There are types of feedback loops
1-     Positive feedback loop
-          The output is positively larger than the input
-          It gets bigger exponentially

A special type of feedback loop is
-          Type: self-reinforcing feedback loop
-          It is a chemical term: some reactions produce what is necessary for them to continue – provide the conditions for the next reaction – even make the reaction be better/ stronger …etc.
-          Output input, and the output is re-inputted in the system again and again
-          Example: marketing campaigns that gets more money than the input amount and then re-input it into the system again (positive, exponential loop)
-          This kind of loop isn't infinite … it is converted with time to balancing loop because of market satisfaction or changes in the environment  
2-     Negative feedback loop
-          You put negative input in the system
-          You get bigger negative output
-          The negative output gets larger and larger exponentially with every cycle

3-     Balancing feedback loop  
-          The output is smaller than the input

-          It gets smaller and smaller with time till it vanishes