Just finished reading
The Personal MBA: Master the art of business by Jorge Kaufman. I have an Executive MBA from the University of Miami (UM or "The U"), so I was very skeptical at the beginning. However, I really enjoyed the book. First of all, there is a lot of stuff that I learned during my MBA, but as he puts it towards the end of the book,
Educating yourself about anything is a Tao - there's no end to the process. The journey itself is the reward.
If you are the type of person that wants to learn more about business, I highly recommend it. The book
distilles a series amount of great books into one. Here's what you learn:
- how businesses work
- how people work (chapter 6 -8)
- how systems work (chapter 9-11)
You shouldn't expect:
- Manager and leadership overload.
- Finance and accounting.
- Financial intelligence for entrepreneurs
- How to read a financial report
- Quantitative analysis: thinking statistics, turning numbers into knowledge
The one thing that I kept using while reading was a notebook and pen handy. I also tried to review this every month.
I found it kind of sad that the book didn't covered any quantitative analysis in this analytic age, but I was happy that he covered how systems work. This is the chapter that really resonated with me. Here are my notes on the systems chapters.
Analyzing Systems
Deconstruction: the only way to analyze a complex system is by deconstructing it. "Deconstruction is the process of separating complex systems into the smallest possible sybsystems in order to understand how things work." You need to find the "ins" and "outs" of the system for you to understand it. Unable to understand complex systems, you need to decompose them into smaller systems for you to understand them.
Measurement: You need to measure the systems so you know if it's doing fine or not. "Measurement helps us avoid the absence blindness when analyzing systems. Remember: we have a hard time seeing things that aren't present. Measuring different parts of a system in operation helps to identify potential issues before they arise." One example is diabetes, a person needs to measure its blood glucose to know if it's too high or too low. A person cannot tell the level of glucose unless he/she measures it.
Key Performance Indicator (KPI): some measurements are better than others. Key performance indicator tell you exactly the status of your system. "Key performance indicators are measurements of the ciritical parts of a system. Measurements that don't help you make improvements to your system are worse than worthless: they are a waste of your limited attention and energy." Few questions the author used to identify business' KPI:
- Value Creation: how quickly is the system creating value? What is the current level of inflows?
- Marketing: how many people are paying attention to your offer? How many prospects are giving you permission to provide more information?
- Sales: how many prospects are becoming paying customers? What is the average customer's lifetime value?
- Value Delivery: how quickly can you server each customer? What is your current returns or complaints rate?
- Finance: what is your profit margin? How much purchasing power do you have? Are you financially sufficient?
Analytical Honesty: always look into data without discrimination of personal feeling. "Analytical honesty means measuring and analyzing the data you have dispassionately. Since humans are social creatures, we tend to care deeply about how other perceive us, which give us a natural incentive to make things look better than they actually are. If you purpose is to actually make things better, this tendency can get in the way of collecting accurate data and conducting useful analysis.
Sampling: is the process of taking at random a small percentage of the total output, then using it as a proxy for the entire system. If you ever had blood taken at the doctor's office, you'll have a good idead of what sampling entails.
Margin of Error: this entails on the percentage of accuracy your system has based on tests. "Is an estimate of how much you can trust your conclusions from a given set of observed samples." When it comes to analytical confidence, more data is always better.
Ratio: is a method of comparing two measurements against each other. By diving your results by your input, you can measure all sorts of useful relationships between different parts of your system. Here are some useful ratios to track:
- Return on promotions: for every $1 you spend in advertising, how much revenue do you collect?
- Profit from Employee: for every person you employ, how much profit does your business generate?
- Closing Ratio: for every prospect you serve, how many purchase?
- Returns/Complains Ratio: for every sale you make, how many choose to return or complain?
Typically: identifying a normal or typical value for some important measurement. There are four common methods of calculating a typical value: mean, median, mode, and midrange.
- mean: average
- median: sort the values in order of high to low, then finding the quantity of the data point in the middle of the range. Median are actually a specific form of analysis called a percentile: the median is the value that expresses the fiftieth percentile. By definition, 50% of the values in the set will be below the median.
- mode: is the value that occurs most frequently in a set of data. Modes are useful for finding clusters of data
- a set can have multiple modes, which can alert you to potentially interesting interdependencies in the system that produced that data.
- midrange: is the value halfway between the highest and lowest data points i a set of values. To calculate the midrange, add the highest and lowest values, then divide by two. Midranges are best used for quick estimates - they're fast, and you only need to know two data points, but they can be easily skewed by outliers that are abnormally high or low - Bill Gate's bank balance.
Correlation and Causation: causation is a complete chain of cause and effect. Correlation is not causation. Just because you can here illegal doesn't make you a criminal. Causation is always more difficult to prove than correlation. When analyzing complex systems with many variables and interdependencies, it's often extremely difficult to find true causality.
Norms: are measures that use historical data as a tool to provide context for current measurements. If you are selling Christmas ornaments, it's a waste to compare them Q4 with Q2. You should compare this Q4 with the previous Q4.
Proxy: measures one quantity by measuring something else. Used with care, proxies can help you measure the measurable - just be sure your proxy is directly and highly correlated with the subject of interest.
Segmentation: is a technique that involves splitting a dataset into well-defined subgroups to add additional context. Finding out that last quarter's sales increased by 20% is good, but knowing that they were done by 80% of women is even better. There are three common ways to segment customer data: past performance, demographics, and psychographics.
- Past performance: segments customers by past known action. For example, you can segment customer sales data using previous sales data, comparing sales to new customers with sales to customers who have previously purchase from you. Lifetime value calculations are a form of segmentation by past performance.
- demographics segments customers by external personal characteristics. Personal information like age, gender, income, nationality, and location can help you determine which customers are your probable purchasers.
- psychographics: segments customers by internal psychological characteristics. Typically discovered via surveys, assessments, or focus groups.
Improving Systems:
Optimization: this is the process of maximizing the output of a system or minimizing a specific input the system requires to operate. Optimization typically revolves around the systems and processed behind your "key performance indicators", which measure the critical elements of the system as a whole. Improve your KPIs, and your system will perform better.
Refactoring: the process of re-engineering the systems to improve efficiency without changing its output. The primary benefit of refactoring isn't improving the output - it's making the system itself faster or more efficient.
The Critical Few: this is the 80/20 rule from Vilfredo Pareto.
For best results, focus on the critical inputs that produce most of the results you want.
Finding the inputs that produce the outputs you want, then make them the focus of your time and energy. Ruthlessly weed out the rest.
Diminishing Return: after a certain point, having more of something can actually be detrimental. In the book the author explains about his work at P&G. At this company, he was the one in charge of analyzing the results of his advertising (tv spots). After time, the commercial will "wear out". That's the effect of diminishing return. "Optimize and refacgtor up to the point you start experiencing diminishing returns, then focus on doing something else".
Friction: Every business process has some amount of friction. The key is to identify areas where friction currently exists, then experiment with small improvements that will reduce the amount of friction in the system.
Automation: refers to a system or process that can operate without human intervention.
Find a way to automate your system, and you open the doors to scale via duplication and multiplication, improving your ability to create and deliver value to more paying customers.
The Paradox of Automation: the more efficient the automated system, the more crucial the contribution of the human operators of that system. When an error happens, operators need to identify and fix the situation quickly or shut the system down - otherwise, the automated system will continue multiplying the error.
The Irony of Automation: the more reliable the system, the less human operators have to do, so the less they pay attention to the system while it's in operation. Remember the Mackworth Clock and vigilance studies conducted on British radar operators in WWII from our discussion on Novelty? Humans get bore extremely quickly if things stay the same, and the more reliable the system, the more things stay the same.
Keep your automated system's operators mentally engaged, and they'll be far more likely to notice when errors inevitably occur.
Standard Operating Procedure (SOP): is a predefined process used to complete a task or resolve a common issue. Business systems often include repetitive tasks or resolve a common issue. Well-defined standard operating procedures are useful because they reduce friction and minimize will power depletion. Instead of wasting valuable time and energy solving a problem that has already been solved many times before, a predefined SOP ensures that you spend less time thrashing and more time adding value.
Don't let your standard operating procedure lapse into bureaucracy. Remember, the purpose of an SOP is to minimize the amount of time and effort it takes to complete a task or solve a problem effectively. If the SOP requires effort without providing value, it's friction.
Checklist: a checklist is an externalized, predifined standard operating procedure for completing a specific task. Checklist will help you define a system for a process that hasn't yet been formalized. Second, using checklists as a normal part of working can help ensure that you don't forget to handle important steps that are easily overlooked when things get busy.
Checklist can produce major improvements in your ability to do quality work, as well as your ability to delegate work effectively. By taking the time to explicitly describe and track your progress, you reduce the likelihood of major errors and oversights, as well as prevent willpower depletion associated with figuring out how to complete the same task over and over again.
Cessation: is the choice to intentionally stop doing something that's counterproductive. In The One-Straw Revolution, Masanobu Fukuoka wrote about his experiments with natural farming, which mostly involved letting nature take its course and intervening as little as possible. Instead of trying to do too much, Fukuoka only did what was absolutely necessary. As a result, his fields were consistently among the most productive in the are.
Cessation takes guts. It's often unpopular to unpalatable to do nothing even if doing nothing is actually the right solution.
Resilience: what business needs is more turtles and fewer tigers. Turtles are nature's tank - they can eat different food, go through hibernation if times are tough, and shelter from an enemy if needed. Tigers depends on their strength, speed, and pray to live. If prey becomes scarce or they lose their hunting powers due to age or injury, death takes them quickly and mercilessly. This is why turtles live longer than tigers.
Resilience is a massively underrated quality in business. Having the toughness and flexibility to handle anything life throws at you is a major asset that can save your skin.
What makes a business resilient:
- low (preferably zero) outstanding debt
- low overhead, fixed costs, and operating expenses
- substantial cash reserves for unexpected contingencies
- multiple independent product/industries/lines of business
- flexible workers/employees who can handle many responsibilities well
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- no single points of failure
- fail-safes/backup systems for all core process
Planning for resilience as well as performance is the hallmark of good management.
Fail-safe: is a backup system design to prevent or allow recovery from a primary system failure. As much as possible never have a single critical point of failure.
Stress testing: is the process of identifying the boundaries of a system by simulating specific environmental conditions.
Scenario Planning: is the process of systematically constructing a series of hypothetical situations, then mentally simulating what you would do if they occurred. Most large business use scenario planning as the basis of a practice called "hedging": purchasing various forms of insurance to reduce the risk of unfavorable future events.
Don't waste time trying to predict an unknowable future - construct the most likely scenarios and plan what you'll do if they occur, and you'll be prepared for whatever actually happens.
The Middle Path: is the ever-changing balance point between too little and too much - just enough.
The Experimental Mind-set: constant experimentation is the only way you can identify what will actually produce the result you desire. Often, the best (or only) way to learn things is to jump in and try.
You learn the most from what doesn't go well. As long as your mistakes don't kill you, paying attention to what doesn't work can give you useful information you can use to discover what does.
I really enjoyed the conference. I also just purchased the videos. Which I highly recommend!! During the next few months, I'm going to try to learn some of these tools and present them at the Miami JVM Meetup. Hopefully I can get to see you there, or better yet, hope to see you at Strata 2015. If you're going to either one of these events, let's meet up and share a beer...or two and discuss Big Data. I promise that my eyes will get dilated.
