# embedding_metadata

key: chroma:document
string_value:
ment affect your system. SHARE THIS CONCEPT: http://book.personalmba.com/environment/ Selection 
Test Any one response to the universe, however powerful, becomes inappropriate with time and change. 
Those who become utterly dependent on one means of mastery will find themselves unable to cope with t
he future. —FRANK HERBERT, SCIENCE FICTION NOVELIST AND AUTHOR OF DUNE Self-perpetuat
ing Systems (like businesses or organisms) can only selfperpetuate as long as they meet the Environmen


key: chroma:document
string_value:
tal conditions necessary to exist. A Selection Test is an Environmental constraint that determines which S
ystems continue to self-perpetuate and which ones “die.” Mammals like humans have several Selection T
ests: breathing enough air, eating enough food, drinking enough water, and retaining enough heat. Busine
sses also have Selection Tests: enough value provided to customers, enough revenue to cover expenses,


key: chroma:document
string_value:
enough Profit to stay financially Sufficient. Many people think of Selection Tests as “survival of the fittest,”
 but “death of the unfit” is a more accurate description. If a self-perpetuating system fails to satisfy a Selec
tion Test, it will cease to exist. If you can’t get enough air, you’ll die. If your business can’t bring in enough 
revenue to maintain Sufficiency, it’ll die. As the Environment changes, the Selection Tests change as well.


key: chroma:document
string_value:
Selection Tests are particularly interesting to watch in the technology market, where the Environment of “
what’s possible” changes constantly. Businesses that fail to take advantage of major changes in technolo
gy quickly find that they’re unable to keep up with the new demands customers make for their products. C
hanging Environments and Selection Tests are an entrepreneur’s best friend—they’re what allow small co


key: chroma:document
string_value:
mpanies to outperform large, entrenched competitors. If you can identify what the Selection Tests in a ma
rket really are, you’ll be able to compete in that market much more effectively. Selection Tests are ruthles
s: satisfy them, and you’ll thrive. Fail to adapt to changing conditions, and you’ll die. SHARE THIS CONC
EPT: http://book.personalmba.com/selection-test/ Uncertainty He who lives by the crystal ball soon learns


key: chroma:document
string_value:
to eat ground glass. —EDGAR R. FIEDLER, ECONOMIST What will interest rates look like ten years fro
m now? Where do you think the price of oil will be next year? How about that company stock—is it cheap 
or overpriced? Is it better to stockpile raw materials now or wait a few months? Businesspeople deal with 
questions like these daily. Here’s the answer to all of these questions: nobody knows. This world of ours i


key: chroma:document
string_value:
s a tremendously uncertain place, which is both a blessing and a curse. Anything can happen, for good or
 ill—we simply can’t know what’s around the bend. There’s an enormous difference between risk and Unc
ertainty. In the immortal words of former U. S. secretary of defense Donald Rumsfeld: There are known kn
owns. These are things we know that we know. There are known unknowns. That is to say, there are thin


key: chroma:document
string_value:
gs that we know we don’t know. But there are also unknown unknowns. These are things we don’t know 
we don’t know. Risks are known unknowns. If you’re planning to pick up a friend from the airport, the prob
ability that their flight will arrive several hours late is a Risk—you know in advance that the arrival time can
 change, so you can plan accordingly. Uncertainties are unknown unknowns. You may be late picking up


key: chroma:document
string_value:
your friend from the airport because a meteorite demolishes your car an hour before you planned to leave
 for the airport. Who could predict that? You can’t reliably predict the future based on past events in the fa
ce of Uncertainty. Unexpected or random events can occur suddenly, which can have major impacts on y
our goals and plans. In The Black Swan, Nassim Nicholas Taleb, a former hedge fund manager, describe


key: chroma:document
string_value:
s the perils of Uncertainty. No matter how stable or predictable things seem, unpredictable “black swan ev
ents” can change everything in an instant. The term “black swan” was a common expression in sixteenth-
century London for something that was impossible or didn’t exist—everyone knew that all swans were whi
te. The problem with the term is what eighteenthcentury philosopher David Hume called the “problem of in


key: chroma:document
string_value:
duction”: until you see every swan that exists, you can never assume the statement “all swans are white” i
s true. All it takes is one black swan to completely invalidate the hypothesis, which happened when black


key: chroma:document
string_value:
swans were documented in Australia in 1697 by Dutch sea captain Willem de Vlamingh. The moment bef
ore they happen, the probability of “black swan” events occurring is essentially zero. In the wake of a blac
k swan event, the probability of its occurring is a moot point: the event changes the Environment in which 
the system operates, sometimes drastically changing Selection Tests without warning. You can’t know in


key: chroma:document
string_value:
advance if (or which) black swan events will occur: all you can do is be flexible, prepared, and Resilient (di
scussed later) enough to react appropriately if and when they do. Even the most detailed analysis with rea
ms of historical data can’t save you from Uncertainty. The primary drawback of the financial models taugh
t in most MBA programs is Uncertainty: your pro forma, (Net Present Value NPV ), or (Capital Asset Pricin


key: chroma:document
string_value:
g Model CAPM) model is only as good as the quality of your predictions. Many a business has been ruine
d by financial predictions that turned out to be wrong. How likely is it that your ten-year financial projection
 predicts absolutely everything that will happen with 100 percent accuracy? Who says tomorrow is going t
o be anything like today? Many people make a business of selling certainty, which doesn’t exist. Predictio


key: chroma:document
string_value:
n, forecasting, and other forms of business soothsaying are popular because they provide the illusion that 
the future is knowable and controllable. Exercises in prediction aren’t worth the cost—if there were a foolp
roof way to predict gas prices, interest rates, or stock prices, the people with that magic knowledge would 
be enormously wealthy and would have no need to sell anything to you. Absorbing the ever-present natur


key: chroma:document
string_value:
e of Uncertainty is an exercise in seeing the world as it really is, not as we want it to be. Instinctually, we a
ll want to feel like we know what will happen in the future, particularly given how prone we are to Loss Ave
rsion and Threat Lockdown. Contemplating Uncertainty feels bad, because not knowing what’s going to h
appen feels like a threat. Instead of fixating on predicting invisible and unknowable threats, it’s better to ch


key: chroma:document
string_value:
annel your energy into enhancing your ability to handle the unexpected. Don’t rely on making accurate pre
dictions—things can change at any time. Planning for flexibility in response to Uncertainty via Scenario Pl
anning is far more useful than pretending to be a seer. SHARE THIS CONCEPT: http://book.personalmba
.com/uncertainty/ Change It is not the strongest of the species that survives, nor the most intelligent, but t


key: chroma:document
string_value:
he one most responsive to change. —CHARLES DARWIN, NATURALIST AND PIONEER OF EVOLUTIO
NARY THEORY All systems Change—there is no such thing as a System in stasis. Complex systems are
 in a constant state of flux. There is a great deal of Uncertainty in how a system will Change over time, but
 it is certain that the System will Change. Plans that do not take Change into account are of limited value.


key: chroma:document
string_value:
Change is a fact of life. Psychologically, it’s very difficult to internalize that some things are random: there’
s no rhyme or reason to many of the things that happen in the world. Because of our natural Pattern Matc
hing abilities, we tend to see patterns where none exist and tend to attribute random Changes to skill if th
e Changes are good or misfortune if they’re bad. As a result, we’re Fooled by Randomness—the title of N


key: chroma:document
string_value:
assim Nicholas Taleb’s first book. You will never develop your business to the point that everything is perf
ect and unchanging. Many business owners and managers share an unexamined belief that by moving a 
business from “good to great,” it’ll be “built to last,” continuing to outperform competitors for decades to co
me. It’s a pleasant dream, but measuring yourself against that yardstick is unrealistic —it requires an unch


key: chroma:document
string_value:
anging world. The only thing you can do about Change is increase your flexibility to handle a wide variety 
of different circumstances. The more flexible you are, the more Resilient (discussed later) you’ll be when t
hings inevitably Change. SHARE THIS CONCEPT: http://book.personalmba.com/change/ Interdependenc
e When we try to pick out anything by itself, we find it hitched to everything else in the universe. —JOHN


key: chroma:document
string_value:
MUIR, NATURALIST Nothing in the world exists in isolation. Complex Systems almost always rely on oth
er systems in order to operate. Your refrigerator requires electricity to operate. When your local power pla
nt fails, your refrigerator fails as well. That’s Interdependence. Highly Interdependent systems are someti
mes referred to as “tightly coupled” systems. The more tightly coupled the processes in a system are, the


key: chroma:document
string_value:
more likely failures or delays will affect other parts of the system. Tightly coupled systems are typically tim
e dependent, rigidly ordered, and have very little Slack. There’s often only one path to a successful outco
me, and a failure in any part of the system can “cascade” to the rest of the system. If you’ve ever seen a 
Rube Goldberg machine or played the children’s board game Mousetrap, you’ve seen a tightly coupled sy


key: chroma:document
string_value:
stem. In a cascade of dominoes, when one domino fails to knock over the next, the entire System grinds t
o a halt. If you’ve ever heard the project management term “critical path,” you know the importance of Inte
rdependencies. The critical path contains only the tasks that must be completed in order for the project to 
be finished on schedule. If something on the critical path changes, that Change cascades to everything el


key: chroma:document
string_value:
se on the path. Any delay in a task on the critical path will delay the entire project. “Loosely coupled” syste
ms have low degrees of Interdependence. Loosely coupled systems are more relaxed: they’re typically no
t time dependent. You may able to use “parallel processing,” completing multiple steps at a time. There’s


key: chroma:document
string_value:
plenty of slack, and you may be able to accomplish your goal using many different strategies. Think of an 
orchestra, which consists of a conductor and many instrumentalists. If the first violin hits the wrong note, t
he quality of the performance will be affected, but the mistake won’t necessarily cascade to the rest of the 
orchestra. You can make a system less Interdependent by removing dependencies. A dependency is an i


key: chroma:document
string_value:
nput that’s required before the next stage of a process can take place. The more dependencies there are i
n a system, the higher the likelihood of delay or system failure. Eliminating dependencies makes a system
 less tightly coupled. Think back to the automotive assembly line example: if you must put in the engine b
efore the windshield is installed, an engine problem will delay the entire system. If it doesn’t matter in whic


key: chroma:document
string_value:
h order the parts are installed, it’s possible to assemble a finished vehicle in more than one way. In The 4-
Hour Workweek, Timothy Ferriss shares a method that made his business work far more efficiently. Initiall
y, when a customer service representative had a problem with a customer, they were required to obtain a
pproval from Tim before resolving it. By instituting a policy that allowed representatives to do anything nec


key: chroma:document
string_value:
essary to solve the problems that cost less than $400 without approval, Tim made his business system le
ss dependent upon him for operation. Eliminate unnecessary dependencies, and you’ll reduce the risk of 
a cascading failure. SHARE THIS CONCEPT: http://book.personalmba.com/interdependence/ Counterpar
ty Risk The man who makes everything that leads to happiness depend upon himself, and not upon other


key: chroma:document
string_value:
men, has adopted the very best plan for living happily. —PLATO, ANCIENT GREEK PHILOSOPHER If yo
ur System relies on other people in order to function, that poses a major risk to the operation of your syste
m. Counterparty Risk is the possibility that other people won’t deliver what they have promised. If your ho
use burns down, you can only make a claim on your homeowner’s insurance if the company you purchas


key: chroma:document
string_value:
ed the insurance policy from is still in business. If it’s not, you’re in trouble. If your manufacturing system r
elies on a third-party vendor to supply certain parts and they’re not able to honor their commitments, your 
manufacturing line stops. If you outsource work to a contractor and that contractor doesn’t perform as pro
mised, your project will be delayed. Too much Counterparty Risk increases the risk of catastrophic system


key: chroma:document
string_value:
failure. In the 2008 Wall Street crash, the world’s largest investment banks stood on the brink of insolven
cy because they all relied on one another in the event something went wrong. Investment banks and finan
cial firms like Goldman Sachs, JPMorgan Chase, and Lehman Brothers made a practice of buying “credit 
default swaps,” a form of financial Insurance, from other large firms. If a highly Leveraged deal went south


key: chroma:document
string_value:
, these investment banks thought the Insurance they had purchased would protect them from multimillion-
dollar losses, so they took on more and more Leverage, increasing their risk exposure. When the housing 
market collapsed and the banks started losing money on the mortgage securities they held, they tried calli
ng in their credit default swaps. Lo and behold, the other banks they had purchased the swaps from had a


key: chroma:document
string_value:
lso lost a huge amount of money on mortgage-backed securities and couldn’t honor the obligations. Every
 large investment bank was a counterparty to the risk of the other banks in the system. Because they all r
elied on one another, when one bank fell, they all fell. Counterparty Risk is Amplified by the Planning Falla
cy. Your partners can’t predict the future any more than you can, and everyone has a tendency to be opti


key: chroma:document
string_value:
mistic regarding plans and deadlines. Make plans and commitments, but always have a plan for when the 
project doesn’t go as expected. When your system relies on the performance of someone outside of your 
control, do all that you can to prepare for the possibility that they won’t perform as expected. SHARE THI
S CONCEPT: http://book.personalmba.com/counterparty-risk/ Second-Order Effects While we are free to


key: chroma:document
string_value:
choose our actions, we are not free to choose the consequences of our actions. —STEPHEN COVEY, A
UTHOR OF THE SEVEN HABITS OF HIGHLY EFFECTIVE PEOPLE A few years ago, Kelsey and I had t
he opportunity to visit the kingdom of Bahrain, a small island country a few miles off the east coast of Sau
di Arabia. Now known for its international banking prowess, pearl diving, and international F1 racing track,


key: chroma:document
string_value:
it wasn’t too long ago that Bahrain was known for its unique ecosystem. A few short decades ago, the int
erior of Bahrain was lush with natural greenery—an island oasis said to be the original site of the Garden 
of Eden. Now the interior of the island is a stark desert, and local plant life is maintained via irrigation. Wh
at changed? Bahrain is surrounded by a network of underground freshwater springs, which were responsi


key: chroma:document
string_value:
ble for both the island’s plant life and spurring the local oysters to cultivate pearls of remarkable quality. A
s the country’s single large city, Manama, developed, land in the city center became scarce, so developer
s adopted a process called “land reclamation,” which involved excavating dirt from the interior of the islan
d and depositing it on the coast, “reclaiming” land from the sea. This approach was successful in creating


key: chroma:document
string_value:
new land, but at a much steeper cost than anticipated—the island’s network of springs dried up, turning th
e country into a desert. Every action has a consequence, and those consequences have consequences, 
which are called Second-Order Effects. Think of a line of dominoes—a single push causes a chain of eve


key: chroma:document
string_value:
nts to occur. Once the chain starts, it’s difficult (if not impossible) to stop or reverse the cascade of cause 
and effect. Rent control in New York City after World War II is another sobering example of unintended co
nsequences. Originally intended to provide returning veterans with affordable housing, the policy capped r
ent prices (and the ability of landlords to raise them) in certain areas of the city. Affordable housing for vet


key: chroma:document
string_value:
erans is a noble idea, right? Here’s what the city planners didn’t expect: every year, the cost to maintain p
roperties in New York City continued to rise, but landlords couldn’t raise rent prices to compensate for thei
r increased costs. By law, rent control couldn’t be removed unless the original leaseholder moved or the b
uilding was condemned, so landlords refused to maintain their property—it was a waste of money. Financi


key: chroma:document
string_value:
ally, it was better to let the building deteriorate around the remaining tenants. The effect of this policy over
 time was a steep decline in the quality of property, and eventually supply, as buildings were condemned, 
making housing even more expensive. A policy intended to make housing more affordable actually destro
yed housing supply and made it more expensive— the opposite of the original intent. Changing some asp


key: chroma:document
string_value:
ect of a complex system always introduces SecondOrder Effects, some of which may be antithetical to the
 original intent of the change. Elements in a complex system can be interrelated or dependent upon one a
nother in millions of different ways, and Uncertainty guarantees that you probably don’t know exactly how.
 Every action has a consequence, and those consequences always have consequences—even if you don


key: chroma:document
string_value:
’t know what they are or don’t want them to happen. Approach making changes to a complex system with 
extreme caution: what you get may be the opposite of what you expect. SHARE THIS CONCEPT: http://b
ook.personalmba.com/second-ordereffects/ Normal Accidents The problem is not that there are problems.
 The problem is expecting otherwise and thinking that having problems is a problem. —THEODORE RUBI
N, PSYCHIATRIST AND COLUMNIST The space shuttle—a vehicle capable of exiting the bounds of Eart


key: chroma:document
string_value:
h’s gravity with human travelers aboard—is clearly an extremely complex System. A highly engineered air
plane strapped to three rockets holding millions of cubic feet of explosive hydrogen gas is the epitome of 
a highly Interdependent system. Any error has the chance of cascading catastrophically, and every time t
he shuttle is launched, millions of things could potentially go wrong. In 1986, the space shuttle Challenger


key: chroma:document
string_value:
suffered a catastrophe—a seal in one of the rockets froze, becoming extremely brittle. When the seal was
 superheated during takeoff, it failed. The Challenger exploded seventy-three seconds after liftoff, instantly
 killing everyone aboard. It’s tempting to believe that it’s possible to create a system in which nothing ever 
goes wrong. Real-life systems always prove otherwise—count on it. The theory of Normal Accidents is a


key: chroma:document
string_value:
more formal way of expressing a universal proverb: shit happens. In a tightly coupled system, small risks 
accumulate to the point where errors and accidents are inevitable. The larger and more complex the syste
m, the higher the likelihood that something will eventually go very, very wrong. Overreacting to Normal Ac
cidents is actually counterproductive. When something goes wrong, our instinctive response is to become


key: chroma:document
string_value:
hypersensitive, locking things down and adding more controls to prevent the unfortunate event from happ
ening again. This response actually makes things worse: locking things down and adding more systems o
nly makes the system more tightly coupled, increasing the risk of future accidents. NASA’s response to th
e Challenger tragedy is extremely instructive: instead of completely shutting down or adding more system


key: chroma:document
string_value:
s that could compound the issue, NASA engineers recognized the inherent risk and focused on finding oth
er solutions to the problem that would minimize the risk of the issue reoccurring without adding more syst
ems that could potentially fail. The best way to avoid Normal Accidents is to analyze breakdowns or “close
 calls” when they happen. Instead of going into the systems equivalent of Threat Lockdown, which can cre


key: chroma:document
string_value:
ate even bigger issues in the long term, looking at near misses can provide crucial insight into hidden Inte
rdependencies. By analyzing the issue, it’s possible to construct contingency plans in the event a similar s
ituation happens in the future. In 2003, the space shuttle Columbia suffered a catastrophe of a different so
rt: the foam heat shields designed to protect the shuttle as it reentered Earth’s atmosphere failed, and the


key: chroma:document
string_value:
shuttle disintegrated. Again, NASA focused on how to prevent the issue from happening again without ma
king the system even more tightly coupled. When the space shuttle Discovery suffered damage to its heat
 shields on takeoff a few years later, NASA engineers were prepared, and the crew landed safely. Normal 
Accidents are a compelling reason to keep the systems you rely on as loose as you possibly can. There a


key: chroma:document
string_value:
re many positive things to be said for systems, but expecting zero failures is unrealistic in the extreme. Lo
ose systems may not be as efficient, but they last longer and fail less catastrophically. The more complex 
a system is and the longer it operates, the more likely it is to suffer a major failure. It’s not a matter of if—it
’s a matter of when. Be watchful for system failure, and be prepared to respond to it quickly. SHARE THIS


key: chroma:document
string_value:
CONCEPT: http://book.personalmba.com/normal-accidents/ 11 ANALYZING SYSTEMS If you can’t unde
rstand it, you can’t change it. —ERI CEVANS, TECHNOLOGIST Before you can improve a System, you


key: chroma:document
string_value:
must understand how well it’s currently operating. Unfortunately for us, that’s tricky business—it’s simply n
ot possible to stop the world however long you want while you take careful measurements. Systems must 
be analyzed as they’re working. Analyzing a system in operation is difficult, but definitely possible—if you 
know what to look for. In this chapter, you’ll learn how to Deconstruct systems into smaller parts you can u


key: chroma:document
string_value:
nderstand, measure what’s important, and discover how parts of the system interact with and depend on 
one another to function. SHARE THIS CONCEPT: http://book.personalmba.com/analyzingsystems/ Deco
nstruction Out of perfection nothing can be made. Every process involves breaking something up. —JOS
EPH CAMPBELL, MYTHOLOGIST AND AUTHOR OF THE HERO WITH A THOUSAND FACES Comple
x Systems, as we’ve already discussed, are made up of many Interdependent Flows, Stocks, processes,


key: chroma:document
string_value:
and parts. As a whole, the system may be too complex to take in all at once—if there are more than seve
n or eight variables or dependencies, the Cognitive Scope Limitation kicks in and confusion takes over. If t
hat’s true, how can anyone analyze extremely complex systems? Deconstruction is the process of separa
ting complex systems into the smallest possible subsystems in order to understand how things work. Inste


key: chroma:document
string_value:
ad of trying to understand the system all at once, you break up the system into parts, then work on unders
tanding the subsystems and how they interact with one another. Deconstruction is the reverse-engineerin
g aspect of Gall’s Law. Remember : complex systems that work inevitably evolved from simpler systems t
hat also worked. If you can identify simpler subsystems and focus on understanding how they work and h


key: chroma:document
string_value:
ow they fit together, you can eventually understand how the entire system works. If you know nothing abo
ut how cars work, popping the hood of your vehicle and examining the contents is an exercise in confusio
n—there are so many parts that it’s hard to know where to begin. Understanding the system is not imposs
ible, however—identifying important subsystems like the engine, transmission, and radiator can give you v


key: chroma:document
string_value:
aluable insight on how the entire system functions. Once you’ve identified important subsystems, tempora
rily isolating them in your mind can help you understand how they work. Instead of focusing on how the en
tire car works, you simply concern yourself with the engine for a while. Where does the subsystem begin?
 What Flows are involved ? What processes take place inside the system? Are there Feedback Loops inv


key: chroma:document
string_value:
olved? What happens if Inflows don’t come in? Where does the system end? What are the Outflows? It’s i
mportant not to lose sight of Interdependence when using isolation to Deconstruct a system, since each s
ubsystem is part of a larger system. Identifying triggers and endpoints—the parts of the system that intera
ct with other subsystems—is just as important. Triggers teach you what makes a subsystem start operatin


key: chroma:document
string_value:
g, and endpoints show you what makes the system stop. In addition, it’s important to understand the cond
itionals present in a system —if-then or when-then relationships that influence the operation of the system
. For example, an engine requires an Inflow of gasoline vapor to operate. If that Inflow is present, a spark f
rom the spark plug ignites it, providing energy that pushes a piston that powers the rest of the system. If t


key: chroma:document
string_value:
hat Inflow is absent or a spark doesn’t come from the spark plug, the energy is absent and the system sto
ps, making both the Inflow of gasoline vapor and the spark from the spark plug conditions of the system’s 
operation. Creating diagrams and flowcharts can help you understand how each Inflow, process, trigger, c
onditional, endpoint, and Outflow comes together. Explaining complex systems in words alone can be limi


key: chroma:document
string_value:
ting—for best results, draw diagrams of the Flows, Stocks, conditionals, and processes involved. Well-con
structed flowcharts can help you understand the Flow of a system as it operates, which can go a long way
 toward helping you fix the system when things break down.1 To analyze a system, Deconstruct complex 
systems into subsystems that are easier to understand, then build your understanding of the system from


key: chroma:document
string_value:
the ground up. SHARE THIS CONCEPT: http://book.personalmba.com/deconstruction/ Measurement In 
God we trust... all others bring data. —W. EDWARDS DEMING, PRODUCTION MANAGEMENT EXPER
T AND PIONEER OF STATISTICAL PROCESS CONTROL Once you’ve understood the parts of the Syst
em and how they interact with one another, it pays to ask another question: how well is the system operati
ng ? To do that, we rely on measuring the system as it’s operating. Measurement is the process of collecti


key: chroma:document
string_value:
ng data as the system is operating. By collecting information related to the core functions of the system, it’
s much easier to understand exactly how well the system itself is performing. Measurement also allows sy
stems to be compared with one another. For example, it’s possible to use several different types of microp
rocessors to build a computer—which one should you use? By measuring various characteristics of each


key: chroma:document
string_value:
processor—cycle time, power consumption, heat generation, etc.—it’s possible to choose the best proces
sor for your computer, resulting in better performance. Measurement helps us avoid Absence Blindness w
hen analyzing a system. Remember: we have a hard time seeing things that aren’t present. Measuring diff
erent parts of a system in operation helps to identify potential issues before they arise. For example, diab


key: chroma:document
string_value:
etes is a condition that represents a fault in the Feedback Loop that controls the body’s blood glucose lev


key: chroma:document
string_value:
els. Too much or too little blood glucose is life threatening, so if the body produces too much or too little in
sulin to keep blood glucose levels stable, that’s a major issue. Even though insulin levels are extremely im
portant to a person with diabetes, you can’t figure out a person’s insulin or blood glucose level just by look
ing at them. Without measurement, Absence Blindness is the rule until the condition becomes bad enoug


key: chroma:document
string_value:
h to become visible, which typically takes the form of the person passing out or going into shock. To avoid
 this situation, people with diabetes make a habit of measuring their blood glucose and insulin levels throu
ghout the day. Measuring something is the first step to improving it. Peter Drucker famously opined, “Wha
t gets measured gets managed.” It’s true. If you don’t know how much money your business is collecting o


key: chroma:document
string_value:
r spending, it’s difficult to know whether or not any change you make to your business system is actually a
n improvement. If you want to lose weight, you first must know how much you weigh right now, then track 
how any changes you make affect your weight. Without data, you’re blind. If you want to improve anything
, you must measure it first. SHARE THIS CONCEPT: http://book.personalmba.com/measurement/ Key Pe


key: chroma:document
string_value:
rformance Indicator It is better to have an approximate answer to the right question than an exact answer 
to the wrong question. —JOHN TUKEY, STATISTICIAN Here’s the primary problem with Measurement: y
ou can measure a million different things. Measure too much, and you’ll inevitably suffer from the Cognitiv
e Scope Limitation, drowning in a sea of meaningless data. Some Measurements are more important than


key: chroma:document
string_value:
others: Key Performance Indicators (KPIs) are Measurements of the critical parts of a System. Measurem
ents that don’t help you make improvements to your System are worse than worthless: they’re a waste of 
your limited Attention and energy. If your intent is to improve the system you’re examining, you don’t have
 to pay Attention to everything—just a few key Measurements that actually matter. Unfortunately, it’s easy


key: chroma:document
string_value:
to fixate on things that are easy to measure instead of things that are actually important. Take, for exampl
e, a business’s revenue—seems pretty important, right? It is, but only to a point: revenue is important only
 because it’s a key component of profit. It doesn’t matter if you collected $1,000,000 in revenue if you spe
nt $2,000,000 to collect it. As Theo Paphitis, a serial entrepreneur and host of the hit BBC series Dragons’


key: chroma:document
string_value:
Den, memorably put it: “Profit is sanity. Turnover is vanity.” Alone, revenue is not a KPI. The same thing 
goes for other in-process Measurements. For example, if you’re managing a team of programmers, it’s te
mpting to measure their output in “lines of code”—a visible, easy-to-collect measure. Here’s the problem: 
more code is not necessarily better. A talented programmer can make a program better by rewriting it usin


key: chroma:document
string_value:
g fewer lines of code. If you fixate on quantity, removing ten thousand lines looks like a setback, even if it’
s actually a huge improvement. The situation gets even worse if you reward programmers based on lines 
of code: Incentive-Caused Bias will ensure that your code looks like the programming equivalent of War a
nd Peace. Typically, business-related KPIs are directly related to either the Five Parts of Every Business


key: chroma:document
string_value:
or Throughput. Here are a few questions I use to identify a business’s KPIs: Value Creation: How quickly i
s the system creating value? What is the current level of Inflows? Marketing: How many people are payin
g Attention to your offer? How many prospects are giving you Permission to provide more information ? S
ales: How many prospects are becoming paying customers? What is the average customer’s Lifetime Val


key: chroma:document
string_value:
ue? Value Delivery: How quickly can you serve each customer? What is your current returns or complaint
s rate? Finance: What is your Profit Margin ? How much Purchasing Power do you have? Are you financi
ally Sufficient ? Any Measurements directly related to these questions are probably KPIs. Anything that’s 
not directly related to a core business process or a system’s Throughput is probably not. Try to limit yours


key: chroma:document
string_value:
elf to only three to five KPIs per system. When collecting Measurements, it’s tempting to build yourself a “
dashboard” that contains every piece of information you’d ever want to see. Resist the temptation : if you 
overload yourself with too much data, you’ll be far less likely to see Changes that are critically important. 
You can always dig deeper into the data at your disposal if necessary. Find your system’s KPIs, and you’ll


key: chroma:document
string_value:
be able to manage your system without drowning in data. SHARE THIS CONCEPT: http://book.personal
mba.com/key-performanceindicator/ Garbage In, Garbage Out Let us watch well our beginnings, and resu
lts will manage themselves. —ALEXANDER CLARK, NINETEENTH-CENTURY U.S. AMBASSADOR AN
D CIVIL RIGHTS ACTIVIST If you analyze poor-quality data, the resulting analysis will be worthless at be
st, and misleading or damaging at worst. The quality of the input you use always has an impact on the qu


key: chroma:document
string_value:
ality of the output. If you build an object from poor-quality materials, that object will be unattractive and unr
eliable. If you eat a lot of junk food, don’t move around much, and pay attention to too much news and rea
lity TV, you’ll feel apathetic instead of energetic. If the people working on a project aren’t skilled or excited,
 the end result will inevitably suffer. Garbage In, Garbage Out is a straightforward principle: put useless in


key: chroma:document
string_value:
put into a System, and you’ll get useless output. Your ability to understand a system is directly related to y
our ability to observe what’s going on in that system. The quality and quantity of the data you collect about


key: chroma:document
string_value:
the system represents an upper limit to how well you’ll be able to understand what’s happening in the sys
tem as it’s operating. If you don’t want garbage when you’re done, don’t use garbage when you begin. Bei
ng mindful of what you’re starting with can help you ensure that the end result of the process meets your 
expectations. To improve your results, improve the quality of what you start with. SHARE THIS CONCEP


key: chroma:document
string_value:
T: http://book.personalmba.com/garbage-ingarbage-out/ Analytical Honesty That which can be destroyed 
by the truth should be. —P. C. HODGELL, PROFESSOR AND AUTHOR OF THE GOD STALKER CHRO
NICLES My last position at Procter & Gamble involved creating an online Marketing Measurement strateg
y: figuring out a way to measure the effectiveness of P&G’s advertising on the Web. P&G spent millions of
 dollars every year on banner ads, search engine advertising, and online video placements. My job was to


key: chroma:document
string_value:
figure out if the investment was worth it. One of the things my team discovered while putting together our 
recommendations was disturbing: the System we were using on most of our Web sites to measure unique
 visitors was wrong. Instead of simply counting human visitors, the system was treating visits from search 
engine programs as “visitors” as well, even though they weren’t people. Computer programs don’t care ab


key: chroma:document
string_value:
out laundry detergent and shampoo, but the system was counting them as potential customers. It’s not un
common for search engine spider programs to visit a Web site many times a day looking for new informati
on, so the system was overstating how many people were visiting each Web site by a significant margin. 
Put simply, it was a Garbage In, Garbage Out situation, and it made our measurements much less useful.


key: chroma:document
string_value:
Naturally, we recommended upgrading the tracking system to collect visitor data more accurately. Almost 
universally, the teams declined. They knew they were getting crappy data, but they didn’t seem to care. W
eird, right? Here’s the rub: installing the new tracking system would make each Web site’s unique visitors 
measurement—considered a Key Performance Indicator by most teams—go down dramatically. Even tho


key: chroma:document
string_value:
ugh the new system was clearly more accurate, installing it would make the team look bad. Instead of corr
ecting the issue, they chose to continue living a lie. As a result, they seriously compromised their ability to 
improve their Web site’s actual performance. Analytical Honesty means measuring and analyzing the data
 you have dispassionately. Since humans are social creatures, we tend to care deeply about how others p


key: chroma:document
string_value:
erceive us, which gives us a natural incentive to make things look better than they actually are. If your pur
pose is to actually make things better, this tendency can get in the way of collecting accurate data and co
nducting useful analysis. The best way to maintain Analytical Honesty is to have your measurements eval
uated by someone who isn’t personally invested in your system. Incentive-Caused Bias and Confirmation


key: chroma:document
string_value:
Bias are all too easy to succumb to if your social status is on the line. Having an experienced but dispassi
onate third party audit your measurement and analysis practices is a neat workaround for these tendencie
s: you might not like what you hear, but at least you’ll be fully aware of potential issues. Don’t look at your 
data through rose-colored glasses: always strive to be honest with yourself about what the data indicates


key: chroma:document
string_value:
you can improve. SHARE THIS CONCEPT: http://book.personalmba.com/analyticalhonesty/ Context If yo
u don’t understand something, it’s because you aren’t aware of its context. —RICHARD RABKIN, PSYCH
IATRIST You brought in $200,000 of revenue this month. Is that good or bad? It depends. If you brought i
n $100,000 last month, it’s good. If your expenses are $400,000 this month, it’s bad. Context is the use of


key: chroma:document
string_value:
related Measurements to provide additional information about the data you’re examining. In the example a
bove, knowing your revenue isn’t very useful without additional information. Knowing last month’s revenue
 and this month’s expenses provides necessary Context, giving you a clearer picture of the situation. Aggr
egate Measurements almost never tell you anything useful. Aggregate measures are worthless when it co


key: chroma:document
string_value:
mes to making tangible improvements because they lack Context. Knowing 2 million people visited your 
Web site this month tells you absolutely nothing useful. Without context, you can’t determine Change or ef
fectiveness, which limits your ability to improve the System. Try to avoid the temptation to focus on a singl
e “magic number” when tracking your results. Relying on a single number sounds like a useful simplificati


key: chroma:document
string_value:
on, but it’s not—removing Context blinds you to important Changes in the data. Knowing your “total qualit
y score” or that revenue went up or down a few points won’t tell you why it happened, whether or not it’s i
mportant, or if it’s due to random fluctuations or a significant Change in the system or its Environment. As 
a general rule: examine no measures in isolation—always look at them in Context with other Measuremen


key: chroma:document
string_value:
ts. SHARE THIS CONCEPT: http://book.personalmba.com/context/ Sampling If you don’t believe in sampl
ing theory, next time you go to the doctor and he wants to take a little blood, tell him to take it all. —GIAN 
FULGONI, FOUNDER AND CHAIRMAN OF COMSCORE, INC. What do you do if your System is too larg
e or complex to collect data on every process? Sometimes it’s not practical to measure the Flows of an en


key: chroma:document
string_value:
tire system. If you’re managing a Scalable system, it’s often not possible to test every unit or find every err
or. How can you identify potential problems quickly when your system is cranking out millions of units or c


key: chroma:document
string_value:
ompleting millions of transactions? 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’ve ever had your blood taken at the docto
r’s office, you’ll have a good idea of what Sampling entails. The doctor or nurse draws a small amount of b
lood, which is then sent to a laboratory for analysis. If testing reveals anomalies in the sample, it’s likely th


key: chroma:document
string_value:
at the same issue is present in the bloodstream in general. Sampling can help you identify systemic errors
 quickly without testing all of the output of the system, which can be time-consuming and expensive. If you
’re manufacturing mobile phones, you don’t have to test every single phone that comes off the line. If you t
est one in twenty phones, you can still identify errors quickly enough to fix the system if something goes w


key: chroma:document
string_value:
rong. Depending on how quickly and accurately you need to spot errors, you can increase or decrease th
e Sampling rate. Random “spot checks” are also a form of Sampling. Many retail stores employ “secret sh
oppers” to periodically test customer service or the skills of their sales staff. These shoppers are hired to e
xpress interest in specific items, ask certain questions, make a return, or generally be annoying. Since the


key: chroma:document
string_value:
staff doesn’t know which customers are real and which ones are not, it’s an effective way for the manage
ment of a store to test their staff without scrutinizing them every second of every day. Sampling is prone t
o bias if the sample is not truly random or uniform. For example, measuring the average household incom
e in the United States by surveying property owners in Manhattan will skew the data considerably higher t


key: chroma:document
string_value:
han if you survey property owners in West Virginia. For best results, use the largest random sample you p
ossibly can. If you need to test for quality, Sampling can help you collect good data without incurring enor
mous costs, provided you stay on the lookout for potential bias that can skew the data. SHARE THIS CO
NCEPT: http://book.personalmba.com/sampling/ Confidence Interval Everyone generalizes from one exa


key: chroma:document
string_value:
mple. At least, I do. —STEVEN BRUST, SCIENCE FICTION AUTHOR Suppose you purchase a trick coin
 from a magician’s shop, and you want to be sure the coin is actually biased to land on heads most of the 
time. How can you be sure you didn’t buy a dud? You start flipping the coin, of course. Let’s assume that i
n the first five flips, you get two heads and three tails. Should you ask for a refund? A Confidence Interval


key: chroma:document
string_value:
is the probability a particular analysis is correct. It’s probably worthwhile to make sure your results are acc
urate before jeopardizing the magician’s good name. The more samples you take, the higher the Confiden
ce Interval of your Measurement. Each coin flip makes your sample size larger. The larger your sample, t
he more confidence you can have in the accuracy of your Measurements. Since you only flipped the coin f


key: chroma:document
string_value:
ive times, you can’t be sure it’s a dud— your sample size is very small. If you flip the coin one thousand ti
mes and it comes up tails two thirds of the time, you can be relatively sure that the coin is biased, but not i
n the way you expected. Since a nonloaded coin should come up heads half the time, your large sample s
ize makes it very likely the magician gave you a tails-loaded coin by mistake. The math behind how to cal


key: chroma:document
string_value:
culate Confidence Intervals is beyond the scope of this book, but it’s relatively easy once you get the hang
 of it, particularly if you use a spreadsheet or database for your analysis. If you need to calculate Confiden
ce Intervals, I recommend picking up Principles of Statistics by M. G. Bulmer for an in-depth primer. Bewa
re of misleading Measurements based on small sample sizes. Whenever you’re presented with an averag


key: chroma:document
string_value:
e or a percentage based on data you’re not familiar with, it always pays to investigate the size of the samp
le and how it was collected. Sample sizes that are too small can significantly influence the final results. W
hen it comes to analytical confidence, more data is always better—collect the largest samples you can. S
HARE THIS CONCEPT: http://book.personalmba.com/confidenceinterval/ Ratio He who refuses to do arit


key: chroma:document
string_value:
hmetic is doomed to talk nonsense. —JOHN MCCARTHY, COMPUTER AND COGNITIVE SCIENTIST W
HO COINED THE TERM “ARTIFICIAL INTELLIGENCE” A Ratio is a method of comparing two Measurem
ents against each other. By dividing your results by your input, you can measure all sorts of useful relation
ships between different parts of your System. For example, assume that for every 30 customers who ente
r your store, 10 of them make a purchase. Your “closing Ratio” would be 10 divided by 30: 1/3. Let’s say y


key: chroma:document
string_value:
ou train your sales staff in techniques that result in 15 paying customers out of 30 who enter the store. Yo
ur new closing Ratio is 15 divided by 30: 1/2. Percentages are simply Ratios with a base of 100. Your first 
closing Ratio, converted into a percentage, is 33 percent. Your second would be 50 percent. Think of a M
easurement like Return on Investment (ROI): you’re simply dividing the amount of money you collect by th


key: chroma:document
string_value:
e amount of money you spent, then subtracting 1.00. The result, when expressed in terms of a percentag
e, indicates your return. For example, if you spend $2 million and bring in $4 million, your return would be 
100 percent: $4 million (earned) / $2 million (spent) = 2.00 2.00 - 1.00 = 1.00 = 100% return on investmen
t HERE ARE SOME USEFUL RATIOS TO TRACK: —Return on Assets: For every $1 you invest in equip


key: chroma:document
string_value:
ment, how much revenue do you collect? —Return on Capital: For every $1 you borrow or take on in inve
stment, how much revenue do you collect? —Return on Promotion: For every $1 you spend in advertising


key: chroma:document
string_value:
, how much revenue do you collect? —Profit per Employee: For every person you employ, how much profi
t does your business generate? —Closing Ratio: For every prospect you serve, how many purchase? —R
eturns/Complaints Ratio: For every sale you make, how many choose to return or complain? Tracking Rat
ios over time can provide a directional indication of how a system is changing. If your closing Ratio or Ret


key: chroma:document
string_value:
urn on Investment keeps going up, that’s a very good thing. If it’s going down over time, it would pay to inv
estigate to find out why. Be creative: study your business, then construct Ratios that highlight the most im
portant parts of your system. SHARE THIS CONCEPT: http://book.personalmba.com/ratio/ Mean, Median
 , Mode, and Midrange It ain’t what you don’t know that hurts you. It’s what you know that ain’t so. —WILL


key: chroma:document
string_value:
ROGERS, AMERICAN COWBOY AND COMEDIAN The average household net worth of a person who r
eads the Wall Street Journal is $1.7 million. Seems that WSJ readers are extremely well off, right? Yes, b
ut less than you might think. Bill Gates and Warren Buffett read the Wall Street Journal, and their wealth i
s measured in the billions— significantly more than even the top 0.01 percent of business professionals. S


key: chroma:document
string_value:
imply by existing, high-net-worth executives like Gates and Buffett skew the average much higher than it 
would be otherwise. If you’re relying on the average to tell you how much the typical Wall Street Journal r
eader is worth, you’re making a mistake. A Mean (or average) is calculated by adding the quantities of all 
data points, then dividing by the total number of data points available. Averages are simple to calculate bu


key: chroma:document
string_value:
t are prone to Gates and Buffett Syndrome: the presence of outliers that skew the average too high or low
 to be representative. (Exclude the outliers, however, and the average becomes more accurate.) A Media
n is calculated by sorting the values in order of high to low, then finding the quantity of the data point in th
e middle of the range. Medians are actually a specific form of analysis called a percentile: the median is th


key: chroma:document
string_value:
e value that expresses the fiftieth percentile. By definition, 50 percent of the values in the set will be below
 the Median. Calculating the Median and comparing it to the Mean can tell you if the average is being influ
enced by a few heavy hitters. A 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 intere


key: chroma:document
string_value:
sting Interdependencies in the System that produced that data. A Midrange is the value halfway between t
he highest and lowest data points in a set of values. To calculate the Midrange, add the highest and lowes
t values, then divide by two. Midranges are best used for quick estimates— they’re fast, and you only nee
d to know two data points, but they can be easily skewed by outliers that are abnormally high or low, like


key: chroma:document
string_value:
Bill Gates’s bank balance. Means, Medians, Modes, and Midranges are useful analytical tools that can ind
icate typical results—provided you’re careful enough to use the right tool for the job. SHARE THIS CONC
EPT: http://book.personalmba.com/mean-medianmode-midrange/ Correlation and Causation Correlation i
sn’t causation, but it sure is a hint. —EDWARD TUFTE, STATISTICIAN, INFORMATION DESIGN EXPE
RT, AND PROFESSOR AT YALE UNIVERSITY Imagine a billiards table: if you know the exact position of


key: chroma:document
string_value:
every ball on the table and the details of the forces applied to the cue ball (impact vector, impact force, lo
cation of impact, table friction, and air resistance), you can calculate exactly how the cue ball will travel an
d how it will affect other balls it hits along the way. Professional billiards players are skilled at Mentally Si
mulating these relationships so well that they can rapidly clear entire tables. That’s Causation: a complete


key: chroma:document
string_value:
chain of cause and effect. Since it’s possible to calculate a complete chain of causality, you can say that 
striking the cue ball caused a ball to fall into the corner pocket. If you hit the cue again in exactly the same
 way in exactly the same situation, you’ll get the same result every single time. Here’s another thought ex
periment, using hypothetical data: people who suffer heart attacks eat, on average, 57 bacon double chee


key: chroma:document
string_value:
seburgers every year. Does eating bacon double cheeseburgers cause heart attacks? Not necessarily. Pe
ople who suffer heart attacks typically take 365 showers a year and blink their eyes 5.6 million times a yea
r. Do taking showers and blinking your eyes cause heart attacks as well? Correlation is not Causation. Ev
en if you notice that one measurement is highly associated with another, that does not prove that one thin


key: chroma:document
string_value:
g caused the other. Imagine you own a pizza parlor, and you create a thirty-second advertisement to air o
n local television. Shortly after the commercial goes live, you notice a 30 percent increase in sales. Did th
e advertisement cause the increase? Not necessarily—the increase could be due to any number of factor
s. Maybe a convention was held in town that day, so there were more visitors in town than usual and they


key: chroma:document
string_value:
needed a quick place to eat. Maybe school let out and families went out to eat to celebrate. Maybe you off
ered a special two-pizzas-for-the-price-of-one promotion at the same time, and that’s what actually brough
t more people in the door. So many things happened at the same time, it’s hard to be certain. In fact, the c
ommercial may have actually caused a decline in sales—maybe people found it unappealing or offensive,


key: chroma:document
string_value:
but another factor caused such a huge increase in sales that it overshadowed the decline. Causation is al
ways more difficult to prove than Correlation. When analyzing complex Systems with many variables and I


key: chroma:document
string_value:
nterdependencies, it’s often extremely difficult to find true causality. The more changes that happen in a s
ystem over a period of time, the higher the likelihood that more than one change had an impact on the res
ult you’re trying to analyze. Adjusting for known variables can help you isolate the potential causes of a ch
ange in your system. For example, if you know that families go out to celebrate the end of school or that a


key: chroma:document
string_value:
n annual convention is coming up, you can adjust for that seasonality by using historical data. The more y
ou can isolate the change you made in the system from other factors, the more confidence you can have t
hat the change you made intentionally actually caused the results you see. SHARE THIS CONCEPT: http
://book.personalmba.com/correlationcausation/ Norms Those who cannot remember the past are condem
ned to repeat it. —GEORGE SANTAYANA, PHILOSOPHER, ESSAYIST, AND APHORIST If you want to


key: chroma:document
string_value:
compare the effectiveness of something in the present, it’s often useful to learn from the past. Norms are 
measures that use historical data as a tool to provide Context for current Measurements. For example, by 
looking at past data you may discover trends in your sales data directly related to the date the sale was m
ade, which is called seasonality. Seasonality is a good example of why Norms are often useful. If you’re in


key: chroma:document
string_value:
the business of selling Christmas ornaments, comparing sales during Q4 (the last quarter of the year— O
ctober through December) to Q3 sales (August through September) probably isn’t useful—no one purcha
ses Christmas ornaments in August. Far better to compare this year’s Q4 sales with last year’s Q4 sales t
o see if you performed better than last year’s comparable period. When Measurement practices Change,


key: chroma:document
string_value:
Norms based on the previous Measurements are no longer valid. At P&G, we had a method of evaluating 
the effectiveness of certain types of advertising. Drawing on several years’ worth of data, it was possible t
o compare new advertisements with old advertisements that had been successful. If the new advertising d
idn’t beat the Norm in testing, it wasn’t used. If the company suddenly decided to use a different testing m


key: chroma:document
string_value:
ethodology, the Norms would no longer be valid—it would be comparing apples and oranges. Change the
 Measurement methods, and you immediately invalidate any Norms based on them. If you still want to use
 Norms, you must build your database of historical information once again. Past performance is no guaran
tee of future performance. Remember, we’re dealing with complex Systems—things always Change over


key: chroma:document
string_value:
time. Just because something was useful in the past does not mean it will continue to perform as well in p
erpetuity. For best results, reexamine your Norms periodically to make sure they’re valid. SHARE THIS C
ONCEPT: http://book.personalmba.com/norms/ Proxy How many legs does a dog have if you call the tail 
a leg? Four. Calling a tail a leg doesn’t make it a leg. —ABRAHAM LINCOLN What do you do if it’s not po


key: chroma:document
string_value:
ssible to measure something directly? A Proxy measures one quantity by measuring something else. For 
example, in democratic political Systems, votes are used as a Proxy to measure the “will of the people.” It’
s not possible to subject every citizen in the country to a brain scan that reveals detailed preferences, so v
otes are used as the Next Best Alternative. Proxies are used all the time in scientific measurement. Ever


key: chroma:document
string_value:
wonder how scientists know how hot the sun is, or how old certain rocks are? They measure Proxies like t
he wavelength of electromagnetic rays or the decay of known radioactive isotopes, then apply well-proven
 relationships and formulas to determine the answer. Useful Proxies are closely related to the primary subj
ect—the closer, the better. Take Web site analytics—you may want to know exactly where and how long


key: chroma:document
string_value:
people pay Attention to different parts of the Web page, but again, you can’t brain scan each visitor to you
r Web site. Tracking the position of the mouse cursor, however, can be a useful Proxy for Attention. Accor
ding to a study done by researchers at Carnegie Mellon University: . . . 84% of the times that a region was
 visited by a mouse cursor, it was also visited by (users’) eye gaze. In addition, 88% of regions that were n


key: chroma:document
string_value:
ot gazed by the eye were also not visited by a mouse cursor. 2 Because mouse movements and eye fixati
on (i.e., Attention) are highly Correlated, mouse movements are a good Proxy for visitor Attention. The bet
ter the Correlation, the better the Proxy. For best results, ensure that the Proxy is actually related to the in
tended subject. Proxies can be tricky or misleading if they seem to measure one thing but actually measur


key: chroma:document
string_value:
e another. Think back to the example of trying to measure programmer productivity by counting lines of co
de as a Key Performance Indicator. As we discussed earlier, “lines of code” is certainly a Proxy for progra
mming effectiveness, but more code is sometimes an inverse signal of productivity, making it a useless M
easurement for the stated objective. Used with care, Proxies can help you measure the immeasurable—ju


key: chroma:document
string_value:
st be sure your Proxy is directly and highly Correlated with the subject of interest. SHARE THIS CONCEP
T: http://book.personalmba.com/proxy/ Segmentation Analytics nirvana rule: never report a metric (even 
God’s favorite KPI) without segmenting it . . . There is no KPI so insightful all by itself, even in a trend or a
gainst a forecast, that can’t be made more impactful by applying segmentation. —AVINASH KAUSHIK, A


key: chroma:document
string_value:
UTHOR OF WEB ANALYTICS: AN HOUR A DAY Very often, aggregate data sets contain hidden nugget
s of gold—if you can find them. Segmentation is a technique that involves splitting a data set into well-defi


key: chroma:document
string_value:
ned subgroups to add additional Context. Splitting the data into predefined groups can uncover previously
 unknown relationships. For example, knowing that orders increased by 87 percent this month is good, but
 knowing that 90 percent of those new orders came from women in Seattle is even better. Find out what m
ade those women order, and you’ll be able to use that information to further capitalize on your success. T


key: chroma:document
string_value:
here are three common ways to Segment customer data: Past Performance, Demographics, and Psychog
raphics. Past Performance Segments customers by past known actions. For example, you can Segment c
ustomer sales data using previous sales data, comparing sales to new customers with sales to customers
 who have previously purchased from you. Lifetime Value calculations are a form of Segmentation by Past


key: chroma:document
string_value:
Performance. Demographics Segment customers by external personal characteristics. Personal informati
on like age, gender, income, nationality, and location can help you determine which customers are your P
robable Purchasers. Knowing that your best customers are males between the ages of twentythree and th
irty-two who live in major metropolitan areas and have over $2,000 per month in disposable income can b


key: chroma:document
string_value:
e quite useful—you can focus your Marketing efforts on reaching more prospects who have those charact
eristics. Psychographics Segment customers by internal psychological characteristics. Typically discovere
d via surveys, assessments, or focus groups, Psychographics are attitudes or worldviews that influence h
ow people see themselves and the world at large. Psychographics can be very useful in creating or adjust


key: chroma:document
string_value:
ing your Value Creation, Marketing, and Sales strategies. For example, if you’re selling home security syst
ems, it’s likely that your Probable Purchasers will believe statements like “the world is a dangerous place” 
and feel somewhat in danger even when in their homes. Experimenting with promoting your product in sur
vivalist and self-defense magazines and Web sites—markets whose customers might have similar beliefs


key: chroma:document
string_value:
—might not be a bad idea. Segment your data, and you’ll find many useful hidden connections worth inve
stigating. SHARE THIS CONCEPT: http://book.personalmba.com/segmentation/ Humanization People ar
e the center of the universe. Not stuff. —STOWE BOYD, SOCIAL TECHNOLOGIST Analyzing data is co
mforting to the quantitative-minded, but to really use data properly, you must go beyond juggling numbers


key: chroma:document
string_value:
to understand what they’re telling you. When analyzing data from a System, it’s easy to forget that it often 
pertains to the actions of real human beings. For example, imagine a customer service department that a
nswers customer complaints by telephone. Numerically, reducing hold times from ten minutes to eight min
utes sounds great—that’s a 20 percent improvement! Put the champagne away: what the data-centric vie


key: chroma:document
string_value:
wpoint misses is the fact that you still have a dissatisfied customer waiting on the phone for eight minutes,
 which still feels like an eternity. Every minute on hold makes that customer angrier, which affects their per
ception of the company. That 20 percent improvement pales in comparison to the Reputation hit your busi
ness takes every time that customer tells their friends and associates how horrible your company is to dea


key: chroma:document
string_value:
l with. Humanization is the process of using data to tell a story (Narrative) about a real person’s experienc
e or behavior. Quantifiable measures are helpful in the aggregate, but it’s often necessary to reframe the 
measure into actual behavior to really understand what’s actually happening. Many businesses Humanize
 by developing a series of personas: fictional profiles of people developed from data. When I developed h


key: chroma:document
string_value:
ome cleaning products for P&G, market research data told us that two broad Segments existed: people w
ho valued regular deep cleaning (“Unless I’m on my hands and knees cleaning with bleach and elbow gre
ase, I’m not satisfied”) and people who wanted cleaning to be quick and convenient (“I’m too busy to clea
n—as long as it looks good enough, I’m happy”). Using this information, we combined these characteristic


key: chroma:document
string_value:
s with other data like household income, family statistics, and hobbies to create a profile of a fictional pers
on. Once the profile was developed, it became easier to use the data we had to make decisions—instead 
of relying on statistics to evaluate an idea, we could rely on our intuition by asking ourselves if “Wendy” w
ould like it. Don’t just present data—tell a story that helps people understand what’s happening, and you’ll


key: chroma:document
string_value:
find your analysis efforts more useful. SHARE THIS CONCEPT: http://book.personalmba.com/humanizati
on/ 12 IMPROVING SYSTEMS In theory there’s no difference between theory and practice. But, in practic
e, there is. —JAN L. A. VAN DE SNEPSCHEUT, COMPUTER SCIENTIST Creating and improving Syste
ms is the heart of successful business practice. The purpose of understanding and analyzing systems is t
o improve them, which is often tricky—changing systems can often create unintended consequences. In t


key: chroma:document
string_value:
his chapter, you’ll learn the secrets of Optimization, how to remove unnecessary Friction from critical proc
esses, and how to build Systems that can handle Uncertainty and Change. SHARE THIS CONCEPT: http
://book.personalmba.com/improvingsystems/ Optimization Premature optimization is the root of all evil. —
DONALD KNUTH, COMPUTER SCIENTIST AND FORMER PROFESSOR AT STANFORD UNIVERSITY
 Optimization is the process of maximizing the output of a System or minimizing a specific input the syste


key: chroma:document
string_value:
m requires to operate. Optimization typically revolves around the systems and processes behind your Key


key: chroma:document
string_value:
Performance Indicators , which measure the critical elements of the system as a whole. Improve your KPI
s, and your system will perform better. Maximization typically focuses on the system’s Throughput.If you 
want to earn more money, create more units to sell, or serve more customers, you’re Optimizing for Throu
ghput. Making Changes to the system that increase Throughput means your system is performing better i


key: chroma:document
string_value:
n a specific, measurable way. Minimization typically focuses on in-process inputs required for the System 
to operate. If you’re trying to increase your Profit Margin, costs are one of the key inputs. Minimize your co
sts, and your margins will increase. By definition, if you’re trying to Maximize or Minimize more than one t
hing, you’re not Optimizing—you’re making Trade-offs. Many people use the term Optimization to mean “


key: chroma:document
string_value:
making everything better,” but that definition doesn’t help you actually do anything. In practical terms, tryin
g to Optimize for many variables at once doesn’t work—you need to be able to concentrate on a single va
riable for a while, so you can understand how the Changes you make affect the system as a whole. You’r
e trying to find Causation (not Correlation) in your Changes, and hidden Interdependencies can make it dif


key: chroma:document
string_value:
ficult to understand which Changes produced which results. Remember: you can’t reliably Optimize a syst
em’s performance across multiple variables at once. Pick the most important one and focus your efforts a
ccordingly. SHARE THIS CONCEPT: http://book.personalmba.com/optimization/ Refactoring Elegance is 
necessarily unnatural, only achievable at great expense. If you just do something, it won’t be elegant, but i


key: chroma:document
string_value:
f you do it and then see what might be more elegant, and do it again, you might, after an unknown numbe
r of iterations, get something that is very elegant. —ERIK NAGGUM, COMPUTER PROGRAMMER Not al
l changes to a System are designed to affect the System’s output. Sometimes it’s more effective to reengi
neer a process without changing the end result at all. Refactoring is the process of changing a system to i


key: chroma:document
string_value:
mprove efficiency without changing the output of the system. The term comes from computer programmin
g—programmers will spend hours rewriting a program that, if all goes well, does exactly the same thing w
hen they’re finished. What’s the point? The primary benefit of Refactoring isn’t improving the output—it’s 
making the system itself faster or more efficient. By rearranging the processes the system uses to produc


key: chroma:document
string_value:
e the result, it’s possible to make the program run faster or require fewer resources while operating. Refac
toring starts by Deconstructing a process or system, then looking for Patterns. What are the critical proces
ses that absolutely must be done right in order to achieve the desired objective? Do those processes hav
e to be completed in a certain order? What are the current Constraints? What appears to be particularly i


key: chroma:document
string_value:
mportant? Collect as much information about how the system works as you can, then sit with it for a while.
 More often than not, you’ll start to notice things about the system that don’t make sense—things that you’
ve done a certain way because it seemed like a good idea at the time but that aren’t the best way to appro
ach the task now. Once Patterns begin to emerge, you can rearrange the system to group similar process


key: chroma:document
string_value:
es or inputs together. Think of rearranging an assembly line: if you constantly have to stop what you’re doi
ng and travel all the way across the factory to obtain a necessary component, rearranging things so the c
omponent is always close at hand is probably a good idea. The system will still produce the same thing w
hen you’re done, but you’ll have removed a little inefficiency from the system that adds up to significant lo


key: chroma:document
string_value:
sses in productivity. If your Goal is to make the system faster or more efficient, Refactoring is critically imp
ortant. SHARE THIS CONCEPT: http://book.personalmba.com/refactoring/ The Critical Few Typically, cau
ses, inputs, or effort divide into two categories: (1) the majority, that have little impact, and (2) a small min
ority, that have a major, dominant impact. —RICHARD KOCH, AUTHOR OF THE 80/20 PRINCIPLE Vilfr


key: chroma:document
string_value:
edo Pareto was a nineteenth-century economist and sociologist who was very interested in the topic of la
nd ownership and the social distribution of wealth. After collecting and analyzing a great deal of data, Par
eto found a curious Pattern: over 80 percent of the land in Italy was owned by less than 20 percent of the 
population. The Italian economy wasn’t distributed evenly, or in the bell-curve-shaped distribution many p


key: chroma:document
string_value:
eople assumed: wealth was highly concentrated among a relatively small group of individuals. As Pareto s
tudied other areas of life, he consistently found the same Pattern: in Pareto’s garden, for example, 20 per
cent of the pea pods produced 80 percent of the peas. What was going on? In any complex System, a mi
nority of the inputs produce the majority of the output. This Pattern of persistent nonlinearity is now called


key: chroma:document
string_value:
the Pareto principle, or the 80-20 rule. Personally, I prefer to refer to it as the Critical Few. Once you unde
rstand this common Pattern, you’ll find it in many areas of life: � In many businesses, less than 20 percent 
of the customers account for more than 80 percent of annual revenue. � Less than 20 percent of a busines
s’s employees typically do 80 percent or more of the highly valuable work. � You wear less than 20 percent


key: chroma:document
string_value:
of the clothing in your closet over 80 percent of the time. � You spend over 80 percent of your time commu
nicating with less than 20 percent of your personal contacts. The nonlinearity of the Critical Few can often
 be extreme. For example, less than 3 percent of the world’s population is in possession of over 97 perce


key: chroma:document
string_value:
nt of the world’s total wealth. Over time, political power (in both countries and companies) also tends to co
ncentrate in the hands of a few people, which results in a very small group of individuals making decisions
 that directly affect the lives of hundreds of millions of people. Far less than 1 percent of movies ever prod
uced become blockbusters, and less than 0.1 percent of books ever written become best sellers. For best


key: chroma:document
string_value:
results, focus on the critical inputs that produce most of the results you want. In The 4-Hour Workweek, T
imothy Ferriss used the Critical Few to identify his best performing customers. Out of the 120 customers F
erriss was serving, 5 accounted for 95 percent of the revenue. By focusing on those top-performing whole
salers and putting the rest on “autopilot,” Ferriss doubled his monthly revenue and cut his work time from


key: chroma:document
string_value:
eighty hours to fifteen hours a week. The same approach is often useful to weed out results you don’t wan
t. While conducting his business analysis, Ferriss realized that two particular customers accounted for mo
st of his frustration and fire fighting. “Firing” these energy-sucking customers, even though they represent
ed significant sources of volume, liberated his time and energy. As a result, he was able to secure distribu


key: chroma:document
string_value:
tion with three additional high-volume customers that boosted the bottom line without the constant headac
hes. Noncritical inputs are significant Opportunity Costs. If you’re spending most of your time in unproduct
ive meetings, for example, you’re wasting time that could be used to actually get important things done. T
he same goes for noncritical expenses: they represent money that you could be using to far greater effect


key: chroma:document
string_value:
. Find the inputs that produce the outputs you want, then make them the focus of most of your time and e
nergy. Ruthlessly weed out the rest. SHARE THIS CONCEPT: http://book.personalmba.com/critical-few/ 
Diminishing Returns The last 10 percent of performance generates one-third of the cost and two-thirds of 
the problems. —NORMAN R. AUGUSTINE, AEROSPACE EXECUTIVE AND FORMER U.S. UNDER SE
CRETARY OF THE ARMY If you have $10 in your bank account, finding $5 in the pocket of your freshly l


key: chroma:document
string_value:
aundered pants is a cause for celebration. If you have $10,000,000 in your bank account, the same situati
on is a pleasant afterthought. In a similar vein, eating one cookie is great. Eating two cookies is even bett
er. Eating a hundred is actually worse. More is not always better. (The same relationship applies to drinki
ng beer and taking vitamins.) All good things are subject to Diminishing Returns—after a certain point, ha


key: chroma:document
string_value:
ving more of something can actually be detrimental. When I was in marketing at P&G, we spent a lot of ti
me and effort analyzing the results of our advertising. In the first few weeks of running a television comme
rcial, it was easy to see if it was performing as expected. If the commercial was performing well, we’d allo
cate more money to it, but that would only work for so long. No matter how much people liked the commer


key: chroma:document
string_value:
cial, at a certain point it would “wear out,” and the company would no longer produce $1 of revenue for ev
ery dollar the company spent showing that ad. That was the “Point of Diminishing Returns”—if we spent 
more dollars showing the same commercial, the company would start losing money. Far better to spend t
hose funds promoting the product in a different way. It’s always better to spend a little time and energy to


key: chroma:document
string_value:
get the big wins than to do nothing. In I Will Teach You to Be Rich, Ramit Sethi recommends applying wh
at he calls the “85% Solution.” So many people get wrapped up in making the perfect decision that they wi
nd up overwhelming themselves and doing nothing. Focus on doing a few simple things that will produce 
most of the results you’re looking for, then call it a day. Don’t feel like you have to Optimize absolutely eve


key: chroma:document
string_value:
rything to perfection. Optimization and Refactoring are affected by the Critical Few as well—a few small c
hanges can produce enormous results. After you’ve picked the “low-hanging fruit,” further Optimization ca
n cost more in effort than you’ll reap in returns. That’s a good point to stop. Perfectionism is a trap for the 
unwary. Optimize and Refactor up to the point you start experiencing Diminishing Returns, then focus on


key: chroma:document
string_value:
doing something else. SHARE THIS CONCEPT: http://book.personalmba.com/diminishingreturns/ Frictio
n The world is wide, and I will not waste my life in friction when it could be turned into momentum. —FRA
NCES E. WILLARD, EDUCATOR AND SUFFRAGIST WHO SPEARHEADED THE CAMPAIGN TO ADO
PT THE EIGHTEENTH AND NINETEENTH AMENDMENTS TO THE U.S. CONSTITUTION Imagine a ho
ckey puck on the ground in front of you. You’re suitably armed with a hockey stick, and the objective is to


key: chroma:document
string_value:
move the puck from its present location to the goal, which is located one mile away. First, assume the puc
k is sitting in a field of tall grass, which is waving in the wind. Each whack of the hockey stick will move th
e puck only a few feet, since the tall grass robs the puck of energy. At this rate, you’ll have to hit the puck 
thousands of times before you get to the goal, and you’ll exhaust your energy quickly. It’ll take you many f


key: chroma:document
string_value:
rustrating hours to reach the goal. Now let’s assume you mow the field until the grass in front of you is ver
y short. Each time you hit the puck, it goes twenty feet or more—a huge improvement. The puck comes in
 contact with less grass, which means that it travels a longer distance with every strike. You’ll still have to 
work to get the puck to the goal, but you’ll achieve your objective more quickly and with less effort. Finally,


key: chroma:document
string_value:
let’s assume you flood the field with water and freeze it, until the landscape is a smooth plane of ice. Now


key: chroma:document
string_value:
the puck will travel hundreds of feet every time you hit it, because the ice doesn’t rob the puck of energy
— the puck glides along the surface effortlessly. At this rate, you’ll only need to hit the puck a few times b
efore you’ve achieved the objective, and you won’t be tired when you’re done. Friction is any force or proc
ess that removes energy from a System over time. In the presence of Friction, it’s necessary to continue t


key: chroma:document
string_value:
o add energy to a system to keep it moving at the same rate over time. Unless additional energy is added,
 Friction will slow the system down until it comes to a stop. Remove the Friction, and you’ll increase the sy
stem’s efficiency. 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


key: chroma:document
string_value:
in the system. Removing small amounts of Friction consistently over time Accumulates large improvement
s in both quality and efficiency. Introducing Friction intentionally can sometimes encourage people to beh
ave in a certain way or make a particular decision. For example, adding a small amount of Friction to your
 returns process, like requiring the customer to provide a receipt or explain the reason for the return, can


key: chroma:document
string_value:
decrease the number of people who return your product. You don’t want to add too much, since that can 
negatively impact your Reputation (customers get angry if you make them work too hard for a refund), but
 a little Friction in the right place can help prevent frivolous returns. Work on removing Friction from your b
usiness system where appropriate, and you’ll generate better results for less effort. SHARE THIS CONCE


key: chroma:document
string_value:
PT: http://book.personalmba.com/friction/ Automation The first rule of any technology used in a business i
s that automation applied to an efficient operation will magnify the efficiency. The second is that automatio
n applied to an inefficient operation will magnify the inefficiency. —BILL GATES, FOUNDER AND CHAIR
MAN OF MICROSOFT Remove enough Friction, and people may not have to be involved in a process at


key: chroma:document
string_value:
all. Automation refers to a System or process that can operate without human intervention. Factory produ
ction lines, utility networks, and computer programs use Automation to minimize the amount of human inv
olvement necessary to complete a task. The less human effort required to operate the system, the more e
fficient the Automation. Automation is best for well-defined, repetitive tasks. For example, if I had to manu


key: chroma:document
string_value:
ally reply to a letter or e-mail every time someone wanted to read my list of recommended business books
, I’d quickly go insane. Fortunately, I can just put the list up on my Web site—every time someone request
s the list, it’s delivered to them automatically, without any effort on my part. My reading list has been view
ed by hundreds of thousands of readers from around the world, and Automation is what makes it possible


key: chroma:document
string_value:
. 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. SHARE THIS CONCEPT: ht
tp://book.personalmba.com/automation/ The Paradox of Automation One machine can do the work of fifty 
ordinary men. No machine can do the work of one extraordinary man. —ELBERT HUBBARD, AUTHOR 
OF A MESSAGE TO GARCIA Automation can be great, but it has very important drawbacks worth under


key: chroma:document
string_value:
standing. Imagine a fully Automated production line that makes computer processors that sell for $200 pe
r unit. All the human operators have to do is push a button, and the production System starts cranking out
 2,400 finished products per minute. Life is good, right? Yes, with a very important caveat. Imagine that a 
drill used to bore holes in the silicon wafer becomes misaligned and starts drilling microscopic holes throu


key: chroma:document
string_value:
gh the middle of the processor core. Every second the system keeps working, forty chips are ruined. Assu
me each processor costs $20 in raw materials—that means the factory starts losing $800 every second th
e error isn’t found. Every minute the system keeps running, the company loses $48,000. And that’s just th
e direct cost—if you take into account that each processor would sell for $200, the company is losing $52


key: chroma:document
string_value:
8,000 a minute: $48,000 in direct costs and $480,000 in opportunity costs. Sound far-fetched? Consider t
his: In late 2009, Toyota identified a major issue with the accelerator pedal in several popular vehicle mod
els, which were top sellers for many years. The error was Multiplied across every vehicle Toyota made, a
nd the recall cost over five billion dollars. Before the recall, Toyota was considered the best automotive m


key: chroma:document
string_value:
anufacturer in the world. They still are in many respects, but their Reputation and financial situation suffer
ed a major blow. Even the best can fall if costly mistakes are allowed to Multiply. Here’s the Paradox of A
utomation: the more efficient the Automated system, the more crucial the contribution of the human opera
tors of that system. When an error happens, operators need to identify and fix the situation quickly or shut


key: chroma:document
string_value:
the system down—otherwise, the Automated system will continue to Multiply the error. Dr. Lisanne Bainb
ridge, a psychologist at University College London, was one of the first to rigorously study the ramification
s of efficient and reliable systems.1 She was the first to identify and express the “paradox” of Automated s
ystems: efficient Automated systems reduce the need for human effort, but make human involvement eve


key: chroma:document
string_value:
n more critical. Efficient Automation makes humans more important, not less. SHARE THIS CONCEPT: h
ttp://book.personalmba.com/paradox-ofautomation/ The Irony of Automation There will always be a set of


key: chroma:document
string_value:
circumstances that was not expected, that the automation either was not designed to handle or other thin
gs that just cannot be predicted. As system reliability increases, the more difficult it is to detect the error a
nd recover from it. —DR. RAJA PARASURAMAN, PROFESSOR OF PSYCHOLOGY AT GEORGE MAS
ON UNIVERSITY Efficient Automated Systems make skilled human intervention critically important to pre


key: chroma:document
string_value:
vent the Amplification of errors, so it’s best to keep skilled operators on hand at all times, right? That’s eas
ier said than done: businesses typically don’t pay highly skilled employees to sit around in a room all day 
doing nothing, which is what they’ll be doing as long as the system appears to be reliable. Even if they do,
 the operators will spend most of their time being bored out of their skulls. Here’s the Irony of Automation:


key: chroma:document
string_value:
the more reliable the system, the less human operators have to do, so the less they pay Attention to the s
ystem while it’s in operation. Remember the Mackworth Clock and the vigilance studies conducted on Briti
sh radar operators in World War II from our discussion of Novelty? Humans get bored extremely quickly if 
things stay the same, and the more reliable the system, the more things stay the same. Ironically, reliable


key: chroma:document
string_value:
systems tend to dull the operator’s senses, making it very difficult for them to notice when things go wrong
—the moment when their attention is most sorely needed. As a result, the more reliable the system, the lo
wer the likelihood that human operators will notice when something goes wrong—particularly if the error is
 small. Left long enough, small errors can become the “new normal,” which is how a company like Toyota


key: chroma:document
string_value:
ends up with a five-billion-dollar recall. (By the way, don’t make the Attribution Error and think that Toyota’
s engineers were stupid or careless—if you rely on Automated systems, it could easily happen to you.) Th
e best approach to avoid major Automation errors is rigorous, ongoing Sampling and Testing. Remember,
 Normal Accidents can and will occur. If you assume that errors will be made and plan a battery of tests to


key: chroma:document
string_value:
find the most critical errors, you can keep your system operators engaged and increase the probability of 
finding important errors quickly. Keep your Automated system’s operators mentally engaged, and they’ll b
e far more likely to notice when errors inevitably occur. SHARE THIS CONCEPT: http://book.personalmb
a.com/irony-ofautomation/ Standard Operating Procedure (SOP) The measure of success is not whether


key: chroma:document
string_value:
you have a tough problem to deal with, but whether it’s the same problem you had last year. —JOHN FO
STER DULLES, FORMER U.S. SECRETARY OF STATE What do you do when a customer has a compl
aint or asks for a refund? What happens when you run out of toner for the laser printer? Who takes the he
lm if the manager is out of town and there’s an emergency? A Standard Operating Procedure (SOP) is a 
predefined process used to complete a task or resolve a common issue. Business Systems often include


key: chroma:document
string_value:
repetitive tasks, and having a standard process in place can help you spend less time reinventing the whe
el and more time doing productive work. Well-defined Standard Operating Procedures are useful because
 they reduce Friction and minimize Willpower Depletion. Instead of wasting valuable time and energy solvi
ng a problem that has already been solved many times before, a predefined SOP ensures that you spend


key: chroma:document
string_value:
less time thrashing and more time adding value. Standard Operating Procedures are also effective ways 
to bring new employees or partners up to speed quickly. Having a central source of SOPs can help new e
mployees or partners learn how you work far more effectively than informal training. Storing your SOPs in 
some sort of central electronic database is best—it ensures that everyone can instantly reference the mos


key: chroma:document
string_value:
t up-to-date procedures available. Don’t let your Standard Operating Procedures lapse into bureaucracy. 
Remember, the purpose of an SOP is to minimize the amount of time and effort it takes to complete a tas
k or solve a problem effectively. If the SOP requires effort without providing value, it’s Friction. For best re
sults, review your SOPs on a periodic basis—once every two to three months is ideal. If you find outdated


key: chroma:document
string_value:
, wasteful, or unnecessary work in your SOPs, change them. Neither you nor your customers are served 
by unnecessary red tape. Create Standard Operating Procedures for important recurring tasks, and you’ll 
see your productivity skyrocket. SHARE THIS CONCEPT: http://book.personalmba.com/standardoperatin
g-procedures/ Checklist No matter how expert you may be, well-designed checklists can improve outcom
es. —STEVEN LEVITT, COAUTHOR OF FREAKONOMICS Want to make sure an important task is done


key: chroma:document
string_value:
correctly every single time? Create a checklist. A Checklist is an Externalized, predefined Standard Oper
ating Procedure for completing a specific task. Creating a Checklist is enormously valuable for two reason
s. First, Checklisting will help you define a System for a process that hasn’t yet been formalized—once th
e Checklist has been created, it’s easier to see how to improve or Automate the system. Second, using C


key: chroma:document
string_value:
hecklists 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. Pilots have extremely detailed Checklists for takeoff and land
ing for a reason: skipping a step is easy, but can have major consequences for everyone on board. Even 
pilots with decades of flying experience always use Checklists to make sure everything is done right and i


key: chroma:document
string_value:
n the proper sequence. As a result, plane crashes are extremely rare—statistically, it’s safer to fly comme


key: chroma:document
string_value:
rcially than to drive. Even simple processes can benefit from Systemization and the use of Checklists. In 2
001, a study on the effects of Checklisting was conducted by Dr. Peter Pronovost, which was described in
 detail in Atul Gawande’s The Checklist Manifesto and in an article Gawande published in the New Yorker
. 2 The study was conducted in a hospital in Detroit that had the highest rate of ten-day IV line infections (


key: chroma:document
string_value:
a costly and life-threatening condition) in the country. Pronovost’s objective was to determine whether or 
not using Checklists would reduce the rate of infections. Here’s the entirety of the intervention: whenever 
a doctor inserted an IV line, they were instructed to use the following Checklist. Step 1: Wash hands with 
soap. Step 2: Clean the patient’s skin with chlorhexidine antiseptic. Step 3: Put sterile drapes over the enti


key: chroma:document
string_value:
re patient. Step 4: Wear a sterile hat, mask, gloves, and gown. Step 5: Put a sterile dressing over the cath
eter site once the IV line is in. None of these steps is particularly complicated. In fact, many doctors resist
ed the study, since they felt that being forced to use a Checklist for such a simple procedure was insulting
, given their status as highly trained specialists. Even more insulting, the head nurse was empowered to s


key: chroma:document
string_value:
top the doctor if they weren’t using the Checklist—an unusual role reversal that had many doctors fuming.
 Nevertheless, the results of this study over two years were astounding: the ten-day IV line infection rate d
ropped from 11 percent to 0 percent and saved the hospital over $2 million in related costs. As it turns out
, forgetting even basic, commonsense procedures is easy in a busy, stressful environment. Checklisting c


key: chroma:document
string_value:
an 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 m
ajor errors and oversights, as well as prevent Willpower Depletion associated with figuring out how to com
plete the same task over and over again. In addition, once your Checklist is complete you can use it as th


key: chroma:document
string_value:
e basis for full or partial Automation of the system, which will allow you to spend time doing more importa
nt things. For best results, create explicit Checklists for the Five Parts of Your Business, then make sure t
hey’re followed every single time. SHARE THIS CONCEPT: http://book.personalmba.com/checklisting/ C
essation There is nothing so useless as doing efficiently that which should not be done at all. —PETER D


key: chroma:document
string_value:
RUCKER, FATHER OF MODERN MANAGEMENT THEORY Sometimes the best way to improve a Syste
m is to stop doing so much. Cessation is the choice to intentionally stop doing something that’s counterpr
oductive. Due to Absence Blindness, we’re predisposed to attempt to improve a system by doing somethi
ng—it “feels wrong” to do nothing. That doesn’t mean that doing nothing is a bad strategy: it’s often more


key: chroma:document
string_value:
effective. In The One-Straw Revolution, Masanobu Fukuoka wrote about his experiments with natural far
ming, which mostly involved letting nature take its course and intervening as little as possible. While most 
farms were introducing chemicals and machinery into agriculture, Fukuoka was consciously doing nothing
—and reaping the rewards of high yields and ever-increasing soil richness. Here’s what he had to say abo


key: chroma:document
string_value:
ut the virtues of cessation: Human beings with their tampering do something wrong, leave the damage un
repaired, and when the adverse results accumulate, work with all their might to correct them. When the co
rrective actions appear to be successful, they come to view these measures as splendid accomplishment
s. People do this over and over again. It is as if a fool were to stomp on and break the tiles of his roof. The


key: chroma:document
string_value:
n when it starts to rain and the ceiling begins to rot away, he hastily climbs up to mend the damage, rejoici
ng in the end that he has accomplished a miraculous solution. Instead of trying to do too much, Fukuoka 
only did what was absolutely necessary. As a result, his fields were consistently among the most producti
ve in the area. Cessation takes guts. It’s often unpopular or unpalatable to do nothing, even if doing nothi


key: chroma:document
string_value:
ng is actually the right solution. As an example, “pricing bubbles” are often caused by government interve
ntion in certain markets, which has the Second-Order Effect of artificially decreasing the costs of certain a
ctions, leading to rampant speculation. When reality sets in and the bubble “pops,” as it did with dot-com c
ompanies in 2000 and the housing market in 2008, it’s politically unpopular for the government to do nothi


key: chroma:document
string_value:
ng, even though doing something is what caused the situation in the first place. More often than not, the g
overnment acts, which causes another, bigger bubble a few years later. Firing customers, quitting your jo
b, discontinuing a product, or pulling out of a market you can’t succeed in are all tough decisions, but thes
e decisions may put you in a better position in the long run. Doing something is not always the best cours


key: chroma:document
string_value:
e of action. Consider doing nothing instead. SHARE THIS CONCEPT: http://book.personalmba.com/cess
ation/ Resilience Placing a system in a straightjacket of constancy can cause fragility to evolve. —C. S. H
OLLING, ECOLOGIST Turtles aren’t the sexiest creatures in the animal kingdom. They can’t run fast. The
y can’t fly. They don’t have big sharp teeth or claws. They can’t puff themselves up to look menacing or p


key: chroma:document
string_value:
oison their enemies with deadly venom. Compared to the raw power of a tiger or a falcon, turtles are rathe
r lame. What turtles do have is a variety of protective strategies—they can swim quickly, use camouflage, 
snap with their jaws, and if all else fails, retract into their shell and wait for the threat to pass. Creatures el


key: chroma:document
string_value:
sewhere in the animal kingdom are in big trouble if they’re cornered by a predator. Turtles have a fighting 
chance—they win because they’re the armored tanks of nature. They can also eat many different things a
nd go into hibernation when times get tough. That’s why they live so long. Tigers, on the other hand, rely 
on their strength, power, and speed to chase down their prey. When times are good, tigers are the kings o


key: chroma:document
string_value:
f the jungle. If prey becomes scarce or they lose their hunting prowess due to age or injury, death takes th
em quickly and mercilessly—no second chances. What the business world needs is more turtles and few
er tigers. The world is a fundamentally Uncertain place. Unexpected things happen— some good, some b
ad. You never know when Mother Nature, Lady Luck, or a hungry predator will decide that today is not yo


key: chroma:document
string_value:
ur day. Resilience is a massively underrated quality in business. Having the toughness and flexibility to ha
ndle anything life throws at you is a major asset that can save your skin—literally and metaphorically. You
r ability to adjust your strategy and tactics as conditions Change can be the difference between survival a
nd disaster. Resilience is never “optimal” if you evaluate a System solely on Throughput. Flexibility always


key: chroma:document
string_value:
comes at a price. A turtle’s shell is heavy— it could certainly move faster without it. Giving it up, however,
 would leave the turtle vulnerable in the moments when moving a little faster just isn’t fast enough. In an e
ffort to chase a few more short-term dollars, many businesses trade Resilience for short-term results—an
d pay a hefty price. The big investment banks are a classic example. Keeping cash reserves on hand to h


key: chroma:document
string_value:
andle the unexpected has become “ultraconservative” and “inefficient”—it’s become a “best practice” to L
everage the entire company many times over times to squeeze out a few more cents in earnings per shar
e each quarter, leaving the business explosively vulnerable to a very small decline in revenues. Operating
 a business with no cash reserves, no insurance, and high levels of debt may improve your returns for a f


key: chroma:document
string_value:
ew months or quarters, but the moment your revenues decline even by a little or someone decides to sue 
the business, you’re sunk. Leverage works just like rocket fuel—depending on how it’s used, it can propel 
your business to dizzying heights or make the entire operation explode. Unfortunately, many of the advan
ced financial manipulation tactics taught in business schools implicitly trade Resilience for paper returns—


key: chroma:document
string_value:
and once-successful businesses pay the price by going out of business when times get tough. Preparing f
or the unexpected makes you more Resilient. On a personal level, investing in a home emergency/first ai
d kit, car kit, and extra resources like food and water isn’t paranoid—supplies like these are cheap insuran
ce for the intelligent. The same goes for purchasing insurance and building up reserves for unexpected ev


key: chroma:document
string_value:
ents. You may never need them, but you’ll be glad they’re there if you do. HERE’S WHAT MAKES A BUS
INESS RESILIENT: • Low ( preferably zero) outstanding debt • Low overhead, fixed costs, and operating 
expenses • Substantial cash reserves for unexpected contingencies • Multiple independent products/indus
tries/lines of business • Flexible workers/employees who can handle many responsibilities well • No single


key: chroma:document
string_value:
points of failure • Fail-safes/backup systems for all core processes Planning for Resilience as well as perf
ormance is the hallmark of good management. Resilience is certainly not sexy, mostly because the benefi
ts suffer from Absence Blindness. It can, however, save your hide when times get tough. Think less like a 
tiger and more like a turtle, and your business will be able to withstand pretty much anything. SHARE THI


key: chroma:document
string_value:
S CONCEPT: http://book.personalmba.com/resilience/ Fail-safe “Always” and “never” are two words that 
you should always remember never to use. —WENDELL JOHNSON, PSYCHOLOGIST AND PIONEER 
OF SPEECH PATHOLOGY E very Wednesday at noon, a generator kicks on outside of the house I grew 
up in. If all goes well, it’ll run for ten minutes, then turn off automatically until the next testing cycle, silently


key: chroma:document
string_value:
waiting to spring into action again when the power goes out. My father once worked as a firefighter and e
mergency medical technician and has refined “being prepared” into a high art. The generator is designed t
o turn on automatically the moment the primary electricity to the house fails, taking over the house’s electr
ical demands seamlessly. The generator is fed via a propane tank behind the garage, which has enough f


key: chroma:document
string_value:
uel to keep the generator running for a week. If a storm knocks out power to the area, Dad is prepared to 
handle it. Dad’s preparedness rubbed off on me. Now that we live in the mountains of Colorado, we have 
to be prepared for the possibility of our car’s breaking down somewhere remote or cold and we can’t rely 
on AAA (or cell phone coverage) to save us. Kelsey often makes fun of me for stocking our vehicles with


key: chroma:document
string_value:
extra clothing, sleeping bags, snowshoes, and satellite-driven personal locator beacons, but I don’t mind. 
If something happens, we’ll be glad we were prepared—I consider the investment in equipment a cheap, 
durable Insurance policy. A Fail-safe is a backup System designed to prevent or allow recovery from a pri
mary system failure. If the primary system fails in some way, welldesigned Fail-safes can keep the system


key: chroma:document
string_value:
from collapsing unexpectedly. You can find backup systems anywhere consistent performance is critical. 
Actors in high-profile Broadway shows have understudies. If “the show must go on,” it pays to know you’ll 
always have a replacement for any actor who can’t perform. Most shows even have a few “swing” actors


key: chroma:document
string_value:
— performers who are ready to stand in for any role at a moment’s notice. External hard drives back up cr
itical computer data. If the hard drive in your computer crashes, you can still access the data via the back
up drive, so you won’t lose everything. Some businesses even take the precaution of storing backup drive
s off-site in case of fire or natural disaster. Airplanes have systems that sense a failure in cabin pressure,


key: chroma:document
string_value:
automatically deploying face masks attached to an oxygen tank. If the airplane’s pressurized cabin fails fo
r some reason, the passengers won’t lose consciousness—a very good thing indeed. Fail-safes are not ef
ficient in the sense that you’re investing time and resources in a system you hope you’ll never use. Backu
p systems and Insurance, from one perspective, can be seen as a waste of money—why spend valuable


key: chroma:document
string_value:
resources on something you hope you’ll never need? Here’s why: by the time you need a Fail-safe, it’s to
o late to develop one. In order to be effective, Fail-safes must be developed before you need them. If you 
wait to develop backup systems until you need them, it’s too late to make a difference. Paying for homeo
wners’ Insurance can feel like a waste of money until your house burns down. If you wait to buy Insurance


key: chroma:document
string_value:
until something bad happens, it’s already too late. Try to separate your Fail-safe and primary system as 
much as possible. One of the reasons people rent safe deposit boxes in banks is to protect certain items f
rom loss in the event of fire or theft—if something happens to the house, the items in the safe deposit box
 will still be okay. The practice of backing up data to an off-site data center serves the same purpose: if so


key: chroma:document
string_value:
mething happens to the business’s primary computers, the data is still safe in another location. Fail-safes 
that are highly Interdependent with the primary system can actually introduce additional risks. One of the 
worst


