A Novel Metric To Capture Value In Healthcare

David Kashmer (@DavidKashmer)

You’ve probably heard the catchphrase “volume to value” to describe the current transition in healthcare.  It’s based on the idea that healthcare volume of services should no longer be the focus when it comes to reimbursement and performance.  Instead of being reimbursed a fee per service episode (volume of care), healthcare is transitioning toward reimbursement with a focus on value provided by the care given.  The Department of Health and Human Services (HHS) has recently called for 50% or more of payments to health systems to be value-based by 2018.

Here’s a recent book I completed on just that topic:  Volume to Value.  Do you know what’s not in that book, by the way?  One clear metric on how exactly to measure value across services!  That matters because, after all

If you can’t measure it, you can’t manage it. –Peter Drucker

An entire book on value in healthcare and not one metric which points right to it!  Why not?  (By the way, some aren’t sure that Peter Drucker actually said that.)

Here’s why not:  in healthcare, we don’t yet agree on what “value” means.  For example, look here.  Yeesh, that’s a lot of different definitions of value.  We can talk about ways to improve value by decreasing cost of care and increasing value, but we don’t have one clear metric on value (in part) because we don’t yet agree on a definition of what value is.

In this entry, I’ll share a straightforward definition of value in healthcare and a straightforward metric to measure that value across services.  Like all entries, this one is open for your discussion and consideration.  I’m looking for feedback on it.  An OVID, Google, and Pubmed search revealed nothing similar to the metric I propose beneath.

First, let’s start with a definition of value.  Here’s a classic, arguably the classic, from Michael Porter (citation here).

Value is “defined as the health outcomes per dollar spent.”

Ok so there are several issues that prevent us from easily applying this definition in healthcare.  Let’s talk about some of the barriers to making something measurable out of the definition.  Here are some now:

(1) Remarkably, we often don’t know how much (exactly) everything costs in healthcare.  Amazing, yes, but nonetheless true.  With rare exception, most hospitals do not know exactly how much it costs to perform a hip replacement and perform the after-care in the hospital for the patient.  The time spent by FTE employees, the equipment used, all of it…nope, they don’t know.  There are, of course, exceptions to this.  I know of at least one health system that knows how much it costs to perform a hip replacement down to the number and amount of gauze used in the OR.  Amazing, but true.

(2) We don’t have a standardized way for assessing health outcomes.  There are some attempts at this, such as QALYs, but one of the fundamental problems is:  how do you express quality in situations where the outcome you’re looking for is different than quality & quantity of life?  The QALY measures outcome, in part, in years of life, but how does that make sense for acute diseases like necrotizing soft tissue infections that are very acute (often in patients who won’t be alive many more years whether the disease is addressed or not), or other items to improve like days on the ventilator?  It is VERY difficult to come up with a standard to demonstrate outcomes–especially across service lines.

(3) The entity that pays is not usually the person receiving the care.  This is a huge problem when it comes to measuring value.  To illustrate the point:  imagine America’s Best Hospital (ABH) where every patient has the best outcome possible.

No matter what patient with what condition comes to the ABH, they will have the BEST outcome possible.  By every outcome metric, it’s the best!  It even spends little to nothing (compared to most centers) to achieve these incredible outcomes.  One catch:  the staff at ABH is so busy that they just never write anything down.  ABH, of course, would likely not be in business for long.  Why?  Despite these incredible outcomes for patients, ABH would NEVER be re-imbursed.  This thought experiment shows that valuable care must somehow include not just the attention to patients (the Voice of the Patient or Voice of the Customer in Lean & Six Sigma parlance), but also to the necessary mechanics required to be reimbursed by the third party payors.  I’m not saying whether it’s a good or bad thing…only that it simply is.

So, where those are some of the barriers to creating a good value metric for healthcare, let’s discuss how one might look.  What would be necessary to measure value across different services in healthcare?  A useful value metric would

(1) Capture how well the system it is applied to is working.  It would demonstrate the variation in that system.  In order to determine “how well” the system is working, it would probably need to incorporate the Voice of the Customer or Voice of the Patient.  The VOP/VOC often is the upper or lower specification limit for the system as my Lean Six Sigma and other quality improvement colleagues know.  The ability to capture this performance would be key to represent the “health outcomes” portion of the definition.

(2) Be applicable across different service lines and perhaps even different hospitals.  This requirement is very important for a useful metric.  Can we create something that captures outcomes as disparate as time spent waiting in the ER and something like patients who have NOT had a colonoscopy (but should have)?

(3) Incorporate cost as an element.  This item, also, is required for a useful metric.  How can we incorporate cost if, as said earlier, most health systems can’t tell you exactly how much something costs?

With that, let’s discuss the proposed metric called the “Healthcare Value Process Index”:

Healthcare Value Process Index = (100) Cpk / COPQ

where Cpk = the Cpk value for the system being considered, COPQ is the Cost of Poor Quality for that same system in thousands of dollars, and 100 is an arbitrary constant.  (You’ll see why that 100 is in there under the example later on.)

Yup, that’s it.  Take a minute  with me to discover the use of this new value metric.

First, Cpk is well-known in quality circles as a representation of how capable a system is at delivering  a specified output long term.  It gives a LOT of useful information in a tight package.  The Cpk, in one number, describes the number of defects a process is creating.  It incorporates the element of the Voice of the Patient (sometimes called the Voice of the Customer [VOC] as described earlier) and uses that important element to define what values in the system are acceptable and which are not.  In essence, the Cpk tells us, clearly, how the system is performing versus specification limits set by the VOC.  Of course, we could use sigma levels to represent the same concepts.

Weaknesses?  Yes.  For example, some systems follow non-normal data distributions.  Box-Cox transformations or other tools could be used in those circumstances.  So, for each Healthcare Value Process Index, it would make sense to specify where the VOC came from.  Is it a patient-defined endpoint or a third party payor one?

That’s it.  Not a lot of mess or fuss.  That’s because when you say the Cpk is some number, we have a sense of the variation in the process compared to the specification limits of the process.  We know how whatever process you are talking about is performing, from systems as different as time spent peeling bananas to others like time spent flying on a plane.  Again, healthcare colleagues, here’s the bottom line:  there’s a named measure for how well a system represented by continuous data (eg time, length, etc.) is performing.  This system works for continuous data endpoints of all sorts.  Let’s use what’s out there & not re-invent the wheel!

(By the way, wondering why I didn’t suggest the Cp or Ppk?  Look here & here and have confidence you are way beyond the level most of us in healthcare are with process centering.  Have a look at those links and pass along some comments on why you think one of those other measures would be better!)

Ok, and now for the denominator of the Healthcare Value Process Index:  the Cost of Poor Quality.  Remember how I said earlier that health systems often don’t know exactly how much services cost?  They are often much more able to tell when costs decrease or something changes.  In fact, the COPQ captures the Cost of Poor Quality very well according to four buckets.  It’s often used in Lean Six Sigma and other quality improvement systems.  With a P&L statement, and some time with the Finance team, the amount the healthcare system is spending on a certain system can usually be sorted out.  For more info on the COPQ and 4 buckets, take a look at this article for the Healthcare Financial Management Association.  The COPQ is much easier to get at than trying to calculate the cost of an entire system.  When the COPQ is high, there’s lots of waste as represented by cost.  When low, it means there is little waste as quantified by cost to achieve whichever outcome you’re looking at.

So, this metric checks all the boxes described earlier for exactly what a good metric for healthcare value would look like.  It is applicable across service lines, captures how well the system is working, and represents the cost of the care that’s being rendered in that system.  Let’s do an example.

Pretend you’re looking at a sample of the times that patients wait in the ER waiting room.  The Voice of the Customer says that patients, no matter how not-sick they may seem, shouldn’t have to wait any more than two hours in the waiting room.

Of course, it’s just an example.  That upper specification limit for wait time could have been anything that the Voice of the Customer said it was.  And, by the way, who is the Voice of the Customer that determined that upper spec limit?  It could be a regulatory agency, hospital policy, or even the director of the ER.  Maybe you sent out a patient survey and the patients said no one should ever have to wait more than two hours!)

When you look at the data you collected, you find that 200 patients came through the ER waiting room in the time period studied.  That means 2 defects per 200 opportunities, which is a DPMO (Defects Per Million Opportunities) of 10,000.  Let’s look at the Cpk level associated with that level of defect:

Table located at https://ssbblky.wordpress.com/2009/11/19/is-3-sigma-quality-level-good-enough/

Ok, that’s a Cpk of approximately 1.3 as per the table above.  Now what about the costs?

We look at each of the four buckets associated with the Cost of Poor Quality.  (Remember those four buckets?) First, the surveillance bucket:  an FTE takes 10 minutes of their time every shift to check how long people have been waiting in the waiting room.  (In real life, there are probably more surveillance costs than this.) Ok, so those are the costs required to check in on the system because of its level of function.

What about the second bucket, the cost of internal failures?  That bucket includes all of the costs associated with issues that arise in the system but do not make it to the patient.  In this example, it would be the costs attributed to problems with the amount of time a person is in the waiting room that don’t cause the patient any problems.  For example, were there any events when one staff member from the waiting room had to walk back to the main ED because the phone didn’t work and so they didn’t know if it was time to send another patient back?  Did the software crash and require IT to help repair it?  These are problems with the system which may not have made it to the patient and yet did have legitimate costs.

The third bucket, often the most visible and high-profile, includes the costs associated with defects that make it to the patient.  Did someone with chest pain somehow wind up waiting in the waiting room for too long, and require more care than they would have otherwise?  Did someone wait more than the upper spec limit and then the system incurred some cost as a result?  Those costs are waste and, of course, are due to external failure of waiting too long.

The last bucket, my favorite, is the costs of prevention.  As you’ve probably learned before, this is the only portion of the COPQ that generates a positive Return On Investment (ROI) because money spent on prevention usually goes very far toward preventing many more costs downstream.  In this example, if the health system spent money on preventing defects (eg some new computer system or process that freed up the ED to get patients out of the waiting room faster) that investment would still count in the COPQ and would be a cost of prevention.  Yes, if there were no defects there would be no need to spend money on preventative measures; however, again, that does not mean funds spent on prevention are a bad idea!

After all of that time with the four buckets and the P&L, the total COPQ is discovered to be $325,000.  Yes, that’s a very typical size for many quality improvement projects in healthcare.

Now, to calculate the Healthcare Value Process Index, we take the system’s performance (Cpk of 1.3), multiple it by 100, and divide by 325.  We see a Healthcare Value Process Index of 0.4.  We carefully remember that the upper spec limit was 120 and came from the VOC who we list when we report it out.  The 100 is there to make the results easier to remember.  It simply changes the size of the typical answer we get to something that’s easier to remember.

We would report this Healthcare Value Process Index as “Healthcare Value Process Index of 0.4 with VOC of 120 min from state regulation” or whomever (whichever VOC) gave us the specification limits to calculate the Cpk.  Doing that allows us to compare a Healthcare Value Process Index from institution to institution, or to know when they should NOT be compared.  It keeps it apples to apples!

Now imagine the same system performing worse:  a Cpk of 0.7.  It even costs more, with a COPQ of 425,000.  The Healthcare Value Process Index (HVPI)?  That’s 0.0165.  Easy to see it’s bad!

How about a great system for getting patient screening colonoscopies in less that a certain amount of time or age?  It performs really well with a Cpk of 1.9 (wow!) and has a COPQ of $200,000.  It’s HVPI?  That’s 0.95.  Much better than those other systems!

Perhaps even more useful than comparing systems with the HVPI is tracking the HVPI for a service process.  After all, no matter what costs were initially assigned to a service process, watching them change over time with improvements (or worsening of the costs) would likely prove more valuable.  If the Cpk improves and costs go down, expect a higher HVPI next time you check the system.

At the end of the day, the HVPI is a simple, intuitive, straightforward measure to track value across a spectrum of healthcare services.  The HVPI helps clarify when value can (and can not) be compared across services.  Calculating the HVPI requires knowledge of system capability measures and clarity in assigning COPQ.  Regardless of initial values for a given system and different ways in which costs may be assigned, trending HVPI may be more valuable to track the trend of value for a given system.

Questions?  Thoughts?  Hate the arbitrary 100 constant?  Leave your thoughts in the comments and let’s discuss.

Obamacare boasts largest day ever Thursday on HealthCare.gov

@DavidKashmer (LinkedIn profile here.)

 

President Obama announced Friday that more individuals signed up for insurance on HealthCare.gov on Thursday (12/15) than on any single day since the launch of the low cost Affordable Care Act exchanges three years ago.

Greater than 670,000 people signed up for coverage ahead of the Dec. 15 cut-off date for Jan. 1 insurance.

The traffic congestion caused the Centers for Medicare and Medicaid (CMS) to announce late Thursday that a new cut-off date for enrollment would be Dec. 19. HealthCare.gov handles enrollment for 38 states. Time limits for state exchanges vary, however several now permit enrollment for Jan. 1 insurance for a number of extra days.

Signups rose regularly this passed week. On Monday, greater than 325,000 citizens selected plans on HealthCare.gov. On Tuesday, more than 380,000 Americans selected plans on HealthCare.gov, marking two of the largest traffic days in HealthCare.gov history.

How The COPQ Helps Your Healthcare Quality Project

Click here for video presentation of content beneath:

Click here for audio presentation of entry:

 

Challenging To Demonstrate The Business Case For Your Healthcare Quality Project

One of the biggest challenges with quality improvement projects is clearly demonstrating the business case that drives them.  It can be very useful to generate an estimated amount of costs recovered by improving quality.  One of the useful tools in Lean and Six Sigma to achieve this is entitled ‘The cost of poor quality’ or COPQ.  Here we will discuss the cost of poor quality and some ways you can use it in your next quality improvement project.

 

Use The COPQ To Make The Case, And Here’s Why

The COPQ helps form a portion of the business case for the quality improvement project you are performing.  Usually, the COPQ is positioned prominently in the project charter.  It may sit after the problem statement or in another location depending on the template you are using.  Of the many tools of Six Sigma, most black belts do employ a project charter as part of their DMAIC project.  For those of you who are new to Six Sigma, DMAIC is the acronym for the steps in a Six Sigma project.  It includes: Define, Measure, Analysis, Improve, and Control.  Importantly, we use these steps routinely and each step has a different objective we must achieve.  These objectives are often called tollgates.  Things must happen in each of these steps before progressing to the next step.  One of the tools we can use, and again most project leaders do use this tool routinely, is called the project charter.

 

The project charter defines the scope for the problem.  Importantly, it defines the different stakeholders who will participate, and the time line for completion of the project.  It fulfills other important roles too as it clearly lays out the specific problem to be addressed.  Here is where the COPQ comes in:  we utilize the COPQ to give managers, stakeholders, and financial professionals in the organization an estimate of the costs associated with current levels of performance.

 

The Four Buckets That Compose The COPQ

The COPQ is composed of four ‘buckets’.  These are:  the cost of internal failures, the cost of external failures, the cost of surveillance, and the cost associated with prevention of defects.  Let’s consider each of these as we describe how to determine the Costs of Poor Quality.  The cost of internal failures are those costs associated with problems with the system that do not make it to the customer or end user.  In healthcare this question of who is the customer can be particularly tricky.  For example, do we consider the customer as the patient or as the third party payer?  The reason why this is challenging is that, although we deliver care to the patient, the third party payer is the one who actually pays for the value added.  This can make it very challenging to establish the Costs of Poor Quality for internal and other failures.  I believe, personally, this is one of the sources that puts Lean, Six Sigma, and other business initiatives into certain challenges when we work in the healthcare arena.  Who, exactly, is the customer?  Whoever we regard as the customer, internal failures, again, are those issues that do not make it to the patient, third party payer, or eventual recipient of the output of the process.

 

External failures, by contrast, are those issues and defects that do make it to the customer of the system. There are often more egregious.  These may be less numerous than internal failures but are often visible, important challenges.

 

Next is the cost of surveillance.  These are the costs associated with things like intermittent inspections from state accrediting bodies or similar costs that we incur perhaps more frequently because of poor quality.  Perhaps our state regulatory body has to come back yearly instead of every three years because of our quality issues.  This incurs increased costs.

 

The final bucket is the cost of prevention.  Costs associated with prevention are other important components of the cost of poor quality.  The costs associated with prevention are the only expenditures on which we have a Return On Investment (ROI).  Prevention is perhaps the most important element of the COPQ because money we spend on prevention actually translates into, often, that return on investment.

 

A Transparent Finance Department Gives Us The Numbers

In order to construct the COPQ we need to have ties to the financial part of our organization.  This is where transparency in the organization is key.  It can be very challenging to get the numbers we require in some organizations and in others it can be very straightforward.  Arming the team with good financial data can help make a stronger case for quality improvement.  It is key, therefore, that each project have a financial stakeholder so that the quality improvement effort never strays too far from a clear idea of the costs associated with the project and the expectation of costs recovered.  Interestingly, in the Villanova University Lean Six Sigma healthcare courses, a common statistic cited is that each Lean and Six Sigma project recovers a median value of approximately $250000.  This is a routine amount of recovery of COPQ even for healthcare projects and beyond.  It can be very striking just how much good quality translates into cost cutting.  In fact, I found that decreasing the variance in systems, outliers and bad outcomes has a substantial impact on costs in just the manner we described.

 

Conclusion:  COPQ Is Key For Your Healthcare Quality Project

In conclusion, the Cost of Poor Quality is useful construct for your next quality improvement project because it clearly describes exactly what the financial stakeholders can expect to recover from the expenditure of time and effort.  The COPQ is featured prominently in the project charter used by many project leaders in the DMAIC process.  To establish the COPQ we obtain financial data from our colleagues in finance who are part of our project.  We then review the costs statements with them and earmark certain costs as costs of internal failure, external failure, surveillance or costs associated with prevention.  We then use these to determine the staged cost of poor quality.  Additionally, we recognize that the COPQ is often a significant figure on the order of 200-300 thousand dollars for many healthcare-related projects.

 

We hope that use of the COPQ for your next quality improvement project helps you garner support and have a successful project outcome.  Remember, prevention is the only category of expenditures in the COPQ that has a positive return on investment.

 

Thought, questions, or discussion points about the COPQ?  Let us know your thoughts beneath.

Risk Is The Standard Deviation of Returns

 

In this entry we will review some of the different products in which you can invest.  We will explore the concept of risk, some historic data on risk vs. return, and provide an examination of each of these for us as personal investors in the market.

 

The concept of risk is a challenging one and yet it is the focus of much of what we decide with respect to personal investing.  One interesting way to measure how much risk you are willing to endure, aka your risk tolerance, is to ask yourself how much you would bet on the flip of a coin.  This gives you an idea of your risk threshold.  Although that simple experiment is a classic way to measure risk tolerance,  it is by no means the most complex or comprehensive.

 

Regardless of how you measure your personal risk threshold, remember:  risk and reward should be closely associated in your mind when it comes to personal investing.  In fact, risk and reward are sort of the flip sides of the same coin.  Risk is what we endure for certain rewards.  Therefore, the reward from a certain investment must be commensurate with the risk we take in putting our money into a certain stock, mutual fund, or other investment vehicle.  Here, we will describe some of the different ways to understand how much risk is inherent in an investment versus its return.  We will examine some classic equity backed securities such as stocks, mutual funds, bonds, and real estate.

 

One way to conceptualise risk is as the standard deviation of returns.  That is, the risk inherent in, for example, a stock can be considered as its standard deviation of returns where returns are plotted as a histogram.  Therefore, the wider the standard deviation of the amount of return on your money, the riskier the investment. Here, we will cite several distributions for risk from a standard text.

 

One of the most popular texts that gives us the concept of risk versus return is Burton Malkiel’s A Random Walk Down Wall Street. Page 185 gives us one of the most useful representations of risk inherent in different types of investment opportunities.  For one, consider the distribution of returns from the stock market.  The historic standard deviation of returns from the stock market is approximately 20% as described by Malkiel’s text.  See Figure 1.  Therefore, of the various opportunities we will discuss, investing in the stock market is one of the most ‘risky’.

 

randomwalkjpg
Figure 1: Histograms with standard deviations of various investment products from Malkiel’s book: A Random Walk Down Wallstreet

 

This is because, although there is great potential for upside, there is also routine potential for downside. As you probably know, plus or minus one standard deviation on either side of the central tendency of the bell curve contains 66% of values.  Therefore, based on historic data, 66% of the time we invest in the stock market our gain or loss will be between plus 20% or minus 20% with an “average” return of around 11%.  Again, the more narrow the standard deviation in a system the less risk inherent in that system. 

 

Consider, next, the bond market.  Corporate and municipal bonds are similar in their return.  Corporate and municipal bonds returns approximately 3-4% per year.  (See Figure 1.) There is a much lower standard deviation of returns, historically, in the bond market. Please notice, however, that on an after-tax basis, the corporate and municipal bonds basically give the same return for the same amount of money.  Therefore, corporate bonds are thought to be slightly more risky than municipal bonds in that an individual corporation may default (bankruptcy) and give you no money back.  Therefore, US municipal bonds are felt to be more conservative investment option (the government is unlikely to go bankrupt) for those interested in investing in bonds.

 

Real estate is another investment option.  The historical return of the real estate market is approximately 2%.  Clearly, just as with stocks & bonds, the real estate market we are talking about is the real estate market as a whole from its inception until now.  There are several things which are not well represented by taking such a global view of the market.  For one, different geographic areas in the country, such as vacation destinations like Hawaii or Florida, may perform better than the market as a whole.  Also, isolated periods of time may buck the trend and outperform history.  The housing bubble, for example, was able to generate significant returns for some participants in the market.  However, in general, real estate is felt to be a secure investment and returns about approximately 2% to personal investors.  Keep in mind, inflation is often higher than this 2% return; however, the real estate can be enjoyed, will generally increase in value with time, and may, depending on the market, generate a nice rental return.  Also, renting a location maybe able to generate some nice passive income.

 

Did you notice how we considered the real estate market as a whole and then focused on how individual segments with in (as well as isolated periods in its history) may differ? Similarly, the stock market data we cite above is for the market as a whole since inception.  There are important limitations to the model we describe.  For one, it does not highlight crash years such as the great stock market crash or the several significant recessions we have had.  Therefore, some cite that the market has a greater standard deviation of returns than 20%.

 

Now we have a concept of risk as the standard deviation of returns on an investment.  Some other questions include “How we can measure risk for individual stocks in the market?”  There are several nice pieces of data I would like to share which are available for you and are publicly available on Yahoo finance as well as other public finance search engines.

 

One piece of data you can use to decide whether to invest in an individual stock is the beta value.  The beta is obtained by plotting the stock’s increase or decrease (on the y axis) versus the market’s increase or decrease (x-axis).  That is, a standard stock market index (such as the Dow Jones Industrial average or S&P 500) will be plotted and the stock’s performance will be plotted against this. This XY plot indicates that when the market as a whole moves a certain way the stock moves a certain way.  Next, a regression line model is used so as to generate the equation of a regression line.  The slope of the regression line is the beta value.

 

cohenjpg
Figure 2: Beta is the slope of the regression line that associates S&P 500 return with an individual stock’s return. From Neil Cohen, DBA CFA in Financial Management MBAD 233-EM1, George Washington University Spring 2010

 

In other words, the beta value is the amount the stock described moves relative to the market as a whole.  (See Figure 2.) Thus, stock with a beta of positive 1 goes up one point when the market increases 1 point.  (It also goes down one point when the market goes down one point.) Therefore, you get a sense of how risky the stock you may like is compared to the market as a whole.  Stocks that have a beta of 2 may increase by 2 when the market goes up and also are more likely to decrease by 2 when the market goes down.  Again, recall this is from a linear regression model.  Therefore, it should not be said that every day the market goes up one point your stock with beta of 2 will go up 2 points.  This is just a general tendency over time.  The beta gives you a sense of how significantly the stock varies when the market varies.  This gives you a concept of risky your stock investment is.

 

Another useful number is the alpha.  The alpha is a measurement associated with mutual funds.  The alpha indicates the amount of return you can obtain from a mutual fund in excess of the risk inherent in the portfolio that makes up the mutual fund.  (Awesome right?  Who wouldn’t want a return higher than the risk involved!) Now you know why the well-known blog SeekingAlpha.com is called that; who wouldn’t want to seek a return in excess of the involved risk?

 

As you probably know, a mutual fund is a group of stocks that are maintained in a portfolio by a given company.  You can purchase shares of the fund of stocks.  It is important to know the managerial fees associated with your mutual fund.  Remember, managers maybe paid to help change the stocks which make up the mutual fund so as to trade in stocks that are performing well and decrease stocks that are performing less effectively.  There are some mutual funds which are indexed to the market as a whole.  These funds attempt to reproduce an investment in the market as a whole and reflect the market increases and decreases by being composed of a broad selection of stocks felt to represent the market as a whole.  These allow you to invest in the whole market.

 

One of the other newer investment vehicles are the derivatives.  The derivatives are so called because they derive from the typical products with which you are now more familiar.  One of the derivative markets is the options market.  Options allow you to purchase or sell a contract that allows someone to buy or sell a stock in the future at a given price.  I will not discuss much about the derivatives market here except to say that it seems as if there is a wider standard deviation of returns for options in general. However there are multiple risk mitigation strategies that allow for some very interesting opportunities in the options market.

 

In conclusion, we have discussed a definition of risk as it relates to personal investment:  risk may be thought of as the standard deviation of returns on an investment product.  We described one classic test to allow you to get a sense of your risk threshold.  We then highlighted the standard deviation of returns across multiple products including stocks, bonds, and real estate.  Good luck in your personal investment decisions and your attempts to beat inflation.  Remember, a key focus as a personal investor is on the return at the end of the day AFTER taxes, any fees (such as those a mutual fund charges for managing the fund) and inflation.

 

Please note:  None of the above constitutes investment advice–professional or otherwise.  I’m sharing just a bit of how risk may be conceptualized in complex investment decisions so that you can make your own decision based on your unique situation.

 

Questions, comments, or feedback?  Feel free to add your thoughts and comments beneath.

 

Shark Tank: The Tank Can Only Do So Much

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Shark Tank is a very entertaining and popular show.  Each week, more than four million viewers tune in to see great ideas, strong pitches and newly minted potential millionaires.  Just as entertaining as the deals that go well are the ones that go poorly.  Here we explore the nature of deals on Shark Tank, the ups and downs of valuation, and the challenges in exposing venture capital type investment decisions to a broad audience.  After all, in the show’s need to reach a popular audience, it can’t show the more technical side of venture capital (VC) decision making.

 

First, let me share that I really enjoy Shark Tank.  I enjoy each of the venture capitalists on it.  Exposing a broad audience to the thought processes involved via a show about entrepreneurs, startups, and venture capitalists / investors is wonderful.  Yet, there are some challenges with exposing the process to a broad audience and that’s our focus here.

 

One of the givens, here, is that drama of the tank needed to be amped up to make it exciting for America.  Thus the dramatic music and monikers the VC team attach themselves including, for example, “Mr Wonderful”. I do not lament this at all.  It makes for excellent TV, drama, and adds to the appeal of the show.  Kevin O’Leary’s “Mr. Wonderful” handle is particularly funny and shows clear wit:  my bet is that, if Kevin is interviewed years from now about the show, he would be the first to explain this was sort of a tongue-and-cheek name with which he dubbed himself to add a little spice to the show.  It makes things a little over the top in a positive way.  Indeed, the juxtaposition of the title “Mr. Wonderful” against some deals which are really not so wonderful is always entertaining.  Of course, there are those moments where the deals Mr. O’Leary makes with business owners truly do make him their Mr. Wonderful–and, after all, the business owners wouldn’t be there if they didn’t need a Mr. Wonderful for something.

 

Besides the entertaining names and amp-ed up drama, there are some challenges in the show that we should explore as they relate to business model innovation, valuation and liquidation preferences.  Liquidation preferences you say? These are never even mentioned on the show.  This is one of the challenges in bringing Shark Tank to a broader audience. Each time Mr. O’Leary (ok, yes, I enjoy his disciplined investor role) asks:  “But how will I get my money back?”, he is boiling down a key part of portion of VC deals to a focus on how money is returned to investors.  In VC deals, this issue is much more complex than what can be covered in the brief, digestible portions required by the Shark Tank format.

 

Real-life VC deals typically include a term sheet, where the entrepreneur team is presented with the terms of the deal with which the venture capitalists will invest.  (Of course, many real life VC deals involve much more, such as a series of meetings rather than a less than five minute interaction on which the sharks base their investment decisions.) One of the most poorly understood elements of the term sheet is liquidation preferences.  It would be very difficult to put liquidation preferences on TV and make these sexy yet they are key in most deals.  Unfortunately, liquidation preferences are some of the most important terms on the venture capital sheet and can often lead to misalignment of the investor / entrepreneur team on down the line.  Let me explain.

 

A typical liquidation preference sheet will include terms such as a 3X, 1X, participation / no participation and no cap / cap feature.  Let’s take each one of these and explain what they can cause later in terms of investor-entrepreneur alignment.  First, when we invest in a new company we join the ‘stack.’  The stack is the order in which teams are paid back for their investment.  The most recent investors are at the top of the stack of cards and are paid back first.  Then, at the bottom of the stack, are the early stage  / series A / seed funding venture capitalists.  An exit event, most commonly selling the company to a buyer, is the time at which the buyout will occur and the investors have the ability to be repaid with their winnings.  The term sheet specifies on what terms and in what manner the investor will make back their money (and then some we hope–otherwise why assume the risk of the investment).  First, let’s focus on the ‘3X’ or ‘1X’ situations.  The investor will obtain either three times, thus the “3X” or one time (“1X”), or somewhere inbetween, amount for their initial investment.  So, if I give $5000 to a startup and there are no other investors later, and I have a 3X term I will expect to be returned three times my initial amount or $15000 during an exit event.  However, there may also be a cap.  A cap means I can receive no more than a certain amount. So, although this wouldn’t make sense for almost any deal, if I have a $10000 cap, and I have a 3X initial investment on $5000 I could only be repaid $10000 total at the end of the day.  Such deals are not done routinely.  We only use this to highlight the nature of a cap.  The cap says:  “Investors you can only obtain this much money in return total for your initial investment.”

 

More interesting is the concept of participation. That means that an investor will receive their 3X or 1X, sometimes called multiple, of investment return and then will go on to participate in the buyout of the shares (of which they own some) at the price stipulated by the buyer company.  So, in the example given above, the investor would receive $15000 plus the value of their stock as they participate in the stock buyout up to whatever cap exists if a cap is in the terms sheet.  No participation means they would receive nothing for that stock.  Keep in mind the investors are paid before the startup team in all scenarios. So, the startup team and the investor can easily become misaligned.

 

If you do the calculations for various sale prices for companies with various liquidation preferences in the term sheet, sometimes the amount the investor makes on the deal will not vary over a certain number of sale prices.  What I mean is that if a company sells between $1 to $5 million the venture capitalist may have the exact same return on the investment depending on their liquidation preferences per the term sheet.  Ut-oh.  Misalignment!  Where the startup team may want to hold out for a 5 million dollar exit (remember the startup team is paid last so they likely wish to hold out for more), the VC group may be content to sell at a much lower price.  After all, the VC makes the same amount at a 2-5 million dollar sale price depending on the liquidation preferences.

 

Do some math with the 3X, 1X, participation and cap versus no cap situation and you will see this to be true.  Again, this may cause misalignment when it comes time to sell a company.  We can’t highlight this enough:  the investors may wish to sell at a much lower price than the startup team because they will obtain the same amount in return regardless of the sale price. The investor team may want to hold out for more reimbursement for their company and yet the investors may wish to sell.  Clearly, pardon our repetition here, liquidation preferences are a source of misalignment.

 

So, on Shark Tank, liquidation preferences are never mentioned.  We can’t blame them!  How could that sort of explanation come across on TV, when many startup business owners are not acquainted with the liquidation preference issues?  In the tank, companies are often valued by saying 100% of the company’s ownership shares are equivalent to their gross sales receipts.  The shark will take that amount of ownership equity for an investment equal to the share price as determined by that calculation, and sometimes the shark also wants a certain amount of royalty for each object sold in perpetuity.  This is very challenging.   The shark becomes a part owner of the company and sometimes even takes majority interest in the company.  Again, usually the liquidation terms will be clear on the initial term sheet.  However, on Shark Tank, liquidation preferences are never mentioned.  Do the Sharks, some of whom are very experienced venture capitalists, expect to simply be reimbursed as if they were a routine owner when an exit strategy is executed? Or do they expect the company to continue ad infinitum and they can take profit as any owner would? It is very difficult to tell and again liquidation preferences would not play well on TV.  Again, in fact, liquidation preferences are often poorly understood by the entrepreneurs who accept investment deals. This is one of the more challenging aspects of venture capital and entrepreneur interaction.  It’s no surprise that some Shark Tank deals despite a handshake on TV, break down in the due diligence process or later once the show is over and the lights are off.  There is a lot more to a deal than how things look on the tank on TV, and that’s ok.

 

Let’s return to valuation:  one of the other challenging aspects of Shark Tank is the valuation.  Valuations are done very strictly and are often based on gross revenue.  Sharks often incredulously ask owners of the company how they can value a company so highly when it has done so little in sales.  For now please recognize that this is a very conservative, pro-Shark method of valuation.  It does not make the Sharks wrong or “evil”.  In fact, they are simply trying to ensure that they are being conservative investors in this respect.  They only have a brief window on which to evaluate a company for significant investments.  If it were you, wouldn’t you adopt a valuation method that is conservative in your favor?

 

However, I would like you to recognize and perhaps search online for methods of valuation for different companies. I think you will find that very enlightening and different than the seemingly straightforward method of valuation that the Sharks use on TV.  Again, I really enjoy Shark Tank and I think it is excellent because it exposes America to certain ideas about investing, building a business, and innovation.  It shows personal stories of Sharks and future millionaires who have worked hard and brought a company very far.  It really highlights the American dream.  Certain limitations are imposed by the fact that it must make for good, watchable, TV.  And I respect that.  It’s more valuable to have an entertaining show that demonstrates the basics of investing and business building rather than have a perfect show that focuses on liquidation preferences, term sheets and valuation models.

 

A lot of what the Sharks talk about is interesting to me for other reasons.  Remember, it is very challenging for a Shark to hear a cold pitch and determine whether to invest or not.  In this respect I don’t blame them, and as a matter of fact compliment them, on using conservative valuation methodology.  This is because they have not built personal relationships with these entrepreneurs.  Recall they have to decide in a relatively short amount of time, if the TV show runs as advertised, whether they will or will not invest in a given situation.  This makes valuation very difficult and makes the deal fraught with much more risk than you would typically have up front in a deal.  As was recently explained in Venture Capital 101 on Coursera by the Ulu Ventures team:  the bulk of cold calls deals, or deals that are not introduced to venture capitalists by friends or others in the VC community, typically go bad and are low-quality investments.  This is why the venture capital community typically gives a “no” 99% of the time to deals which do not come to them from friends or contacts.  Although we don’t know all the background on Shark Tank and we don’t know how entrepreneurs are vetted before they are on TV, if Sharks truly have such a brief time to vet the deal and decide whether to invest we can understand and appreciate why they are so conservative in the valuations.  My bet is that entrepreneurs and teams are often selected based on their story, the quality of the potential deal, their looks, and other things that may make them more TV friendly with only the investment opportunity as one parameter.

 

In the end, Shark Tank is an excellent TV show that exposes America to the investment community, some of the ways in which investment deals are done, and highlights many of the tenants of the American dream.  This useful, excellent show has certain constraints owing to the fact that it functions popular TV show.  Again, the dramatic music, the over the top pitches, and sometimes even the Sharks’ responses (I don’t recall as many surprised whooooaaa’s from the Sharks in the first season), are meant to heighten drama and interest in this excellent show.  Rather than feeling this detracts from the show, I feel it entices a broad audience to understand and be exposed to the rudiments of investing.  The limitations of Shark Tank include the valuation methodology and the absence of discussion of liquidation preferences to name a few, yet we can all enjoy this excellent TV show and that brings real value to us as an audience.

 

Don’t Just Decide With Your Gut: A Decision Tree Is A Great Tool

 

I have a personal interest in decision making that started from an MBA course on decision analysis.  It made me fascinated with the idea of advanced techniques like decision trees with conditional probability versus making decisions with our intuition alone.  One of the more interesting things that I have run across that I want to share with you includes the idea that the human mind is a programmed coincidence machine.  That is, because of how we have evolved, we are set up to notice unusual cases.  For example, when lightening strikes a log we imagine fire.  However, commonly, there is not fire when lightening strikes.  In short, rather than notice the everyday, mundane, central tendency of a set of occurrences, we recognize the exception to the rule. This is very normal and it is just how, some say, we are built. There are entire books written about intuition versus more explicit decision making.  Decision making tools can help us move beyond how we evolved and how we simply react.  Here we explore one tool of explicit decision making and its far-reaching effects.

 

Rigorous decision making has several advantages, including the fact that it is more easily taught, can make our assumptions in decision making very clear, and can force us to be reproducible in our decision making.  It also allows us to demonstrate how we arrived at a decision very clearly.  One of the most useful tools I have found to achieve these ends is the decision tree.

 

The decision tree utilizes conditional probability to demonstrate the expected payoff for each possible occurrence in a scenario.  Above, I have included a sample from one of our team’s projects.  The question is should we invest or not invest in a given startup.  You can see, as we work from left to right, we have several different scenarios outlined. Each scenario has an expected payout and a probability of that expected payout occurring.  We are able to multiply the expected payout from each branch, times the probability of it occurring plus at each node the similar risk adjusted probability from the other branch.  This is called rolling back the decision tree. Eventually, we will obtain an expected payoff from each branch.  Here we weigh the expected payoff from investing in a company versus the expected payoff for a more passive income type investment such as investing in mutual funds or a buy and hold strategy in equity based securities.  The specifics of what the decision is are not as important as the fact that we can frame it this way and do the best we can to find high quality probabilities for each event occurring.  The returns from the stock market are fairly well known, and, by the way, don’t bank on the returns we saw in 2013 continuing.  In any event, we can plug in high-quality probabilities to the equity back securities branch (invest in the stock market branch) fairly directly.

 

Calculating the expected payout from the investment in the new company strategy is more challenging.  We are using a home run, base hit, strike out type mentality and nickname each of our branches in that way.  Over time, we have come to describe a home run return as one with a 9 x MOI (Multiple Of Investment) return.  We are very conservative in assigning our probabilities such that we can make the highest quality decisions.  To be conservative, we place this as a low-probability event on the decision tree.

 

Another useful property to emerge from this is that we are able to examine our assumptions and the probabilities we use in terms of how they affect the model. This is called a sensitivity analysis.  We can vary the probabilities and determine if changing the probabilities changes our ultimate answer.  Interestingly, sometimes in very complex decision trees, changing our underlying probabilities does not effect the outcome owing to the magnitude of the expected payout, or other probabilities, etc.  This is always enlightening and shows us that no matter whether we agree on a certain probability our end decision does not change.  This has always been personally fascinating to me and has lead our angel team to what we feel, overall, to be higher quality investment decisions.  I invite you to read more about conditional probability along with decision trees, and the progenitor of many of these techniques:  John Nash (who received the Noble in part for his work on probabilities in Economics).  Consider watching the hollywood movie version of Nash’s life, A Beautiful Mind, if you have some time.

 

I think you will find the decision tree very useful as has our team.  A recent venture capital course, Venture Capital 101, given on Coursera.org highlighted how Ulu ventures and other venture capitalists use similar techniques in their vetting of high quality deals and of decision making in an invest or don’t invest type scenario.  Clearly this type of work would not play well on TV and is not readily performed for investment related TV shows like Shark Tank.  It would be very challenging to explain this in a way that is palatable to a broad audience.  However, conditional probability diagrams and decision trees such as this are very useful to obtain high quality decisions in investment arenas, healthcare, and many other endeavors.  Decision making tools can help us move beyond our old mammalian brain and make higher quality decisions.

 

Speaking of Shark Tank, our next blog entry will include some thoughts on Shark Tank and its positives for innovators as well as entrepreneurs.

Did You Know? Interesting Facts About Angel Investing and VC

One of the questions I often get from would be founders is ‘Where do I get the money to do my startup?’  This is an interesting question that has been covered in a lot of introductory business books and beyond.  Here I will highlight some of the interesting facts about how to find and raise money to found your project.

 

First, be aware that most conversations regarding funding result in a “not right now” or outright “no” answer. You need to get used to approaching people with your idea and having them not invest for one reason or another. These are often not commentaries on your idea, you as a person, or your talent.  There are many things that go into the decision about whether or not to invest in a startup.

 

We should also highlight that the initial money to fund a business model comes from a few sources including the classic three F’s: Friends, Family and Fools.  This is a tongue in cheek way of saying that the initial funding for any business model is often extraordinarily high risk and that only someone who really cares about you or who is very foolish should invest in your new, unproven idea.  Shows like ‘Shark Tank’ etc. highlight that business models that have income or demonstrable sales can be valued a lot more readily in different ways than brand new ideas with new, novice, or even an experienced team.

 

After the initial business model is created and funded by the three Fs or even the founding team itself, there are additional sources of funding that can come in different rounds. One of the ways you can obtain seed funding for your business is with what’s called angel investors.  Angel investors are individuals or teams that provide seed funding according to certain criteria.  Often teams have what is called an investment thesis.  An investment thesis describes that team’s approach to investing, the niche in which they choose to invest and other important factors they consider when it comes to investing.

 

In addition to the idea of an investment thesis, you may be interested to learn some factors that venture capitalist are well aware of.  It is important to understand some of the interesting consequences of an investment thesis, whether that be for a venture capital (VC fund) or an angel investment team.  There are other important facts as well.  First, interestingly, 99% plus of cold calls, meaning deals that come to a venture capitalist or angel investor which are not referred to them by someone they know, fail.  This is an incredible attrition rate and one well known to VC and angel investors.  In short, if high quality deals are not introduced by people the VC team knows, there is already a known substantial failure rate.

 

Next, interestingly, you may be surprised to hear that the vast majority of VC is in one of two geographic areas. This is the Silicone Valley area and the Boston / Greater Metropolitan area of Boston.  In other words a great deal of the United States VC funding occurs in one of these two areas and of these two the Silicone Valley / Stanford area has significantly outnumbered the Boston area in terms of total amount invested and other measures like the number of startup boards on which a given venture capitalist sits.  (Many VC team members sit on multiple boards.)  These are indicators of VC activity and really highlight the geographically narrow venue for VC in the United States.  Other centers are starting; however, these two comprise far and away the majority of VC in the United States.

 

So, when you go to take on investors for your newly minted business, it is again important to realize that often their decision to invest or not invest is not a direct commentary on the quality of you, your idea, your team or your experience.  Importantly, in fact the VC / Angel Investors decision is often contingent on their investment thesis. You may not be in the area of interest or expertise for the Angel / VC investor.  They may refer you to someone who is.  Again, remember, there is a great deal of failure before success when you are seeking seed or series A funding.

 

Last, there are some interesting consequences to VC and Angel funding, which we could easily fill a book with.  One of the more interesting ones, and least understood ones, is called liquidation preference.  This is the manner in which venture capitalist or angel investor extracts their money in a so-called exit event from the company.

 

An exit event can be, for example, when the company is purchased by another company.  Purchases such as those constitute the majority of exit events. Then, what is known as the ‘stack’ gets executed.  The stack, if you can imagine as a stack of a deck of playing cards, means the last round of investors are paid first from the top of the stack etc, down to the your initial or seed investors at the inner most layer.  The manner in which payouts occur is called liquidation preference and there are many interesting factors in liquidation preference.  Before you start a company and take on investors I encourage you to read and learn more about liquidation preference.  For now, let me share that liquidation preferences often cause a misalignment between the interests of the investor and the initial startup designer and owner.

 

Investors become part owners of the startup in almost every deal.  However when an exit event occurs there can be significant misalignment between the investor-owner and the initial startup team’s interest. These may be owing to liquidation preference.    Interestingly, the liquidation preference sometimes means that the investor owner would be willing to sell the company for a much lower amount than the initial startup team. Again, liquidation preference is often misunderstood and has significant consequences for eventual payout from the startup in the event of an exit strategy execution.  For more information regarding liquidation preferences, exit strategies, and how these may impact your startup idea along with investor opportunities I would perform a quick google search and learn all you can.  Specifically focus on terms like “1x”, “participation”, and “cap”.

 

In startups I have helped perform we use multiple techniques to keep everyone aligned.  These include some classic techniques like dynamic ownership equity and liquidation preferences that attempt to keep everyone’s interest in the company aligned, so the company can move forward as a team.  These are just some of the challenges and nuances of startups and some of the ideas that make starting a business so interesting and so much fun.

 

In the next blog entries we will describe other interesting facts about business model innovation and how to mitigate certain risks while accentuating the benefits of a startup.  I would also add that one of the single most useful tools in business model innovation has been the concept of dynamic ownership equity.  I first encountered this concept of dynamic ownership equity in a text by Noam Wasserman, from Harvard press called The Founder’s Dilemmas. For more information regarding tools to improve alignment in your fledgling business model I invite you to take a look at that useful text.

Dogs Walking On Their Hind Legs: Tales Of What Happens When You Don’t Know Your Business Model’s Numbers

 

 

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from:  http://tinyurl.com/przwj3o

I have seen several businesses now that don’t know themselves via numbers.  They may be founded by highly relationship-focused entrepreneurs, which can be a great thing, or they may be focused by people who are not numbers savvy.  However, I can’t tell you strongly enough about how important it is to know key metrics for your business and to follow them.  

 

Sometimes, my colleagues and I have seen businesses that, when we finally look at the numbers, appear as dogs walking on their hind legs.  That is, these are businesses that currently shouldn’t be doing what they are doing and probably cannot do it for very long.  One of the key techniques we focus start up teams on to achieve a sustainable position was discussed in an earlier entry.  The business model canvas is one of the techniques we recommend to set up a condition where you can know your business by the numbers and follow it over time to get a sense of where you really are.

 

The business model canvas can be used to create a pictorial history of the business.  The business model canvas can then be considered at different meetings and revised.  Then, over time, we obtain a history of the business and can look back on this to gain certain insights.  It will focus us on those areas on which our business rests.  Next, we need to establish and focus on key metrics for the business.  Many new businesses are highly dependent on new customer acquisition.  In those cases, we recommend getting metrics together about that key sector.  Whatever parts of the canvas are key we recommend putting some metrics in which you can believe attached to that.  

 

However, often there are several areas of the business on which we should focus. One of these is cash-flow.  Cash is, in fact, king as the the saying goes.  This is because it is highly liquid and very transportable.  Cash-flow is incredibly important to businesses and, although I was told that in business school, I didn’t fully appreciate it until situations arose in one of the first businesses I helped co-found.  

 

In short, I learned important lessons like:  it is possible to grow the business so much so quickly that the business actually grows its way into bankruptcy. That can be because, although the business is very worthwhile and profitable, it is unable to meet its current obligations owing to cash-flow restrictions. So, for that reason, I can’t stress enough the importance of knowing your businesses’ key metrics and establishing these upfront. 

 

There are multiple sources you can go to in order to discover what key business metrics there are for startups.  Some of the key metrics we look at to prevent the dog-on-hind-legs-syndrome (or DOHLS, because, being in healthcare, it seems I have to attach an acronym to everything) are business financial ratios.  These can tell you about the current financial health of the business. 

 

Some of the most important ones include the acid test ratio, which focuses on your businesses’ ability to meet its current obligations. The acid test ratio is called that for the very important reason that it is one of the most central, key metrics for how your business is doing. However, these are not the only lenses through which you should view your business.

 

One of the other important things is the days in accounts receivable. If it is taking you too long to collect on outstanding bills you may need to incentivize customers to pay those bills faster.  Taking too long to collect on invoices can directly inhibit your cash flow and ability to meet those current obligations. For a more in depth discussion on financial ratios and associated metrics, including the classic three levers of financial control, I invite you to read a brief primer on financial ratios, either available from Amazon for Kindle or many online sources.  

 

Some of the key ones we use include the acid test ratio and the ROIC (return on invested capital).  However, you should recognize that startups need different ratios than established companies.  For startups there are other metrics which are no less central to understanding the quality and life of the business.  Sometimes when we give talks to surgeons and other physicians about their startups we even use the analogy of the business as the patient and focus on some of the metrics we use as if they are vital signs. This is a useful exercise and my colleagues and I do this routinely at our yearly seminar.

 

The yearly seminar really helps both physicians, non-physician caregivers and other providers in healthcare get their minds wrapped around how to know how well their business, patient, or business model canvas is performing.  There are some other useful metrics that are indigenous to startups.  For example it is very key to highlight a customer-specific metric.  Some startup books advise that the core team actually focus mostly on customer development at the onset of the business.  That means the entrepreneurial team spends a great deal of its time developing the market and focusing on techniques such as evergreening.  

 

Evergreening is a classic technique that focuses on obtaining more or repeat business from a client pool.  This evergreening technique references trees and tree growth where the tree is green all year long. This is the focus for techniques collectively called evergreening.  Beyond evergreening there are also other useful areas of focus for business metrics of the startup.  Some of these include the number of new potential customer contacts and the attrition rate of customers.  How much time, effort, and ability does it take to convert a set number of calls to a new customer.  Related to this there can be costs associated with customer acquisition. If you ever watched the show ‘Shark Tank’ this is one that you have seen repeatedly question by some of the sharks.  If a startup knows its cost of customer acquisition this tells us a great deal about the startup.  First, it tells you that the startup is focused on bringing in new business and really has focused on it to the point where they can name a price associated with the cost of acquiring new customer.  It shows that they have spent time working on it. And it shows they have thought about the inflow to their company to an appropriate degree.  

 

Regardless of what the specific number is, Mark Cuban’s typical question on Shark Tank indicates that the startup has a good sense of how it brings in new customers and there is a ready-made stream of inflow developed. For startups, again, it is very key to have an understanding of metrics associated with customer acquisition and business acquisition so as to prevent dog walking on hind legs syndrome.

 

Have you ever seen any business that has this dog walking on hind legs syndrome (DOHLS)?  It happens all the time that, when a business finally looks at its numbers, it becomes clear that it can’t continue onward doing what it’s doing for very long just like that wobbly dog. 


To share a personal story, I have been very fortunate with at least one of the startups in which I have participated.  My cofounder and I were not as focused on our business model’s metrics at the beginning of the startup, and instead took the route of the very personal, very relationship-oriented startup.  This had many upsides.  However there were a few downsides including the fact that we began to encounter cash-flow problems etc. and quite nearly did grow ourselves into a bankruptcy-type situation where we could not cover our costs.  This was because of cash-flow as the company grew.  Each time the company grew into a new venue we had to be able to have approximately 20k cash on hand to be able to pay our first independent contractors who worked at that site before that site was required to pay us.  This 20k of float, or floating money, was not something we appreciated as well as we could have initially.  Fortunately, owing to excellent work on the part of my cofounder and the business team associated with the project the company has gone on to do well.  However, we were almost too late when it came to appreciating our financial metrics.  We had to pay more attention to our days and accounts receivable etc, and this was something that it took sometime to get a feel for in our business.  So there are multiple business metrics on which we can focus for our startup. 


Learn from my mistake:  regardless of the specific ones you choose to believe in and rely upon it is essential that there be some on which you rely.  I recommend some of these include customer-focused metrics so you have a sense of how to develop a continuous, effective, cost-conscious pipeline for new customers into your business model.  For more information regarding financial ratios, including those focused on profitability, cash-flow and inventory I direct you towards any of the classic primers on management by financial ratios which you can find on Amazon.com or the Google.  Also, remember to look at one that is startup-focused.