Friday, March 15, 2019

How to Protect Your Intellectual Property from Serial Thieves Posing as Investors

You are an innovator with a brilliant mind. With years of hard and smart work you have developed an AI-based solution that you are ready to commercialize. But you do not have the capital to move forward with it. You realize you are at the mercy of outside investors. You contact a whole host of accredited venture capitalists and angel investors. Months pass by. No positive news. You are becoming impatient, perhaps somewhat disheartened. As desperation kicks in, you start to contact the so-called small investors from online lists. They are giving you big stories about their investment philosophies and portfolio companies, but without any verifiable track records.

You are so eager to get started that you are ready to sign up with the one with the sweetest talk and biggest promises. You know you are supposed to check them out (i.e., do some due diligence). Other than a handful of references listed on their site (perhaps developed elsewhere where English is the seventh most important language) you have nothing else to go by. After speaking to one of them, it did however don on you that those references could be fake. Yet, you are ready to take the plunge.    


Within this particular investor group there are too many serial thieves waiting to steal your invention. Since these serial thieves are intellectually incapable of differentiating between a digital watch with a new alarm tone (wow!) and an AI-based solution that advances the cause of humanity, they will steal anything. But they are generally good at three things: serial lying (they tend to believe truth is for the devil), serial stealing (they will steal anything to satisfy and advance their greed) and running ponzi schemes (to keep some hard-nut clients quiet).

Of course, they primarily develop their business by stealing client contacts. Needless to say, some of those contacts do fall for these thieves’ flashy lifestyles, constant lies and pushy salesmanship, becoming future portfolio investors (a.k.a., victims) themselves. At one point, you will find out about it. Anyway, it doesn’t matter how well you know your investors, do not (share or) introduce your contacts to them; let it take its own natural course. Obviously, the contacts-turned-investors (or future investors) are outside the purview of this blog post (couldn’t care less!).

So, how do you protect yourself from these serial thieves? Here are some red flags and safeguards:

1. Check them out at the local BBB and Chamber of Commerce – Ignore the positives (could be cooked up as they often hunt as a pack) and zero in on the negative reviews/comments, even if the ratio is 10:1. Contact that one negative reviewer and find out what the underlying story is. If the investor does not subscribe to the local BBB or Chamber of Commerce, I would be very skeptical of their intentions (despite the BS you might get from them “Oh, that’s old-fashioned; nobody cares about them anymore, etc.”). The genuine ones will brag about their BBB/Commerce standing, etc.

2. Try to avoid the Key-man Insurance – Since it’s a start-up, the investor may insist on taking out a large (relative to the money being invested) key-man insurance on you. Try to avoid it, or at least defer it until the product (based on your concept) has been launched. If you have to do it, insist on having your spouse or parent as the co-beneficiary, preferably 60/40. If they continue to insist on their business entity being the sole beneficiary, I would be very skeptical of their intentions and consult a lawyer for legal safeguards. 

3. Initial IP Patent Filing must be in your name – Do not fall for a joint patent filing (with the business). If the relationship works out, you can always transfer it to the business for a substantial fee or equity option. Either way, it benefits the business. If the initial filing is in the business name only, the serial thieves will do everything possible to push you out or will create an intolerable atmosphere wherein you push yourself out. If they insist on their way, show them the highway and look elsewhere. This clause must be anchored in the first agreement itself. This is your primary protection.

4. You must be the CEO of the new corporation – If the whole business is going to be founded on your IP, you must be the CEO of the new company with total hiring authority – no two ways about it. In fact, the legitimate investors will insist on your stewardship. The serial thieves, on the other hand, might fuss about it. Starting out, if you are not in charge, despite what the serial thieves say, your innovation would be road-killed, just matter of time! Down the road, you can always step down, paving the way for a professional CEO, which is quite common. Again, this must be clearly laid out out, upfront.

5. Insist on your own Independent Office with long-term lease – This will give you more stability and independence. If you are forced to work out of a room inside of their offices, you will gradually lose ground and become their pawn. It’s a trick the serial thieves often play. If they think your IP is valuable, they must do everything possible to accommodate, nurture and promote your requirements. While the parent company would be responsible for all rents and utilities, the lease must be in your company’s name.

6. Insist on owning 51% shares of the new company – If you own 51%, you may not be pushed out easily. When you are dealing with a small investor, you are inherently in a high risk situation, thus requiring higher rewards. Similarly, do not allow them to place majority directors of their choosing on the board. Also, try to hire an independent CPA and Lawyer for your company; it’s not a question of bias, rather a question of transparent billing, meaning your company must not subsidize their other portfolio companies.   

7. Negotiate a sizable salary during the gestation period – Due to the high ownership percent, if they are unwilling to give you a salary, you must nonetheless negotiate a decent salary, at least, until the company becomes profitable (easily two to three years), post which you must be allowed to sell a certain percentage of your unrestricted shares every now and then on the open market, thereby enabling you to take care of your family expenditures. 

8. Insist on having the pre-negotiated capital locked in escrow – Since you are dealing with a small investor, it is imperative that you ask them to put up the entire capital in escrow, with a lawyer acting as the escrow agent. The lawyer will then disburse the working capital on a monthly basis. This is a critical test; while the legit investors will not have any issues with this, the serial thieves will invariably try to talk you out of it. If you succumb to their sweet talk, this is what will happen: Once the business is up and running, one sunny morning you will get a call for an emergency meeting where they will announce ‘we are out of money.’ And, there goes your dream. Now you have to get hold of an expensive lawyer to get yourself distanced from those serial thieves. Meanwhile, they will go around and tell the world (primarily your contacts that they managed to steal) how you have destroyed a huge sum of their extremely hard-earned (LOL) money without producing anything. Do not walk into this trap!

9. Do not outsource your IT or other important services to their overseas portfolio companies – Outsourcing IT services to a quality US-based portfolio company would be fine. But these serial thieves often set up some portfolio companies overseas, luring you to outsource some of your essential services, primarily IT, to them. In return, you will get very low quality products and services coupled with hefty bills. In no time, your working capital will dwindle, forcing you to sell a significant chunk of your shares back to them, just to stay afloat – and it will be difficult for you to get out of this cycle until the eventuality hits (‘we are out of money’). And, it’s all by design.

If you are dealing with a well-known/accredited venture capitalist, you are in safe hands. Your success is their success so they will stand by you through thick and thin. But if you have to deal with a small, unverifiable investor, do your due diligence. We know you are not greed-filled. When you succeed, the humanity progresses and we all succeed.

Do not let a low-life steal your dreams!

Disclaimer - The characters portrayed here are hypothetical in nature and any likeness to any individual or entity is strictly coincidental. The author is not offering this blog post as professional services advice in any shape, form or manner whatsoever. Every investor is different, so seek the advice of a competent professional, preferably an experienced attorney, before deciding on a non-accredited investor.

Thank you,

Sid Som MBA, MIM
President, Homequant, Inc.

Wednesday, March 13, 2019

Why Major Mass Appraisal Jurisdictions Should Hire AI Engineers

“AI engineers don’t write code to build scalable data pipelines like a data engineer...instead, they understand how to extract data efficiently from a variety of sources, build and test their own machine learning models, and deploy those models using either embedded code or API calls to create AI-infused applications."

Conversely, Regression models are not intelligent as they are highly modeler-dependent (subjective). Thus, given the same sales dataset, five modelers may come up with five different models with variant results. Of course, the biggest failure is the Sales GIS (very dynamic) as it's representativeness to the population (more or less static) is difficult to establish. That is why, in my AVM book I proposed and reverted to fixed neighborhoods (not sales dependent and are population-derived).

As I understand, AI engineers do not use any data variable modeling. Their data extraction process is extremely smart leading to very smart machine learning models. In mass appraisal environment, they will be able to precisely identify and demonstrate where the sales datasets and populations are at variance. Whereas, the mass appraisal (known as “cama”) modelers will simply remove them from the model as outliers, creating unexplainable gaps and major fault lines they won't even know.

In our future consumer environment (Homequant, Homeyada, Condoyada, etc.), we may ask the first-time users (optionally) to take a three minute tutorial. As the user interacts with the tutorial, our machine learning models will extract the data (by reading the responses) and fine-tune the model, specifically for that user. When the user returns to value a subject (log-in will be needed to identify the user), our model will populate the comps as soon as the subject is defined. So the ten minute exercise will be reduced to fifteen seconds.

Alternatively, in a traditional modeled environment, it's all sample-based so the results are, at best, bell-curved with the customary 68% efficiency. The error-based cama regression models fail to test the optimality of the solution; for example, is a model Coefficient of Dispersion (COD) of 8 better than a COD of 10? The COD of 8 could represent a post-optimal solution, whereas the COD of 10 could perfectly represent an optimal solution. But in cama environments, the COD of 8 would be universally preferred. In fact, several years ago, I presented a paper along these lines at a conference, raising some serious questions.

The mass appraisal industry is extremely antiquated. They are still using the 30-year old Regression Modeling and mostly Sales GIS. That is why I think the major mass appraisal jurisdictions should hire AI engineers, proving that the industry needs to look ahead. 

Granted, given the paucity of AI engineers, it is not going to be easy but they should try. They should also remember what Steve Jobs said, "It does not make sense to hire smart people and then tell them what to do. We hire smart people to tell us what to do."


Sid Som MBA, MIM
President, Homequant, Inc.

Thursday, March 7, 2019

Let’s Phase out and Replace Personal Income Taxes with Middle-class friendly Progressive Consumption Taxes!

Under the existing income tax system, the top 1% pays 40% of all federal taxes. According to the Tax Policy Center, 44% of Americans will not pay any income taxes this year. On the other hand, Warren Buffett claims he has a lower tax rate than his secretary. While much buzz was created about the carried interest, nothing has been done yet and as a result hedge fund billionaires continue to enjoy one of the lowest tax rates. According to Fortune, “Amazon will pay a whopping $0 in federal taxes on $11.2 billion profits.” These conflicting scenarios demonstrate how irrational our income tax system has become. Therefore, it’s high time that we (phase out and) replace the personal income tax with a set of progressive consumption taxes.

Of course, the one-size-fits-all consumption tax – which was proposed before and was justly unsuccessful – is inherently regressive, as poor and middle class folks tend to spend a much higher percentage of their incomes compared to the rich folks. Yet, the consumption tax could be an ideal replacement for the current income tax, as long as it is progressive. How? Quite simple – all non-food goods and services must be broken down into three tax-progressive categories: Basic, Luxury and Ultra-luxury. While the basic category will have the lowest tax rates, luxury and ultra-luxury will carry progressively higher rates; for example, the national sales tax rate (atop the state and local sales taxes as it replaces the federal income tax) for basic durable goods (e.g., appliance) could be 2 to 3%, whereas the luxury and ultra-luxury could carry 5% and 10% rates, respectively. Needless to say, the lower rates for the basic category will advantage the middle class while the rich will be more than happy to pay higher national sales taxes in lieu of their disproportionately higher share of the federal income taxes (case in point: the top 1% pays 40% of all federal taxes). 

So, how will the progressive consumption tax system work?

1. National Sales Tax on Basic and Luxury Durable Goods – In order to save, say $5K to $5M on annual income taxes, taxpayers would be amenable to an additional national sales tax – obviously atop the current state and municipal sales taxes – on durable goods. Unlike income taxes, consumption taxes are more humane meaning families can budget or plan for these expenditures. Since the basic durable goods impact the poor and middle class, the rate must be lower, say 2 to 3%, followed by progressively higher rates on luxury durable and ultra luxury durable goods demanded by the rich; for instance, all appliances under $10K could be basic, $10K to $20K being the luxury and >$20K as the ultra luxury category, with progressively higher rates. Likewise, automobiles could have three categories as well. Since this a national sales tax, it must cover all online purchases. While states and municipalities will continue to charge different sales tax rates, the national sales tax rates will be uniform across states as they will replace the federal income taxes.

2. National Sales Tax on Unhealthy (processed) Foods and Beverages – It’s about time that the health-conscious folks are not forced to subsidize those who basically live off junk foods and high-calorie beverages. This is a (preventive) health issue and, hopefully, this national sales tax will save citizens billions in health insurance premiums down the road. The counter case is equally compelling: Today smokers are paying a hefty price for their lifestyle (significantly higher taxes on their lifestyle products and higher premiums on life and health insurances, etc.). While we must not take smokers’ choice away, the rest of us must not finance their lifestyles either. The phase-out of the income tax system will take 5 to 7 years, during which as the income tax revenue starts to come down, the junk food/beverage sales tax should start at, say 10%, graduating up and perhaps leveling out at 20%.

3. National Sales Tax on all Name Brand Prescription Medications – When a particular medication (all forms: oral, injection, iv, etc.) has a generic counterpart, it must be subjected to the national sales tax. Since the name brands are significantly costlier, they are generally meant for the rich folks. Obviously, when the generic is not available (or is not easily/readily available), the brand must be exempted from the proposed tax. Even prescription generics produced in foreign facilities could be taxed (excise or sales).

4. National Sales Taxes on Million$-plus Home Sales – Since the rich and ultra-rich owning the upscale and expensive homes will be big beneficiaries of the phase-out (followed by no income taxes), the million$-plus home sales must be subjected to additional progressive national sales taxes. It must not be a blanket one-size-fits-all rate; instead, it must be progressive, for example, sale price $1M to $2M @5.00%, $2M to $3M @5.25%, $3M to $5M @5.75%, $5M to $10M @6.00% and $10M+ @6.25%, etc. At the individual level, unlike the income taxes, these sales will impact them once in a while, thus a far preferable option than the high annual income taxes they have been paying. On the contrary, in order to keep the upscale housing market liquid and economic, the property tax component of the SALT cap must be separated and de-capped. Should sales clusters start to balloon just under $1M, the threshold could be lowered to the jumbo mortgage (non-conforming) level.

5. National Sales Tax on Luxury Hotels (4 and 5-Star) – These hotels are primarily for the corporate executives and rich folks so an additional 5-6% national sales tax will not harm the hotel industry. In fact, these hotels might even use this sales tax as a promo (“We Will Pay Your National Sales Tax”) in order to compete for the traffic during off-peak seasons. A vast majority of these hotels have medium-to-large convention centers – seasonal to round-the-year – so convention center surtax could be an ancillary surtax as well. The hotels that are run as resorts must be subjected to an additional resort surtax. Similarly, all private golf courses must have additional surtaxes. None of these will adversely impact the middle class; even if they impact the middle class to some extent, it will be insignificant when compared to the tax savings they will be enjoying from the elimination of income taxes.

6. National Sales Tax on all Luxury Air Travels, Amtrak, Vacation Cruises and Car Rentals – Business and first class air travel, both domestic and international, is primarily for the corporate executives and rich folks so an additional 5-6% national sales tax will not harm the airline industry. Similarly, those who spend thousands more on luxury and ultra-luxury vacation cruise suites can afford an additional 5-6% national sales tax and it won’t harm the cruise industry either. Foreign cruises coming to the US shores may be subjected to additional port charges. Luxury car, charter flights and private jet rentals must carry sizable luxury and ultra-luxury national sales taxes. Likewise, upscale suites and berths on Amtrak must be subjected to the national sales tax as well. Again, none of these will adversely impact our middle class.

7. Consider Selling Non-specific National Sales Tax Data to Private Companies – Undoubtedly, the national sales tax data will pave the way for the largest warehouse of the most uniform consumer spending and market performance Big Data, so the Commerce Department might consider selling the generic data to private companies, reducing the importance of the back-door data from the social media. Private companies in the consumer sphere, including the market research and econometric consulting firms, will pay large sums on an on-going basis to have access to such central and uniform data. Since the data will constantly change in line with the economic cycles, companies will be dependent on it, perennially. Additionally, the sale of data to the end-user private companies will be directly taxed while the value-added resellers will collect sales taxes from their clients. In no time, the national sales tax data could be a big money maker for the federal government. Citizenry would be relieved as the dominance of the social media data taking a nosedive.


8. Consider Selling Naming Rights to Lesser-known or Un-named Federal Infrastructures – Let the rich people/private institutions pay to put up their names on lesser-known federal government buildings, town squares adjacent to federal buildings, highways, bridges, parks and recreational centers, education/job training centers, shelters, libraries, etc. (that the federal government owns and operates). Federal government must also take back/reserve the naming rights while funding (or primarily funding) non-profit institutions with federal dollars. If we build a wall on the southern border, naming rights to each stretch/segment must be auctioned off as well (in fact, this could provide partial funding for the wall, as well as on-going maintenance!!). The selling process must be totally open and transparent (via open tenders), thus awarding the naming rights to the highest bidders (some restrictions could apply). Also, in order to attract the right market price, it must also be term-limited, say 3 to 5 years. US DOT should also consider private-public joint ventures to build new toll roads and bridges (unable to get federal funding) wherein the private party incurs all costs to build the infrastructure in return for the toll incomes for 10-15 years.

9. Last but not least, Massive Savings will be generated by Downsizing IRS – IRS has over 80,000 employees with an operating cost of $11.5B. Obviously, the vast majority of them are expected to work on the personal income side. With the phase-out and eventual elimination of personal income taxes, the overall manpower could be significantly downsized, reducing the operating cost to $2B to $3B. Of course, a much smaller national sales tax group (Collection, IT and Data Science) will be needed under the umbrella of the Commerce Dept. Along with the reduced headcount, many IRS Centers around the country could be closed, data centers merged and cloud/storage scaled back. The corporate income tax rate has already been lowered to 21% and any further reduction would necessitate some compensating European Union-style VAT. 

Instead of forcing the top 1% to pay 40% of all federal income taxes, we should seriously consider switching to a more humane progressive consumption tax system wherein people at large get to plan and decide the amount of taxes they would pay. While progressive consumption tax is poor and middle-class friendly, the rich would also welcome the idea considering the trade-off. Studies will be needed to make the switch revenue neutral.


Sid Som
President, Homequant, Inc.

Saturday, March 2, 2019

How to Analyze and Present Large and Complex Home Sales Data – in 30 Minutes (2 of 2)

- Intended for Start-up Analysts and Researchers -

In our prior post (1 of 2) we talked about analyzing and presenting a large and complex dataset in 30 minutes. Would you handle it differently if you had 60 minutes? Here is one approach you might like to consider:

1. Just because you are starting out, do not underestimate yourself. The very fact that you have been tasked with this critical presentation speaks volumes, so take full advantage of this visibility in narrowing the competition down. These meetings are often frequented by other department heads and high-level client representatives, leading to significant loss of time in unrelated (business) discussions. The best way to prepare for such contingencies is to split the presentation up into a two-phase solution where phase-1 leads seamlessly to phase-2. 

2. In a business environment, it's never a good idea to start with a complicated stat/econ model. Start a bit slow but use your analytical acumen and presentation skill to gradually force people to converge on the same page, thus retaining maximum control over the presentation (time and theme). Therefore, the phase-1 solution should be the same as the full* 30-min solution we detailed before (*including the sub-market analysis). Even if the meeting leads to unrelated business chit-chat, off and on, you will still be able to squeeze in the phase-1 solution, thus offering at least a baseline solution. Alternatively, if you have one all-encompassing solution, you will end up offering virtually nothing. 

3. Now that you have finished presenting the phase-1, establishing a meaningful baseline, you are ready to transition to the higher-up phase-2 solution. In other words, it's time to show off your modeling knowledge. In phase-1 you presented a baseline Champ-Challenger analysis (Champ=Median Sale Price, MoM; Challenger=Median SP/SF, MoM). You used the "Median" to avoid having to clean up the dataset for major outliers. Here is the caveat though: Sales, individually, are mostly judgment calls; for example, someone bent on buying a pink house would overpay; an investor would underpay by luring a seller with a cash offer, etc. In the middle (middle 68% of the bell curve), the so-called informed buyers would use five comps, usually hand-picked by the salespeople, to value their subjects - not an exact science either.   

4. Now, let's envision where you would be at this stage - 30 minutes on hand and brimming with confidence. But it's not enough time to try to develop and present a true multi-stage, multi-cycle AVM (see my recent post on 'How to Build A Better AVM'). So, settle for a straight-forward Regression-based modeling solution, allowing time for a few new slides to the original presentation. Build the model as one log equation with limited number of variables (though covering all of the three major categories). Variables you might like to choose: Living Area, Age, Bldg Style, Grade, Condition and School/Assessing District. Avoid 2nd tier variables (e.g., Garage SF, View, Site Elevation, etc.).

5. Derive the time adjustment factors from phase-1 (it's a MoM) and create Time Adjusted Sale Price (ASP), the dependent variable in your Regression model. Explain this connection in your presentation so the audience (including your SVP/EVP boss) knows the two phases are not mutually exclusive, rather one is the stepping stone to the other. At this point, you could face this question "Why did you split it up into two?" Keep you answer short and truthful: "It's a time-based contingency plan."

6. Keep the Regression output handy but do not insert it into the main presentation as it is a log model (audience may not be able to relate to the log parameter estimates). If the issue comes up, talk about the three important aspects of the model: a) variable selection (how you managed to represent all three categories), b) most important variables as judged by the model (walk down on the t-stat and p-value) and c) overall accuracy of the model (r-squared, f-statistics, confidence, etc.).    

7. Present model results in two simple steps. Value Step: ASP vs. Regression values. Show the entire percentile curve - 1st to 99th. Point out the smoothness of the Regression values vis-a-vis ASP. Even arms-length sales tend to be somewhat irrational on both ends of the curve (<=5th and >=95th). Standard deviation of the Regression values would be much lower than ASP's. Ratio Step: Run stats on the Regression Ratio (Regression Value to ASP). It's easier to explain the Regression Ratios than the natural numbers so spend more time on the ratios.    

8. Time permitting, run the above stats both ways - with and without outliers. Define outliers by the Regression Ratios. Keep it simple; example: remove all ratios below the 5th and above the 95th percentile or below 70 and above 143, etc. Considering this is the outlier-free output, run Std Dev, COV, COD etc. These stats would be significantly better than the prior (with outliers) ones. Another common outlier question is: "Why no waterfront in your model?" The answer is simple: Generally, waterfront parcels comprise less than 5% of the population, hence difficult to test representativeness. FYI - in an actual AVM, if sold waterfront parcels properly represent the waterfront population, it could be tried in the model, as long as it clears the multi-collinearity test.  

9. Last but least, be prepared to face an obvious question: "What is the point of developing this model?" Here is the answer: A sale price is more than a handful of top-line comps. It comprises an array of important variables like size, age, land and building characteristics, fixed and micro locations, etc. so only a multivariate model can do justice to sale price by properly capturing and representing all of these variables. The output from this Regression model is the statistically significant market replica of the sales population. Moreover, this model can be applied on to the unsold population to generate very meaningful market values. Simply put, this Regression model is an econometric market solution. Granted, the unsold population could be comp'd but that's a very time-consuming and subjective process.

Ace the next presentation. Be a hero. Prove to your bosses you are a future CEO.

Good Luck!

- Sid Som, MBA, MIM
President, Homequant, Inc.

How to Analyze and Present Large and Complex Home Sales Data – in 30 Minutes (1 of 2)

- Intended for Start-up Analysts and Researchers -

If you have very limited time - say 30 minutes - to summarize and present a fairly large and complex home sales dataset, comprising 18 months of data, with 30K rows and 10 variables, here is one approach you might like to consider:

1. Given the limited time, instead of trying to crunch the data in a spreadsheet, invoke your favorite statistical software like SAS. What SAS will do in four short statements (Proc Means, Var, Class and Output) and in matter of minutes, you will need much longer to accomplish the same in spreadsheets. When you are starting out, take full advantage of these types of highly visible - often rewarding - challenges to narrow your competition down.

2. Have a realistic game plan. Instead of shooting for an array of parameters, start with the most significant one, i.e., Monthly Median Sale Price (and the normalized sale price). Since median is not prone to outliers, you do not have to edit the dataset for outliers, saving significant amount of time.  

3. Now that you have the monthly median prices, you are ready to create graphs for the presentation. While you may create one graph depicting both prices (Y1 and Y2) against months (X axis), keep them separated for ease of presentation. 

4. If you are more comfortable graphing in Excel (in fairness to the remaining time), transfer the output from SAS to Excel. Make sure your graphs are properly annotated and dressed up with axis titles, legends, gridlines, etc. Remember, just doing things right is not good enough, learn to do things elegantly as well. 

5. Since you have summarized and rolled up so much of data behind one or two graphs, make sure they not only tell the overall story, but also convey enough business intelligence to make you look like a hero in front of your EVP/SVP. In the presence of clients, it enhances their image as well. So, add trendlines alongside the data trend. Select the primary trendline by eyeballing the data trend (linear, logarithmic, polynomial, etc.). Also, add a moving average trendline to iron out any monthly aberrations. When the series is extended, use 3-month moving averages.     

6. Keep your reporting verbiage clear and concise. Explain the makeup of the dataset; methodology including the use of monthly medians; how the normalized prices add value and help validate the primary; trendlines and their statistical significance; other statistical measures like r-squared, slopes, etc. you might display on the graphs (avoid printing equations on the graphs). 

7. Add business intelligence to your talking points. First off, stick to the market you are presenting but show off your knowledge of that market by highlighting: possible headwinds and tailwinds; how that market would react to an inverted yield curve; is there a structural shift in demand for homes (are more millennial showing interest in that market); what is the NAR's prediction of the summer inventory there; is the inventory of affordable homes on the rise there; any expected change to the FHA to help first-time homebuyers in general, etc. etc. 

8. Try to control the conversation by sticking to what you have, rather than what you don't have. For example, out of the 10 variables, you managed to use only 3 (Sale Price, Sale Date and Bldg SF), so do not start a conversation about the other important variables - Lot size, Age, Bldg Characteristics and Location - you had to leave out ('If I had 30 more minutes' would be a wrong hypothesis to test). If that question comes up, answer it intelligently and truthfully emphasizing, of course, the utility of the 3 you happened to use.

9. Let's assume that you managed to complete the first cycle (as indicated above) in 20 minutes. In that case, go back to SAS and crunch the sales analysis by the sub-markets (Remember: Location! Location! Location!). This is how you walk down on the analysis curve. Have these printouts handy, but do not try to alter the initial presentation.

Ace the next presentation. Be a hero. Prove to your bosses you are a future CEO.

Good Luck!
- Sid Som, MBA, MIM
President, Homequant, Inc.