Sunday, August 25, 2019

Planning Restaurants in Locations with Predominantly Generation-Y Demographics

Stacy, a college graduate with concentration in hospitality and food service, is interviewing for a Senior Analyst position.

Question # 1
Interviewer: One of our clients, a national restaurant chain, wants us to a find a new location in our city where Generation-Y demographics predominate. What additional factors would you consider in your initial plans?

Stacy: I would recommend customizing the interior and exterior décor as well as other family attractions in order to be demographically more appealing to the Gen-Y population; for instance, for a fast food chain I might recommend annexing a kids’ play area.   





Question # 2
Interviewer: Our interns randomly surveyed a group of Gen-Y students and presented the summary results at a management meeting. Explain to me their findings as shown in the Generic Taste table.  

Stacy: They like higher than average salt content in their meals. They are young folks so they still have the sweet teeth. Obviously, they love the savory taste, but they have not developed much taste for sour or bitter yet.


Question # 3
Interviewer: What is the reason we are publishing the stats between the 5th and 95th percentile? If you have to extend the curve, how would you go about doing it?

Stacy: Since the survey results are going to be used in important business decision-making, you avoided using the outlier data points, which is extremely prudent. If I were to extend the distribution, I would use 1st to 99th percentile, avoiding the minimum to maximum range.





Question # 4
Interviewer: After surveying the generic taste, our interns asked them to sample and score the actual food sample we received from our restaurant client. This survey comprised an overall score, as well as scores in three relevant categories, on a scale of 1 to 5, where a score 5 was considered excellent. Interpret the actual scores.

Stacy: The overall median score is 4.0, meaning 50% thought the food was good to excellent while the other 50% rated it average to good. Given their higher liking for salt and sweet, they had some issues with the salt and sweet components in the samples they tried, thus suggesting that the foods could use a notch more salt and sweet to meet their tastes. Obviously, it’s typical of this age group. In other words, while developing the menu items for this location, the salt and sweetness levels need to be permanently bumped up.


Question # 5
Interviewer: What is the statistical difference between generic savory and actual savory tastes?

Stacy: The distribution of the generic savory taste is more compact ranging between 4 and 5, while the distribution reflecting the actual score has a wider range of 3 to 5, signifying that there is some room for improvement in catering to their actual taste, absent which the bottom 10% that gave a score of 3 might fall off.





Question # 6
Interviewer: We know that the folks who rated the food samples below 4 would come along once the menus are adjusted to their tastes, but we wanted to find out if their higher-score counterparts who rated the food 4 and above would continue to feel that way. How would you interpret the actual vs. the predicted scores?

Stacy: The table shows that the predicted scores are as good; for example, the median predicted score was 4.32 relative to the actual median of 4.25, while the standard deviation fell from .31 to .28, further authenticating the stability of the higher scores. In other words, their high-score counterparts would continue to like the food.





Question # 7
Interviewer: What is the purpose of inserting the graph here?

Stacy: The graph is more telling. When you graphed the same table data, it makes the inconsistencies stand out more vividly. The predicted score after the 75th percentile has flattened out, proving their generic tastes didn’t justify the abrupt spike in scores from 4.50 to 5.00. That jump from the 90th to 95th percentile is irrational. Likewise, the sideways movement at the lower end of the distribution, i.e., between the 5th and 25th is not logical either.





Question # 8
Interviewer: Any idea how we developed the regression model?

Stacy: Yes, you developed the regression model by joining the two pieces of data from the two questionnaires. Specifically, you used the actual scores as the dependent variable and their generic tastes as independent variables in the regression model.

Question # 9
Interviewer: Interpret the regression output and the impact of the variables.

Stacy: The regression model shows that sweet and savory are stronger than salt, thus indicating that even the high-score group would require more adjustment to the salt level in individual entrées than the sweet and savory. The strength of an independent variable in regression models is evidenced by the higher T-stat and lower P-Value. Clearly, the sweet has the highest T-stat and lowest P-value, closely followed by the savory.     

Thank you,

Sid Som, MBA, MIM

Homequant, Inc.
homequant@gmail.com   

Coming soon...Sid's New Book: Modern Interviewing Techniques and Skills - Live Simulations with actual Market Data

Friday, August 23, 2019

Median-based Trend Analysis – despite being Industry Standard – must be Statistically Challenged

(Click on the image to enlarge)

Ryan, a new college graduate with co-concentrations in Economics and Math, is interviewing for the Market Data Analyst position with a major Research firm.

Question # 1
Interviewer: These two graphs are derived off the same housing market and reflect the same time period. Why do they look so dissimilar? In order to keep the conversation more professional, let’s address the Monthly Median Sale Price as the Champion or Champ and the Monthly Median Sale Price per Square Feet as the Challenger.

Ryan: This dissimilarity proves that an industry standard Champ must always be validated or statistically challenged. A prudent market analyst must not take a set of established assumptions for granted; instead, such assumptions should be subjected to frequent tests and validations.


Question # 2
Interviewer: Why do you think that is important? What’s wrong with a time-tested Champ? Why do you need to introduce an untested Challenger?

Ryan: The Challenger helps identify any on-going shifts in the market; for example, when the prospective buyers are gradually moving towards smaller homes, the demand pattern shifts. The Champ will not capture and reflect that shift in the demand pattern, but the Challenger definitely will. That is why the Champ must be meaningfully challenged.


Question # 3
Interviewer: Why is the double top bearish? Shouldn't the double bottom be bearish as well?

Ryan: A double top is bearish because it fails to break out of the congestion, generally trending downward. A double bottom, on the other hand, is bullish as it’s a breakout event with an up-sloping linear trend and potential for new highs.  


Question # 4
Interviewer: Explain the difference between the two in more quantitative terms.

Ryan: After peaking at $320,000, the Champ remains sideways, congesting between $300,000 and $310,000. The Challenger trend is almost diametrically opposite with an extremely bullish up-sloping double bottom, even eclipsing the prior high of $180/SF. The moving average is confirming the breakout as well.


Question # 5
Interviewer: If you have to show one of the two graphs to our clients, which one would you choose and why?

Ryan: Obviously, the Challenger graph, as it captures and depicts the underlying fundamentals of the market.  


Question # 6
Interviewer: Is there a missing piece in this presentation that would explain as to why these two solutions are diverging? If so, how would you present that data?

Ryan: Yes, the Monthly Median Home Size (SF) is missing. The movement of SF would explain why they are diverging. I would use a simple table showing all three monthly data variables, without having to show these two-dimensional graphs.   


Question # 7
Interviewer: Why do you think the bullish R-squared is so much higher than its bearish counterpart?

Ryan: Because that’s the right trendline for that slope of the curve. The bearish one does not demonstrate a linear trend so the resulting R-squared is low.


Question # 8
Interviewer: In that case, what type of trendline would you fit and how much difference would that make?

Ryan: I would fit a polynomial trendline of the 6th order, expecting fairly similar results.   
Interviewer: Give me a minute and let me check it out. Yes, you are right; it’s 0.794. That’s great data visualization. Congrats!


Question # 9
Interviewer: Would you use the median-based analysis in business decision-making? If not, how would you improve upon it?

Ryan: The median-based analysis is necessary (for quick and dirty analysis) but not sufficient in taking business decisions. I would use an extended percentile data curve like the 5th to 95th, without the outliers.   

Interviewer: Did you learn data analysis and modeling on your own?

Ryan: No. My mom is a consulting Economist so I get to learn a lot from her.

Interviewer: So, who do we hire – you or your mom?

Ryan: Got to be me because it’s BOGO.


Thank you,

Sid Som, MBA, MIM
Homequant, Inc.
homequant@gmail.com   

Coming soon...Sid's New Book: Modern Interviewing Techniques and Skills - Live Simulations with actual Market Data

Wednesday, August 21, 2019

Factors Impacting the Pricing of Late Model Cars



Paul is interviewing for a Price Analyst position with a national independent car dealer.

Question # 1
Interviewer: The correlation matrix (1) is unrestricted, representing the entire inventory without any constraints whatsoever. The correlation matrix (2) is however constrained to those with the balance of the factory warranty, re-certified warranty or special dealer warranty. What is your most important observation here?

Paul:  The dealer Price has the highest negative correlation with Miles, signifying that the higher miles tend to dampen the dealer’s asking prices in the market.

Question # 2
Interviewer: What is the next best predictive variable?

Paul: Given the entire population, Warranty is the next best predictive variable, with extremely low collinearity with the other potential independent variables. When only the warranted cars are evaluated, the homogeneity of the inventory, i.e., lack of distribution, lowers the predictive correlation. Either way, the positive coefficient points to buyer’s preference of the warranted vehicles over their counterparts with expired warranties.

Question # 3
Interviewer: How does the Accident variable impact both populations?

Paul: Unsurprisingly, the Accident variable has a negative impact on the overall dealer pricing. As far as the warranted cars are concerned, the limited period on the road and the resulting capped mileage have made the Accident variable more or less irrelevant (uncorrelated).

Question # 4
Interviewer: How would you interpret the Owner and Service variables?

Paul: Well-maintained cars (Service) are rewarded. Surprisingly, the highest-rated original ownership is unrewarded. The plausible conclusion is that the 3-yr leases are so popular that the first owner is truly the first purchaser after the expiration of the lease. For the warranted cars, the Owner variable has turned into a big positive, suggesting that the original ownership would be rewarded. Service has become the most positive correlation coefficient, emphasizing that the maintenance of the vehicle by the manual would be economically wholesome.




Question # 5
Interviewer: The scatter graph reflects the entire inventory. What is it telling us?

Paul: The scatter graph is depicting the usual negative relationship between the Dealer Prices and Miles. Prices generally decrease commensurately with the increasing mileage. In fact, the graph is essentially confirming the most classic pricing relationship in the pre-owned auto industry.

Question # 6
Interviewer: In that case, the fit would be tighter and the resulting R-squared would be higher. How come we don’t see that?

Paul: Since the scatter reflects the entire inventory of pre-owned cars, it needs removal of some outliers. In fact, this fit would be much tighter with the trimming of outliers, thus paving the way for a much higher R-squared, perhaps to a more customary level. 

Question # 7
Interviewer: If you are asked to develop a regression-based pricing model for the entire inventory, which independent variables are you going to choose?

Paul: Since a limited number of variables are available and multi-collinearity is not an issue here, I would use all of them, letting the model decide their significance and effectiveness.

Question # 8
Interviewer: Do you expect the Miles variable to be the most significant in the regression model?

Paul: No. In multiple regressions, the variables with the most predictive relationships with the dependent variable do not necessarily become the most significant independent variables as they are evaluated alongside other variables in the same equation. Also, the distribution of the variable is important too.

Question # 9
Interviewer: Given your logic, the Service variable which has the least predictive relationship with Price can be significant in the model. Is that what you are saying?

Paul: Precisely. Considering its low multi-collinearity with the other variables, it could be one of the most significant variables.

Thank you,

Sid Som, MBA, MIM
Homequant, Inc.
homequant@gmail.com

Coming soon: Sid's New Book: Modern Interviewing Techniques and Skills - Live Simulations with actual Market Data

Tuesday, August 20, 2019

Median-based Trend Analysis – despite being Industry Standard – must be Challenged

(Click on the image to enlarge)


Ryan is interviewing for the Market Data Analyst position with a major think-tank.

Question # 1
Interviewer: These two graphics are derived off the same housing market and reflect the same time period. Why do they look so dissimilar? In order to keep the conversation more professional, let’s address the Monthly Median Sale Price as the Champion or Champ and the Monthly Median Sale Price per Square Feet as the Challenger.

Ryan: This dissimilarity proves that an industry standard Champ must always be validated or challenged. A prudent market analyst must not take a set of established assumptions for granted; instead, such assumptions should be subjected to frequent tests and validations.


Question # 2
Interviewer: Why do you think that is important? What’s wrong with a time-tested Champ? Why do you need to introduce an untested Challenger?

Ryan: The Challenger helps identify any on-going shifts in the market; for example, when the prospective buyers are gradually moving towards smaller homes, the demand pattern shifts. The Champ will not capture and reflect that shift in the demand pattern, but the Challenger definitely will. That is why the Champ must be meaningfully challenged.


Question # 3
Interviewer: Why is the double top bearish? Shouldn't the double bottom be bearish as well?

Ryan: A double top is bearish because it fails to break out of the congestion, generally trending downward. A double bottom, on the other hand, is bullish as it’s a breakout event with an up-sloping linear trend and potential for new highs.  


Question # 4
Interviewer: Explain the difference between the two in more quantitative terms.

Ryan: After peaking at $320,000, the Champ remains sideways, congesting between $300,000 and $310,000. The Challenger trend is almost diametrically opposite with an extremely bullish up-sloping double bottom, even eclipsing the prior high of $180/SF. The moving average is confirming the breakout as well.


Question # 5
Interviewer: If you have to show one of the two graphs to our clients, which one would you choose and why?

Ryan: Obviously, the Challenger graph, as it captures and depicts the underlying fundamentals of the market.  


Question # 6
Interviewer: Is there a missing piece in this presentation that would explain as to why these two solutions are diverging? If so, how would you present that data?

Ryan: Yes, the Monthly Median Home Size (SF) is missing. The movement of SF would explain why they are diverging. I would use a simple table showing all three monthly data variables, without having to show these two-dimensional graphs.   


Question # 7
Interviewer: Why do you think the bullish R-squared is so much higher than its bearish counterpart?

Ryan: Because that’s the right trendline for that slope of the curve. The bearish one does not demonstrate a linear trend so the resulting R-squared is low.


Question # 8
Interviewer: In that case, what type of trendline would you fit and how much difference would that make?

Ryan: I would fit a polynomial trendline of the 6th order, expecting fairly similar results.   
Interviewer: Give me a minute and let me check it out. Yes, you are right; it’s 0.794. That’s great data visualization. Congrats!


Question # 9
Interviewer: Would you use the median-based analysis in business decision-making? If not, how would you improve upon it?

Ryan: The median-based analysis is necessary (for quick and dirty analysis) but not sufficient in taking business decisions. I would use an extended percentile data curve like the 5th to 95th, without the outliers.   

Interviewer: Did you learn this data analysis on your own?

Ryan: No. My dad is a valuation expert so I get to learn a lot from him.

Interviewer: So, who do I hire – you or your dad?

Ryan: Got to be me because it’s BOGO.


Thank you,

Sid Som, MBA, MIM
Homequant, Inc.
homequant@gmail.com   

Coming soon: Sid's New Book: Modern Interviewing Techniques and Skills - Live Simulations with actual Market Data

Wednesday, August 14, 2019

Homequant Offers Property Tax Appeals AVM on Revenue Sharing

Homequant Offers Custom Home Sales and Assessment Stats

Monday, August 12, 2019

Modern Home-based Businesses for Stay-at-home Moms

By stay-at-home moms I am here referring to the parents who choose to stay home, taking care of their growing kids. Thus, whether a parent is mom or dad is immaterial. Conversely, the folks who are working “remote” for their employers are obviously excluded from the purview of this post. 

According to Pew Research, "Stay-at-home moms and dads account for about one-in-five U.S. parents."

Of course, the vast majority of those parents are either professionally self-employed or are running some home-based businesses, but those who are planning to take the plunge in not too distant future may, among others, explore the following options as well.

    1. E-book Creation for 3rd Party Writers – Due to the fast-growing popularity of self-publishing platforms like Amazon’s KDP, Barnes & Noble Press, Lulu, etc., the publication of E-books has skyrocketed in recent years. Of course, the idea of “creating” the E-book forces many writers on to the sideline, meaning they could use some technical help in going live. Stay-at-home moms exploring new business opportunities should seriously evaluate this technical option – connecting future writers to the hosting platform – as part of their overall mix of alternatives. All one needs to get started is a simple landing page (e.g., Word Press website) which could be easily marketed via the social media.     

    2. E-book Marketing Service – One of the basic differen ces between the traditional book publication and E-book publication is the marketing and promotion. Publishers take full responsibility to market and promote traditional books, while self-publishing comes with self-marketing. While the E-book writers possess the domain knowledge or technical expertise to write their books, they are not necessarily experts in marketing and promoting them, making them stand out and narrowing the competition down. The stay-at-home moms with good knowledge and understanding of social/marketing may explore this home-based opportunity. Specialized 3rd party marketing tools are available for subscription. Some platforms have built-in marketing/promotion tools like affiliates, cross-selling, referrals, mailing lists, special discounts and coupons, etc. This can be a standalone service or can easily be run as an add-on to # 1 above.

    3. E-Book Writing and Editing Service – Many people have brilliant ideas but do not have the necessary time or professional writing skills to take them to the finish-line. The stay-at-home moms with good writing skills may step in and fill in that economic void. Those with very limited time may simply consider the “Editing” service. On the other hand, those with backgrounds in fine arts or visual arts may seek out the prospective writers needing such skills, including the designing of children’s books and science fictions. As the business grows, other similarly-qualified stay-at-home moms or local students majoring in those areas could be trained as sub-contractors. Again, all an entrepreneurial mind needs to get started is a landing page coupled with targeted social marketing. Later, this service could be vertically integrated with aforesaid # 1 and # 2.

    4. Local Restaurant Brand Promotion Service – While the national and regional chains have their own brand promotion and market research services, there are many smaller non-chain restaurants, especially the ethnic varieties, which lack proper marketing efforts to promote their brands to remain competitive. Such restaurants could be targeted and signed up for a fixed monthly fee for the first six months or so, connecting later to the traffic growth. With the help of a landing page and targeted social marketing, the online traffic could be directed to the client restaurants. Any traffic analytics software including Google Analytics can help analyze such campaigns. In order to target such (restaurant) clients, a 30-day free trial could be thought of. Owners can be met in the evening/weekends for face-to-face discussions and presentations. Once the clients see the growing traffic, they would love to stay with the service. And, as the word goes around, other restaurants struggling to stay afloat or are vying for growth would come on their own. Down the road, other research and analytics services – rewards, survey, satisfaction, etc. – could be added.

    5. Airbnb-style Online Matching of Long-term Adult Daycare Services – With the growth of our aging population, the need for adult daycare services has been rising around the country. Of course, unlike the child daycare services, the adult daycare services are more unstructured and primarily home-based. Subject to the local laws and legalities, the online matching of such care-givers and care-seekers will be an emerging trend, which the stay-at-home moms could take advantage of. A flat monthly fee to subscribe to the marketing program or a percent of the revenue from each sale could be charged to the care-givers. Of course, the long-term contract, say at least one month, would be the key, with a non-circumvention clause binding upon both parties within a certain period post initial introduction or at the completion of the first contract period. A simple mobile site (where the site automatically works as an App as well), being promoted socially, would be a good starting point.

    6. Conducting Online Surveys for Research Institutions and Political Parties – Market research houses and political parties need constant help with online surveys. Those who have backgrounds in market surveys, polling and conducting online interviews can explore this business opportunity. Alternatively, some stay-at-home moms can do the survey/polling on their own and then package and sell the services to various institutions or political parties in need of such survey results. This business may have a longer gestation period, but with proper social marketing and networking, it could be very rewarding over a period of time. Of course, sound technical knowledge regarding online sampling, survey methodologies, polling techniques, etc. are imperative. Political elections, from local to state to national, have become extremely poll-driven so the parties have been learning to evaluate myriad of external poll results to challenge their internal results. Again, excelling in local political polling would require significant interactions with the grassroots (could be time-taking!).    

    7. Online Property Tax Appeal Filing – Property tax assessment is one of the most controversial services local governments are generally tasked with. In larger jurisdictions, almost every other property assessment is frowned upon, leading to sizeable appeals. Unfortunately, a good percentage of homeowners are either unaware of or are too afraid to challenge their values. While the old-fashioned consultants are still hanging on to their antiquated solutions, a new generation of problem solvers is on the horizon posing existential threat to them. The stay-at-home moms with the basic knowledge of the local residential market can easily get into this online business and claim a piece of the forward-looking pie. All it requires is an online comparable sales (comps) program, along with access to the home sales database (they generally come bundled together from the data vendor). This is a marketing oriented business but rewards are significant considering the tax savings are generally evenly split. Stay-at-home moms with Data Science/Quantitative background can easily take the solution to the next level, potentially doing away with the old-fashioned competition altogether.

    8. Blog Marketing Service – The popularity of blogs, both consumer and commercial, has grown by leaps and bounds in recent years. While most bloggers are passionate at what they do, meaning good at presenting their viewpoints, many nonetheless succumb to the competition due to inadequate or ineffective marketing. Given their passion, they would more likely to spend on marketing to stay afloat and grow than concede and ring down the curtain. This creates a new small business opportunity. The stay-at-home moms who majored in English, Literature, etc. can easily turn things around for them by creating intelligent campaigns out of their blog posts and marketing them on the social media. In fact, there are AI-based social media applications that automatically identify the appropriate target audience and then place the content in front of them.

   9. Owning and Marketing Niche Job Sites – Nowadays ready-made job sites can be purchased or licensed for as little as $99/year from a whole host of well-known developers. Of course, as purchased or licensed, those sites are simply empty shells without any jobs to offer. The easiest way to get started is to become a licensee (generally free) of a major site operator like Indeed, CareerBuilder, SimplyHired, ZipRecruiter, etc. which allows the licensee’s site to be instantly populated with tens of thousands of current jobs from the parent site. Since the jobs are already available and are constantly updated, the stay-at-home moms can concentrate on targeting candidates. When a redirected candidate (from licensee site to parent site) is hired from the parent site, the fee is shared. Ideally, instead of running the site as a generic site like the parent’s, it would be prudent to run it as a very specialized site (preferably in line with the stay-at-home mom’s area of specialty) with highly targeted jobs and candidates, e.g., travel nursing, airline crew, new STEM, appraisers, etc., to avoid having to compete with the major players from the get-go. While streaming in the jobs, filters can be set up complementing the niche. The sites can be hosted by well-known US-based companies like GoDaddy, Bluehost, etc. for under $15/mo.

Nowadays, there are numerous online business opportunities for stay-at-home moms, aligning very well with their strengths. The marketing-oriented opportunities (surveys/polling) will take longer to yield results than their counterparts requiring much lesser marketing efforts (E-book creation). Similarly, the high-ticket-value opportunities (job sites) will require more creative marketing than those requiring straight forward marketing (blog marketing).

Thank you.

Sid Som, MBA, MIM
President, Homequant, Inc.
Coming Soon...Sid's New Book: 
Life, Logic and the Power of Nine (Branding)