In other news, I had my first shopping experience at the Russian Baazar today – and might I say it was an amazing experience. One of the worst things about living in the Northeast compared to the Midwest is how terrible grocery store produce is. And typically to get good fresh fruits and vegetables, you have to go to a store like Trader Joes (or Harvest Co-op for me), which typically run 15-30% more expensive than a place like Star Market. But now, I’ve been introduced to the Baazzar which features produce similar to the high end grocery stores at prices half of what they are in Star Market. I don’t know how they do it, and it’s probably some sort of illegal front, but I love it and will continue to go back.

Brownian Motion

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Every once in a while, my job affords me the opportunity to learn something really cool – granted in a very nerdy kind of way.  Recently, I learned one method for modeling stock prices and interest rates called Geometric Brownian Motion (first used in particle theory, but later used in financial instruments). This conversation might get a little technical, but I’ll start first with a conceptual description before moving into the math. For those who are uninterested in the nerdier parts of finance, feel free to skip this post

In theory, it is nearly impossible to predict what stock prices are going to be in the future – if someone knew, they would be very very very wealthy (or in jail for using illegal methods).  If you know of a legal way, let me know and we can quit our jobs and trade stocks for the rest of our lives! But just because stocks are unpredictable doesn’t mean there aren’t ways to try to figure out what these prices over time might look like, especially if you are trying hundreds or thousands of iterations to test for averages, highs, and lows. For instance, what are the odds that Microsoft’s stock price will hit 40, or the odds that it will hit 20? We do this by way of probability and statistics.

For instance, we can probably guess that a stock like General Electric will likely stay around the $15-$16 range that it’s been at for the last month.  Maybe there is a 50% chance that it rises a bit tomorrow, and maybe there is a 50% chance that it falls, but we can overwhelmingly say that it’s probably not going to drop to $1.

Image via Wikipedia

To demonstrate this, lets take that GE stock and try to figure out what one path of stock prices over the next week might look like. Take out a coin and flip it: if it comes out heads, add $0.25 to the price of GE’s shares, and if it comes out tails, subtract $0.25. Now repeat this process 10 times. You should have a series of prices that looks somewhat plausible – perhaps GE’s price will trend upwards, or perhaps it will trend downwards, but more likely, it will look like what financial engineers call a “random walk“, or a seemingly random series of prices – sometimes moving up, sometimes moving down.

So, to start to define this better, we know that tomorrow’s stock price will likely equal today’s stock price plus or minus some small but random amount. Note that random is the key word here. Now, that’s just using a coin to figure out our probability of stock increases and decreases with a 50% chance of rising by a quarter, and a 50% chance of falling by a quarter. These are certainly not the only rises and falls that could happen, and things are hardly ever assigned a 50% probability.  For instance, what happens if the US government black lists GE and refuses to ever buy any GE products again? The stock would tank! A low probability, for sure, but it could happen.

Thus, we need a more sophisticated way of doing this. Luckily, statistics has something called a “Normal Distribution” which will provide us with more granularity than just a binary flip of the coin to figure out how stock prices might change. This will also allow us to factor in those seemingly low probability events (like GE tanking). A normal distribution looks something like this:

What this graph says is that most of the frequency data for a particular sample will cluster around the mean in the center (the symbol that looks like µ). As you get further and further away from the center and head to the extremes, the frequency of certain values becomes less and less. For instance, take the average height of a man, which is about 5′ 10″ in the US. Most guys you meet will probably be about 5′10″. There are going to be several that are 5′ 11″ or 5′ 9″, but you will very rarely find someone who is 5′1″ or 6′6″ – those people are on the extremes.

So to end the conceptual part of this discussion before getting into the modeling, to figure out one possibility tomorrows price,  we simply take today’s price and then add some normally distributed (around a mean of zero) change (be it 0 or -.1 or +2), and then repeat for the day after and so on.

An Example using Excel:

You’ll have 3 input’s to this model:

1. the current stock price
2. the standard deviation of the stock price ( =stdev(stockprices))
3. the time units for which you want to make this prediction (days or 1/360, weeks or 1/52 , months or 1/12, etc) – make sure to stay consistent between the units of time for 2 and 3.

Now your formula should look like this:

P1 =  P0 + Stdev * Sqrt(time) * normsinv(rand() )

What does this mean? To directly translate: take the standard deviation of the stock, multiply by the square root of time, then multiply by a random normally distributed number (the function rand() generates a random number of uniform distribution between 0 and 1 and normsinv takes this as a probability and maps that to a normal distribution – thus, if rand() returns .60, normsinv says, given a probability of 60% where does that fall on a curve with mean zero and standard distribution of one), and finally add this amount to today’s stock price.

The one thing that threw me off at first was the multiplication by the square root of time, however this is basically due to the standard deviation’s units being in price/(square root of time), so to cancel units you have to multiply by the same factor.

I’ve attached a sample Excel spreadsheet which demonstrates this process. Just hit F9 to see how the price of GE’s stock changes over time. Brownian Motion.xls

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As a business owner, I would always wish that my customers or users would email me feedback regardless whether I asked for it. It’s nice to hear when you are doing things well, and its great (though not pleasant) to hear when you screw up. Screwing up allows you to fix things, and more often than not, your customers will thank you.

As such, I do stupid things, like wait on hold to make silly requests – like when Comcast didn’t offer CNBC, or Red Zone, or a whole host of other channels to subscribers in Cambridge, I called to request it (and waited for 30 minutes).  Lo-and-behold, 4 months later Comcast added these stations. Do I really believe that my feedback spurred the change? No. Do I believe that enough people called to complain? Yes, and that’s why I do these things – the marginal utility of my call.

That’s why I just sent an email to Sprint to request that they start carrying the Nexus One. They’ll probably ignore my one email, but maybe, just maybe, they’ll get enough requests to realize they have an opportunity. Maybe they’ll understand that the reason they’ve been bleeding so many customers is because to-date, they’ve offered an inferior product with no competitive advantage.  They are a me too player, which lags in innovation…so far.

If Sprint is serious about winning their customers back, that means leapfrogging their competition: actually deploying a 4G network instead of over-promising and under-delivering, and also deploying only top of the line handsets which could handle this network, handsets currently only found on ATT or Verizon or T-Mobile. High end used to be the bread and butter of Nextel before Sprint watered it down with crap…so I have hope that maybe, just maybe, Sprint will find its way.

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For the last 3 weeks, I’ve been working with a firm out of India to help me with the design of my financial planning site.  So far, things are going relatively well, but there have been some bumps along the way. For those of you interested, here’s what to look out for.

Elance, for those who don’t know, is a site that connects freelancers with people in need of professional work.  I was able to post some basic specs, and a whole host of firms were able to bid on this work.

Choosing a Contractor

This really is going to be highly dependent on what you are looking for (and will seem a little discriminatory).  Keep in mind that you get what you pay for, so the better developers are  going to cost you more than $20/hr. As per some basic discrimination, avoid all developers in the US who charge $20/hr or less -cost of living alone in the US is phenomenally high compared to developing countries such that a similarly priced US and foreign firm will tell you something about what you will get back.  And if you are looking for something extremely high quality, avoid India and Pakistan.  Developers from this region are looking to cut corners and put something out as quickly as possible, regardless of quality. Something you also need to consider will be your own technical and product management skills. If you haven’t overseen a developer before, you might want to consider shelling out some more moolah.

Elance also provides samples of work from each firm, customer reviews, and a skill-set testing system so you can get a basic idea of what each firm can do. Before choosing a firm, make sure that the firm has taken Elance’s tests (instead of self rating which obviously is going to lead to arbitrarily high scores), and has received high marks from previous customers.

So why did I choose India?

Because the developer had ton a TON of work previously completed via Elance and had received mostly positive reviews. Also, per my own advice, I am getting a very alpha version out as quickly as possible so that I can test before I spend too much money. I’ve spec’d out what I consider a minimum viable product for initial feedback, and only once I feel we’ve developed a sustainable idea will I find a higher quality firm (or co-founder). Moreover there’s something to be said about having worked with Indian firms before, and having worked extremely closely with a wide variety of highly skilled developers here in the States.

My dream firm was this studly Ukrainian team that unfortunately would have cost me about 3 times as much. They were responsive, technically savvy, and honest about their qualifications and time needs. Sadly, for now I need something cheap and dirty, and am willing to sacrifice quality for cost effectiveness.

The Bumps

So far, communication has been the largest issue so far.  After I first selected the firm, when my project was being handed over from the marketing team to the developers, the firm stopped responding. Flat, cold stopped responding. I basically had to threaten to take my work elsewhere before someone got back to me and a flurry of activity began.  Luckily, the initial mockups of the homepage were of high enough quality to justify sticking with them.

My other issue with communication is around dialogue. I’m used to asking developers a question and getting an answer with a few options as well as a recommendation. This doesn’t occur with the Indians – instead, I ask “would this navigation work better horizontally instead of vertically?” and a day later they just respond “we have changed the navigation tabs”.

My last issue is one of quality. You can tell that some of the aesthetics are rushed, and often I have to ask for 4 or 5 iterations before something looks like it should’ve the first time. The code looks clean enough so far, mostly because I think they are using 3rd party open sourced plugins.  I’ll see how the custom code ends up looking, and hopefully that will be clean as well.

Final Thoughts

I’ll definitely follow up on this after the project is done, but so far so good. Here’s what I’ve learned:

1) Micromanage, micromanage, micromanage: you have to be on top of these guys day in and day out. Every week begins with me asking what the plan for the week is, and then for every iteration I critique and immediately send back my feedback. Typically, I hate to micromanage as I think it is hugely inefficient, but this is one of the exceptions to the rule.

2) Everything takes twice as long as you plan for: the typical adage is that it should cost twice as much as well, but this is a fixed bid. We’ll see about how much follow on work costs.

3) Know EXACTLY what you want: You can’t assume that the firm will go above and beyond to wow you, so you must have your project perfectly specified and planned.

Yes, you read that right. My testicles apparently didn’t show up for this post. Perhaps the snowstorm scarred them away, but regardless, today I watched a marathon of Tabatha. She’s this slender, brash Simon Cowell wannabe who takes over failing hair salons and turns them around in a week – and it’s a great crash course in business.  It’s a consulting biz and I highly recommend checking it out. Here are the ABCD’s of Tabatha.

Aesthetics Count
Your clients notice when your office is dirty (or website for that matter), and what they view should be pleasing to the eye.  It’s really incredible what good design can do, and Tabatha goes in and guts their salons for better version.

Be Professional
Personality is great, but if you aren’t professional, then your clients won’t respect you and you certainly won’t be able to charge premiums for your service. So far I’ve seen Tabatha demolish people who start arguments with coworkers or yell across the salon, wear unbecoming clothing, or treat their clients with disrespect.

Customer Service, Customer Service and, oh yeah, Customer Service
Get out of the backroom and start talking to your clients.  Welcome them, make them feel comfortable, entertain them, and understand them.

Don’t Suck
There’s no excuse for you to do something you suck at. If you offer a shoddy service, you deserve to fail, or in Tabatha’s case, be fired.

The NY Times has a great interview with Mark Pincus of Zynga. They’ve got a great process for running the company which he describes here:

Q. What else is unusual about how you run the company?

A. John Doerr [the venture capitalist] sold me on this idea of O.K.R.’s, which stands for objectives and key results. It was developed at Intel and used at Google, and the idea is that the whole company and every group has one objective and three measurable key results, and if you achieve two of the three, you achieve your overall objective, and if you achieve all three, you’ve really killed it.

We put the whole company on that, so everyone knows their O.K.R.’s. And that is a good, simple organizing principle that keeps people focused on the three things that matter — not the 10.

Then I ask everybody to write down on Sunday night or Monday morning what are your three priorities for the week, and then on Friday see how you did against them. It’s the only way people can stay focused and not burn out. And if I look at your road map and you have 10 priorities for you and your team, you probably don’t know which of the three matter, and probably none of the 10 are right.

I can look at everyone’s piece of paper, and their road map shows every item you were going to do and your predicted results and actual results, and then the results are in red if you missed them, yellow if they’re close and green if you passed them. I think road maps are a great principle just for managing your life. It keeps everybody focused, and it lets me know what trains are on or off the tracks.

I really love this – it keeps things simple and achievable, breaking complex goals into very manageable tasks.  In the article, he also talks about making everyone the CEO of something, which is a nice way of saying, give people ownership of tasks – have them do stuff that matters.

I just spent this past weekend snowboarding in Vermont at the Pico Resort. It’s a quaint mountain, but nice for an intermediate or beginner rider. Certainly no match for the neighboring Killington Resort, but for what it lacks in size, it makes up for in lack of crowds. I don’t think I waited in line for more than 30 seconds at the busiest of times, and I never had to worry about crowds on the slopes getting in everyone’s way.

It was a fairly relaxing getaway despite the subzero temperatures (thank you layering) and a few roommates who were determined to destroy the place by body slamming the bunk bed (then consequently blaming the bed construction when it cracked), knocking the dustbuster from the wall, smoking cigars in the kitchen and wearing ski boots on the hardwood floors.  Luckily, the Pico Frathouse was more or less returned to it’s original condition upon departure.

I did have a few thoughts on our 3 hour drive back home:

1) Thank goodness for helmets, which almost certainly prevented my girlfriend from a concussion (a nasty fall at the end of our second day).

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2) Why don’t ski resorts offer a Sunday half day pass that begins in the morning? I think one of the reasons that Pico was so undercrowded is that it offers no comparative advantage to the Killington resort. Killington is larger, has better conditions, more interesting terrain, and an earlier half day (starts at 11:45am instead of 12:30pm at Pico). There are also many people who refuse to wait until 12:30 when they have to make a 3-5 hour trek back home, so choose to head home earlier. If a morning pass was offered, I think many people would ski from 10 to 12:30 instead of forgoing skiing on Sunday. It’s also not a question of gaming the system or cheating since the ski lift operators scan your pass every time you use the lift and would catch freeloaders easily.

The good thing about failure is that it allows us to learn, so I suppose it’s a good thing that I’ve failed quite a bit, especially at my last startup. One of the things I eventually learned is that startups are to be treated as a science experiment. But first, let me describe a tremendously dangerous mentality that all startup founders have.

First, you come up with an idea which you think is pretty good. You talk to your friends and family, and everyone seems to think its a good idea. Thus, you jump into development of this idea, wholly believing in the premise that this is a good idea…after all, you wouldn’t be developing it if it wasn’t. But your product takes a while to develop, months go by and you don’t want to release  a shoddy product, so you work on perfecting it – bugs could kill you, scalability could kill you, bad UI could kill you…

The problem is, your idea sucks. Or at least it’s untested and the market hasn’t had time to tell you whether or not it’s a great idea. At my last startup, we fell into this trap, and it took 2 years before the first beta version was released to the world. Think about that – developing in a vacuum for 2 YEARS before there was any market feedback. We released a stable, mature, scalable product which promptly received very little usage.  I brought hundreds of thousands of visitors to our site through PR, advertising, SEO and word of mouth, yet active user growth stagnated, and churn was nearly 100%.  We felt pretty ridiculous.

That’s when I realized that we had developed a technology with no awareness for our market, and by the time we realized our mistake and launched into full scale market research, it was nearly too late.

I’ve said it before, but Peter Drucker has a great quote about how business has only two functions: marketing and innovation.  And one without the other fails.

As such, the most important component of any early stage startup is to: 1) determine if your technology can be built and 2) determine if people want your product.  The end result is what most people call product/market fit.

Startups as a Science Experiment

Every science experiment has 5 components:

1. Research
2. Problem
3. Hypothesis
4. Experiment
5. Results

You will use each of these steps to test your market and technology.

Research: What products are currently available. How are people using them? What problems are they having? What needs are unmet? You will establish a broad understanding of the market and technology options available.

Problem: What specific problem will you attempt to solve?

Hypothesis: Here is when you establish the who/what/when/where/why/how of your startup. It must be testable and more importantly, measurable.  At my last company we should’ve said something like “lawyers who research case law need annotation tools to generate reports for their clients (and are willing to pay for this possibility)”.

Experiment: If you have an enterprise startup, this is when you hit the pavement and start talking to your end users before you’ve written a line of code. Determine if your particular technology implementation is valuable to them.  Do they have this problem? Do they KNOW they have this problem? Have they actively tried to find a solution? If you can answer yes to all three of those questions, you’ve hit the jackpot. If you have a consumer play, the easiest thing to do is build what you consider to be a minimum viable product (buggy as all hell and literally only a way to capture data), then release it. Follow the creed, “release early, release often”.  This is not a time to be a perfectionist, this is a time to collect data, so if you find yourself building a product to do anything other than prove the technology works, STOP.

Results: Compile all of your data, look it over, and see if you need to collect anything else. What does your data tell you? Did you prove or disprove your hypothesis? If you’ve disproved it, hypothesize and test again.

Moral of story, stop building for perfection and start testing your market.

Just got back from lunch with a friend of mine named Zach Servideo. He introduced me to “The Black Sheep”, a restaurant located in an old Firehouse in Kendall Square which has phenomenal food. If you don’t know Zach, he’s a passionate PR professional who could befriend the most anti-social person in a room and turn them into an entrepreneur.  Needless to say, had Jeffrey Dahmer met Zach in the early 70’s, he would’ve started up a software company.

Zach is starting up a little side project called All White Kicks aimed at individuals interested in White Shoes. It’s a niche I would’ve never thought of, but with his passion, he can clearly make it work.

It also reminded me of my friend Alan who always has a few side projects going on. He’s experimenting with a few random AdSense pages such as My Reticulated Python and he’s also working on a niche site called The Curry Project, which aims to review every Indian restaurant in the world.

All of these side projects have inspired me, and I wanted to let you know about a new project I have called HapiMoney. Personal finance education is woefully inadequate and most people don’t know the first thing about where their money should go and in what amounts. I hope to shed some light on money management. Check it out and let me know if you have any ideas. Also, the name is awesome because Hapi is the Egyptian deification of the Nile flooding. This flooding helped water Egyptian crops and brought prosperity to the region.

These little projects also reminded me about one of the biggest mistakes that we ever made at WebNotes- we failed to follow the adage ” release early and release often”. The project was started in 2005 and wasn’t actually released to the public until 2008- 3 years of time which could’ve desperately used public feedback. But I’ll talk more about this in a future post.