When yes means no, maybe? ‑ Intercultural communication

When “No” means “Yes” 
An American tech lead was traveling to Bulgaria to work face-to-face with a team of excellent software developers. He was looking forward to a productive collaboration because they had alreadyworked together remotely for a while. To his surprise and dismay, his every proposal was met with a “no”.  He could not understand why it was so difficult to reach a consensus.  Luckily, there was a local team lead who explained to the American that “no” does not mean absolute disagreement. The Bulgarian engineers were actually on board with his ideas; they just wanted to add their input, and the only way they know how to do that is to reject the original proposal. 

The goal of communication 

 One goal of work-related communication is to reach a common understanding about a particular problem or task.  In American culture, good communicators are often considered direct, straight-forward and concise.  When an American hears a “yes”, they assume consensus is reached; whereas “no” usually means a dead-end.
As it is clear from the story of the American tech lead working with the Bulgarian team, “yes” and “no” mean different things in different cultures.  When those differences were explained, the tech lead was able to collaborate successfully with his Bulgarian team mates. 

When “Yes”’ means “no” 

A story of an American businesswoman in negotiations with Japanese suppliers illustrates a similar communication problem: the American businesswoman heard a clear “yes” to a price she had proposed, only to receive questions about pricing a couple of days later. Turns out, her Japanese counterparts’ main goal was to avoid disharmony during face-to-face negotiations.
But probably the best phrase to illustrate the ambiguity of “yes” and “no” in other cultures is in Russian “да нет наверно” (da net naverno), literally translated as “yes no probably”, but which means “well, I guess no”.
In some cultures (Greek, for instance) saying “no” is just not done. So one has to pay extra attention to nonverbal communication — posture, gestures, eye contact—- to make sure an agreement has really been reached.
Such differences in communication style can be explained by the type of the culture your colleague has been raised in — high context or low context.

High context and low context cultures
High context implies that a lot of information is shared indirectly. France, India, China, Mexico, Eastern Europe are examples of high context cultures, where priorities are on relationships, with a lot of unwritten rules and information that is shared via nonverbal communication.
Low context implies that a lot of information is exchanged directly and rarely is anything implicit or hidden. US, UK and Switzerland are examples of low context cultures, where people follow rules and standards closely and are generally very task-oriented.
Identifying whether your colleagues’ are from high context or low context cultures, will help you to understand tricky phrases like “yes, no probably”, “we’ll see” or “let me think about it”.

Reaching understanding
If you are dealing with a colleague who belongs to a different kind of culture, it helps to keep an open mind about the immediate outcome of your conversation, and to pay extra attention to body language, tone of voice, eye contact and other wordless clues. Summarizing what you you had agreed on at multiple points in time helps to minimize misunderstandings so you can reach consensus faster.

Read more:
Erin Meyer, Affiliate Professor at INSEAD and author of The Culture Map: Breaking Through the Invisible Boundaries of Global Business). 

“So much hostility, so little love"

2 ways to make sure you do not hire “terrible engineers”.

Why does it seems like the main task of the interviewer is to uncover the weakness of the candidate, rather than to find their strength? Why is there “so much hostility, so little love”, in the words of Danny Crichton?

Crichton is an early-stage VC investor at CRV, a dropout PhD student at Harvard, with a B.S. in Mathematical and Computational Science from Stanford. I recently came across his article on TechCrunch, “On Secretly Terrible Engineers” that offers this explanations:

“The difference between finance, management consulting, and engineering is that the first two fields have status hierarchy, and the third one doesn’t. Having the right pedigree of job experience and academic background is sufficient to get a job in the vast majority of fields in existence without too many questions. Simply being at Goldman Sachs for four years is already proof that you can do investment banking.
Yet, we don’t make the same assumptions in Silicon Valley.”

The case for a rigorous technical interview

The most common interview process today seems to filter out the most confident and experienced engineers. They have the luxury to take themselves out of consideration if they are not keen on whiteboard or “algorithmic” challenges because they know they are not going to have a problem finding a job. Yet, this self-selecting, or, more accurately, self-unselecting, may be exactly what’s needed. Some hiring managers are looking for someone who is so enthusiastic to join, that they are willing, and able, to jump through all kinds of hoops to get that job.

Hiring processes that work

How do you design a process to only hire good engineers?
There are two approaches:

1. Trying to avoid hiring bad players at all costs: “Despite the worst talent crunch that Silicon Valley has ever experienced, we still regularly throw away huge groups of talent for not perfectly answering the latest hip algorithm question.”

2. Make the interview process easy, and make firing people who “did not work out” just as easily.

A few years ago, I worked for a company that practiced the second approach — everybody was being hired as a contractor for the first three months (no benefits, no ESPP, no vacation accrual), and after 3 months you either became a permanent employee, or your contract terminated. Since we were just coming out of recession, there were a lot of candidates who were willing to go this route. With the current talent shortage, I’d expect - not so many.

What are the possible solutions to avoid both false negatives and false positives?

Develop great candidates

Thomas Ptacek, an engineer and a popular commentator, describes an alternative approach: After candidates got through a simple phone screen, they got a study guide, a couple of free books, and an open invitation to proceed with the process whenever they were ready. “Those $80 in books candidates received had one of the best ROIs of any investment we made anywhere in the business.”

There is no hostility in this approach, and if a candidate is willing to invest time to study, this, in itself, shows that they are ready to go an extra mile for this job.

So does it makes sense to invest in a good engineer even though they cannot — off the bat — be productive in the exact area you need them to? I think it does. Unless you are lucky to quickly find a candidate with the (often idiosyncratic) set of skills you need, you might be wasting your time. While you are searching for this illusive ‘purple squirrel’, you could have a really good engineer learning your product and business while getting up to speed on a missing skill - or two, or three.

Behavioral interviews

If we are willing to take a chance on a candidate, how then do we make sure that this candidate is a truly good engineer - and a great fit for your team?

Laszlo Bock, senior vice president for people operations at Google, suggests: “Behavioral interviewing also works — where you’re not giving someone a hypothetical, but you’re starting with a question like, “Give me an example of a time when you solved an analytically difficult problem.” The interesting thing about the behavioral interview is that when you ask somebody to speak to their own experience, and you drill into that, you get two kinds of information. One is you get to see how they actually interacted in a real-world situation, and the valuable ‘meta’ information you get about the candidate is a sense of what they consider to be difficult.”

And that approach - or just talking about projects on a candidate’s resume - should give you a pretty good indication of skills and intelligence of a candidate. This is a good start, but it might not be enough for screening out potential underperformers.

Assessing interpersonal skills is hard

Gayle Laakmann McDowell, author of Cracking the Coding Interview, says that the strongest factors in job performance — work ethic, teamwork and interpersonal skills — are also the hardest to evaluate in an interview. “Work ethic is basically impossible to measure in an interview. Unfortunately, interpersonal skills are very difficult as well. You can rule out the really obnoxious people, but most people can put on a good face during an interview. Plus, interpersonal skills are also about who else is on the team. It’s not just about that candidate, so an interview can’t do a great job here.”

There are no fool-proof interviewing techniques out there, but at least we can avoid using interviews to “gotcha” candidates. In the words of Crichton, “There are far less secretly terrible engineers than we might expect if we give them mentorship and support to do great work. There is a whole group of secretly great engineers ready to be developed, if only we realized our field’s animosity.”

So why not concentrate more on interpersonal skills by creating a friendly welcoming atmosphere during the interview? And, if it feels that working with this candidate will be a positive experience, allow them a flexible time period to prepare on particular topics of interest. When they come for the next visit, you will be better able to judge their capabilities.

It might take more time per individual, but will yield much better results, and create more love in the process.

Suggested Articles:

Chrichton, D. (2015) On Secretly Terrible Engineers New York Times.

Bryant, A. (2013) In Head-Hunting, Big Data May Not Be Such a Big Deal. New York Times.

McDowell, G. L. (2013) Is There A Link Between Job Interview Performance And Job Performances. Forbes Magazine.

Ptacek, T (2015) The Hiring Post

Suggested Books:

McDowell, G. L. (2011). Cracking the Coding Interview

Should I invest my time in doing this interview?

You are invited for an interview, so you go on Glassdoor to research your potential employer. If all reviews are positive, great! But what if they are mixed?  How do you decide whether it is worth your time talking to their hiring team?

Let me show you some examples of actual posts on Glassdoor:

“...a good place for people who are driven and want to work hard to succeed. You will get rewarded according to your effort.”

“Diversity. Talented people. Things moving fast. Nice working environment. A great place to try out new technology”

“The vibe you get with the colleagues is outstanding. Never have I been part of such a mixed culture of people from all over the world and have them all love to be around one another.”

“The management has been working hard to create a pleasant work environment. … The engineering team is great, very smart and friendly.”

“Smart and passionate execs and coworkers - Promising product - Open communication “

Sounds like a great company to work for, doesn’t it?

How about this set?

“...worse place for growth, team collaboration and inspiring team input. Petty and immature co-workers complaining, instead of focusing on improving product features. Management lost control of teams which resulted in lack of focus and quality of work. No team cohesion, poor choices for process..”

“Notoriously toxic culture characterized by lack of trust, deceit, and false promises.”

“The upper management seems pretty much inexperienced. They don't know how to motivate their employees…”

“Probably not a place to build your career because the "company direction" seems to change weekly.”

Not such a good place to work, wouldn’t you agree?

What if we told you that those reviews are for the same company - Tango.me? You might think the reason for such different opinions is that the company has changed over time - but this is not the case. Positive and negative reviews are following one another on the timeline - 5 stars, 1 star, 1 star, 4 stars, 3 stars …

We placed a number of people with Tango.me, so we know that the engineering team is really strong - their technical interviews are very rigorous. And, according to the article in TechCrunch, Tango is still number 12 out of 20 Unicorn Companies paying best for programmers.

At the same time, according to tech writer Josh Dickson, morale at Tango.me IS low, and there are issues with upper-level management and product vision.

Despite that, when we talk to our contacts at the company, it is clear that there are quite a few people who are happy there, and are not planning to leave.

The latest news are still a mixed bag.  On one hand,  co-founder Uri Raz stepped down as CEO, and the new CEO, Eric Setton, another co-founder and former CTO, announced  a couple of months ago that the company is splitting its service into two to rediscover the core chat experience that made it successful.

On the other hand, Tango.me had another round of layoffs recently.

...And then, those offices are gorgeous!

So how do you decide if you want to work at a particular company? One way is to think through your priorities.  

In the case of Tango, if releasing a guaranteed good product is important to you, this might not be your top choice, at least not right now.  But, if you want exposure to various tools, an opportunity to work with a really strong team of engineers, and to try your hand at interesting new technologies, then Tango.me is a good place to consider.

Of course, there is no substitution for a personal impression about any company - so do take this interview, go talk to a hiring team, ask a lot of questions, see if you click with their culture - and then decide!

Shall I compare thee...

After reading yet another article where a job search is compared to dating, I got curious to find out what other metaphors are being used for this process. Here are the results of my brief research:

While the dating comparison is, indeed, very common, approaching job search like a marketing campaign is popular, too.

How about looking at the process from the employer’s side? Turns out, the dating metaphor works on this side, too.

What else?
I have found posts comparing hiring process to:
- House buying - on both sides
- Car buying
- Shopping for groceries
- Shopping for shoes

So where does this leave me, a recruiter?
I can see my role as similar to that of a matchmaker or a real estate agent, but a salesmen? Not so much.

What does a job search/hiring process reminds you of?

Silicon Geography and History

We have Silicon Valley, we have Silicon Alley and now we have Silicon Beach.

What started as a nickname has now become a metonym for a place where hi-tech startups grow.

Silicon Valley is a name used for the southern portion of the San Francisco Bay Area, a region where a large number of silicon chip innovators and manufacturers were located. Among the first was Shockley Semiconductor Laboratory in 1956. This area is now home  to many of the world's largest high-tech corporations, as well as thousands of tech startup companies.

After Silicon Valley came Silicon Alley. This term was invented by a recruiter, Jason Denmark, who had posted several job ads in 1995 with the “Silicon Alley” label for companies in the technical hub of downtown Manhattan. Since then, the term has evolved to encompass all of the New York City metropolitan region and more fields within information technology, such as new media, telecommunications, biotechnology, game design and financial technology.

Now, we are witnessing the emergence of “Silicon Beach” - the west side region of the Los Angeles metropolitan area - as a new hi-tech hub with over 500 startups.

It reached the point where Google’s Los Angeles jobs page asks the question: “Who needs Silicon Valley when you can have Silicon Beach?” and entices with, “Prefer the sand and surf over a mountain view? Want 300 days of sun a year? Forget the Valley – pack your bags for Google L.A.”

So what is it, besides “sand, surf and 300 days of sun a year”, about this area that attracts hi-tech companies?  

In the article “Silicon Beach: Los Angeles emerges as contender for tech crown” Shawn Langlois explains, “El Segundo and Playa Vista ... are key to Silicon Beach’s next phase of growth. The area just south of Venice has it all. It is more affordable than Santa Monica and the Bay Area, has space to grow and is right next to the airport. Throw in its traffic-skirting proximity to some of the more attractive areas to live, like Manhattan Beach and Hermosa Beach, and it is not hard to foresee a continued boom.”

What is next for Silicon geography?

According to the article in Forbes, those cities - Austin, Dallas, Seattle, Chicago and Miami are poised to become the next hi-tech hub.

Huffington Post has a different opinion - it lists 8 cities, with some overlap: Miami; Boston; Detroit; New Orleans; Chattanooga; Cincinnati; Houston; Washington, DC.  

Does it mean that an aspiring software engineer should pick up and move to one of those areas?

You can read our article on advantages and disadvantages of Silicon Valley living: http://eltisolutions.blogspot.com/2014/10/bay-area-living.html

Also - we have jobs with the really cool Series B startup in Silicon Beach, check them out:

Newport Beach, CA,

• Software Engineer. Build machine learning based talent matching platforms, and help great companies find great people. 
  Software Engineer, recent College Grad. Build the next generation employment platforms, and help great companies find great people.
• Senior Software Engineer, Algorithms. Lead design and implementation of new data processing algorithms, system architecture, and product features for the next generation machine learning based talent matching platform. 
  Senior Software Engineer, Full-stack. Lead design and implementation of new data processing algorithms and system architecture for the next generation machine learning based talent matching platform.
• Senior Software Engineer, Big Data. Lead design and implementation of new data processing algorithms and system architecture for the next generation machine learning based talent matching platform.