Mentoring: Give a Little, Get a Lot

Last summer, I heard that my alma mater was launching a mentoring program between graduates and enrolled Seniors. Even though I no longer reside in my college town, I quickly volunteered to be a guinea pig for remote mentoring

Last summer, I heard that my alma mater was launching a mentoring program between graduates and enrolled Seniors. Even though I no longer reside in my college town, I quickly volunteered to be a guinea pig for remote mentoring.

The woman running the program was hesitant at first—her vision was to put grads and students together face-to-face and create events that would bring the mentor/mentees together outside of 1:1 meetings.

Even though I reside in the San Francisco Bay Area and my college is in chilly Ottawa, Canada, I convinced her to team me with a student who was studying abroad for a semester so neither of us would be on campus.

Luckily I was paired with a wonderful senior named Mitch who was spending a semester in The Netherlands and studying marketing. We hit it off immediately, swapping stories about our pasts, our work experiences and talking about his goals when he graduates (to work in sports marketing). Mitch proved to be intelligent, inquisitive and eager to learn about the real world of marketing and advertising.

In our weekly calls, I answered a lot of questions (about marketing strategies and tactics and concerning specific job functions in the industry), but we also talked about some very practical things like how to put together a solid resume and a LinkedIn profile. Frankly, I was a bit surprised that in this social media crazed world, this very bright student was not that familiar with LinkedIn and how to use it to his advantage. Upon having further conversations with my college graduate son and his friends, it seems none of them were particularly savvy about LinkedIn and how leverage it to their advantage.

Helping Mitch with his resume was a fascinating exercise in marketing. His first draft provided a laundry list of all his summer jobs, but didn’t successfully position his experience and his growing expertise. As I quizzed him on what he actually did at each job, I helped him extract the salient messages he needed to convey about his skills and accomplishments—it was similar to working with a client to help them clarify and synthesize a product’s attributes and benefits, and how they stacked up to the competition.

For example, during his Junior year, Mitch worked for a marketing agency that was helping Microsoft increase its mindshare among college students. He described that job as “Independently reach and educate University students regarding the benefits of Microsoft products while entrusted with expensive technology.”

After some probing into what he was REALLY doing and the knowledge and skill set it required, we rewrote it to read “Manned an on-campus booth and answered questions about various Microsoft software products while retaining proficiency in Microsoft Windows 8.1 and the Microsoft Office Suite of products. Using Microsoft-provided software / hardware, performed a Pre- and Post- Attitudinal Behavior Study.”

Now he sounded impressive!

What was most exciting, however, is that this week Mitch advised me that a Netherlands-based sports organization that he follows on Twitter had tweeted about an opening for a marketing assistant. We quickly got to work refining his resume to match all the skills the job description required and crafted an introduction letter that further highlighted his skills.

We also did a LinkedIn search to determine who the position would report to and poured over the hiring managers resume. I encouraged Mitch to spend time on the company’s website, social media sites to become immersed in the brand, its mission, brand positioning, communications messages and key issues the company is facing.

Yesterday Mitch was contacted by the hiring manager and asked for work samples and to set up an interview. We then went to work prepping him with questions he might ask during the interview process. Honestly, I was as excited as Mitch was!

As I finish this column, I’m waiting to hear the outcome of that first important job interview, but either way, I’m confident that this young man will be a marketing rock star and any firm would be lucky to employ him. And, I relish the opportunity to help another grad enter the world of marketing fully knowledgeable with the skill set to market themselves successfully.

How to Be a Good Data Scientist

I guess no one wants to be a plain “Analyst” anymore; now “Data Scientist” is the title of the day. Then again, I never thought that there was anything wrong with titles like “Secretary,” “Stewardess” or “Janitor,” either. But somehow, someone decided “Administrative Assistant” should replace “Secretary” completely, and that someone was very successful in that endeavor. So much so that, people actually get offended when they are called “Secretaries.” The same goes for “Flight Attendants.” If you want an extra bag of peanuts or the whole can of soda with ice on the side, do not dare to call any service personnel by the outdated title. The verdict is still out for the title “Janitor,” as it could be replaced by “Custodial Engineer,” “Sanitary Engineer,” “Maintenance Technician,” or anything that gives an impression that the job requirement includes a degree in engineering. No matter. When the inflation-adjusted income of salaried workers is decreasing, I guess the number of words in the job title should go up instead. Something’s got to give, right?

I guess no one wants to be a plain “Analyst” anymore; now “Data Scientist” is the title of the day. Then again, I never thought that there was anything wrong with titles like “Secretary,” “Stewardess” or “Janitor,” either. But somehow, someone decided “Administrative Assistant” should replace “Secretary” completely, and that someone was very successful in that endeavor. So much so that, people actually get offended when they are called “Secretaries.” The same goes for “Flight Attendants.” If you want an extra bag of peanuts or the whole can of soda with ice on the side, do not dare to call any service personnel by the outdated title. The verdict is still out for the title “Janitor,” as it could be replaced by “Custodial Engineer,” “Sanitary Engineer,” “Maintenance Technician,” or anything that gives an impression that the job requirement includes a degree in engineering. No matter. When the inflation-adjusted income of salaried workers is decreasing, I guess the number of words in the job title should go up instead. Something’s got to give, right?

Please do not ask me to be politically correct here. As an openly Asian person in America, I am not even sure why I should be offended when someone addresses me as an “Oriental.” Someone explained it to me a long time ago. The word is reserved for “things,” not for people. OK, then. I will be offended when someone knowingly addresses me as an Oriental, now that the memo has been out for a while. So, do me this favor and do not call me an Oriental (at least in front of my face), and I promise that I will not call anyone an “Occidental” in return.

In any case, anyone who touches data for living now wants to be called a Data Scientist. Well, the title is longer than one word, and that is a good start. Did anyone get a raise along with that title inflation? I highly doubt it. But I’ve noticed the qualifications got much longer and more complicated.

I have seen some job requirements for data scientists that call for “all” of the following qualifications:

  • A master’s degree in statistics or mathematics; able to build statistical models proficiently using R or SAS
  • Strong analytical and storytelling skills
  • Hands-on knowledge in technologies such as Hadoop, Java, Python, C++, NoSQL, etc., being able to manipulate the data any which way, independently
  • Deep knowledge in ETL (extract, transform and load) to handle data from all sources
  • Proven experience in data modeling and database design
  • Data visualization skills using whatever tools that are considered to be cool this month
  • Deep business/industry/domain knowledge
  • Superb written and verbal communication skills, being able to explain complex technical concepts in plain English
  • Etc. etc…

I actually cut this list short, as it is already becoming ridiculous. I just want to see the face of a recruiter who got the order to find super-duper candidates based on this list—at the same salary level as a Senior Statistician (another fine title). Heck, while we’re at it, why don’t we add that the candidate must look like Brad Pitt and be able to tap-dance, too? The long and the short of it is maybe some executive wanted to hire just “1” data scientist with all these skillsets, hoping to God that this mad scientist will be able to make sense out of mounds of unstructured and unorganized data all on her own, and provide business answers without even knowing what the question was in the first place.

Over the years, I have worked with many statisticians, analysts and programmers (notice that they are all one-word titles), dealing with large, small, clean, dirty and, at times, really dirty data (hence the title of this series, “Big Data, Small Data, Clean Data, Messy Data”). And navigating through all those data has always been a team effort.

Yes, there are some exceptional musicians who can write music and lyrics, sing really well, play all instruments, program sequencers, record, mix, produce and sell music—all on their own. But if you insist that only such geniuses can produce music, there won’t be much to listen to in this world. Even Stevie Wonder, who can write and sing, and play keyboards, drums and harmonicas, had close to 100 names on the album credits in his heyday. Yes, the digital revolution changed the music scene as much as the data industry in terms of team sizes, but both aren’t and shouldn’t be one-man shows.

So, if being a “Data Scientist” means being a super businessman/analyst/statistician who can program, build models, write, present and sell, we should all just give up searching for one in the near future within your budget. Literally, we may be able to find a few qualified candidates in the job market on a national level. Too bad that every industry report says we need tens of thousands of them, right now.

Conversely, if it is just a bloated new title for good old data analysts with some knowledge in statistical applications and the ability to understand business needs—yeah, sure. Why not? I know plenty of those people, and we can groom more of them. And I don’t even mind giving them new long-winded titles that are suitable for the modern business world and peer groups.

I have been in the data business for a long time. And even before the datasets became really large, I have always maintained the following division of labor when dealing with complex data projects involving advanced analytics:

  • Business Analysts
  • Programmers/Developers
  • Statistical Analysts

The reason is very simple: It is extremely difficult to be a master-level expert in just one of these areas. Out of hundreds of statisticians who I’ve worked with, I can count only a handful of people who even “tried” to venture into the business side. Of those, even fewer successfully transformed themselves into businesspeople, and they are now business owners of consulting practices or in positions with “Chief” in their titles (Chief Data Officer or Chief Analytics Officer being the title du jour).

On the other side of the spectrum, less than a 10th of decent statisticians are also good at coding to manipulate complex data. But even they are mostly not good enough to be completely independent from professional programmers or developers. The reality is, most statisticians are not very good at setting up workable samples out of really messy data. Simply put, handling data and developing analytical frameworks or models call for different mindsets on a professional level.

The Business Analysts, I think, are the closest to the modern-day Data Scientists; albeit that the ones in the past were less so technicians, due to available toolsets back then. Nevertheless, granted that it is much easier to teach business aspects to statisticians or developers than to convert businesspeople or marketers into coders (no offense, but true), many of these “in-between” people—between the marketing world and technology world, for example—are rooted in the technology world (myself included) or at least have a deep understanding of it.

At times labeled as Research Analysts, they are the folks who would:

  • Understand the business requirements and issues at hand
  • Prescribe suitable solutions
  • Develop tangible analytical projects
  • Perform data audits
  • Procure data from various sources
  • Translate business requirements into technical specifications
  • Oversee the progress as project managers
  • Create reports and visual presentations
  • Interpret the results and create “stories”
  • And present the findings and recommended next steps to decision-makers

Sounds complex? You bet it is. And I didn’t even list all the job functions here. And to do this job effectively, these Business/Research Analysts (or Data Scientists) must understand the technical limitations of all related areas, including database, statistics, and general analytics, as well as industry verticals, uniqueness of business models and campaign/transaction channels. But they do not have to be full-blown statisticians or coders; they just have to know what they want and how to ask for it clearly. If they know how to code as well, great. All the more power to them. But that would be like a cherry on top, as the business mindset should be in front of everything.

So, now that the data are bigger and more complex than ever in human history, are we about to combine all aspects of data and analytics business and find people who are good at absolutely everything? Yes, various toolsets made some aspects of analysts’ lives easier and simpler, but not enough to get rid of the partitions between positions completely. Some third basemen may be able to pitch, too. But they wouldn’t go on the mound as starting pitchers—not on a professional level. And yes, analysts who advance up through the corporate and socioeconomic ladder are the ones who successfully crossed the boundaries. But we shouldn’t wait for the ones who are masters of everything. Like I said, even Stevie Wonder needs great sound engineers.

Then, what would be a good path to find Data Scientists in the existing pool of talent? I have been using the following four evaluation criteria to identify individuals with upward mobility in the technology world for a long time. Like I said, it is a lot simpler and easier to teach business aspects to people with technical backgrounds than the other way around.

So let’s start with the techies. These are the qualities we need to look for:

1. Skills: When it comes to the technical aspect of it, the skillset is the most important criterion. Generally a person has it, or doesn’t have it. If we are talking about a developer, how good is he? Can he develop a database without wasting time? A good coder is not just a little faster than mediocre ones; he can be 10 to 20 times faster. I am talking about the ones who don’t have to look through some manual or the Internet every five minutes, but the ones who just know all the shortcuts and options. The same goes for statistical analysts. How well is she versed in all the statistical techniques? Or is she a one-trick pony? How is her track record? Are her models performing in the market for a prolonged time? The thing about statistical work is that time is the ultimate test; we eventually get to find out how well the prediction holds up in the real world.

2. Attitude: This is a very important aspect, as many techies are locked up in their own little world. Many are socially awkward, like characters in Dilbert or “Big Bang Theory,” and most much prefer to deal with the machines (where things are clean-cut binary) than people (well, humans can be really annoying). Some do not work well with others and do not know how to compromise at all, as they do not know how to look at the world from a different perspective. And there are a lot of lazy ones. Yes, lazy programmers are the ones who are more motivated to automate processes (primarily to support their laissez faire lifestyle), but the ones who blow the deadlines all the time are just too much trouble for the team. In short, a genius with a really bad attitude won’t be able to move to the business or the management side, regardless of the IQ score.

3. Communication: Many technical folks are not good at written or verbal communications. I am not talking about just the ones who are foreign-born (like me), even though most technically oriented departments are full of them. The issue is many technical people (yes, even the ones who were born and raised in the U.S., speaking English) do not communicate with the rest of the world very well. Many can’t explain anything without using technical jargon, nor can they summarize messages to decision-makers. Businesspeople don’t need to hear the life story about how complex the project was or how messy the data sets were. Conversely, many techies do not understand marketers or businesspeople who speak plain English. Some fail to grasp the concept that human beings are not robots, and most mortals often fail to communicate every sentence as a logical expression. When a marketer says “Omit customers in New York and New Jersey from the next campaign,” the coder on the receiving end shouldn’t take that as a proper Boolean logic. Yes, obviously a state cannot be New York “and” New Jersey at the same time. But most humans don’t (or can’t) distinguish such differences. Seriously, I’ve seen some developers who refuse to work with people whose command of logical expressions aren’t at the level of Mr. Spock. That’s the primary reason we need business analysts or project managers who work as translators between these two worlds. And obviously, the translators should be able to speak both languages fluently.

4. Business Understanding: Granted, the candidates in question are qualified in terms of criteria one through three. Their eagerness to understand the ultimate business goals behind analytical projects would truly set them apart from the rest on the path to become a data scientist. As I mentioned previously, many technically oriented people do not really care much about the business side of the deal, or even have slight curiosity about it. What is the business model of the company for which they are working? How do they make money? What are the major business concerns? What are the long- and short-term business goals of their clients? Why do they lose sleep at night? Before complaining about incomplete data, why are the databases so messy? How are the data being collected? What does all this data mean for their bottom line? Can you bring up the “So what?” question after a great scientific finding? And ultimately, how will we make our clients look good in front of “their” bosses? When we deal with technical issues, we often find ourselves at a crossroad. Picking the right path (or a path with the least amount of downsides) is not just an IT decision, but more of a business decision. The person who has a more holistic view of the world, without a doubt, would make a better decision—even for a minor difference in a small feature, in terms of programming. Unfortunately, it is very difficult to find such IT people who have a balanced view.

And that is the punchline. We want data scientists who have the right balance of business and technical acumen—not just jacks of all trades who can do all the IT and analytical work all by themselves. Just like business strategy isn’t solely set by a data strategist, data projects aren’t done by one super techie. What we need are business analysts or data scientists who truly “get” the business goals and who will be able to translate them into functional technical specifications, with an understanding of all the limitations of each technology piece that is to be employed—which is quite different from being able to do it all.

If the career path for a data scientist ultimately leads to Chief Data Officer or Chief Analytics Officer, it is important for the candidates to understand that such “chief” titles are all about the business, not the IT. As soon as a CDO, CAO or CTO start representing technology before business, that organization is doomed. They should be executives who understand the technology and employ it to increase profit and efficiency for the whole company. Movie directors don’t necessarily write scripts, hold the cameras, develop special effects or act out scenes. But they understand all aspects of the movie-making process and put all the resources together to create films that they envision. As soon as a director falls too deep into just one aspect, such as special effects, the resultant movie quickly becomes an unwatchable bore. Data business is the same way.

So what is my advice for young and upcoming data scientists? Master the basics and be a specialist first. Pick a field that fits your aptitude, whether it be programming, software development, mathematics or statistics, and try to be really good at it. But remain curious about other related IT fields.

Then travel the world. Watch lots of movies. Read a variety of books. Not just technical books, but books about psychology, sociology, philosophy, science, economics and marketing, as well. This data business is inevitably related to activities that generate revenue for some organization. Try to understand the business ecosystem, not just technical systems. As marketing will always be a big part of the Big Data phenomenon, be an educated consumer first. Then look at advertisements and marketing campaigns from the promotor’s point of view, not just from an annoyed consumer’s view. Be an informed buyer through all available channels, online or offline. Then imagine how the world will be different in the future, and how a simple concept of a monetary transaction will transform along with other technical advances, which will certainly not stop at ApplePay. All of those changes will turn into business opportunities for people who understand data. If you see some real opportunities, try to imagine how you would create a startup company around them. You will quickly realize answering technical challenges is not even the half of building a viable business model.

If you are already one of those data scientists, live up to that title and be solution-oriented, not technology-oriented. Don’t be a slave to technologies, or be whom we sometimes address as a “data plumber” (who just moves data from one place to another). Be a master who wields data and technology to provide useful answers. And most importantly, don’t be evil (like Google says), and never do things just because you can. Always think about the social consequences, as actions based on data and technology affect real people, often negatively (more on this subject in future article). If you want to ride this Big Data wave for the foreseeable future, try not to annoy people who may not understand all the ins and outs of the data business. Don’t be the guy who spoils it for everyone else in the industry.

A while back, I started to see the unemployment rate as a rate of people who are being left behind during the progress (if we consider technical innovations as progress). Every evolutionary stage since the Industrial Revolution created gaps between supply and demand of new skillsets required for the new world. And this wave is not going to be an exception. It is unfortunate that, in this age of a high unemployment rate, we have such hard times finding good candidates for high tech positions. On one side, there are too many people who were educated under the old paradigm. And on the other side, there are too few people who can wield new technologies and apply them to satisfy business needs. If this new title “Data Scientist” means the latter, then yes. We need more of them, for sure. But we all need to be more realistic about how to groom them, as it would take a village to do so. And if we can’t even agree on what the job description for a data scientist should be, we will need lots of luck developing armies of them.

Mobile Isn’t Just About Marketing

When we talk about mobile, it’s often about how we can leverage it to market offers that connect with our customers and drive engagement or sales. … You need to determine what you’re trying to accomplish and then see if mobile could help you achieve that goal. Mobile may not always be the answer. Yes, the mobile guy just said that mobile will not always be the answer.

When we talk about mobile, it’s often about how we can leverage it to market offers that connect with our customers and drive engagement or sales.

The other day, I had someone call me for advice and he was interested in leveraging mobile in his business-to-business-focused company that optimized shipping/boxing for small- to medium-sized companies.

He was unclear on how to use mobile to market to other businesses that might be interested in his company’s services and was sort of skeptical that mobile really could even work for B-to-B companies.

I asked him a simple question: “What problem are you trying to solve or are you using mobile for mobile’s sake?”

He was sort of confused for a second and asked if I could clarify. I explained that he gave off the impression that he didn’t really know why he was interested in using mobile in his business other than that people are talking about it.

You see, just like this gentleman, you need to determine what you’re trying to accomplish and then see if mobile could help you achieve that goal. Mobile may not always be the answer. Yes, the mobile guy just said that mobile will not always be the answer.

The most unique aspect of mobile is its utility. When it comes down to it, mobile can do, and be, a lot for your business that doesn’t involve marketing. You just have to approach it strategically and not tactically to start to see it this way.

Don’t jump to tactics. Trust me, you won’t find success that way.

The most successful uses of mobile are ones that are so seamless that your customers even forget they are using a mobile device.

Because mobile threads through all of our daily experiences, you should look to use mobile to help solve a business problem or eliminate inefficiencies.

I wanted to share three ways mobile can impact your business that aren’t directly tied to a marketing initiative.

Solve an Operational Problem

Not too long ago, I interviewed the head of mobile for Yamaha. We chatted about how they’ve slowly integrated mobile into their operations over the last two to five years. Yamaha originally thought it’d leverage mobile to connect with customers. But, little to their surprise, their dealers and dealer staff began leveraging the tablet application to sell on the floor.

Boats are expensive … As a dealer, you can’t afford to have every single model with every single feature on the showroom floor. So, Yamaha’s sales teams used the app to show customers what a specific product may look like or cost by using their consumer-facing tablet application.

Yamaha realized this was creating a more efficient system to deliver the latest and greatest content to the dealers and make sure everyone was showcasing the most up-to-date materials.

Shortly thereafter, they eliminated delivering printed materials for dealers and equipped them all with tablets and can now deliver the latest product information on the fly.

At the end of the day, the dealers were able to engage with customers and showcase products that would never have to be on the floor to help close deals and give the best customer experience. Oh, and they even saved money from their continual printing costs.

So, if you have a sales or business development team, think about leveraging mobile to enable them to do their job better, more efficiently and always be equipped with the knowledge they need out in the field.

Your Product or Service Can Be Mobile

Have you ever used the app Hotel Tonight or Uber? If you haven’t, you should check them out as both of these businesses rely on the mobile device to deliver amazing customer experiences. Their apps drive their business by delivering a utility to their customer.

Hotel Tonight lets you find last-minute specials on hotel rooms in the city you’re in. When you open the app, the latest room rates will display around midday and you can book for that evening.

They don’t let you book hotels in advance … only that day and that day alone.

Uber is an application that lets you request a private driver based on your location. You can order a taxi, a black car or even a nice SUV. When you need a ride, you open the app and you can see all the vehicles in your proximity. When you request a driver, the app notifies all drivers in the near proximity that you’d like a ride.

Shortly thereafter, you see which driver is coming to pick you up and the time it will take for them to get to your pick up destination. The whole business is powered via this app. Your credit card is on file, so you never even exchange any cash. The tip is included and you pay a slight premium for the service, but it’s amazing.

I was just in San Francisco for five days and used it frequently to get around. I never had to flag a cab on the corner—I just pulled out my phone and, in minutes, I was on my way.

You see, both Uber and Hotel Tonight generate business by offering their customers an easy-to-use tool right on their phones to accomplish tasks that were once a pain to complete.

These are two great examples of leveraging mobility AS your business.

Mobile Can Be a Training or Education Tool

I follow two online marketers and business owners who recently launched their own apps as a part of their overall business. Now, they didn’t just go and repurpose their content from their site and put it in an app.

They wanted to deliver tremendous value that helped their customers.

Ramit Sethi, a blogger and best-selling author of “I Will Teach You To Be Rich,” teaches people how to earn money on the side and get their dream jobs.

Over the last few years of studies and research he was able to give his students word-for-word scripts to help them get a raise, get a job, work from home and much more.

He knows a lot of the situations he trains his students for don’t happen at home … they happen while they are out and about nowhere near a computer to refer to these resources.

So what did Ramit do?

He built an app called Negotiate It that includes scripts to help you negotiate just about anything. You can open the app and find scripts to use to lower your credit rate, lower your credit bill, get a raise at your job and a ton of other common situations. He even charged about $4 and turned it into a revenue-generating product that was solving a super-specific need for his students.

Then there is Grant Cardone. He is an amazing salesman and businessperson. He frequently trains people about how to better sell and sell “the right” way that can actually impact your business.

He decided to create a mobile app called CloseTheSale, which offered scripts of closing techniques for just about every single scenario you can think of. They all have clever names and you can refer to the app whenever you’re preparing for a big sales meeting or you want a quick selling strategy to learn.

Both of these guys realized that creating an app would allow them to put so many valuable lessons in the palm of their customers’ hands to help them reach their own goals. Very specific use cases, but both demonstrate how mobile can be a training or educating tool for your customers.

As you can see, mobile doesn’t have to be a marketing tool. In some ways, these three examples indirectly affect your marketing. But their main purpose stems from something entirely different …

So, I challenge you to first ask yourself if you’re just doing mobile for mobile’s sake. If you are, you need to re-evaluate your “why” immediately.

If you’re about to get started using mobile in your business, be sure to have a problem you’re trying to solve, a process you’re trying to optimize or a product or service that could best be used by a consumer’s mobile device.

What are some non-marketing use cases you’ve seen with mobile?