Silicon Valley State of Mind, a blog by John Weathington, "The Science of Success"
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    Welcome to a Silicon Valley State of Mind, thoughts tips and advice based on the consulting work of John Weathington, "Silicon Valley's Top Information Strategist."

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Silicon Valley State of Mind

Tips, thoughts, and advice based on the consulting work of John Weathington, "The Science of Success."

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Posted by on in Information Exploitation

If you can’t get your data scientists and other analytics to be concise, you’ll never get anything done. To make the most effective use of your time, educate and coach your analytics on how to be concise.

As much as I love working with data scientists, this has to be the most frustrating part of my job. Analytic managers and consultants like me are responsible for getting things done; however, the very talented resources we deal with value brilliance over deadlines.

Notwithstanding their analytic disposition, everyone–including your data scientists–wants to succeed. To succeed, they’ll need to be concise: in their speech, in their writing, and even in their approach to solving difficult problems. Here are my seven best tips for making that happen.

Tip # 1: Analyze the Impact

You must do your homework before you broach the subject of concision. At the onset concision is very uncomfortable with analytics, so they’ll need to rationalize it for themselves before they unseat their de facto behavior. So when in Rome, do as the Romans. Do some research on the benefits of concision and the costs of not being concise, and prepare some analysis.

In my experience, you can double or triple your productivity, when your team effectively practices concise behaviors. You’ll need the numbers for your specific situation to make it relevant. High-level studies are interesting, but when the analysis is brought into their reality, it becomes impactful.

Tip # 2: Communicate the Need

Armed with your analysis, you must let them know what your intentions are. You can do this formally or informally, depending on the structure of your organization. I like informal–it’s better for engagement; however, do whatever you feel works best. Double- and triple-check your analysis; remember, you’re dealing with people who can spot a hole in your analysis a mile away.

This should be an engagement, not a communication. Engagement implies dialog and discussion. Listen to what they have to say: their feedback and concerns. Make them understand that you understand. If they don’t voice any concerns, they’re either not listening or not internalizing the implications of the message. Continue the dialog until they stop head-nodding and start sharing.

Tip # 3: Teach Them How

Concision is a skill that needs to be taught. Work with your team coach, Human Resources, or an external consultant to design a program that teaches concision. The facilitator should be familiar working with analytics—they are a special breed when it comes to this type of instructional design. Analytics have always been good at whatever they try to learn; you’re asking them to learn something they won’t initially be good at. It takes finesse to navigate through this human dynamic.

Tip # 4: Show Them How

Modeled behavior should follow education. Once your analytics have some guidelines to ponder, they’ll want to see it modeled in exemplars. The analytic manager on a data science team should be the paragon of concise behavior. Shorten one hour working sessions to thirty minutes and eliminate status meetings altogether. When documents are created or reviewed, focus on communicating the most amount of information in the least amount of space, with the question, point, or thesis within the first few sentences.

Tip # 5: Help Them Build

Be encouraging and supportive, not critical or condescending. Analytics are especially sensitive to skills they can’t quickly master. Give them time to grow and they’ll eventually come around. In addition to modeling concise behavior, I suggest introducing them to a well-written newspaper like the New York Times or the Wall Street Journal. I receive regular email alerts from the Wall Street Journal. They’re usually a hundred words or less do a great job of communicating breaking news within a few seconds.

Tip # 6: Give Them Feedback

Give them positive feedback when concision is done right. They won’t do it right for some time, so here’s where you have to be very careful. Criticizing an analytic for rambling or producing a tome when a brief will suffice, is a natural tendency that should be avoided. Even when it’s in the spirit of improvement, highlighting any shortcomings should be done with care. In this situation, just ask them to produce a more concise version, and be specific. I once had a data scientist give me a 50-page PowerPoint of all words. My feedback was that it had a lot of great content, but I’d need a 2-page process visual to call it done.

Tip # 7: Give Them Kudos

When you see your analytics exhibit concise behavior, whether a brief response or a quick turnaround on a priority deliverable, make a big deal out of it. Constructive feedback should always be done in private, but exemplary behavior should be well publicized. Leaders should support analytic managers in this effort; even a handshake from a higher-up is a big deal to most people. Everyone appreciates kudos, but more importantly when analytics see their peers getting rewarded, they take notice.

Summary

Be concise, and coach your analytics to do the same–enough said.

Submitted for Publication in TechRepublic’s Big Data Analytics Blog

This is the sneak peak of my latest contribution to TechRepublic’s Big Data Analytics Blog. As editors do, when this gets published, some of the words and content may be arranged or deleted for a variety of reasons including SEO. What you’re looking at here is the uncut, unabridged, unedited version of the article that was submitted.

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Posted by on in Information Exploitation

Are you noticing anything wrong with your data science team?

I'm sure you are; it's human nature. A client recently told me that she came home one day and noticed that there was a water-filled glass sitting directly on a wood table. She asked her husband, "Where is the coaster for this glass?" Her husband responded, "That's what you noticed? I just finished cleaning the entire house!"

I see a lot of leaders frustrated with their data science team. They've spent a lot of money so the have very high expectations. In consulting, we call that White Knight Syndrome, and I deal with it all the time. So when things don’t go as expected, they go down a very classic route of identifying gaps and solving problems. Not only is this enervating, but it's a reckless abuse of your data science team's potential. It's far better to build on the strengths of your data science team, than it is to improve on their weaknesses. Here are five things to absolutely love about your data scientists.

They Fuel An Uncatchable Competitive Advantage

Your data science team is a key ingredient for a breakthrough competitive advantage. This is no joke; so don't ever overlook this fact. They tackle unsolvable problems for fun, in a way no other profession can. Most people take for granted how the data scientists at Google have changed the world, with a search engine that was late to the party. Sure, the leaders had the vision that powerful search capabilities would equate to market domination; however, it was the data scientists that figured out to jump into our brains, figure out what we were trying to find, and bring back the most relevant results. Google's data scientists made it one of the most powerful organizations in the world.

They're A+ Students In School and Life

Data scientists learn fast and retain extremely well. They've done it their whole lives. Most data scientists you encounter excelled in school—4.0 GPA in high school and college. And although you would expect them to get good grades in computer science and math, remember that a computer science degree has more than just computer science classes. Data scientists don't only get good grades in math and science; they get good grades in everything. Don't be shy about bringing them into your business world. They'll start contributing real value faster than you realize.

They Deliver No Matter What

Data scientists are extremely loyal under the right conditions--sometimes to a fault. I can't count the number of times I've been roped into an all-nighter because of situations far out of my control. We dig in and we deliver anyway; it's part of that excellence gene that I referenced earlier. The only thing you need to do is setup the right conditions, which has more to do with job satisfaction than money (although a good paycheck doesn't hurt either). Data scientists love to create data masterpieces with people they enjoy. With the right environment and the right challenge, they'll stay with you all the way.

They Are A Magnet For Other Talent

It seems like everybody's having a hard time finding good data scientists, except for other data scientists. If you're a leader, you probably know a lot of other leaders; so, guess who data scientists hang out with? You guessed it--other data scientists. This is important to you on a number of levels. If you ever need to extend your team, the best source for finding more data scientists is the team you already have. Also, the data scientist community is very supportive. So if your team actually gets stuck on a problem, there's a huge brain trust at their disposal that's ready and willing the help.

They Save Your From Yourself

Data scientists think through everything before making a decision. This will and should drive you crazy if you're an impulsive leader. Impulse is good for immediate action, but like all things the best results come from Aristotle's golden mean--the desirable middle between two extremes. At one extreme is a knee-jerk reaction that gets you into trouble (sound familiar?) and at the other extreme is analysis paralysis. The trick is to get the right balance, and you won't do that without the counsel and reason of your data scientists. You may think you have a good idea, but it won't sit right with your data scientists until there's data, research, and analysis. This voice will save your assets more times than not.

Summary

Identifying problems and closing gaps with your data science team will only bring you status quo; however, identifying strengths and raising the bar will catapult you to a place nobody can catch. Instead of obsessing about what's wrong; invigorate your organization by using the strengths within your data science team. There's a lot to love: they're extremely bright, loyal, and precise. Make this your starting point and enjoy your immaculate house, instead of worrying about a missing coaster.

Submitted for Publication in TechRepublic’s Big Data Analytics Blog

This is the sneak peak of my latest contribution to TechRepublic’s Big Data Analytics Blog. As editors do, when this gets published, some of the words and content may be arranged or deleted for a variety of reasons including SEO. What you’re looking at here is the uncut, unabridged, unedited version of the article that was submitted.

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Posted by on in Leadership

Do happy employees create successful organizations? Well, according to Glassdoor, the happiest companies in Silicon Valley are:

  1. Facebook
  2. Google
  3. LinkedIn
  4. Apple
  5. Informatica
  6. Shutterfly
  7. NetApp

After scanning this list, I’d say these companies are pretty successful. And although it’s debatable which came first—success or happy employees—most of the extant literature on organizational development confirms the great contribution that happy employees make to successful companies. Personally, I’ve worked with many companies over my illustrious career as a consultant, and I can attest that I’ve made far more valuable contributions to companies when I was having fun.

Happiness works differently for various people; however, I can give you some insights when it comes to analytics: data scientists, analysts, and most IT professionals:

Smart people like working with other smart people.

I had lunch last week with Sridhar, a good friend of mine who currently manages a team of IT professionals at StubHub. We were previously partners in crime at Hitachi Data Systems and together we solved some of its difficult challenges. At one point during the lunch he said, “I just like solving problems with other smart people.” The comment struck a chord with me that stayed for a while.

It was harmonious with a discussion I had earlier with Jennifer Selby Long, a brilliant management consultant who develops leaders. Jennifer and I are looking to pair up on an estimable intervention at a local telecommunications company. At one point while working through the proposal she said, “This one may be tough, but I just love working on difficult problems with other smart people.”

Of course there are other factors that contribute to employee happiness; however, for smart people, this is an important one. Make sure to surround your smartest people with other smart people. Oh—and a huge salary doesn’t hurt either.

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Posted by on in Strategy

Happy Tuesday, folks! I hope everyone had a fun and relaxing Memorial Day weekend. I sure did; Kim and I lounged around all weekend, usually doing something close to nothing. If you know me at all, you know cooking was on the agenda; however, this year I went a little mellow compared to some of the other holidays. I need to drop some pounds, so I started on Atkins a few weeks back. It’s going pretty well so far; I’m down about 7 or 8 pounds. One adjustment that I thought was going to be tough was eating more vegetables; however, it has pleasantly turned out well. The key I’ve found is this: the right ingredients make all the difference—that’s true with diets and it’s true with strategy.

One thing I’ve really grown to love is tomatoes. Before starting the diet, I would rarely eat tomatoes; however, now I eat two to three every day. And now that I’m a tomato connoisseur, I’ve noticed that not all tomatoes are created equal. Sure, Roma tomatoes will not taste like Beefsteak tomatoes. What matters more though is where I get the tomatoes from. The tomatoes from Safeway aren’t as good as the same type of tomatoes from Whole Foods; and these aren’t as good as the same type of tomatoes from Windmill Farms (they carry a lot of fresh produce from local farmers). The tomatoes on the vine at Windmill Farms are awesome and the same type of tomatoes from Safeway are barely okay, even though they look similar.

Selecting people for your strategy—whether they’re full-time employees or consultants—is like selecting tomatoes. The talent differential between average, good, and great is sizable; and looks can be deceiving. It astounds me every time I come across someone from a big-name firm like McKinsey, Deloitte, or Accenture, who doesn’t know the difference between strategy and long-range planning. Or, an Executive Vice President with an MBA who cannot make a decision.

One of the critical elements of executing a successful strategy, is making sure you have the right people on your team. Selection is crucial—you don’t want to end up with a bunch of sour tomatoes.

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Posted by on in Leadership

A few hours in Fry’s Electronics gives me powers beyond belief. I spent the whole day yesterday meeting with clients in Campbell and Sunnyvale. An unexpected call at around 4:00 PM put me on the 880 Freeway at around 5:00 PM when it’s in parking lot status. After inching my way to Mission Boulevard, I decided to stop off at Fry’s Electronics—my Fortress of Solitude. I entered tired and weary from a long day of meetings and emerged with the vigor to conquer Mount Everest (okay, maybe I’ll start with Mount Diablo). Burnout drains talent; understanding how to recharge your analytic team is vital to getting the most from them—both in productivity and loyalty.

Like most analytics, I’m an introvert (INFJ for those who understand what this means). If you lead and/or manage a team of analytics, it’s important to understand how introverts work. There are many misconceptions. Contrary to popular belief, introverts like being in social settings, have no problem voicing their opinion, typically have a great sense of humor, and can be very fun to hang out with.

The accurate distinction between introverts and extroverts is where their locus of energy lies. Introverts revitalize when they’re alone. They’ll function fine in a social setting; however, their battery is draining quicker than extroverts. If you put them in meetings all day or extended team-building exercises, they will quickly burn out.

To protect your analytic team from burnout, schedule downtime for them: especially on the heels of extended and extensive social interaction. A field trip to Fry’s Electronics from time to time might not be a bad idea either.

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