Harvard Business Review: Stop People from Wasting Your Time

By Dorrie Clark

We’re all too busy, spending our days in back-to-back meetings and our nights feverishly responding to emails. (Adam Grant, a famously responsive Wharton professor, told me that on an “average day” he’ll spend 3-4 hours answering messages.) That’s why people who waste our time have become the scourge of modern business life, hampering our productivity and annoying us in the process.

Sometimes it’s hard to escape, especially when the time-waster is your boss (one friend recalls a supervisor who “called meetings just to tell long, rambling stories about her college years” and would “chastise anyone who tried to leave and actually perform work”). But in many other situations, you can take steps to regain control of your time and your schedule. Here’s how.

State your preferred method of communication. For years, millennials have famously eschewed phone calls — but almost everyone has a communication preference of some sort. Regina Walton, a social media and community manager, told me that she, too, hates talking on the phone, a habit she developed after years of living abroad; email is almost always better for her, as “I can respond when I have time and usually am very fast to reply.” You can often limit aggravation (and harassment via multiple channels) by proactively informing colleagues about the best way to reach you, whether it’s via phone calls, texts, emails, or even tweets.

Require an agenda for meetings. Pointless or rambling meetings account for a disproportionate share of workplace time leakage. Here’s a solution: insist on seeing an agenda before you commit to attending any meeting, “to ensure I can contribute fully.” You can model the practice by writing an agenda for any meetings you chair, and offering to share the template with others. In fact, you could push to

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Harvard Business Review: Hire Great Guessers

By Michael Fertik

Analytics are now king. And they should be. (If you're not already convinced, read Competing on Analytics, one of the best HBR articles I've ever read). It's so much easier to collect and digest numbers on your business than it was even ten years ago.


No less than 5% of your payroll should go toward data analysis. Who is your customer? What is she buying? How often? After what event(s)? Which version of the product sells better? At which price point? Which version of the packaging is more appealing? Which salesperson is more effective with which customer cohort? What zip code is responding most to your ad? How quickly/reliably/effectively does your product accomplish its stated goal, or your vision for it? How satisfied are your customers?

Your analysts should be setting up systems to collect these data streams and then chugging through the numbers to help you drive the company.

However! Test a bad premise, and your analytics will be pretty useless. If your entire question is wrong (e.g. "Do customers prefer the 200-ounce burger to the 250-ounce burger?"), you'll get bad answers.

Marty Cagan, a thought leader on product development, wrote a piece distinguishing "product discovery" from "product optimization". He explains that product discovery — prototyping, user testing — is the right way to identify "significant new functionality" and product optimization — analytics-based A/B testing — is the correct way to "optimize the user experience and/or business results of an existing product." His implicit point is that analytics about the customer experience are a waste until you have some early feedback on the product or feature idea to know whether you are even in the zone of test-worthiness.

Marty is right. (Full disclosure: he advises my company, ReputationDefender.) However, there's more to it than his essay suggests. The jump from discovery to optimization requires good guesses. Without good guessers, the project is doomed. Good guessers know what is worth investigating in the first place. And they have strong instincts — usually coupled with a knack for scrappy, lightning-fast research — into where the best bets lie. They are great not just at product dev, but at hiring, market development, strategy, vendor selection, advertising, and market segmentation and definition.

Take our burger example. Let's imagine three versions of the story:

Version 1. A bad guesser may actually entertain the notion that a 12-pound burger will have market appeal. Fire him politely but immediately. The focus group he wants to set up will drain time and resources.

Version 2. If we modify the scenario and call it a repositioning exercise, in which a giant patty is tested as a "family burger," to be ordered and consumed like a family-sized pizza, it might be worth a second look. But it's still not an obviously great guess.

Version 3. But what if the idea was to make a twelve-ounce burger with small ridges at the edges, so that the condiments don't slide out quite as easily? That could be worth testing.

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The Best NYT Business Columnist You've Never Heard Of

Michael Schrage at the Harvard Business Review blogs that it is Steven Strogatz.

Schrage writes:

...his columns have quickly become "must reads" for entrepreneurs and executives who grasp that mathematics is now the "lingua franca" of serious business analysis. There is no better English-language explicator of complex quantitative concepts than Steven Strogatz. His work is a model for how mathematics needs to be popularized

Here's Strogatz on doctors, the OJ Simpson case and probability. After reading this, you will realize that statistics can not only lie, but really confuse.