Reinventing the To-Do List: A Multi-billion Dollar Opportunity

October 10, 2013 Editor 0

Gotta love Dan Markovitz’s post decrying to-do lists. Contrarian, yes.  But it unfortunately ignored the digitally-enhanced tomorrow made possible by the very device you’re reading this on.

To-do lists, in fact, will likely be the internet’s next multibillion dollar global innovation. The only serious question is whether the to-do breakthroughs come from Google, Amazon, Microsoft, Apple, LinkedIn or a Zuckerberg yet to emerge from the venture capital chrysalis. To-do lists are too big, too rich and too transcendent a business and technical opportunity to ignore. All the digital ingredients exist; what’s missing is the right intrapreneurial—or entrepreneurial—master kitchen to mix them.

Multibillion dollar markets in gray market to-do lists already exist; they’re called recommendation engines.  Amazon and Netflix have effectively branded themselves as superior recommenders. Those Web 2.0 innovators succeed through blending algorithmic alchemy and data-driven decisions into user experiences inviting exploration, sampling and outright purchase. You’re under no obligation to do any of those things, of course. But the odds are you— rightly—take many of those recommendations seriously. The better their recommendations, the more you trust their judgment. They’ve little incentive to squander your time or their credibility.

Google, of course, is the ultimate recommendation engine. Gmail increasingly nudges and autosuggests other folks who you might want to copy on that email you’re sending. Microsoft’s “Outlookification.com” of email similarly sets the digital stage for a powerful new genre of recommendation integration. Do you sync your iPhone and/or Android with your tablet and/or laptop, too?

Consider: A Google and/or Microsoft and/or Apple likely has access to your calendar, your address book, your email, your apps and most of your searches. Because you’re probably using your devices to help manage every single aspect of your life, those companies have excellent insight into both your personal and professional life. If you provided Facebook, LinkedIn and Amazon with calendar/schedule access, they’d have similarly rich visibility into what you’re doing and how you plan to spend/invest your time.

Now make the obvious leap: How difficult do you think it would, could or should be for a Google, Microsoft, Amazon, Apple or LinkedIn to engineer recommendation engines that generate custom to-do lists based on that ever-growing embarrassment  of real-world  data riches.  Not very. They have all the algorithms and infrastructures they need to provide as targeted —or as comprehensive—a weekly/daily/hourly/real-time to-do list you think you might want or need.

Wake up in the morning, for example, tap your Google/Microsoft/Amazon “TDL” icon — or whisper “to do” to your Google Glass—then skim the day’s Top Ten List of what you should do based on an algorithmic scan and review of your calendar, phone calls, Fitbit/Jawbone, Facebook status reports, twitterstreams, etc. Your RTDs—recommended to-dos—could be as simple and straightforward as a list of people to call or email or as sophisticated as minute-by-minute day plan decision tree suggesting a variety of different options depending on how much you want to accomplish.

What kind of recommended to–dos would influence or inspire you most?

To-do lists could be tunable; you could ask for to-do lists with recommended reminders for you to do a better job of keeping in touch with friends and family or being more productive at work. Make personal, professional or some happy medium between.  Your to-do list could only appear at the beginning and end of each day or be programmed to pop-up intrusively when you perform unscheduled or time-wasting tasks. To-do lists could be further operationalized with Thaler-ian “nudges” and/or Schelling-esque “precommitments.” Your to-do recommendations could be as instantly perishable as a text or persist as the daily interface for auditable achievement.

Of course, just like a Netflix or Amazon recommender, your to-do list will learn from the to-dos you actually do and the ones you consistently defer or ignore outright. Do you want to train your to-do list to suggest the activities and obligations you most enjoy and effectively achieve? Or do you want your RTD reminding you to take the essential next steps to finish the tasks you most loathe?  Just as people appreciate the occasional oddball movie or television recommendation from a Netflix, you’d likely want the usefully surprising to-do recommendation suggesting luck with a LinkedIn contact or buying a friend a gift.  Are you the kind of person who wants a master recommended to-do list? Or would you be better off managing a portfolio of recommended to-dos for review—like a stock portfolio?

The power and virtue of recommendations is that they are just that: recommendations, not obligations. But just as someone would learn a lot about you seeing the movies and shows recommended by Netflix or the books and products Amazon recommends or the searches you’re performing on Google and/or Bing, people would gain enormous insight into who you are and what you want to become if they could monitor your recommended to dos and track which ones you acted upon.

To-do lists offer a fantastic organizing principle for integrating the physical and digital elements of people’s lives. As surely as recommendations changed the way people shop on Amazon, binged on Netflix and listened to music on Spotify and Pandora, they’re going to transform how people prioritize their time.

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Categories: HBR, Insights

Tags: Computing, Human–computer interaction, linkedin, Recommender system, World Wide Web