It’s time to turn the focus and mechanisms of big data analytics onto the topics of our work tasks, projects, and careers. Organizations continue to apply more and more powerful analytics capabilities to customer identification, customer engagement, and strategic planning. Now it’s time to see what we can learn about how we approach our work and education. (And for those of you who want to know more about business analytics in general, I suggest Jain & Sharma’s new book, Behind Every Good Decision.)
Here is the slide deck from a talk I gave last week (click on the Notes icon within Slideshare for additional links for many of the slides). Predicitive analytics (e.g., analyses that suggest next steps — like Amazon suggesting other books based on your past purchases) offer huge benefits to how we think about the future of work, if we can get to the data.
From LinkedIn to Elance/oDesk, Coursera, & Watson
I've been studying the benefits of "computer monitoring" since 1984. It wasn't the book, 1984, that triggered my interest at that particular time, but rather being at Carnegie Mellon University where it was, and is, common to intermingle computers, analytics, and work.
In the above talk, I extrapolated from the predictive analytics that LinkedIn uses to suggest jobs which might interest us, to a future where some wonderful combination of a variety of platforms could do much more: Interlinked systems that would know the work we can do, how we’ve done at that work in the past, the people who need work, and even predict the skills we need to learn to move ahead in our goals. Such as system could improve on even the best organizational training and development departments. Here are just a few extant systems that might be at the heart of this approach:
- Elance /oDesk: Hugely successful platforms for linking people who want to do freelance project work with people who have project needs. Preferences and quality ratings from past work steer you to your next projects.
- Coursera : One of the top platforms for taking massive online open courses. They know what you know and what you are interested in and have talked about offering career services.
- IBM Watson : The artificial intelligence that won the gameshow Jeopardy! and is now supporting physicians, financial experts, and human resources directors in their daily work. I would love to see Watson become an ally in getting all of our work done. What do we want to do and what do we want to leave to Watson?
It isn’t much of a leap to see how these three platforms could work together to map out our medium term work futures. We know the projects that need to be done, it just takes a bit of prediction to line up the education that we need to be ready for the next projects.
The technology is likely there, but more of us need to be thinking about how to leverage more advanced technology systems. While teams of chess players have figured out how to ally with mid range computer programs to beat the best humans and super computers , my colleague Christine Isakson and I haven’t found much work on team configuration where machines are in the hiring pool. As Brynjolfsson & McAfee say, we need to learn to race with the machines, not against them.
Up Soon: How Might Google Help Us Plan Our Day?
The discussion above focused on mid range work goals: What project can I do now and what might I do next? What happens if we turn the lens of analytics onto our daily work? In an upcoming post, I’ll consider the combination of analytics and our daily work decisions. My homework:
- Automation Makes Us Dumb, from Nicholas Carr in the Wall Street Journal — thank you, Lucas Mayer for the reference during our discussion of Birst.
- Why Managers Still Matter, from Nicolai J. Foss and Peter G. Klein in the MIT Sloan Managment Review, includes a reference to my colleague in the other hemisphere, Tim Kastelle.
If you have thoughts to share about the above ideas, or this upcoming post, please let me know by commenting here. Also, thank you to IBM Almaden for the opportunity to give the November 20th, 2014, IBM Research Distinguished Speaker talk.