Not an entirely silly rhetorical question — in our work world of endless data aggregation and analysis, the reading of books remains a curiously solitary and hard-to-track enterprise.
It’s easy enough to hand someone a book. It’s easy enough to require a signature acknowledging receipt and even demand answers to a compliance question or two to check headline-level comprehension.
But it’s hard to do anything with a book approaching a deep and actionable, let alone shared understanding of the content without classes and clubs — meaning that costly in-person conversations in and around the act of reading are still what makes reading, at least the extended kind, real and useful.
But for the corporate world, the idea of reading as a purely personal pursuit may be changing. Three developments — e-book readers, the advent of technology-mediated social reading and the X API (nee Tin Can) — together make books cost-efficient, communal and reportable in new ways.
e-book readers are now ubiquitous and cheap. Even general-purpose iOS and Android tablets support the e-pub standard. New services like Zola make reading a compelling group exercise (it’s very cool). Established services like Lulu let any company build its own libraries for private, on-demand distribution. The X API means that the reading of a book can be recorded by chapter and task in any competency framework a company may need.
I just read an article on Forbes magazine online about IBM CEO Ginni Rometty predicting three ways that technology will change the way we do business. The Forbes article was based on Ms Rometty’s speech at the Corporate Conference of the nonprofit Council on Foreign Relations. There is a video recording of this session here.
I couldn’t agree more with all the three ways that Ms Rometty analyses, and I believe all three of these ways profoundly affect the business we are in: human capital management. Here’s how:
- Analytics – data analytics are coming to HR and the ability to harness talent-related data affects every talent-related function from hiring, to training, to engagement, to career development, to succession planning, to retention, to compensation, to dismissal. Moreover, talent analytics provides the link between talent management processes, business metrics, and value creation.
- Social – it may sound like a cliché, but the new fabric of the enterprise is social and it is strategic. Social technologies are enabling employee collaboration, knowledge and expertise sharing, people search and team formation, informal learning, continuous coaching and mentoring, and peer recognition models in a way that transcends formal organizational structures and redefines strict HR transactional processes.
- Personalization – we see personalization into the talent management as targeted recruitment, personalized learning and development plans, on-demand performance support, workplace technology consumerization, and individualized career paths. This is the point when talent management is transformed from an HR-driven process to a business-driven one.
These three ways are not predictions into the future, but instead they are changing our business today. Thoughts?
David Brooks just wrote an opinion piece in The New York Times, What Data Can’t Do.
It’s really good; reasoned, nuanced, supported by relevant example and contextualized in the literature. Well worth reading.
It got me thinking about the limits of data-driven decision making in general. Bertrand Russell argued that no system can be understood by reference to anything from inside the system, no matter how clever the arguments. Ludwig Wittgenstein argued that nothing can be understood, or even adequately explained — period.
The data scientists are giving us amazing insights and trying to explain everything. They will doubtless continue to generate lots of actionable insight, including insight into the world of talent management, but they will fail at the “everything” part.
Everything is too tall an order.
Read Brooks’ piece. It’s food for thought.
Big Data is all the rage right now. Industry analysts and pundits of every stripe are singing the praises of analytics the way snake oil salesmen once hawked miracle potions to help us all live longer, healthier, more fulfilling lives.
Would that data analytics were as simple as buying a bottle of potion.
Josh Bersin, one of the best non-financial analysts covering the world of talent and HR solutions today, recently posted a blog piece that ended with a shout out to Moneyball, the Michael Lewis book (and now Brad Pitt movie) about The Oakland A’s.
For the two or three people in the world who don’t already know this story, the A’s manager Billy Beane hired a young statistician from Yale, a hitherto uncommon hiring choice in the world of Major League Baseball.
In an effort to create a winning team on a limited budget, the two men ditched the talent scout model for sourcing players and instead adopted serious statistical modeling, the equivalent of price arbitrage analysis in the world of finance.