Dion Hinchcliffe recently took a look at the evolution of workplace collaboration technologies and the move toward data-driven control by organizational leadership.
But, as Constellation analyst Alan Lepovsky recently observed to me and I’ve had CIOs tell me on several occasions, the real play is the ability to peer deeply using machine learning into this collective intelligence to make better decisions based on ground truth that comes from what the organization as a whole actually knows. Essentially, it’s applying IBM’s Watson-style machine learning to the full collaborative output of your organization. – Dion Hinchcliffe , ZDNet
Dion concludes, “I predict that the digital organization of tomorrow will make the fullest of its most important information assets, especially the full measure of digital knowledge of its workers”. Is this the future? As minions scurry about, leaving traces of their collaboration and knowledge-sharing, managers will be able to see the whole picture and make informed decisions. This future reminds me of F.W. Taylor’s Principles of Scientific Management (1911).
It is only through enforced standardization of methods, enforced adoption of the best implements and working conditions, and enforced cooperation that this faster work can be assured. And the duty of enforcing the adoption of standards and enforcing this cooperation rests with management alone.
It’s a most interesting term, “enforced cooperation”, which could easily be added to the Newspeak dictionary of Orwell’s Nineteen Eighty-four. My own definition of cooperation is that it is freely sharing, without any expectation of direct reciprocity. No enforcement is needed.
In Frederic Laloux’s Reinventing Organizations, there is a story by Dennis Bakke, CEO of AES. This is a company that actively practices wholeness, self-management, and evolutionary purpose. The story is about one of his colleagues showing off a new IT system.
On his desk, he had a computer that had the control panel for the plant. “Dennis, I can essentially watch and control the operations from here. I can get one for you as well, and we can add all the new plants as they go commercial.” I told him not to bother and suggested he get rid of his as well. This kind of centralization can have a major negative effect on the workplace.
Laloux further states that there is nothing wrong with total information transparency, “as long as the data is supplied to everyone else”. We see this tendency to control data in consumer social networks as well, with media platforms using information asymmetry to sell behavioural insights to advertisers. If you are not paying for an online service, then you are likely the product. It may be true also that you are not really self-managed if you do not have total information transparency.
If the evolution of enterprise collaboration platforms is toward increased information asymmetry and more centralized control, then workers would be wise to get out of the modern enterprise as fast as possible. Of course, they will be told that the enterprise will only use ‘metadata’ to make its decisions, so everything will be just fine. You decide.
1984?
“If the evolution of enterprise collaboration platforms is toward increased information asymmetry and more centralized control, then workers would be wise to get out of the modern enterprise as fast as possible.”
My first employer made a big deal about not having time clocks, but they would monitor people based on their desk phone login records. I thought of that experience yesterday when I ran across a FastCo article on the Place Lamp, a device which connects to the GPS on your smartphone and changes color to tell your co-workers where you are. My exact thoughts were, “Is this a leash, or an electronic fence?” And that’s to say nothing of what they could do with search data from any company provided devices and networks. Get out indeed.
The modern obsession with big data is only fuelling these (doomed) attempts at greater centralisation and control.
I wonder what it will take for leaders to realise that the people who work “beneath” them are no less intelligent, wise or knowledgable about improving the system in which they work?
And if leaders believe so strongly in data, why do they not lead by example and first apply it to their own performance?
Data is critical to improvement – but so is proximity to the work and improvement is everyone’s responsibility, not the preserve of gods.
As you’ve written many times Harold – it’s about power, people, trust and openness. Sadly, without these, control will be the main use case for technology. It’s a tragedy that so many in organizations have such a poor socialized view of human nature and potential.