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State of The Blogosphere — Infographiclabs
First published on The Blog Herald.
Boosting the productivity of knowledge workers - McKinsey Quarterly -
Are you doing all that you can to enhance the productivity of your knowledge workers? It’s a simple question, but one that few senior executives can answer.
Their confusion isn’t for lack of trying. Organizations around the world struggle to crack the code for improving the effectiveness of managers, salespeople, scientists, and others whose jobs consist primarily of interactions—with other employees, customers, and suppliers—and complex decision making based on knowledge and judgment.1 The stakes are high: raising the productivity of these workers, who constitute a large and growing share of the workforce in developed economies, represents a major opportunity for companies, as well as for countries with low birthrates that hope to maintain GDP growth.
Nonetheless, many executives have a hazy understanding of what it takes to bolster productivity for knowledge workers. This lack of clarity is partly because knowledge work involves more diverse and amorphous tasks than do production or clerical positions, where the relatively clear-cut, predictable activities make jobs easier to automate or streamline. Likewise, performance metrics are hard to come by in knowledge work, making it challenging to manage improvement efforts (which often lack a clear owner in the first place). Against this backdrop, it’s perhaps unsurprising that many companies settle for scattershot investments in training and IT systems.
Since knowledge workers spend half their time on interactions, our research and experience suggest that companies should first explore the productivity barriers that impede these interactions. Armed with a better understanding of the constraints, senior executives can get more bang for their buck by identifying targeted productivity-improvement efforts to increase both the efficiency and effectiveness of the interactions between workers.
Toggle Sidebar About the research
This article summarizes the results of a research project under way since 2006. In the first phase, more than 200 knowledge workers at four organizations—the research institute Battelle, Educational Testing Service (ETS), Novartis, and the US Defense Intelligence Agency—kept daily logs of their knowledge interactions (more than 3,000 in total). Subsequently, we conducted field research and interviews with about 35 people at the original four companies plus three new ones: Ecopetrol, NASA, and Petrobras. For more on the first phase of research, see Al Jacobson and Laurence Prusak, “The cost of knowledge,” Harvard Business Review, November 2006.
Among companies we’ve surveyed (see sidebar, “About the research”), fully half of all interactions are constrained by one of five barriers: physical, technical, social or cultural, contextual, and temporal. While individual companies will encounter some obstacles more than others, our experience suggests that the approaches to overcoming them are widely applicable.
Best Buy Prediction Market Videos
“Big companies are like communist countries – we all know how well communist countries worked. At some point they fell apart, not because the leaders were dumb, but because nobody would tell the leaders at the top, who had to make decisions, what decisions to make.”
Jeff Severts, EVP, Best Buy
Think of the possibilities! Tapping into the wisdom of the crowd is the new way of predicting future outcomes.
EatMedia.com: VRM - Vendor Resource Management
Yes, another acronym to share - VRM - Vendor Relationship Management. This one captures the value of the efficiencies of the Internet... making relationships easier. Particularly with the companies that you want.VRM combines a customer-centered philosophy about industry guidelines and the technology platforms for making interactions more efficient and effective. Our clients have asked us to assess the "best practices" being developed from this initiative.
Last week Doc Searls led the CRM = VRM 2010 conference at the Berkman Center at Harvard. Here are notes from the event by Trust Fabric.
On Great Websites, Information is Craft, not Commodity
The same principle applies to the websites that are distinctive because their authors combine content and packaging into a beautiful product that others aspire to recreate. Mega-sites like Facebook, Yahoo!, CNN, and many others designed to keep you moving through content like merchandise racks in a department store will never define the web, because they don’t push it forward. They have the biggest, brightest signs, but can’t match the experience and quality of sites that are the product of craftsmanship and dedication.
Doc Searls Weblog · Beyond caveat emptor
Talk about asymmetry. You are no longer just a client to a server. You are a target with crosshairs on your wallet.
Trying to make advertising more helpful is a good thing. Within a trusted relationship, it can be a better thing. The problem with all this tracking is that it does not involve trusted relationships. Advertisers and site owners may assume or infer some degree of conscious assent by users. But, as the Journal series makes clear, most of us have no idea how much unwelcome tracking is really going on. (Hell, they didn’t know until they started digging.)
So let’s say we can construct trusted relationships with sellers. By we I mean you and me, as individuals. How about if we have our own terms of engagement with sellers—ones that express our intentions, and not just theirs? What might we say? How about,
- You will put nothing on my computer or browser other than what we need for our relationship.
- Any data you collect in the course of our relationship can be shared with me.
- You can combine my data with other data and share it outside our relatinship, provided it is not PII (Personally Identifiable Information).
- If we cease our relationship, you can keep my data but not associate any PII with that data.
- You will also not follow my behavior or accumulate data about me for the purposes of promotion or advertising unless I opt into that. Nor will your affiliates or partners.
I’m not a lawyer, and I’m not saying any of the points above are either legal or in legal language. But they are the kinds of things we might like to say within a relationship that is symmetrical in nature yet includes the kind of asymmetry-by-choice that Joe talks about: the kind based on real trust and real agreement and not just passive assent.
The Technium: Data-Driven Life
In The Data-Driven Life he sketches out the general trend towards self-monitoring.
In science, in business and in the more reasonable sectors of government, numbers have won fair and square. For a long time, only one area of human activity appeared to be immune. In the cozy confines of personal life, we rarely used the power of numbers. The techniques of analysis that had proved so effective were left behind at the office at the end of the day and picked up again the next morning. The imposition, on oneself or one’s family, of a regime of objective record keeping seemed ridiculous. A journal was respectable. A spreadsheet was creepy.We use numbers when we want to tune up a car, analyze a chemical reaction, predict the outcome of an election. We use numbers to optimize an assembly line. Why not use numbers on ourselves?
Sure, but that is geeky. Does this pertain to normal people? Gary answers:
Ubiquitous self-tracking is a dream of engineers. For all their expertise at figuring out how things work, technical people are often painfully aware how much of human behavior is a mystery. People do things for unfathomable reasons. They are opaque even to themselves. A hundred years ago, a bold researcher fascinated by the riddle of human personality might have grabbed onto new psychoanalytic concepts like repression and the unconscious. These ideas were invented by people who loved language. Even as therapeutic concepts of the self spread widely in simplified, easily accessible form, they retained something of the prolix, literary humanism of their inventors. From the languor of the analyst’s couch to the chatty inquisitiveness of a self-help questionnaire, the dominant forms of self-exploration assume that the road to knowledge lies through words. Trackers are exploring an alternate route. Instead of interrogating their inner worlds through talking and writing, they are using numbers. They are constructing a quantified self.As Gary notes, people have kept journals, diaries and logs for centuries. What's new here?
Four things changed. First, electronic sensors got smaller and better. Second, people started carrying powerful computing devices, typically disguised as mobile phones. Third, social media made it seem normal to share everything. And fourth, we began to get an inkling of the rise of a global superintelligence known as the cloud.Behind the allure of the quantified self is a guess that many of our problems come from simply lacking the instruments to understand who we are. Our memories are poor; we are subject to a range of biases; we can focus our attention on only one or two things at a time. We don’t have a pedometer in our feet, or a breathalyzer in our lungs, or a glucose monitor installed into our veins. We lack both the physical and the mental apparatus to take stock of ourselves. We need help from machines.
