Category: Knowledge work

Technology for us – the heart of Enterprise 2.0?

[Cross posted at FASTforward]

The phrase “technology for us” has been kicking around in my head for the past several months. At the FASTForward ’08 conference, I took a first pass at articulating my thinking in a video interview with Jerry Michalski. Consider this my next attempt. I expect there will be more.

Technology for Them

Information systems in organizations generally have been “technology for them.” Accounting systems, inventory control systems, ERP systems, reservations systems are all designed and imposed on their users.

Done properly, these systems yield efficiencies, predictable quality, and significant economic benefits. The design and implementation processes for these systems are industrial engineering at its best. Expert designers observe, redesign, and streamline processes to define and constrain what the target user population is allowed to do.

In these systems, users are simply one component in a mechanistic environment designed to constrain behaviors. User roles are limited to situations where technology is too expensive and a human user is more economical. Individual creativity and initiative are neither desirable or appropriate.

Technology for Me

The personal computer revolution brought “technology for me.” We saw innovation and scores of programs designed to improve the productivity and effectiveness of individual knowledge workers. Few of us would go back to a world without spreadsheets, word processors, or the other tools made possible and accessible via personal level information technology.

The first waves of innovation in the PC world focused largely on individual productivity. Attention to work process, if any, was a function of the idiosyncrasies of each user. Broadly speaking, innovation took one of two forms. Programmers and developers generalized from their own needs to develop unique tools solving their own problems. With luck, those solutions found enough kindred spirits to sustain a market. Early examples here would include the original Visicalc, ThinkTank, More, and dBase. More recent examples would include MindManager, SketchUp, Powerpoint, and the Brain.

The alternate development path was more corporate, with planned attempts to meet the application needs of perceived large markets of individual information and knowledge workers. Examples here would include the original Lotus 1-2-3, Microsoft Word, and Visio.

This development path emphasized industrial and mechanistic conceptions of work. Moreover, the logic of mass markets produced products targeted to the perceived lowest common denominator of user needs. At its worst, this path leads right back to technology for them and Microsoft Bob as a distorted model of users and use cases.

Us as Knowledge Worker

There are two dimensions of “technology for us” worth exploring. The first is “us” as knowledge workers; individuals charged with “thinking for a living” in Tom Davenport’s coinage and expected to exercise substantial initiative and autonomy in the design and execution of their work. The second dimension of “us” is the degree to which key work products and deliverables emerge from the collective and coordinated action of multiple knowledge workers. We’ll return to this second form of us in a bit.

There are both political and practical problems with applying technology effectively to the unique needs of knowledge workers. Previous organizational uses of technology have not had to deal with situations where the target audience was free to ignore you. Knowledge workers occupy positions of power and influence within the enterprise. They have the power and inclination to ignore, dismiss, and actively undermine ill-conceived and poorly executed efforts to modify their work practices. For that matter, they have to power to dismiss well-conceived and well-executed efforts on their behalf. 

If you’re smart enough to avoid the trap of trying to dictate an approach to this user community and actively engage them in the design and implementation process, you run into the next constraint. Knowledge workers can’t articulate quality, effectiveness, or efficiency with anything resembling the precision that applies to manual or information work. The nature of knowledge work and its deliverables makes typical measurement approaches suspect (see Crafting Uniqueness in Knowledge Work and The Invisibility of Knowledge Work, for example). We have only recently begun to understand individual knowledge work practices in ways that let us apply technology with some likelihood of success. In many ways we are still working out the details of the vision of knowledge work support first articulated by Vannevar Bush in the mid-1940s in As We May Think.

Us as Groups of Knowledge Workers

Organizations exist to solve problems beyond the capacity of individuals to tackle. This is as true of knowledge work as it is for all other types of work. For all the power of technology to make individual knowledge workers more productive and effective, the greater opportunity lies in developing skill at using technology to support collective activity.

What we haven’t yet done well is knit together our knowledge of how to improve group oriented work practices and technological possibilities. Further, the more promising efforts have seen limited penetration into organizations. When dealing with collective knowledge work we compound the problem of knowledge worker autonomy with the problem that the knowledge work processes we wish to improve are vague, imprecise, and squishy in ways quite uncharacteristic of the work processes we are comfortable working with in industrial settings.

If we take the analysis and improvement tools we are comfortable with in industrial process settings and simply port them to knowledge work environments, one of two things happens. Either, we become hopelessly frustrated trying to force a dynamic and fluid process into the confines of our swimlanes. Or, we mistake the small fraction of the process we can force fit into our tools for the entire phenomenon; guaranteeing that our target users will ignore us and route around our efforts.

While there are people who have thought about the problems of applying technology to complex knowledge work processes and practices, their work has not achieved the widespread adoption it needs to be a meaningful factor in most organizations. Some good entry points into this work include:

The inventory of technology solutions promising to streamline, improve, or transform group activities continues to grow, although it often seems more like baroque and rococo variations on a handful of themes than like new insights or frameworks. Will the next implementation of threaded discussion make any major contribution to educating a group on when and how to make effective use of that technique? Or to understanding what situations make it a poor choice of tool?

What seems to be missing is a synthesis of Group Behavior 101 and a groupware pattern language. I’m not aware of anything that would fit that bill, although Stewart Mader’s recent Wikipatterns might represent a potential starting point. Can anyone point to some examples I’m unaware of? Is this something that we should be working to develop?

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Prusak on Knowledge, Community, and Dunbar’s Number

These are my notes from a talk that Larry Prusak gave at my invitation at the Kellogg School back when I was on the faculty there. (For posterity’s sake, here is a link to the original blog post, although that version is suffering from bitrot. The Magic Number 300: Knowledge and Community)

His reference to the “magic number 300” is what I now recognize as Dunbar’s Number, which most people seem to estimate at closer to 150. The point remains largely the same.

I persuaded Larry Prusak to swing through Evanston last week (February 2002) and talk about knowledge management to students here at Kellogg. Over the course of 90 minutes he shared his perspective on knowledge as part of organizational life.

On a side note, Larry has abandoned Powerpoint. He’s always favored storytelling anyway. It does make the audience have to work harder, but that’s a good thing.

Unit of Analysis

Larry started with an old research design question – what the right unit of analysis. His answer? The group. Not the individual, not the enterprise. While he argued that there are important ideas tied up in the terms “network” and “community of practice,” he’s also concerned that the terms are well down the devolutionary path toward buzzword. “Group” is a nice simple word and you then have to listen to the actual points he makes instead of tuning out.

His research reinforces others in setting 300 people as a “magic number” — about the limit on the number of people you can know by name. He added one tidbit I hadn’t thought of before; that the typical military working unit has also averaged about 300 through history (worth tracking down the evidence for that later).

Social Capital

Given In Good Company, it wasn’t surprising that Larry tied the issue of group size and knowledge to social capital. He sees knowledge largely in terms of trust and of the conditions where reciprocity works. His evidence says that incentives are useless in knowledge management settings. You have to look to the level where people share without explicit incentives.

As Larry put it, “people want to find each other and want to talk.” You can force this into an economic framework, but that 300 number hints that we’re dealing with something pre-economic. “Gift culture” is the technical term for what Larry has tagged as one of the driving forces of knowledge creation and uses in organizations. What’s interesting about that is that it creates a point of tangency with open source software development as a social phenomenon. Eric Raymond’s writings on The Hacker Milieu as Gift Culture is a good entry point. I’ve got an old essay on linking KM and Open Source ideas that I’ll dust off and post as a story.

Defining Knowledge

Here’s Larry’s densely packed definition of knowledge: “embodied, tacit, pattern recognition.” Whew!

Here we tie in directly to the community of practice literature and to the learning processes that take someone from novice to expert. The late Herb Simon estimated that it takes 10-12 years to become an expert in a field. Experts reveal themselves in their ability to see the patterns in a situation that are invisible to a novice. I had a partner who was an expert on call centers. Dave could walk into a call center and tell you in a matter of minutes where the problems were. If you grilled him for a day or so, you might be able to figure out about half of what went into his judgments. This was why expert systems never succeeded.

Promoting Community

If you believe that capturing knowledge is a vain quest, then you need to direct resources toward community. That’s certainly where Larry comes down. While I believe that community is the more important and more malleable element, I’m not quite so quick to dismiss investments in capturing and organizing knowledge.

The keys to encouraging community relate more to providing time an space than providing money. That’s actually trickier, because it’s easier to throw money at problems. Chapter 4 of In Good Company is the place to go for more details.

Knowledge and Learning

Community is a means to the end of learning how to put knowledge into practice. To IBM’s great disappointment, Larry isn’t keen on document management as a path to better knowledge and he’s pretty skeptical about the value of technology tools to nurture communities. I think he finds much of the money poured into formal knowledge management systems wasted. As he put it “asking about the ROI on knowledge management is like asking about the ROI on babies.”

While Larry is no Luddite, some of his technological skepticism is generational. He’s squarely in the middle of Negroponte’s digital homeless. His skepticism is a useful counterbalance to the usual utopian promises of technology advocates. But I take his input more as design constraints than a meaningful argument to avoid technology.

Larry closed with a really great question to use when poking around in an organization trying to get a sense of its attitudes toward knowledge and learning — “can you make a mistake around here?”

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Knowledge management and innovation

What’s the relationship between knowledge management practices and innovation? On first thought, you would think that effective knowledge management would contribute to more effective innovation as well. On the other hand, knowledge management has often been justified on the value of not routinely reinventing solutions to problems that an organization has already solved. This potentially puts knowledge management and innovation at odds with one another.

The sticking point lies in the measurement and reward systems put in place to encourage active use of the knowledge management system. Absent careful thought about the various ways in which the contents of a knowledge management system feed into business processes, the risk is a measurement system that actively inhibits rather than promotes innovation.

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Going hands on to get your arms around Enterprise 2.0

I was not able to attend last month’s Enterprise 2.0 conference in Boston. I wanted to pick up on something Andrew McAfee had to say during his keynote there, however. Here’s his set up:

I found myself in an uncomfortable position at the end of my short keynote speech during the Enterprise 2.0 conference yesterday. I got through my prepared material and still had about five minutes left in the alloted time. So I had to ad lib.

The idea that occurred to me (from no identifiable source) was to make Enterprise 2.0 personal. I compared where my thinking was a year ago to where it was today, and tried to convey how big a shift had taken place.

[Speaking From the Heart, and off the Top of My Head ]

He goes on to share some of his observations about blogs, social networks, and how organizations are taking up the mix of technologies that fall under the Enterprise 2.0 rubric. For example:

I used to believe that blogs were primarily vehicles for blaring opinions, and that bloggers generally proved Kierkegaard’s great quote that “People demand freedom of speech as a compensation for the freedom of thought which they seldom use.” I now get a large percentage of my daily food for thought from blogs, and write one myself. It’s proved to be an unparalled vehicle for getting ideas out into the world, getting useful feedback on them, and meeting people who are interested in the same things I am.

[Speaking From the Heart, and off the Top of My Head ]

What struck me was the particular importance of hands on knowledge in appreciating the importance of these technologies. The organizational value of these technologies is in how they change the possibilities for productivity and effectiveness of the managerial and executive core. You need to work with them in a substantive way to appreciate what they can do for you. That makes them different from so many other applications of technology in the organization. McAfee has made that investment and has become an effective spokesperson for them. How do we get others in similar positions to invest in the necessary learning?

Better thinking about performance improvement

  Better: A Surgeon’s Notes on Performance, Gawande, Atul

I’ve always been troubled by the phrase “best practices” thrown around loosely in business settings. In certain engineering and professional settings, the term can have an important legal meaning. Even then, “best practice” is always a moving target. Better, Atul Gawande’s most recent collection of essays nicely crystallizes my reservations and offers useful insight into how to think about performance and performance improvement in knowledge work environments.

Drawing on his experience as a surgeon, Gawande reflects on the connections between learning and practice; both as an individual practitioner and as a field. His essays provide fascinating insights into how the practice of medicine has evolved over time; ranging over such diverse topics as hand-washing, battlefield injuries, and obstetrics. For that alone, Better is well worth reading. But it offers broader lessons as well.

Rooted in science and medicine, one thread that Gawande examines is quality of evidence. The gold standard is that of the double-blind, controlled laboratory experiment. However, action in the world and the demands of day-to-day practice cannot always wait for that standard to be met. There’s a wonderful quote from Samuel Butler that captures this problem; “Life is the art of drawing sufficient conclusions from insufficient premises.” Many of Gawande’s stories shed light on the reality that we often must make decisions on the basis of imperfect information and knowledge. We may not be able always to meet a gold standard of evidence, but we still benefit from a methodological commitment to hypothesis, experiment, and measurement.

Gawande’s observations on measurement and performance evolution in obstetrics provides one good example. He starts with the development of the Apgar score; a simple, concrete, measure of a baby’s condition at one minute and five minutes after birth. I am particularly struck by the insight and cleverness represented by recording the score twice in such a short interval. That creates a connection between measurement and action that drives performance improvement; it creates a feedback loop well matched to the human system it is embedded in.

Moving up a level from an individual delivery to a hospital’s performance, the Apgar score also serves to drive performance improvement at a more systemic level. In addition to informed clinical judgments about performance, we now have some numbers we can compare against one another and over time. Because these numbers tie to clinical judgment and performance, they can be used to evaluate changes in practice. Changes that improve the scores stick; those that don’t are abandoned.

This logic sheds some interesting light on a tension between “evidence-based medicine” and performance improvement more broadly conceived. Careful, clinical studies of problematic deliveries showed that Caesarian-sections had no measurable advantage over forceps assisted deliveries. Yet, no obstetrician uses forceps anymore and C-sections are used more and more routinely to the point where some claim they are over-used.

Understanding why has important lessons for anyone interesting in improving the performance of knowledge work in organizations. The difference comes from whether you are looking at performance at the systems level or the individual practitioner level. Learning to use forceps is a complex skill; difficult to observe, difficult to learn and difficult to teach. A C-section, on the other hand, is straightforward as surgical procedures go, highly observable, and teachable to a wider range of competent OB/GYNs. If you are trying to improve the outcomes and reliability of the system as a whole, your payoff from pushing C-sections over forceps is much higher. This is a classic example of improving a system by reducing variability. It is also an important reminder to be clear about where you are trying to improve performance.

 

 

Literate thinking as a barrier to Enterprise 2.0 adoption

Most of the technologies lumped under the Enterprise 2.0 label presuppose some facility with the written word. I wonder to what extent that presents a barrier to adoption in many organizations? Moreover, I wonder how visible that organizational barrier is to those who are already facile?

I’ve written before on oral vs. literate cultures in organizations (Bridging the IT Cultural Divide, Part 1 and Part 2), using the distinctions that the late Walter Ong introduced. Leadership and power in many organizations correlates with comfort and facility with the spoken word. Those same individuals are not necessarily as facile or comfortable with expressing themselves in writing.

Email doesn’t really count, as it appears to be less public and, therefore, feels less threatening. Even so, we still hear of senior executives who avoid using email directly. (Maybe one of the attractions of the Crackberry is that it provides a built-in excuse for doing little real writing). So too for Powerpoint. It is not a tool that lends itself to literate argument and expression.

Jordan Frank of Traction Software argued a while back that organizations benefit from using the tools in simpler ways (Beta bloggers need not lurk in the enterprise). While I agree with his arguments, they also reinforce the notion that feeling uncomfortable with literate thinking is a barrier to be addressed. Jordan’s suggestions are probably among the best advice for routing around this issue in most organizations.

If my hypothesis has any merit, it does suggest that some of the objections to these technologies will be rooted in emotional fears and insecurities that will be unexpressed and potentially inexpressible. To someone who can’t swim, “come on in, the water’s fine” isn’t very helpful encouragement.

 

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Alan Kay on learning and technology

Alan Kay is talking once again about what went wrong with the personal computer and personal computing. Here’s a pointer to a recent interview he did with CIO Insight magazine that is well worth your attention.

A CIO Insight

Alan Kay was recently interviewed for CIO Insight magazine’s Expert Voices feature. In this piece entitled Alan Kay: The PC Must Be Revamped–Now, Alan discusses the mindsets that stand in the way of real innovation – and what his not-for-profit VPRI is doing to address the issue. In the article, Alan defines Croquet as one of those efforts and as “a new way of doing an operating system, or as a layer over TCP/IP that automatically coordinates dynamic objects over the entire Internet in real time. This coordination is done efficiently enough so that people with just their computers, and no other central server, can work in the same virtual shared space in real time.”
[Julian Lombardi’s Croquet Blog]

Alan is up to his old tricks of trying to invent the future instead of predicting it. His focus remains on viewing the personal computer as a learning tool more than a productivity tool, which means, among other things, that you should be prepared to invest time and effort in that learning. He is not fond of efforts that sacrifice the real potential of tools by focusing on making the first five minutes easy and entertaining at the expense of crippling the long-term capabilities of the tools.

Alan remains a disciple of Doug Engelbart:

 Engelbart, right from his very first proposal to ARPA [Advanced Research Projects Agency], said that when adults accomplish something that’s important, they almost always do it through some sort of group activity. If computing was going to amount to anything, it should be an amplifier of the collective intelligence of groups. But Engelbart pointed out that most organizations don’t really know what they know, and are poor at transmitting new ideas and new plans in a way that’s understandable. Organizations are mostly organized around their current goals. Some organizations have a part that tries to improve the process for attaining current goals. But very few organizations improve the process of figuring out what the goals should be. [Alan Kay: The PC Must be Revamped Now]

There is a potentially deep and rich connection between challenging knowledge work and technology. But realizing that potential will require different attitudes about how much time and effort we should be prepared to invest in learning. Organizations thinking about investing the technologies collectively identified as Enterprise 2.0 should also be thinking about what investments they should be making in the appropriate individual and organizational learning

Strategic sensemaking and Enterprise 2.0 technologies

The increased importance of sensemaking will prove to be one of the central drivers for Enterprise 2.0 technologies adoption. Organizational theorist Karl Weick positions sensemaking as one of the central tasks in organizations. Dan Russell at Creating Passionate Users provides a nice definition of sensemaking that will serve as a useful starting point:

Sensemaking is in many ways a search for the right organization or the right way to represent what you know about a topic. It’s data collection, analysis, organization and performing the task. [Sensemaking 3]

The value of the sensemaking notion in organizational settings is that it highlights the active requirement for managers and leaders to construct sensible accounts out of ambiguous, ambivalent, equivocal, and conflicting data. In a world (imagine Don LaFontaine here) characterized by significant technology, organizational, and strategic change, the problem of sensemaking becomes more acute.

It occurs to me that there is an useful analogy to be made between sensemaking and open source development practices; in particular with the adage that “with enough eyes, all bugs are shallow.” Instead of counting on the insights of a mythological strategic genius, you distribute the problem to the wider organization. Many of the more interesting strategic planning processes (think scenario based planning and future search conferences, for example) are ultimately grounded in that notion.

One of the attractions in Enterprise 2.0 technologies is that they make these strategies more feasible and scalable. Blogs, wikis, tagging, etc. allow participation to scale beyond what face-to-face methods can support. They make it possible to generate and organize more extensive raw materials and inputs to planning/sensemaking processes. Wikis with good version tracking and refactoring capabilities make it both safer and easier to generate and work through alternative representations/sensemakings.

Realizing this sensemaking potential will require brokering some introductions and partnerships. Those adept in the techniques are likely to not be versed in the ways that the technologies reduce or eliminate some of the key barriers to successfully using the techniques. Those who understand the technologies may not be aware that the techniques exist, much less that they could benefit from technological improvement. One starting point I would suggest is for those promoting Enterprise 2.0 technologies to investigate the sensemaking planning techniques and practices and map points where the technologies enable, simplify, or improve the techniques.

Strong Opinions, Weakly Held

Ross Mayfield points to an interesting post by Bob Sutton at Stanford. Ross nicely captures the essence of Bob’s post.

More important, for my selfish purposes, is learning that Sutton is blogging. Sutton is a Professor at Stanford’s Engineering School, the author of several recent, excellent, books on management and innovation and one of the vocal proponents of the design dimension of management in today’s knowledge-based organizational world. I’ve added his blog, Work Matters, to my subscriptions and commend it to you as well.

Strong Opinions, Weakly Held

Bob Sutton, who was an inspiration around the time we started Socialtext, is becoming one of my favorite bloggers. I’ve been sharing his posts like The Snowstorm Study in my internal blog and talking too much about the No Asshole Rule. But Strong Opinions, Weakly Held is an absolute gem:

…Perhaps the best description I

Balancing diligence and laziness

Some time back I came across the following quote in The 80/20 Principle : The Secret of Achieving More With Less by Richard Koch, which I’ve been pondering ever since for its implications for knowledge work and knowledge workers:

There are only four types of officer. First, there are the lazy, stupid ones. Leave them alone, they do no harm…Second, there are the hard- working, intelligent ones. They make excellent staff officers, ensuring that every detail is properly considered. Third, there are the hard- working, stupid ones. These people are a menace and must be fired at once. They create irrelevant work for everybody. Finally, there are the intelligent, lazy ones. They are suited for the highest office.

General Erich Von Manstein (1887-1973) on the German Officer Corps

You can also map this quote into the following matrix representation:

Diligence vs. laziness

One implication certainly is that you want to keep the average IQ up in your organization (setting aside all the limits on accurately measuring or assessing something as complex as intelligence for the moment). My own theory is that it also suggests that you want to keep your organization relatively small to maintain some degree of control over that average IQ. You may also want to keep the distribution of IQ in your organization as tight as possible.

The laziness/diligence dimension is the more interesting of the two in the context of knowledge work organizations. Common organizational practice is biased in favor of diligence, while laziness doesn’t get the respect it deserves. Granted, the appearance of blogs such as Slacker Manager is a hopeful sign, as is the recent spate of activity and commentary around the importance of innovation and creative thinking for knowledge based organizations. But our Puritan/Calvinist heritage still dominates reward and evaluation systems. Regardless of the actual importance of thought and reflection to long-term organizational success, you are better off looking busy than looking like you are thinking. Even organizations that exist to promote reflective thought (e.g., universities, research institutes, think tanks) fall into the trap of encouraging diligence at the expense of reflection/laziness.

I don’t yet have a fully workable solution to the problem of carving out sufficient and appropriate time for thinking and reflection. More often than not, it gets relegated to plane-time, travel-time, and after-hours time; essentially bypassing the organizational problem. I’ve found that mind-mapping, either by hand on on the computer, is one form of thinking that can be done in public without triggering unwanted negative perceptions.  Setting aside time to maintain some form of journal (whether in the form of a blog or more private diary) is another thinking/reflecting discipline that is both productive and not immediately threatening to the activity police.

Here are some questions I think are worth exploring in this context.

  1. What alternate terms than diligence and laziness could we use to better frame the issue?
  2. How important is it to carve out times and places to engage in visible laziness within organizations?
  3. Is this a problem that needs to be solved at the organizational level? For which types of organization?
  4. What barriers to innovation, if any, does a bias toward diligence create?

Any takers?