Category Archives: Knowledge Management

Defining Collaborgagement

I coined the term collaborgagement while attending a conference on content strategy. At this conference, John Newton (Alfresco’s CTO) commented that the next generation of enterprise IT tools needs to serve the middle of the enterprise – the domain of the knowledge workers. These tools need to support collaboration, knowledge management, and just-in-time sharing of expertise. Even so, collaboration/knowledge management software doesn’t automatically empower knowledge workers. There must be more than just new tools.

Collaboration is important but it is not enough. What is needed is something that would continue the benefits of collaboration between the collaboration sessions. A way of engaging the person’s thoughts and focusing those thoughts on the collaboration work even when the person is working alone. A process I call collaborgagement. Not just a combination of collaboration and engagement but a synergistic process.

The foundation of collaborgagement is the mental model. The mental model has been variously defined by different fields, but the consensus seems that mental models are “deeply ingrained assumptions, generalizations, or even pictures or images that influence how we understand the world and how we take action” (Wind and Crook, 2005). Individuals have mental models, but so do teams and departments. The purpose of the mental model is to make sense of various aspects of our lives including our work. Mental models take a great deal of effort to build, but the benefit is that once created, they reduce our thinking load.

For example, researchers have found that expert chess players think less than novice chess players because the expert chess player can focus on several pieces at once and perceive patterns of board arrangements. The novice chess player has to concentrate on separate pieces and build the pattern from the individual pieces. The expert chess player has a library of mental models they can consult that makes them better players because they can “lookup” the answer to a chess problem while a novice is still calculating the problem.

The same process can be seen in everyday life. Think of how you learned to drive. Remember all the steps you had to master to start the car, put it in drive, and begin your journey. Repetition and observation helped you build a mental model so that driving almost becomes an automatic process requiring little conscious thinking.

The challenge is that we rely on our mental models so much we strenuously resist changing or discarding our existing models. This goes for team mental models and individual mental models. But our changing world requires that we change our mental models, or they quickly lose their benefit and can even harm us in the new realities we face. We need a process of engaging people’s attention at the level of their mental models and then collaborate to help explore current mental models and modify or even replace these mental models on an individual and team level. This is the purpose of collaborgagement.

There are probably several methods for examining current mental models and altering them, but I like the process Wind and Crook (2005) outline in their book The Power of Impossible Thinking:

  • Understand the power and limits of mental models.
  • Test the relevance of your mental models against the changing environment, generate new models, and develop an integrated portfolio of models.
  • Overcome inhibitors to change by reshaping infrastructure and the thinking of others.
  • Transform your world by acting quickly upon the new models, continuously experimenting, and applying a process for assessing and strengthening your models. (p. xxiv)
Two people collaborating at a white board.

With Wind and Crook’s (2005) process in mind, this is how collaborgagement would work:

  • Before a team meeting, the individual members examine their existing mental models that relate to the topic of the meeting. The team member may want to blog, mind map, or similar tool to help him or her to surface the mental models and produce it in a tangible form.
  • During the team meeting, the individual members display their mental models. Then the team works together to surface the team mental models in a tangible form.
  • The team then examines the new reality of the topic and lists the characteristics. The goal of this phase is to come to a consensus about the new reality.
  • After a consensus has been reached, the team compares the current team mental model to the new reality. Does the team mental model need revising, or is an entirely new team mental model required? The team works to determine the revisions or constructs the new mental model.
  • After the team meeting, the individual members go on their own to reflect on the consensus about the new reality and how their current mental models compare to the new reality. The member then revises their existing mental models or constructs new mental models that reflect both the new reality and the team mental model.
  • What is significant about this process is that it engages people on a deeper level than what usually happens in change efforts. I have been to plenty of meetings where great ideas and energy has been generated, but it quickly dissipates once the meeting is over. For profound and sustainable change to happen, you must engage people at a fundamental level and produce collaboration that carries on ever after the meeting is over. Starting at the mental model level is the best way to create lasting transformative change.

Reference:

Wind, Y., & Crook, C. (2005). The power of impossible thinking: Transform the business of your life and the life of your business. Upper Saddle River, NJ: Wharton School Publishing.

Decision Intelligence Plus Knowledge Management Plus Foresight

Just started reading Link: How Decision Intelligence Connects Data, Actions, and Outcomes for a Better World. Great read and I encourage you to read more about the emerging field of decision intelligence.

Woman surrounded by flying books.

As I am reading the book, I’m taking notes that will eventually turn into a model of combining knowledge management and foresight with decision intelligence. There are some powerful parallels here. And decision intelligence seems fit for knowledge automation.

Eight Reasons Why Your Collaboration System Is Failing

At the beginning of this year, I swore off using Slack. My resolution amazed my friends who extolled the virtues of Slack. Slack isn’t the collaboration app proclaimed to be the “next big thing’” I remember back in the early 90′s when computer-supported work applications were all the rage (remember when “Lotus Notes” was first rolled out). Organizations threw a lot of money and resources at early collaboration systems, but many were failures from the beginning.

The failure of many new collaboration systems to catch on was perplexing because software packages for individuals and organizations were doing well. What was it about developing software for groups that made it so different from developing software for individuals and organizations?

In 1994, Dr. Grudin published an article that answered that question with the simple observation that groups were just different from individuals and organizations. How they are different is explained in his eight challenges for developers:

People collaborating in front of a laptop.

Who Does the Work and Who Gets the Benefits? Ideally the labor in operating and maintaining the groupware application must be roughly equal among the group members. This ideal division of labor is rarely the case. Consider a project management application where the team members must update it regularly with progress reports, performance data, and other data. A good deal of the team member’s team is compiling information and feeding the system while the project manager must spend a minimal amount of time reading reports the system generates. The team member sees only a burden from the software and soon avoids doing this extra work which leads to poor reports causing the Project Manager to quit relying on the system for information. Soon, no one is using software.

Critical Mass of Users. The collaboration software field is filled with many platforms for collaboration. Many offer similar features, and each has an enthusiastic community of supporters. In large government agencies you can see several collaboration systems in various pockets of the organization that don’t communicate outside of their pocket. Ironically the systems that exist to promote collaboration often promote organizational silos as the groups argue that their system is the best solution.

Social, Political, and Motivational Factors. Dr. Grudin gives a great example of this challenge when he describes the failure of meeting management software. It assigned meeting rooms based on priority but quickly became useless because no one wanted to admit that their meeting was anything but “high priority.” As Dr. Grudin explains, collaboration software can only model a rational workplace, but actual workplaces are much more complicated due to organizational culture.

Exception Handling. We rarely work the exact way described in our work processes. Collaboration software built only based on the documented office procedures is too rigid and not able to handle the flexibility required frequently at work. Just think of how often you don’t have a typical day at work and have to improvise a workable solution. Now, imagine trying to program that into software.

Decreasing Communication and Coordination Load. Organizations search for ways to reduce the communication and coordination needed to do the job. How often have you said that you could get more done if you were not interrupted so often? Of these interruptions, how many were due to email, phone calls, a colleague stopping by to talk, etc.? Sometimes you can over-collaborate, and this often results from poorly designed groupware.

Hard to Evaluate Groupware. It is challenging to test groupware because the group dynamics are so hard to replicate. It can take several weeks of careful observation to understood how a group works, and software designers don’t have the time or expertise to evaluate how their software will aid in collaboration. Often the groupware vendor blames this on inadequate user training and will continue the same software with better tutorials and help aids but never realizing that the fundamental problem is that people don’t like collaborating the way the system is forcing them to collaborate.

Intuitive Decision Making. Because of the nature of our work, we often must decide based on little evidence, and thus we rely heavily on our intuition. Groupware applications rarely support intuitive decision making but force users to input significant data so a fully reasoned decision can be made. Often, we do not have the necessary data, and a quick decision must be made. Thus, we abandon the groupware application to use a simple spreadsheet or other individual application to support our intuition.

Managing Acceptance of the Groupware. Too often, I have seen a collaboration solution launched where the users are expected to adapt themselves to how the software works rather than the software adapting to the way the group works. A collaboration system at my work is universally despised because it practically handcuffs a group of users to a cumbersome and protracted painful process. I’ve only used the system once, but that was enough for me to avoid ever having even to click on the program icon.

Despite these principles being 25 years old I still see the same mistakes being repeated in today’s collaboration tools. I also see where companies have put these principles into practice and have made excellent collaboration software that has endured and grown in popularity. I suspect that Google engineers must have memorized these principles when they developed their Google Docs system.

I leave a final exercise for the reader: how many of these principles does SharePoint violate (if any)? Or does SharePoint violate new principles of collaboration software?

“You’re so dumb!:” The Next Generation

“Our youth now love luxury. They have bad manners, contempt for authority; they show disrespect for their elders and love chatter in place of exercise; they no longer rise when elders enter the room; they contradict their parents, chatter before company; gobble up their food and tyrannize their teachers.”

The above complaint was from Socrates. St. Thomas Aquinas lamented that the world would be left to an ill-prepared and careless youth. A year after I was graduated from college, I read Steve Allen’s Dumbth which “humorously” recounted tales of how Generation X didn’t know how to think.

Thirty years later it’s the Millennial Generation’s turn with The Dumbest Generation label (and Generation Z not far behind). “According to recent reports from government agencies, foundations, survey firms, and scholarly institutions, most young people in the United States neither read literature (or fully know-how), work reliably (just ask employers), visit cultural institutions (of any sort), nor vote (most can’t even understand a simple ballot). They cannot explain basic scientific methods, recount foundations of American history, or name any of their local political representatives. What do they happen to excel at is – each other. They spend unbelievable amounts of time electronically passing stories, pictures, tunes, and texts back and forth, savoring the thrill of peer attention and dwelling in a world of puerile banter and coarse images.”

The crux of the “dumb generation” argument is that their generation doesn’t have the knowledge that our generation has with the implication that our knowledge is inherently superior. It reminds me of summers that I spent at my grandparent’s farm where I was pitied because I didn’t know how to milk a cow, can vegetables, or could identify all the trees on the farm. “Didn’t I know anything?” they asked.

Then, I bought my grandparents a microwave oven, a VCR, and hooked their TV up to cable. Now I got to mutter under my breath, “didn’t my grandparents know anything?” As our workplaces become multi-generational, I am sure there is a lot of grumbling about the limitations of the different generations. And that is wrong.

Young girl walking with an old man.

The real issue is how to transform our organizations into learning organizations, so we capture the knowledge we already have and determine the knowledge we need. We produce new data and information at an astounding rate, and it is growing faster every year. The challenge is to determine what knowledge we need to keep, what knowledge we need to discard, and how to find the new knowledge we need. Like the way I cling to 1980s rock, knowledge we already have feels comforting and empowering, but we need to have the courage to let some of that go and embrace the new knowledge being produced. We also need to recognize that not all old knowledge is useless and should be discarded.

Others have written that the best learning is in our workplaces and with conversations with our colleagues. We can learn a lot from each other, and our organizations desperately need our efforts to keep the organizational memory growing and thriving. That means younger workers should not just immediately dismiss current practices and processes because that is how they used to do things. And older workers should not be defensive and dismissive when younger workers suggest new ways of doing the organization’s business.

Back when I worked at a state agency, I had a colleague who insisted on using Lotus 123 for his spreadsheets, although we had Microsoft Excel. He would bitterly complain when they tried to install Excel on his machine, and we would have to support Lotus 123 even though it was getting harder to do so every year. I then hit upon a strategy of having him teach me his spreadsheets. I would go over to his cubicle and learn the macros he created. I would recreate the macros in Excel and then show him how much more powerful they were and how the reports looked better with charting available to Excel. He was reluctant at first, but what sold him on upgrading is that he would not lose the original knowledge he had in his spreadsheets and macros but that they would be faster and more effective in a newer environment. Two years later, he relished his role as the “Excel Guru” who was the go-to guy about the intricacies of Excel spreadsheets.

So, maybe what is needed are fewer books about how stupid the other generations are and more books on how much we can learn from each other.

U.S. Congress Finds One solution to It’s Information Problem

The U.S. Congress’ Select Committee on the Modernization of Congress has created the United States Legislative Markup (USLM) to standardize the format for drafting, viewing, and publishing legislation.

Open book with a page of text

Importantly, this standardization means that rule of law nations can help each other far more effectively. It means that –at long last– democratic values might be able to beat the trolls, out compete data mercenaries and diminish the information weaponization that is paralyzing democracy worldwide. This global democratic resilience will be especially important when we arrive at machine learning, artificial intelligence and algorithms. Will we build an auditable public good system? One that can visualize and help forecast implications of policy? One that is able to identify misinformation and financial conflicts of interest in the data supply chain? Or, will this new openness become yet another opportunity to commodify, privatize and capture democratic functions?

https://thehill.com/blogs/congress-blog/technology/448265-your-interoperable-democracy

The USLM is a great step toward tackling the increasing data overload of Congress and the federal government as a whole.