Category Archives: Innovation

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.

Failure Is an Option: The Way To High-Performance Innovation

The three keys to innovation are to seek new ideas, test these ideas on a scale where failure is survivable, and continuously monitor these trials for feedback. The three keys come from Tim Hartford’s book, Adapt: Why Success Always Starts With Failure. Hartford argues that the world is too complex for top-down “big project” innovation-based purely on expert judgment. The best path to innovation is to try a lot of ideas simultaneously (even if they contradict each other), build in robust feedback loops, and use the winning ideas to start a new round of trials.

Hartford’s three keys are not a new method of innovation; it is the oldest method of innovation around – evolution. Nature is continually creating variations of species and then selecting the species that best survive current conditions. Hartford applies that concept to organizations to see if a similar process works in determining what companies succeed and which close. The organizations that best survive a continually changing business environment combine incremental improvement along with the occasional long-shot idea to propel them into a better part of the business landscape ahead of their competitors

So, what does this have to do with government agencies? Hartford flatly states this innovation method will not work in government agencies because of several barriers. First, there is not enough time for political appointees to fully see these experiments before a new administration comes in office. Second, the process depends on many failures for innovation, but failure carries a high stigma in government. Third, it is difficult to demonstrate that a policy innovation had an effect due to the lack of robust feedback loops in government.

Think outside of the box sign.

Hartford’s opinion about government innovation is way overstated. There have been numerous government projects that have been extremely innovative: the Hoover Dam, rural electrification, the Interstate Highway System, the Moon landings, the Space Shuttle, the Internet, and so on. When you examine how these agencies developed these projects, you do see these agencies tried many ideas and learned from these trials. NASA has a fantastic knowledge management culture, and DARPA’s successful record of innovation is built on the concept of trying many long-shot ideas at once.

What holds the government back from being even more innovative is the stigma of failure. Many agency cultures are too cautious because of the constant external scrutiny and the internal cultural practices of not sticking your neck out and just waiting out the latest change effort. Often, this caution is well-warranted. Many people depend on government agencies, and thus agencies cannot fail in their primary mission of delivering Social Security checks, defending the nation, or enforcing laws and regulations

But failure to innovate will also lead to mission failure for agencies. In the sixth chapter, Hartford describes how the 2008 economic meltdown was inevitable, given the tight coupling of economic institutions and the failure of the government to prevent financial organizations from becoming too entangled. He argues that in any complex system, accidents will typically occur and that often our failure-prevention efforts will only increase the probability of failure. What is needed are the twin strategies of placing buffers between parts of the system and setting up feedback loops to warn us of emerging failure events.

The government must continually innovate so it can continuously deliver on its mission. This means that the culture must change so the agencies accept the small failures that teach to avoid the massive failures that cripple the agency and harm the people it serves. Whether we call it “experimentation,” “pilot tests,” or some other euphemism, the better the government is at innovation, the better it can serve its citizens.

Failure Is An Option: The Way To High-Performance Innovation

The three keys to innovation are to seek new ideas, test these ideas on a scale where failure is survivable, and continuously monitor these trials for feedback. Failure is the path to success according to Tim Hartford’s Adapt: Why Success Always Starts With Failure. Hartford argues that the world is too complicated for top-down “big project” innovation-based purely on expert judgment. The best path to innovation is to try a lot of ideas simultaneously (even if they contradict each other), build in robust feedback loops, and use the winning ideas to start a new round of trials.

Learning from failure is not a new method of innovation; it is the oldest method of innovation around – evolution. Nature is continually creating variations of species and then selecting the species that best survive current conditions. Hartford applies that concept to organizations to see if a similar process works in determining what companies succeed and which close. The organizations that best survive a continually changing business environment combine incremental improvement along with the occasional long-shot idea to propel them into a better part of the business landscape ahead of their competitors

So, what does this have to do with government agencies? Hartford flatly states this innovation method will not work in government agencies because of several barriers. First, there is not enough time for political appointees to fully see these experiments through before a new administration comes in office. Second, the process depends on many failures for innovation, but failure carries a high stigma in government. Third, it is difficult to demonstrate that a policy innovation had an effect due to the lack of robust feedback loops in government.

Person holding a light bulb.

Hartford’s opinion about government innovation is overstated. There have been numerous government projects that have been extremely innovative: the Hoover Dam, rural electrification, the Interstate Highway System, the Moon landings, the Space Shuttle, the Internet, and so on. When you examine how these agencies developed these projects you do see these agencies tried many ideas and learned from these trials. NASA has an amazing knowledge management culture, and DARPA’s successful record of innovation is built on the concept of trying many long-shot ideas at once.

What holds government back from being even more innovative is the stigma of failure. Many agency cultures are too cautious because of the constant external scrutiny and the internal cultural practices of not sticking your neck out and just waiting out the latest change effort. Often, this caution is well-warranted. Many people depend on government agencies, and thus agencies cannot fail in their primary mission of delivering Social Security checks, defending the nation, or enforcing laws and regulations

But failure to innovate will also lead to mission failure for agencies. In the sixth chapter, Hartford describes how the 2008 economic meltdown was inevitable, given the tight coupling of economic institutions and the failure of the government to prevent financial organizations from becoming too entangled. He argues that in any complex system, accidents will typically occur and that often our failure-prevention efforts will only increase the probability of failure. What is needed are the twin strategies of placing buffers between parts of the system and setting up feedback loops to warn us of emerging failure events.

Government must continually innovate so it can continuously deliver on its mission. Continuous innovation means that the culture must change so the agencies accept the small failures that teach to avoid the significant failures that cripple the agency and harm the people it serves. Whether we call it “experimentation,” “pilot tests,” or some other euphemism, the better the government is at innovation, the better it can serve its citizens.

“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.

Scenario Planning – An Essential Career Planning Skill

I am continuing to work on the career book which will be released on December 1st. Along with the book, I will be releasing an online course that teaches the job-seeking skills for the new job seeker.

A vital skill for future job seekers will include scenario planning. Scenario planning was developed by the Shell Corporation in the 1970s to help deal with economic uncertainties. One scenario, oil embargo by the OPEC nations, was considered too fanciful – until it happened. Thanks to scenario planning, Shell weathered the oil embargo successfully.

The job hunter will use scenario planning to help them plot the future of their career path. To create the scenarios, follow these steps:

Identify the driving forces – what are the significant shifts in technology, society, the customer base, and other factors in the industry.

Identify two of the most critical uncertainties – From the list of the driving forces, pick two that are most critical to your future career.

Create four scenarios – Using the two critical uncertainties as axis, develop four plausible scenarios. The best way to present the scenarios is as stories.

Person wearing VR goggles

For example, I created these scenarios when I first entered the federal government in 2009. This was when newly elected President Obama wanted to reinvent government technology. The critical factors were the new digital technologies and how effective the federal government would be in implementing the latest digital technologies.

First Scenario – SteamGov

This scenario borrows from the steampunk genre[iv] in describing a future where the government attempts to implement Gov 2.0, but the rest of the world has moved on to Web 3.0 or even Web 4.0.

Government IT is still a generation behind the current technology available to citizens, thus limiting the engagement offered by the agencies. Large, centralized IT architectures dominate the agencies and employees are continually frustrated by the underpowered workstations they have to deal with, especially when their own personal technology is much more powerful. There are small pockets of innovation and pilot projects, but organizational cultures prevent scaling up these innovations to the agency.

Second Scenario – Google.Gov

Following a Supreme Court ruling that narrows the definition of inherently governmental, most government functions are outsourced to the private and nonprofit sectors. A Google-like company consolidates most of the outsourcing contractors into one contracting firm that applies the latest technology and business practices to deliver a diverse range of government services. The Executive Branch now consists of the White House staff and a larger GAO. The new GAO administers the mega-contract that governs the quality and accountability of government services provided by the huge contracting firm.

Third Scenario – LabGov

Still suffering under crushing budget constraints and frustrated by the continuing number of programs forced onto the states by the Federal government, state governments see Gov 2.0 as the way out of their fiscal mess. Living up to Justice Brandeis’ metaphor as “laboratories of democracy,” the state governments experiment with the latest open-source technologies, agile project management, and any other IT or management innovations that promise greater efficiency at lower costs and higher citizen satisfaction.

Citizens respond with enthusiasm and petition to have more federal programs (and funds) transferred to the states because they can manage services better, faster, and cheaper than the federal government. States form into regional and programmatic associations that shift the federal-state balance-of-power from the national government to regional governmental organizations.

Fourth Scenario – InnoGov

In 2011 the civilian equivalent of the Defense Advanced Research Projects Administration was established. Its mandate is to be the project management office for Gov 2.0, and the office seeks innovative Gov 2.0 projects, funds the development of these projects, and helps other agencies to copy the innovations. New radical management techniques are introduced, and organizational cultures become more collaborative and innovative.

By 2014 the federal government is the leading innovator in IT and management practices and helps to revitalize the private and non-profit sectors with its technology/best practices transfer programs. Citizen engagement and trust in government rises while the cost-savings and greater efficiencies bring about an era of budget surpluses.

In the past ten years, I have used the scenarios to help me plan my federal career. In fact, the LabGov scenario drives my long-term plans to be a consultant to state and local governments.

My career book will help job seekers create guiding scenarios to map out their career futures.