Bill's Notebook

Does this look like your typical day as a local, state, or Federal worker?

• 31% of your work day is made up of purely ad-hoc, never happens the same way twice tasks
• 30% of your work revolves around consistent, defined goals but various ways to achieve those goals
• 20% of your work involves documented and managed tasks that are not automated
• 17% of your work is automated but there are numerous exceptions to the automated processes
• 9% of your work is fully automated and there are no ways to change the process (Fischer, 2011, p. 84)

Except for a very few exceptions, every government worker is a knowledge worker because they deal with constantly varying situations that we package into cases. In general, we may deal with specific subject areas and perform repeatable functions but the actual execution of this work will differ greatly from case to case. For example, when I was a paralegal/investigator for a public defender’s office, I helped on numerous assault cases. We had a specific process for interviewing the client, preparing the pleadings, assembling the evidence, and presenting the case. But the facts of the case were always different.

One case was about an assault by a drunken student on an equally drunk off-duty policeman. Another case was a domestic violence issue while a third involved a store employee who tackled a complaining customer. For each case, the kind of pleadings filed, how I conducted the investigation, and so on would differ based on the specific events in that case. You really didn’t know what was going to happen from day to day so it was difficult to determine routines beforehand.

This is why I don’t believe that the best way to improve government work is to start imposing Six Sigma and Lean processes onto government employees. Six Sigma and Lean are great methods if you are talking about repeatable processes that have clear paths and outcomes. But as the above statistics demonstrate, less than 10% of a knowledge worker’s day will benefit from traditional business process management techniques.

On the other hand, traditional case management as practiced by many government workers has many problems. Most government offices have overwhelming case loads, there are conflicting rules and procedures imposed by the top management, and the current support systems cannot easily handle the many exceptions that occur frequently (Swenson, 2010, pp. 10-24). What is needed is a way that allows for the great variation in knowledge work but makes that knowledge work more efficient and effective. I believe that the newly emerging management concept of Adaptive Case Management (ACM) is the answer along with its closely-allied discipline of Social Business Process Management (SBPM) (Fischer, 2011).

ACM is still evolving but there are several core elements. First, instead of being based on the principles of scientific management/Taylorism, it revolves around modern knowledge work. This means that ACM is designed to deal with change and ad-hoc processes as a case is being processed. Second, processes are not formalized and designed up front but are developed as the knowledge worker continues to see the same issue in a number of cases. Third, rules and regulations operate more like guardrails that constrain the actions taken in a case. The fourth element is that the knowledge workers rely heavily on a community-built template library and body of knowledge that is built collaboratively in the organization.

This is why ACM relies so heavily on social networking in the form of SBPM. In traditional business process modeling, discovering what processes exist and modeling these processes were done first and then the knowledge workers were expected to follow the newly-established processes until the weight of exceptions demonstrated that the new processes needed to be modified. Under SBPM, process discovery and modeling occurs as knowledge workers work on cases and share their experiences with each other. Thus, there is a great deal of variation at first in handling cases but as the knowledge workers gain more experience, they collaboratively develop best practices that can easily be modified when exceptions occur.

I have just given the briefest overview of these two new management concepts but I am greatly excited by the potential to reform government work for the better. There are numerous case studies in Taming the Unpredictable including how one local government agency used ACM for better customer service in its case management processes. Much of ACM and SBPM makes intuitive sense and should be especially attractive to those who argue we need more knowledge sharing and collaboration in our offices.

(Disclaimer: All opinions in this posting are my personal thoughts and do not reflect upon my employers or any organizations I belong to.)

References:
Fischer, L. (editor) (2011). Taming the unpredictable: Real-world adaptive case management: Case studies and practical guidance. Lighthouse Point, FL: Future Strategies, Inc.

Fischer, L. (editor) (2011). Social BPM: Work, planning, and collaboration under the impact of social technology. Lighthouse Point, FL: Future Strategies, Inc.

Swenson, K. D. (editor) (2010). Mastering the unpredictable: How adaptive case management will revolutionize the way that knowledge workers get things done. Tampa, FL: Meghan-Kiffer Press.

Additional Resources:
Law and Order: How Adaptive Case Management Serves the Public Good – http://community.global360.com/bpm_practitioner/b/weblog/archive/2011/08/11/law-and-order-how-adaptive-case-management-serves-the-public-good.aspx

Simplify Your Work Life: Adaptive Case Management – http://i-sight.com/tech/adaptive-case-management/

The Future of Adaptive Case Management – http://www.industryweek.com/articles/the_future_of_adaptive_case_management_22981.aspx

What is Adaptive Case Management? – http://www.cmswire.com/cms/enterprise-cms/what-is-adaptive-case-management-008277.php

Adaptive case management: New tools for doing more of what we do best – http://www.kmworld.com/Articles/Editorial/Feature/Adaptive-case-management-New-tools-for-doing-more-of-what-we-do-best-74486.aspx

What Could Cause Adaptive Case Management to Fail in 2011 – http://blog.actionbase.com/what-could-cause-adaptive-case-management-to-fail-in-2011

From an early age, I have never liked the observation that something is complex. It usually meant that person is just resigning themselves to never understanding the problem. I couldn’t stand this defeatist attitude and have spent most of my life trying to devise ways to tackle complex problems including the aptly-named “wicked problems.” Even though I may never find the solution to the P versus NP Problem, it has taught me a great deal about problem solving in general.

So, what do we mean when say a problem is complex? According to Dr. Melanie Mitchell, there are nine definitions for complex as used by complexity theorists. These definitions range from “complex as a matter of size” to “complex as a degree of hierarchy” to “complex as a measure of algorithmic information content” (pp. 96-111). I tend to think of complexity in terms of systems theory in which you have a number of discrete components with numerous feedback loops and many variables that are hidden within the system processes.

A good example of a complex system is the American economy. There are many discrete components in the forms of companies, consumers, banks, regulatory agencies, etc. all passing information to each other and reacting to that information. Attempts to model the American economy range from the simple macroeconomic diagrams in textbooks to detailed microeconomic equations that requires years of mathematical study to even understand. Yet these models, no matter how detailed, cannot fully describe and fully predict how the American economy operates.

If you accept my definition of complexity then you can see how the next concept describes why complex problems are hard to solve. We have difficulty in solving complex problems because our observation of the problem is hindered, we cannot fully understand the problem, our decision-making processes are flawed, or we cannot act appropriately in confronting the problem. If any of the difficulties I mentioned sound familiar it is because I am describing the four components of the “OODA Loop.”

The Observe-Orient-Decide-Act Loop (OODA) was created by Colonel John Boyd who was a fighter pilot and scholar in military strategy. This concept has been adopted both by the U.S. military and championed by such business experts as Tom Peters. As the diagram below demonstrates, a person, team, or an organization observes a situation along with other inputs. Based on the observations and several internal factors, the subject attempts to orient themselves or understand the unfolding situation. Based on that understanding, the subject then makes a decision and acts upon that decision. Throughout the OODA Loop, there are several feedback channels that make the entire process nonlinear.

Colonel Boyd explained that the use of the OODA Loop was to travel through the Loop faster than your opponent. You present confusing and ambiguous information to your opponent so that they have difficulty orienting themselves and thus are slower to decide and act. Essentially, you want to go through your own OODA Loop faster than your opponent does so that they start falling behind and then are paralyzed by their inability to analyze the situation. Time is the key factor in OODA Loops.

The OODA Loop is why I think complex problems are so difficult to solve. Consider the five components of the OODA Loop as it applies to your personal abilities or the abilities of your team/organization:

• Observe: This is the beginning of the Loop and also feeds into another iteration of the Loop. If your observational abilities are hindered or you just cannot observe all parts of the unfolding situation then you are working with incomplete information. History is replete with examples where disasters occurred because of the lack of key information.
• Orient: This is where you/the team/the organization takes in the new information and pairs it with your previous knowledge, cultural traditions, and other internal factors that influence how you process and analyze information. So, even if you are able to observe the entire unfolding situation, your internal abilities to process and analyze this information can prevent you from fully understanding what is happening.
• Decide: This relates to your ability to generate hypothesis about the situation and possible responses. There is the common “paralysis by analysis” which hinders decision making because you are still trying to orient yourself to the situation. Or, even if the organization has a good understanding of the situation, decision processes may be so cumbersome that you cannot make a decision in time to act on the situation.
• Act: You may not have the resources to act promptly and/or appropriately. Your understanding of the situation may have led to a flawed decision that forces an invalid response to the situation. You do not have the proper feedback mechanism built in your action to determine how your act affected the unfolding situation.
• Feedback: As you go through the OODA Loop, you are constantly generating and receiving feedback from your current iteration and previous iterations. Without good feedback design, your own actions can contribute to the ambiguity of the situation. This is especially true of wicked problems where there is no consensus on the actual shape of the problem and your actions can drastically morph the problem into a completely new problem.

The good news here is that you can also use the OODA Loop to better your abilities to handle complex problems. Use the five components as a checklist for improving your (or your organization’s) processes in handling complex problems.

For example: how well do you observe? How good is your organization at collecting and disseminating information internally? Do your people have the necessary prior knowledge and analysis skills to properly orient themselves when new observations come in? How robust and quick is your team’s decision-making skills? What barriers can you remove so that you can act faster? What can you do to improve your feedback mechanisms?

Government is going to face more complex problems especially in a climate of reduced budgets and increasing responsibilities. All government employees at all levels need to sharpen their problem-solving skills so that we are more innovative and can better tackle the looming wicked problems that face the nation. Whether you accept my suggestion to use the OODA Loop or come up with your own problem solving method, the process of thinking about complex problems is a great way to sharpen your problem solving skills.

Reference:
Mitchell, M. (2009). Complexity: A guided tour. New York: Oxford University Press.

As the first decade of the 21st Century ends, I hope that the economic events of the last thirty-five years finally loosen the hold that neoclassical economics has on public policy.  It is widely recognized that the accepted economic models that governments use to shape policy are just not empirically valid.  Today’s economies are vastly different from the industrial revolution economies that shaped neoclassical economic theory.  Yet, these theories are the basis for setting interest rates, regulating the stock market, determining the level of environmental protection, almost every aspect of government regulation (Smith 2010, p. 65).  It is time to modernize the economic theories that are used to guide government and economic policies.

The case against neoclassical economics has been growing in recent years.  As Yves Smith (2010) details in her book:
1)  Economics is not a real science because it is difficult to do the empirical evidence to validate the models economist develop from their assumptions (pp. 20-21).
2)  Many of the core assumptions of neoclassicism (people are totally rational, have complete information, only act to maximize utility, etc.) have been disproved by experiments in behavioral economics (pp. 94-97).
3)  Despite the fact that they are working with faulty assumptions, economists claim that the implications derived from the assumptions are still valid because they are good approximations of reality (p. 41 and pp. 47-48).
4)  Hard sciences also use simplified models to explain phenomena but the crucial difference is that economists add unrealistic properties to validate their models.  For example, economists add the property of perfect information to make supply and demand models work (pp. 48-49).

Some economists counter by admitting that neoclassical economics has these problems but the cure is to do more empirical research.  But with more empirical research, the neoclassical assumptions are giving way to a new economic theory – complexity economics.

Eric Beinhocker (2007) surveys the rise of complexity economics in which researchers apply complexity and network theory concepts to economic activities.  The main advantage of complexity economics is that its assumptions can be empirically validated and that its findings apply to modern economic phenomena.  Thus, this is a better basis upon which to base policy decisions.

Beinhocker’s  (2007) core argument is easy to understand.  Businesses use a mixture (business plan) of physical technologies and social technologies to compete with other businesses.  The businesses that have more fit business plans out-compete businesses with less-fit business plans.  Based on this model Beinhocker details several implications for policy makers:
1)  The role of markets is to process the immense amount of information from buyers and sellers into the most coordinated and effective manner while also determining how fit a business is.  Thus free and open markets must be maintained by regulations that do not impede the flow of information available to all parties (p. 423).
2)  Government’s role is to provide and preserve the vast array of social technologies that make it possible for businesses and markets to exist.  Social technologies such as contract law, antitrust enforcement, and securities regulation (p. 425).  Therefore, government plays an important role in shaping the fitness determination role of markets (pp. 426-427).
3)  Behavioral economics indicates what kind of social programs will be more readily accepted and politically-supported.  People will support aid programs that have strong reciprocity – programs designed to help people become functionally independent (pp. 418-421).
4)  Countries that score higher on measures of societal trust also have higher economic performance than countries with lower societal trust scores (pp. 432-433).  Thus, an important role for American government is to build up social capital in the U.S. (pp. 439-440).

As the above demonstrates, government has a vital role in preserving and strengthening the U.S. economy.  The argument of neoclassical economics that government should have little or no role in market economies is a false one and has led to extreme reactions from the Left and the Right.  With a clearer understanding of government’s actual role in the U.S. economy policy makers can craft effective policies that preserve the best features of the market system while building up the necessary social capital to strengthen the economy and serve the U.S. people.  We just need to move beyond the false answers given by neoclassical economics to the insights of complexity economics.

References:
Beinhocker, E.D. (2007). The origin of wealth: The radical remaking of economics and what it means for business and society. Boston, MA: Harvard Business Press.

Smith, Y. (2010). Econned: How unenlightened self interest undermined democracy and corrupted capitialism. New York: Palgrave MacMillan.

Further Reading:
Berreby, D. (2005). Us & Them: The science of identity. Chicago: The University of Chicago Press.

Cassidy, J. (2009). How markets fail: The logic of economic calamities. New York: Farrar, Straus, and Giroux.

Lehrer, J. (2009). How we decide. Boston: Houghton Mifflin Harcourt

Pfaff, D.W. (2007). The neuroscience of fair play: Why we usually follow the golden rule. New York: Dana Press.

Schelling, T.C. (2006). Micromotives and macrobehaviors. New York: W.W. Norton & Company.

Shermer, M. (2008). The mind of the market: Compassionate apes, competitive humans, and other tales from evolutionary economics. New York: Times Books.

Stiglitz, J.E. (2010). Freefall: America, free markets, and the sinking of the world economy. New York: W.W. Norton & Company.

Thaler, R.H., & Sunstein, C.R. (2009). Nudge: Improving decisions about health, wealth, and happiness. New York: Penguin Books.

Ubel, P.A. (2009). Free-market madness: Why human nature is at odds with economics – and why it matters. Boston, MA: Harvard Business Press.

Great story on how network analysis can explain the 2008 collapse.  Look at the four network diagrams in the middle of the article.  You can see the various sectors of the economy gradually merge together.  The most alarming trend is how real estate went from an almost isolated sector to being the center of the combined networks.  Graphic proof of how the growing interdependence between the sectors fueled by increasingly exotic investment instruments short-circuited the regulatory safeguards of  the economy.

A book that I constantly recommend is Beinhocker’s The Origin of Wealth for two reasons. First, Beinhocker demonstrates how traditional economics is inadequate for explaining today’s economic systems. Second, he introduces complexity economics which is still developing but does a much better job in describing how real-world economies work and how people behave economically. To illustrate, let me give a simplified description of his core theory.

You start with a business plan. A business plan is a description of how you will meld physical technologies and social technologies to create a business that competes in an economy. Physical technologies (PT) are “methods and designs for transforming matter, energy, and information from one state into another in pursuit of a goal or goals.” Social technologies (ST) are the “methods and designs for organizing people in pursuit of a goal or goals.” Your business then competes with other businesses on the economic fitness landscape.

The best way to think of a fitness landscape is to imagine a square piece of land with hills and valleys. Businesses want to climb as high as they can on the highest hills because the higher you are up on a fitness landscape the more successful you are. Conversely, if you are in a deep valley you are failing in being fit on that landscape. Various factors determine fitness such as profitability, customer relations, and so on.

So, what does this have to do with Gov 2.0 or government in general? Replace business plan with plan and business with either project or program. You still have PT and ST but instead of building a business to compete on an economic fitness landscape, you are building a project or program to compete in government agency fitness landscape or policy area fitness landscape. This may seem rather abstract but this new perspective helps to consider fundamental questions about your Gov 2.0 project.

1. What are the factors that determine fitness in your landscape? Is it citizen engagement, cost-efficiency, and ease of implementation? Or is it increased collaboration and knowledge generation? Understanding what constitutes success will help to determine what the goal or goals should be for your Gov 2.0 project.
2. What PT an ST will the project need? How will these technologies blend together? Are there barriers to a good blending? Will the proposed blend fulfill the fitness factors more effectively than other blends?
3. How do I know if the Gov 2.0 project is climbing hills in the fitness landscape? How do I find the highest peaks in the fitness landscape and keep the Gov 2.0 project from being stranded on a smaller peak? How do I keep the Gov 2.0 project out of the valleys?
4. What do I do if the fitness landscape shifts? How do I determine when the fitness landscape shifts and what can I do to move the Gov 2.0 project so it stays on the peaks?

Another concept from Beinhocker that is also useful to government agencies is the idea of social architecture. Social architecture determines how adaptable an organization is and is composed of three factors:
1. Behaviors of individuals in the organization (Mental Models)
2. Structures and processes that align people and resources in pursuit of the organization’s goals.
3. The emergent culture that arises from people’s interactions with each other and their environment.
A robust social architecture gives the organization better abilities to determine the shifts in the fitness landscape and to better adapt to the shifts.

The advantages of the fitness landscape perspective is that it starts the dialogue on what the goals of the the Gov 2.0 project are and how the current environment will help or hinder reaching those goals. It also requires an honest assessment of the agency’s abilities to understand their current environment and to adapt when the environment changes. Beinhocker’s book is dense with ideas but he writes in a approachable style and his last chapter is especially vital in understanding government’s role in complexity economics.

Reference:

Beinhocker, E.D. (2006). The origin of wealth: The radical remaking of economics and what it means for business and society. Boston: Harvard Business Press.

Take a moment and look around your personal office space. Now look at your computer and notice what your desktop icons are and what programs you have open. According to Richard Ogle, the books, documents, computer programs, and other work aids are parts of our extended mind. We create documents, spreadsheets, whatever to offload our intellectual task load so that we can function better in our tasks.

In doing so we have made our tools more intelligent so that they could do some thinking on their own. Think of a spreadsheet you created. Building it took concentrated intellectual effort on your part. But now, you just open the spreadsheet, enter a few numbers, and it does the thinking for you. The spreadsheet has embedded intelligence. Embedded intelligence can also exist in organizational procedures, processes, documents, and even culture. Put enough of these embedded intelligences together and you have an Idea Space.

So what does this have to do with innovation? It is through exploring different Idea Spaces and using analogical thinking that many innovation breakthroughs were achieved. Ogle gives the example of Frances and Crick’s discovery of the structure of DNA. Frances and Crick succeeded where other researchers failed because they were able to apply concepts from other fields and applied it to their problem. Instead of analytical thinking where they reduced the problem to its component parts they used analogies to view their problem from different perspectives and discover a solution.

This happens all of the time. You are working on a problem and then you think of something similar you did on another project. You apply the solution you created before and, with a little tinkering, it works just as well for the new problem. Real innovation occurs when you can apply a seemingly dissimilar analogy and make a truly creative breakthrough.

What all this means for you and your agency is that Idea Spaces follow the common laws of networks. Richard Ogle posits nine such laws such as the “fit get fitter” and “tipping points.” These laws boil down to two: Idea Spaces self-organize into networks and creative leaps occur by connecting Idea Spaces through analogical thinking.

Go look at your colleagues offices. What is their extended mind like? Think of your agency procedures and practices. What Idea Spaces exist there? How would you characterize the network of Idea Spaces? Is it easy to navigate? Can your apply analogical thinking from your colleagues’ Idea Spaces? What barriers exist in agency policies that prevent navigation and analogical thinking?

Nick Charney wrote in a recent blog posting about what is the goal of collaboration. He is correct in that just getting together to talk is not enough. I suggest that the goal of collaboration is to share our Idea Spaces and help others navigate the Idea Spaces so that we can apply analogical thinking to solve our collective problems. We should map our Idea Spaces, help the network of Idea Spaces grow, and clear away the underbrush and barriers to navigation. That is the return on investing in collaboration.

This is why Gov 2.0 and Open Gov are so important. They are not ends in themselves but they make the Idea Spaces network stronger and easier to navigate because the Gov 2.0 tools make it easier to embed intelligence while Open Gov encourages more collaboration. As you go about your work try to see your agency as a collection of Idea Spaces. Is the network strong or does it need help? What barriers are preventing you from applying analogical thinking in your work? Can Gov 2.0 and Open Gov help your agency create a better Idea Spaces network?

Reference:

Ogle, R. (2007). Smart world: Breakthrough creativity and the new science of ideas. Harvard Business School Press.

Appendix A – Formal Definition of Idea Space: “a domain or world viewed from the perspective of the intelligence embedded in it, intelligence that we can use – consciously or not – both to solve our everyday problems and to make the creative leaps that lead to breakthrough” (p. 13).

I believe that the best argument made by Eggers and O’Leary in If We Can Put a Man on the Moon was the need for lawmakers to consider how their proposals will be implemented when the programs are passed to the agencies. I was thinking about this when I was visiting the Woodrow Wilson Center’s electronic archives for the (now defunct) Office of Technology Assessment.

For those not familiar with OTA, it was an agency that performed deep technical analysis of current science and technology topics. Founded in 1972, it produced reports on the impact of the supersonic transports, how to best prepare citizens for disasters, and the benefits of early childhood health programs. OTA provided objective and succinct guidance to Congress on technology issues until it was shut down in 1995. The science community has continually called for OTA’s reestablishment and in 2008, GAO was tasked with producing technical assessment reports.

This year, the Woodrow Wilson Center argued [PDF] for creating a network of nonpartisan organizations to provide objective technical assessments (Expert & Citizen Assessment of Science & Technology – ECAST Network). This is a great idea but I think it should be taken one step further: a nonpartisan network of scholars and practitioners to provide analysis and strategies for implementing major legislation.

Now, your first response is probably that we already have more than enough organizations that provide detailed advice on how to implement almost every bill before Congress. Very true but the problem with their advice is that it is often politically-motivated and rarely deals with the realities of how the agencies will make the programs work effectively and efficiently. Also, I’ve yet to see these proposals consider how their strategies will impact other program and government operations as a whole.

We have a unique community of practitioners and scholars from all levels of American government on GovLoop. I envision developing some type of online structure that could tap into the expertise and practical knowledge that this community possesses and channel it into implementation strategies for such topics like health care, emergency preparedness, and similar topics. We already have tools for collecting ideas, judging those ideas, and crowdsourcing innovations and best practices.

I’m just tossing this idea out there to see if anyone would be interested in discussing it further. I have a few concepts for next steps but I really want to just start the dialogue. This could also serve as a general conversation on creating virtual agencies and better citizen engagement through crowdsourcing (like Beth Noveck’s concepts in Wiki Government).

What exactly is the nature of the Gov 2.0 challenge? This question was inspired by Andrew Krzmarzick’s post (“What Gov 2.0 Needs Now: Managers, Money and Models”) and Christina Morrison’s post (“What is Gov 2.0? A survey of Government IT pros”) on the recent GovLoop survey about Gov 2.0. As Andrew and Christina argued, the survey demonstrates many differing perspectives on Gov 2.0 in terms of what it actually means and how to implement Gov 2.0. To me, this suggests that Gov 2.0 is the classic wicked problem.

Wicked problems were originally an IT concept but it has spread to other fields as we confront more complex challenges. Definitions of wicked problems vary but the Rittel and Weber’s definition is the most cited:
“ 1. There is no definitive formulation of a wicked problem (defining wicked problems is a problem).
2. Wicked problems have no stopping rule.
3. Solutions to wicked problems are not true-or-false, but better or worse.
4. There is no immediate and no ultimate test of a solution to a wicked problem.
5. Every solution to a wicked problem is a “one-shot operation”; because there is no opportunity to learn by trial-and-error, every attempt counts significantly.
6. Wicked problems do not have an enumerable (or an exhaustively describable) set of potential solutions, nor is there a well-described set of permissible operations that may be incorporated into the plan.
7. Every wicked problem is essentially unique.
8. Every wicked problem can be considered to be a symptom of another problem.
9. The existence of a discrepancy representing a wicked problem can be explained in numerous ways. The choice of explanation determines the nature of the problem’s resolution.
10. The planner has no right to be wrong (planners are liable for the consequences of the actions they generate).”

Gov 2.0 seems to fit nine of the ten criteria (I have my doubts about point five) but I think the better definition is Conklin’s incorporation of social complexity into wicked problems because of the great number of stakeholders , the multitude of solutions, and the multiple perspectives of Gov 2.0. I believe Mark Drapeau’s diagram of Gov 2.0 best captures this complexity.

So, why should it matter if we determine that Gov 2.0 is a wicked problem? Well, once we know the kind of challenge we face, we can determine the best strategies to confront it. If Gov 2.0 were a tame problem then we know that our standard toolkit of problem solving methods and data analysis are adequate for creating solutions. The tame problem does not change as we attempt to analyze it and we can model the interactions as simple cause and effect relationships. The definition of a tame problem can be easily agreed to as also the solution.

But if we establish that Gov 2.0 is a wicked problem, then we know that even defining the problem will be difficult much less knowing what the solution will be. In fact, with most wicked problems, you don’t solve the problem as much as manage it (climate change is a good example of this). Much of the work is in building consensus among the stakeholders on the wicked problem and developing innovative methods to manage the problem. There is also a substantial amount of work in identifying and containing undesirable effects stemming from the management of the wicked problem.

In dealing with a wicked problem, we need collaboration across government organizations while helping to build up skills for innovation among the employees. Beinecke (2009) argues for a new type of leadership that is transformational rather than transactional. We also have to develop a new perspective on risk management as Krigsman (2010) argues in his article. The Australian Government has produced a great manual on how to deal with wicked problems in government management that is excellent guidance for current Gov 2.0 activities.

Establishing Gov 2.0 as a wicked problem may seem discouraging but the good news is that there is many tools to help us understand and manage wicked problems that emphasizes the benefits of our solutions while minimizing the undesired effects. It also confirms the need for more openness, collaboration, and innovation in government.

References:
Australian Government. (2007). Tackling Wicked Problems: A Public Policy Perspective. http://www.apsc.gov.au/publications07/wickedproblems.pdf

Beinecke, R.H. (2009). Introduction: Leadership for Wicked Problems. The Innovation Journal: The Public Sector Innovation Journal, 14:1. http://www.innovation.cc/scholarly-style/beinecke1.pdf

Conklin, J. (2008). Wicked Problems & Social Complexity. http://cognexus.org/wpf/wickedproblems.pdf

Drapeau, M. (May 24, 2010). What does Government 2.0 look like? http://radar.oreilly.com/2010/05/what-does-government-20-look-l.html

Krigsman, M. (May 7, 2010). ‘Wicked problems’: collaboration, risk, and failure. http://www.zdnet.com/blog/projectfailures/wicked-problems-collabora…

Science Daily. (December 5, 2007). Complex ‘Wicked’ Problems Better Solved Individually Than Through Internet Groups. http://www.sciencedaily.com/releases/2007/11/071130172937.htm

Wicked Problem. http://en.wikipedia.org/wiki/Wicked_problem

Wicked Problems, May 2002. http://www.poppendieck.com/wicked.htm

I was going to post more about Process Intelligence and the Adaptive Project Framework last Monday but I was snowed under at work. Good thing because John Kamensky posted a great comment on President Obama’s Accountable Government Initiative. As I read the snapshots of the six initiatives, I was struck by how the success of each initiative depends on good project management and good business process management. There was a good discussion recently about the role technology plays in Gov 2.0 but I personally think the key to successful Gov 2.0 and OpenGov are the management methods. We need new methods for managing projects and for continuously improving Gov 2.0 processes.

Traditional project management is still useful. Thanks to TPM, the US Government built Trident submarines, nuclear aircraft carriers, and landed men on the Moon. Much of what made TPM so effective are the innovations pioneered by the Federal project managers such as Earned Value Management and Program Evaluation and Review Technique. But, for TPM to be effective, the goal and the solution must be known in advance and change must be minimized as much as possible.

In the Gov 2.0 reality, change is paramount and rapid while the goal may be well-defined but the solution to achieve the goal is often vague. Timelines are extremely short and so are resources and budgets. Using TPM to manage Gov 2.0 projects is just inviting failure (as the numerous examples in the IT Project Failures blog will attest). For Gov 2.0 and OpenGov to succeed we need new methods to manage these projects and their implementation. That is why I advocate the Adaptive Project Framework.

The APF was created by Dr. Robert Wysocki during his 40+ years as a project manager. He wanted a project management method that could better handle change and allowed for exploring a way to a solution while minimizing wasted time and resources. The best feature of APF is that the project scope is variable and that is what makes it perfect for Gov2.0 projects.

Scope in a project is what work needs to be done during the project (Project Scope) and what features the project product will have(Product Scope). In TPM, both Project Scope and Product Scope is fixed as early as possible. All planning, scheduling, and resource requirements are anchored to the scope and this is why change is so disruptive to the TPM project.

APF uses Cycle Plans and Cycle Builds to incorporate change into the project management process. In the initial planning, the project manager and project customer(s) create a high-level document that defines the project goal and conditions of satisfaction. Then a Requirements Breakdown Structure is built that captures the project product requirements at that time. A Cycle Plan is created that details what requirements will be created during the Cycle Build. The Cycle Build is time-boxed which means that it is a short duration (two weeks to a month).

During the Cycle Build you can have two streams of work. In one stream, some team members explore new features to include in the final project product while the other stream integrates proven features together into the product. As new ideas emerge they are added to the Scope Bank to be part of future Cycle Builds. Any features that are not completed within the Cycle Build are added to the next Cycle Plan. The Cycle Build can also be terminated early if the features are not working or if the current solution no longer fulfills the project goal.

To illustrate the difference, let’s use an example from recent events. Suppose you are working on a project to apply Search Engine Optimization (SEO) strategies to your agency website. You are halfway through the project when Google launches Google Instant. Then Twitter launches a redesigned search service. This requires a major change in your SEO strategies. Now what do you do?

Under TPM you could continue on with the project but your project product will be outdated and ineffective by the time you deliver it. Or you could cancel the TPM project and start all over again. You have wasted time and resources while incurring the additional costs of a new project. This will not look good on the IT Dashboard.

Under APF, the most you have to do is modify the Conditions of Satisfaction document and the Project Overview Statement. You can cancel the current Cycle Build and begin a new Cycle Plan to incorporate the new technologies and techniques into the final project product. Waste and loss of time are minimized while the current project can continue on toward the original goal but with an improved solution.

In my next posting, I will go into detail about Process Intelligence and how that can help address the issues raised by William Eggers and John O’Leary in If We Can Put a Man on the Moon… Getting Big Things Done in Government. I have also added two new pages devoted to collecting resources about Process Intelligence and Project Intelligence to my personal blog.

Graetz and Smith’s (2010) article starts off well enough:

“Traditional approaches to organizational change generally follow a linear, rational model in which the focus is on controllability under the stewardship of a strong leader or ‘guiding coalition’.  The underlying assumption of this classical approach, ever popular among change consultants, is that organizational change involves a series of predictable, reducible steps that can be planned and managed (Collins, 1998).  The evidence from case studies of failed change implementations indicates, however, that this uni-dimensional, rational focus is limited because it treats change as a single, momentary disturbance that must be stabilized and controlled.  Such a view fails not only to appreciate that change is a natural phenomenon which is intimately entwined with continuity but, also, that the change-continuity continuum is what defines organizations and their ability both to exploit and explore.  Change and continuity represent competing but complementary narratives, bring in ambiguity and novelty to destabilize as well as validate existing organizational routines.” (pp. 135-136).

But the rest of the article doesn’t live up to the promise of introducing a new method for bringing about organizational change.  The authors catalog ten change philosophies* by describing each philosophy’s methods for change and associated shortcomings.  They then discuss the continuity-change continuum and argue that change agents must use a “multi-philosophic” approach even though the authors don’t specify what they mean by multi-philosophic. That is unfortunate because I believe that they have pinpointed the fundamental problem with change management in modern organizations.

Organizations are in a constant state of change as an inherent part of its interactions within and without.  Organizations are also constantly resisting change because the members are trying to maintain continuity.  Most of the time, change is a constant background hum in the organization that periodically causes minor changes in processes (switching from voice mail to email to communicate requests or distributing information via the web versus the previous method of printed reports).

Change agents need to realize that change already exists in the organization and that to bring about deep change is to dial up the change part of the continuum while realizing that people in the organization are conditioned to respond by dialing up the continuity part.  If the organizational change is meant to destroy the existing continuity part of the continuum in favor of a new continuity, there will be a period of chaos until the new continuity is established in the continuum.  Change produces feedback and this has to be handled carefully or the increasing disruption can upset the continuum balance.

Graetz and Smith (2010) have the beginnings of a successful change method.  Harness the change inherent in the organization and realize how the continuity portion of the continuum will resist the change.  Convince a critical mass of the organization’s members to drop the continuity in favor of the change in order to shift the balance.

The big question is just how do you handle these tasks in the change-continuity continuum?

Note:

* Biological, Rational, Institutional, Resource, Contingency, Psychological, Political, Cultural, Systems, and Postmodern.

Reference:

Graetz, F., & Smith, A.C.T. (2010). Managing organizational change: A philosophies of change approach. Journal of Change Management, 10:2. 135-154.