• 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

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.

It was that advice that has guided me ever since. It is very easy in the euphoria surrounding the triumph of solving a difficult problem or pulling off the near-impossible project to not spend the time questioning just why you succeeded. To do so seems to be diminishing the success and even doubting that you actually did succeed. On the contrary, an objective review of how you succeeded will greatly help you in continuing to succeed.

When we succeed, we can become victims of three biases, according to Gino and Pisano (April 2011). There is the attribution bias in which we overestimate how our knowledge and actions contributed to the success and we downplay any external factors that could have just made us more fortunate. We also become overconfident in our abilities as we tackle the next challenge. The third bias (and which I believe is most important) is that we don’t ask why we succeeded because the success is proof enough.

To illustrate this last bias, Gino and Pisano (April 2011) recount a study in which students were given a set of math problems to complete. When the students submitted their answers, they were only told if they had the answer right or wrong. The students were given time to reflect before they were given a second set of math problems. The second set was designed so that a key concept in the first set of problems was needed to solve the second set. The students who successfully solved the first set of problems generally spent much less time reflecting before they started on the second set of problems. Thus, many of these students failed to find the answer for the second set of problems. Reflection, whether the student succeeded or not, is the key to continuing to be successful.

So, how do we best learn from success? We should celebrate success but also examine the causes of success. For every project, we should hold a systematic review. Gino and Pisano (April 2011) give the example of Pixar’s review process. Even though Pixar has had eleven hit animated films in a row, the company still goes through an exhaustive review process to determine what made the film successful and how to repeat that success.

Another point to keep in mind is to fully investigate the feedback. Was it immediate or at least can be connected to the actions taken? Is the feedback a true indicator of success or just a random event that looks like a successful outcome? Feedback is an important concept and I explore it in greater detail in this discussion posting.

Two final points. First, “[r]ecognize that replication is not learning” (Gino and Pisano, April 2011). Blindly following the same formula again and again can suddenly turn against us as the nature of the problem changes and what worked before doesn’t work now. And, second, we should always be experimenting. We can always improve how we do something. Plus, we can create variations on our actions that may not apply to the current situation but can apply to a challenge in the future.

Failure is a great teacher but so is success. Learning from our successes will keep us from becoming “one-hit wonders” and give us the string of successful “hits” to be “rock stars.”

Reference:
Pino, F., & Pisano, G.P. (April 2011). Why leaders don’t learn from success. Harvard Business Review. 68-74.

Culture is a natural byproduct of humans as social beings. We develop culture so that we can get along, survive, and achieve goals. It is only naturally that we develop cultures at work because a large part of our waking hours is spent at work or thinking about work. A single person cannot have a culture; it takes interactions between each other to create a culture. But what exactly is culture?

There are many academic definitions for culture but for our purposes I prefer this simple definition: the way we do things around here. “We” come together in a defined group (eg. IBM, HUD, Star Trek fans) and in a defined boundary such as a department, office, or online community (“around here”). We develop methods, practices, policies, etc. (“way”) that govern the actions (“do”) members of the culture take in response to “things” (issues, events, etc.) that we face as a culture. Essentially, organizational culture is how we collectively solve the problems we face everyday in our work and life.

Thus, the resistance to changing the organizational culture. Problem-solving is hard and takes a lot or resources and effort. Humans are incredible at problem-solving but they are also good at optimizing. We don’t like having to solve the same problems over and over so we create things like writing, forms, email, databases and the like to embody the solutions we have created so that the next time the same problem shows up we can just solve it without having to think about it. We only give up our solutions when a demonstrably better solution comes along. And it better be a really good solution if it has a chance of displacing the current solution.

Cultural change is not only possible but it is necessary. Groups change, new events confront the group, and new problems face our culture. I believe that the reason why many intentional cultural efforts fail is that they don’t recognize the paradoxes of cultural change. This is what I can the Zen of culture because we blend many paradoxical ideas to develop culture. Here are three paradoxes that makes cultural change difficult for those who do not first seek to understand the culture:

1. The culture is not the culture. There is no one culture but many cultures that people belong to. You may have an overall agency culture but you also belong to the subculture of your department, the subculture of Redskins fans, the subculture of people who eat out for lunch, and so on. Some of these subcultures are easily changed while others are ingrained in you. And how these subcultures interact cause the resistance to change. For example, IT folks are often most open to new technologies while the law department would rather stay with the software they have been using for the last 20 years because they have built many of their processes around how the software works.
2. We seek the novel and the safety of the familiar. A colleague has a great example of this. Imagine a playground in an open field without fences. The children will often huddle together in the middle of the playground and are reluctant to wander out in the field. Now, put a fence around the playground. Then the children will often hang around the fence and are more willing to venture out in the open field. It is the setting of boundaries that makes us adventurous. We have the safety of the fence that we can run to in between our adventures. Culture equals safety.
3. Culture remains the same by changing. Thanks to the Internet, many ancient religions are now being practiced today. Many Amish businesses use a personal computer in their business dealings with the outside world. There are numerous monasteries that sustain themselves by creating websites for clients. Cultural groups will often use the new technologies or practices as a way to sustain the culture and its core beliefs. This can be frustrating for a change agent when they see their innovation being used to defeat the intent of the change.

I want to invite you to join the conversation on cultural change and keep Open Government alive. There is well-justified concern that the 2011 budget cuts to the Open Data sites will stall the Open Government but I believe that the best way to keep Open Government going is to change the cultures in our agencies and governments so that the citizens demand further change. This concern has prompted several of us to start an online group with two purposes:

1. to collect the best thinking on how to effectively change cultures so that they are more open, transparent, and collaborative, and
2. to establish worldwide unconferences where government workers, academics, and citizens gather to discuss how to change the culture of their governments to be more open, transparent, and collaborative.

Please join us at Culture Change and Open Government.

(Disclaimer: The views expressed are my own and do not reflect the views of my employers or any groups where I am a member.)

The failure of many early 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 (a computer scientist from the University of California) 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:

1. 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. In reality this is rarely the case. Consider a project management application where the team members are required to 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 just has to spend a minimal amount of time reading reports the system generates. The team member sees only a burden from the software and soon starts to avoid 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.
2. Critical Mass of Users. The collaboration software field is filled with a number of different platforms for collaboration. Many offer similar features and each has its 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 end up promoting organizational silos as the various groups argue that their system is the best solution.
3. 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 complex due to organizational culture.
4. Exception Handling. We rarely work the exact way that is described in our work processes. Collaboration software built only based on the documented office procedures is seen as 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 work solution. Now, imagine trying to program that into software.
5. Decreasing the Communication and Coordination Load. Organizations are designed to reduce the amount of communication and coordination needed to do the job. How many times 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 is the result of poorly-designed groupware.
6. Hard to Evaluate Groupware. It is difficult to test groupware because the group dynamics are so hard to replicate. It can take several weeks of careful observation to fully understood how a group works and software designers just don’t have the time or expertise to fully evaluate how their software will aid in collaboration. Often the groupware vendor blames this on poor user training and will continue the same type of software with better tutorials and help aids but never realizing that the fundamental problem is that people just don’t like collaborating the way the system is forcing them to collaborate.
7. Intuitive Decision Making. Because of the nature of our work we often have to make decisions based on little evidence and thus we rely heavily on our intuition. Groupware applications rarely support intuitive decision making but rather force users to input great amounts of data so that a fully-reasoned decision can be made. Often we do not have all of the data and a decision must be made quickly so we abandon the groupware application to use a simple spreadsheet or other individual application to support our intuition.
8. 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. There is a particular system at my work which 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 over sixteen-years old I still see the same mistakes being repeated in today’s Web 2.0 collaboration tools. I also see where companies have put these principles into practice and have made great collaboration software that has endured and grown in popularity. I fully suspect that Google engineers must have memorized these principles when they developed their Google Docs system. You can also see these principles at work in the various products from 37Signals and Zoho.

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?

Reference:

Grudin, J. (1994). Groupware and Social Dynamics: Eight Challenges for Developers. Retrieved at http://research.microsoft.com/en-us/um/people/jgrudin/past/papers/cacm94/cacm94.html.

Now on to the topic. There is a lot of cynicism both in and outside of government concerning Gov 2.0 and Open Gov. I believe most of this comes past government reform efforts which had, at best, mixed results. In my first round as a Federal employee I was involved with Gore’s Reinventing Government effort. Reagan had a blue-ribbon commission on reform as did Nixon. Government reform has been a continuing effort since Wilson and Taylorism. I believe they even found evidence of government reform efforts in Ancient Egypt (I wonder how you tell a god-emperor he or she needs to go “lean”).

So, with this long history of government reform which has some brought some innovation but disappointment what makes Gov 2.0 and Open Gov different? And is this difference enough to make a real impact? To me there are three major reasons why Gov 2.0 and Open Gov will succeed and succeed big:

1) Government is re-engaging their citizens. Public agencies can no longer operate as vending machines where citizens put in tax dollars and out pops government services. Agencies are becoming transparent and accountable for how they spend tax money and are encouraging citizens to become part of providing government services. Think of Dr. Noveck’s Peer-to-Patent program and the recent SeeClickFix programs.

2) Democracy is changing. I have written before about the emergence of monitory democracy and the recent events in Egypt, Libya, Yemen, and other Middle Eastern countries just demonstrates the desire for democracy and how media-rich nations empower citizens to grow democracy. Even in well-established democracies citizens are no longer content to vote for a representative and then trust that the government will operate in their interest. People want to speak directly to agencies that affect their lives and are demanding the right to monitor even the inner workings of the Federal, state, and local governments.

3) Balance of Information Power has shifted. Before the Open Data movement, government essentially held all the cards when it came to information about what government did and how it operated. Yes, there were investigative journalism articles, legislative hearings, and the occasional FOIA request but obtaining government information that wasn’t selectively released by agencies was difficult to obtain for the average citizen. Now, thanks to the Internet and Social Media technologies it is easier to gain access and to aggregate data sources to give a more complete picture of what government is doing. The Balance of Information Power is shifting in favor for the citizen and will continue to shift that way as government engages citizens and as monitory democracy evolves.

In Gov 2.0 and Open Gov the citizen is no longer a customer who passively receives government services. Past reform movements were built upon the vending machine model and that is why they didn’t deliver as promised. Gov 2.0 and Open Gov are built upon engagement and collaboration and that is why they will prove to be more successful.

What do you think? Are these three reasons valid? Are there better reasons for why Gov 2.0 and Open Gov will succeed? Or is Gov 2.0 and Open Gov just like previous government reform efforts?

What I took away from the conference was some ideas from Alfresco’s CTO, John Newton. He argues that enterprise IT has essentially been on hold since 2000 while consumer IT (Facebook, Twitter, etc.) has been on fire all throughout the first decade of the 21st century. Employees are demanding enterprise versions of what they use in their daily lives to connect and collaborate with their families. Not an original thought but a good summary of what is about to hit enterprise IT.

What was original and started me thinking was his later point that enterprise IT needs to build systems of engagement. That is, applications that focuses on the middle of the enterprise where the knowledge workers are. He states that we don’t need anymore applications for the frontline workers nor the top management because their needs are already met. I agree with the point about the top management but I am still not convinced about leaving out the frontline workers.

I do fully agree that the people in the middle of the enterprise do need better tools from enterprise IT. Tools that incorporate collaboration, knowledge sharing, and a whole host of activities under a new umbrella term that I just coined – collabogagement. A quick Google search shows that no one has used this term so I claim to be the first. In a future posting I will try to define it.

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.

Then I came across a recently published book that offered specific advice on communicating a change vision. Written by Dr. Nickerson, the concept is called changecasting and it is a simple method. The leader records a series of weekly or biweekly videos that are no more than two-to-four minutes in length. In these videos the change leader speaks directly to the camera while explaining the change vision using only one idea per a video. The videos are released through a secure website for the entire organization to view simultaneously. The members of the organization are then encouraged to give their feedback to the videos through an anonymous web-based communication method. The change leader answers the feedback in subsequent videos.

In support of changecasting, Dr. Nickerson offers a case study of two firms (identities hidden) where the presidents initiated a major organizational change. One president used the changecasting method as outlined by the author while the other president used video but didn’t follow the changecasting method. The firm that used changecasting of course prospered while the other firm failed at its organizational change effort. There is a website and, for a fee, your organization can have their changecasting videos reviewed for effectiveness.

I’m usually wary of such books because many business books have plenty of anecdotes but not much empirical evidence to support the author’s claim. In this case, I think the changecasting method is a good idea because it does track well with what I found out in my research on organizational change and general theories on communicating effectively.

When change is communicated the general model is that the change leader(s) creates a vision and then broadcasts the vision to organization through different communication channels such as posters, newsletter, all-hands meetings, intranets, etc. Rarely is feedback encouraged and even rarer is the opportunity to offer anonymous feedback. Much of the advice on handling resistance to the change vision is either by marginalizing the dissenters or enforcing compliance with the change effort. Most change efforts are initiated because of a threatening situation to the organization so there is little time for dissent or even questioning of the change effort. As you can imagine, there is very little interactive communication about the change vision.

This explains why a large majority of change projects fail despite the fact that organizational change must be one of the most studied topics in management science. According to research by the Standish Group, roughly 70% of projects will not deliver promised results, go over the budget, use more time than scheduled, and/or consume more resources than planned for . Clearly, current methods for organizational change are not working effectively. There are many reasons for this but the biggest reason is resistance to change due to uncertainty about the proposed change.

Now, I don’t believe that people in general are naturally resistant to change. If that were true, people wouldn’t buy lottery tickets. What people are naturally afraid of is not understanding the implications of the change that they are compelled to follow. And it also human nature to imagine the worst in situations we do not fully understand.

This is what attracted me to changecasting. I like the aspect of keeping the messages short and simple so as to fully engage your audience. I also like the frequency of communications but what really interests me about process is the anonymous feedback. Opening up a dialogue about the proposed change can help to reduce the uncertainty and thus the resistance to change. There will probably be some residual resistance but I believe that the change leader(s) will gain more acceptance of the change vision than if they simply broadcast the change vision.

Organizational change is a fascinating area of study that also has major practical implications. Methods that can switch the 70% failure rate to a 70% success will be extremely beneficial considering the vast amounts of time, money, and resources the government now wastes on bad change projects. I am greatly interested if any readers of this blog were engaged in a change project where feedback was encouraged and if this feedback led to a successful outcome. I think the changecasting concept is a good method but it needs more empirical support.

References:
Fernandez, S., & Rainey, H. G. (2006). Managing successful organizational change in the public sector. Public Administration Review, 168-176.

Nickerson, J. (2010). Leading change in a web 2.1 world: How changecasting builds trust, creates understanding, and accelerates organizational change. Washington, D.C.: Brookings Institution Press