017 What starts as a trickle can become a flood

forest-1308484_960_720This week’s episode deals with complex adaptive systems, which are found both in nature and in organizational settings (among other places)…

With storm clouds overhead, I stand along a dry creek bank in Texas. As the rain starts, very soon there is a small trickle of water, it grows larger, and in time becomes a comparative flood. If I remain long enough, eventually the rain stops, and the creek goes back to its original dry state within a few hours. This is an example of a complex adaptive system. No one is in charge, yet the system self-organizes through the interaction of the drops of water with the land, and with the other features of the environment. One simple principle drives the system, that is, that water runs downhill to find its own level. The system undergoes a rapid phase transition, moving quickly from its static steady state where the creek bed is dry, to a dynamic state in which the creek is full of water. In most rainfall events, the creek bed acts to contain the water and to channel it safely downstream. But historic events can also occur in which the supply of water overtops the banks and floods wide stretches of adjoining area. The dry steady state can last for long periods, especially during drought; so long, in fact, that entire subdivisions can be built in close proximity to the creek without the authorities being fully aware of the hazard.

Trickles can become floods in other contexts, as well. Avi Dan, writing in Forbes, noted that for 40 years you couldn’t walk through Grand Central Station in New York without admiring the large 18 by 60 foot Kodak photographs displaying panoramas of America. These were designed to showcase the Kodak brand to travelers that passed through the station. In those days, Kodak marketing executives were adept at weaving the brand into the fabric of America, and they captured 90% of the US film market for generations. At the time, Kodak was one of the world’s most valuable brands. But Kodak’s story is ultimately one of failure, rooted in decades of success. Kodak didn’t miss the digital age, rather, it invented the digital camera in 1975. Instead of marketing the new technology, however, the company held back so as not to hurt its film business, which was quite lucrative at the time. Sony and Canon eventually exploited the opening and moved to absorb much of the market with digital cameras. What started as a trickle became a flood. Kodak saw its market share decline precipitously as digital imaging became dominant. In the new regime, only a small percentage of digital images were printed on Kodak film. In this example, the environment culled Kodak because it did not evolve quickly enough to give customers what they wanted within the dynamic new digital reality.

This episode of our podcast explores organizations as complex adaptive systems (or CAS). It is a valuable perspective for examining organizational performance because it reveals hidden patterns that are present beneath the surface. In the past, such patterns did not lend themselves to study due to a lack of tools to examine what was going on. In the CAS perspective, organizations are seen as complex systems made up of individuals that may act on their own. These individuals are called agents, and might typically include an organization’s management, employees, and suppliers. In such a system, order emerges from below based on the interaction of the agents with each other, and produces such things as a culture, a set of underlying principles, and a general sense of “how we do things around here”.

In the natural world, complex adaptive systems can be seen in flocks of birds, schools of fish, and colonies of ants, among many others. Within a flock of birds, individual birds synchronize their states in the flock based on simple local rules. No single individual controls the system, but order emerges from the interaction of the agents with each other. In a school of fish, agents interact in a nonlinear fashion and synchronize their movements by rapidly changing direction in surprising patterns. In ant colonies, individual ants self-differentiate to conduct different tasks, although no one is in charge (including the queen). While there is no agreed definition of a complex system, emergence occurs when complex systems function as an integrated whole, allowing consistent patterns to emerge from below.

Organizations are often thought of as fairly conventional entities that are focused on specific goals and organized somewhat like a factory to achieve them. When the organization is threatened, it is anticipated that staff will react with one accord to counter the threat. But this model does not work reliably, especially when the environment in which an organization lives is changing rapidly. In these cases, it is useful to think of an organization as a complex adaptive system, where the parts of the system are not assumed to act in unison, but may act separately. During periods of rapid phase transition, individuals, and social grouping within the organization can enter a state of turmoil. Complex adaptive systems react in unpredictable ways at these times. When the system is far from equilibrium, individual employees may adapt to the new reality by either cooperating to fix the problem or, alternatively, display a non-cooperative or competitive attitude by rejecting the storyline that management offers. During transition periods, so-called ‘attractor’ regimes can emerge. For example, when confronted with a zero-sum game, such as outsourcing some jobs overseas, employees seldom cooperate. On the other hand, the positive sum game presented by the expansion of a firm into a new segment of the market readily gains employee acceptance.

The complexity theory of organizations rejects the metaphor of organizations as well-oiled machines made up of replaceable parts. Instead, an organization’s collection of agents has been brought together for a specific purpose, where they exhibit aspects of self-organization, emergence, and interdependency. Over time, the organization generally attempts to retain agents based on their individual contributions to the whole. Exemplary individuals are promoted while those that seem to be a poor fit are encouraged to go elsewhere. While these can be thought of as common HR processes, it is important that a climate of fairness and good will be maintained throughout in order to avoid adverse behavior by those affected.

On the macro level, organizations are integral parts of their environment, where they act as agents themselves on a larger stage and where they interact with customers and other organizations that frequent the same space. Within the environment in which organizations live, evolutionary processes of selection and retention continuously act on them. Organizations survive and thrive based on the strength of benefit exchanges with their environment. When environments are far from equilibrium and undergoing rapid change, evolutionary processes act strongly to encourage them to adjust their offerings in order to remain relevant to the changing needs of demand-side actors in the environment. In these situations, it may be important for organizations to have a variety of offerings in the pipeline and ready for deployment to meet these emerging needs. In a real sense, the environment is selecting organizations for retention based upon their effectiveness.

A good example of this phenomena is Qualcomm. In May 2016, Qualcomm’s CEO Steven Mollenkopf described the dynamic nature of the tech environment to The Street, “What people kind of forget in the tech industry is that you are [in a battle of] life or death, basically. You either win technology transitions or you don’t live to tell the [tale] because things move so quickly. We have had to pivot the company so many times either to a different end market or a different core competency, and the rate we have had to do that would surprise people. It could be every five years that we really have to make sure that we hit the next transition very, very well.”

Some scholars distinguish an organization as a complex evolving system (rather than adaptive system) because its human agents have the capacity to learn and evolve with each change. This allows an organization to better influence its environment, predict likely future changes, and prepare for them.

There is a tension between the two extreme states that organizations face, homeostasis and chaos. Homeostasis can be represented by an old-style bureaucratic organization in equilibrium, where the goal is predictability and stability. Chaos is the opposite state, where an organization is operating far from equilibrium and is in a state of turmoil, typically brought on by a catastrophic event. Neither of these extremes is conducive of good performance. Between the two extremes, but just short of the onset of chaos, organizations can find their mojo. Here, random events in the environment can be amplified by feedback loops and become important new paths toward the future.

The CAS perspective lends itself to the study of organizational performance. For instance, as mentioned in Episode 015, the use of the goal model for organizational effectiveness, and today’s computer-based scorecards, dashboards, and indicator monitoring systems that many organizations have adopted to implement the goal model, encourage competition among individuals and groups within an organization rather than cooperation. The CAS perspective predicts that the phenomena of competition would be a common emergent phenomena under the goal model and that it is unlikely to be good for the performance of the organization as a whole.

Another instance relevant to the CAS perspective was Episode 010 of this podcast series. There we explored ‘efficiencyism’, which is a belief in the tenets of efficiency without questioning its assumptions and consequences in specific circumstances. As was explained at that time, ‘efficiencyism’ often holds organizations back from realizing their true potential for three reasons: 1) systems theory tells us that an efficiency improvement in one part of an organization does not necessarily provide an improvement in the performance of the organization as a whole; 2) elevating efficiency to a sacred value (to be pursued at all costs) often leads to counterproductive actions at the first sign of financial trouble, such as layoffs, downsizing, and general efforts to do “more with less”; and 3) ‘efficiencyism’ seldom works, because organizations are complex human systems that can react in unpredictable ways when disturbed. Episode 010 found that organizational dysfunction appeared to be a common emergent phenomena under ‘efficiencyism’, as illustrated by the many examples provided in that episode.

What we have done in this episode is look at organizations as complex adaptive systems. The CAS perspective provides interesting tools to look under the hood of organizations and explain what is really going on. I hope you have enjoyed this somewhat different view of the world. The CAS perspective deals with what has been called “the interesting in between”, far from equilibrium, but just short of chaos. Here, what starts as a trickle can become a flood.

Charles G. Chandler, Ph.D.
cchandler@AssumptionAnalysis.com

 

 

016 Meet the robotic overlords that are already here

robot-947924_1920 One of the recurring themes I see expressed from time to time in the media is humanity’s fascination, mixed with fear, that a humanoid robot equipped with artificial intelligence could be created, and that it’s kind would one day take over the world, perhaps subjugating humans in the process. This scenario is termed the “AI takeover”. Many people have worried that as artificial intelligence progresses over time, this kind of horror is inevitable. Notable individuals such as Stephen Hawking and Elon Musk have called for research into measures that would keep AI under human control and thus make such an eventuality less likely.

Of course, intelligence in robots and in computers takes many forms, but the one that people most worry about is AGI, or artificial general intelligence, where computers act with the skill of humans. Some of the tests that have been used to distinguish whether AGI capabilities are present in a given robot include some common tasks that humans can do but robots have had difficulty in carrying out so far. One of them is the coffee test, in which a robot is sent into a typical American household and told to find the coffee machine, the coffee, the water, and combine the ingredients, push the right button to make the coffee. Another one is the college freshman test where the robot enrolls in college, attends classes, and takes exams just like a human would. There are some other tests, of course, but I won’t belabor the point here.

The factors that make a future AGI takeover possible come down to basic biology and physics, coupled with consistent advances in computer technology. Our human brains are three pounds of tissue with a gelatin-like consistency, often termed ‘wetware’ rather than hardware. The brain houses our mind, and the mind can be thought of as the software of the brain. Though a human brain is a processing device, and the most complex object in the known universe, signals within the brain only move at about 100 miles per second, as opposed to a computer where signals move at the speed of light, which is 186,000 miles per second. In addition, biological neurons operate at a frequency of about 200 Hz, while the processing frequency of a modern computer has exceeded 2 Billion Hz. This means that computers have a significant, and growing edge in raw processing power over the human brain.

But aside from raw processing power, the fear of robots comes down to a fear of their intentions, and particularly their goals and values. Our species seems obsessed with goals and values, some of which could be categorized as incredibly idiotic, harmful, and destructive. Goals can assume various forms, and can even become obsessions within the human mind, including the pursuit of money, fame, power, or any of a hundred other choices. There are many types of goals, that when pursued to the extreme, create bad results for humanity in general, although the individuals involved may feel fulfilled for a time. There is essentially no connection between how intelligent a being is and how appropriate its goals and values are. Any level of intelligence can be combined with any set of goals, including goals that are basically stupid and values that are amoral.

If AGI does emerge one day, the fear is that robot processes could run off the rails if programmed with the wrong goals and values, coupled with sufficient power to achieve them. For instance, in a somewhat silly example, a robot that was a paperclip maximizer could theoretically destroy the world by continuing to produce paperclips at a rapid rate utilizing whatever inputs were handy. As we assign goals and values to robots and design processes for them to carry out, it would seem to be important to understand the implications in order to keep them from becoming our robotic overlords. Almost any goal, when taken to an extreme by a robotic machine that seeks goal maximization, may not turn out well.

That brings us to a discussion of the robotic overlords that are already here. Perhaps you have not recognized them as such. I am speaking of the large computer / human integrations that are among us. This is where humans, generally operating in the belly of a large public corporation, pursue specific goals and utilize computer-driven processes to gain scale and speed advantages. The goals can take different forms. Whether it is the maximization of profit, shareholder value, or production, the single-minded pursuit of growth through goal maximization can be destructive in the long run. Yet, there are many self-reinforcing mechanisms in the stock market and elsewhere (including quarterly reporting for public companies) that perpetuate this unhealthy reality.

Companies that operate in robotic fashion often care little for their employees. One such employee described his experience in surviving a series of eight corporate layoffs in a hostile environment. When he became toast on the ninth, he said it was like being a prairie dog in a prairie dog town located next door to an angry farmer who occasionally leaned across the fence with a shotgun to take out a few of your fellow prairie dogs. You never knew when the next attack was coming. It wasn’t until he had actually been laid off that he realized the amount of stress he had been living under.

Yes, robotic overlords are currently in place, and their goals are not benevolent to most of us. The Economist has noted that the goal of shareholder value maximization (as reflected in the stock price) provides a license for bad conduct, including skimping on investment, exorbitant pay for the C-suite, high leverage in the financial makeup of the company, silly takeovers, accounting shenanigans, and large share buybacks (which have been running around $600 billion in America in recent times). A corollary to shareholder value maximization is agency theory that holds that the C-suite should be well compensated with stock options in order to align their interests with those of the owners. Ironically, the short-term pursuit of shareholder value results in the destruction of shareholder value in the long run. It is not surprising that Steve Denning, writing in Forbes, has called this the second robber baron era, complete with the rise of monopoly power and little enforcement of antitrust regulations. Investment by public companies in their businesses is running near historic lows, only about 4%, while profits are at record highs of 12% or so. We don’t see the same problem in privately owned companies because different incentives are in place. There, investment is twice as high as in public companies. Main Street beats Wall Street in this area.

Peter Drucker noted in 1954 that the only valid purpose of an enterprise is to create a customer. Public companies listed on the stock market seem to have forgotten this truth. The current refrain from executives about “the stock market made us do it” is becoming a cliche somewhat akin to “the dog ate my homework”. The reasons that we have robotic overlords in place is that shareholder value thinking coupled with agency theory has things back to front. Steve Denning believes that the root of the second robber baron era is essentially shareholder value maximization, which Jack Welch, the former CEO of GE has called “the dumbest idea in the world”. The problem is with the single-minded pursuit of a goal in robotic fashion, especially one focused on shareholder value maximization.

There is some history to what we see going on in large public corporations. Much of the logic for shareholder maximization originated at the Chicago School of Economics under the direction of Milton Frieman and his colleagues. His famous opinion piece in the NY Times in September 1970 proclaimed (in response to the growing movement for Corporate Social Responsibility or CSR) that the sole social purpose of a firm was to make as much money as possible for its owners. The CEO was viewed as being ultimately responsible to the shareholders (equated with owners). Many business schools and economics department have been teaching shareholder value maximization ever since. But it is really not true. Shareholders do not own the company, they only have a claim to some of the residual assets of the company. No one owns a public company; it owns itself. As the British say, it’s like the river Thames, nobody owns it.

What we have tried to do today is to talk about the goal model, and how the robotic pursuit of certain goals can lead organizations astray; in fact, they give undeserved legitimacy to the robotic overlords that are currently in place. It is likely to be difficult to remove them. Michael Porter, in a 2011 article, tried to address this by offering a new “shared value” creation model, where a company operating in society is admonished to think broader, expand its reach, and create additional value with society in mind. Others have criticized this idea as a one-trick pony because the model relies only on economic value creation, but is missing social value and other values that could be brought into play.

As a listener to this podcast, another solution may readily come to mind — the Outcome-focused Model (OFM) for organizational effectiveness. Within the OFM, the goal of every organization is the same, that is, to be effective within its environment. The effective organization understands its environment, serves it to the best of its ability, and is rewarded in return. It is not about maximizing shareholder value, but about providing customer value, and creating products and services that elicit favorable customer responses. In the OFM, the demand side always remains in control of whether any given transaction will be completed. The supply side cannot run full steam ahead unless the demand side is in agreement. In this model, the achievement of effectiveness is a win-win for both the organization and its environment, so robotic overlords could not run amuck if programmed to obey this production function. The future of the world may come down to simply programming the right goals and values into our robotic future. Of course, there is still the question of what we do about the robotic overlords that are currently in place.

Charles G. Chandler, Ph.D.
cchandler@AssumptionAnalysis.com

015 “Think different” about effectiveness

IMG_0535[1]In 1997, Apple began an ad campaign called “think different”, which featured billboards with large pictures of notably famous people like Albert Einstein, Thomas Edison, Amelia Earhart and others alongside the Apple logo and an ad slogan that said, “think different”. In essence, Apple wanted to associate itself with greatness. The implication was that by purchasing an Apple product the customer was beginning to think different and was entering a path that could lead to greatness. The ad campaign proved to be an enormous success for Apple.

When it comes to organizational effectiveness, few organizations think different. The most common way to think about effectiveness is by using the goal model. There are few organizations that do not use it in some way. In this model, an organization is effective to the extent that it achieves its goals and objectives. Management by objectives, advocated by Peter Drucker, subscribes to this idea. Today’s computer-based scorecards, dashboards, and indicator monitoring systems that many organizations have adopted take this idea to the next level. It’s the goal model on steroids, but the goal model does not reliably improve effectiveness.

Why? Even advocates of the goal model admit that not all goals are created equal, and it is hard to argue that all goals are meaningful with respect to effectiveness. Many times, goal setters are simply admonished to set clear goals, with the emphasis on clarity. Another framework for goal setting calls for SMART goals (Specific, Measurable, Attainable, Relevant, and Timely). But it is not sufficient to set goals based on so-called S.M.A.R.T. criteria, as these criteria do not ensure effectiveness.

Let’s talk about why we set organizational goals in the first place. In the common view, goals offer people within an organization clarity of purpose. The idea is that with a “big hairy, audacious goal”, or some variation thereof, even if it’s not fully achieved, it will still drive the organization toward significant achievements. It’s sort of like playing a video game, where you try to beat your old score, or the score of a competing team, by trying to do better this time. It’s about tapping into our seemingly inbuilt drive for competitiveness. But tapping into the competitiveness of its employees may not improve the effectiveness of the organization. Using the goal model, an organization can easily fall prey to the tyranny of ‘efficiencyism’ (which I discussed in Episode 010) by focusing on the wrong goals.

There is, I believe, a more meaningful way to think about effectiveness and goal setting. The Outcome-focused Model, or OFM, described in episode 009 of this podcast series utilizes ideas from Results-Based Management. Under the OFM, goals are first apportioned into four categories, based on their level within a results hierarchy. The four levels are Inputs, Outputs, Outcomes, and Impacts. The first two (Inputs and Outputs) are on the supply side and are within the control of the organization itself. Organizations convert inputs into activities that produce outputs. Outputs become offerings to the external environment (in the form of product and services, or projects and programs). The remaining two (Outcomes and Impacts) are on the demand side and are outside of the control of the organization. Why does this matter? It is because, under the OFM, an organization is effective to the extent that it achieves its expected external outcomes. The OFM does not motivate an organization’s employees to be competitive, but rather tries to motivate demand-side actors to adopt and use its offerings. This is a more useful and meaningful way to think about effectiveness.

When we refer to an outcome in the OFM, we do not mean a final result such as is assumed in the goal model. Rather, an outcome within the OFM is an effect caused by an antecedent event. While outputs are produced by the organization in the form of its offerings, it is demand-side actors that must decide whether or not an organization’s offerings are attractive enough to compel them to exhibit behaviors of uptake, adoption or use. When such behaviors do occur, they can be observed in the real world, and supply the “objective referent” that has been missing in models of organizational effectiveness thus far.

The OFM explains why the goal model (which will accept virtually any goal) often does not improve organizational performance. Under the OFM, it is only outcome-level goals that are meaningful for effectiveness. In other words, its standards for selecting meaningful goals are quite restrictive. If we assume that goals selected for use in the goal model are distributed equally among the four categories mentioned earlier (Inputs, Outputs, Outcomes, and Impacts), the wrong kind of goals would be selected 75% of the time. The goal model would work just like the OFM if it restricted itself to outcome-level goals (defining outcomes as relevant demand-side behaviors).

Will you “think different” in order to make your organization effective? You don’t have to buy Apple products to create a great organization, but adoption of the outcome-focused model and its restrictive view of goal setting would certainly help.

The OFM still provides an organization with a sense of purpose. In fact, it does a better job than the goal model. Under the OFM, the goal of every organization is the same, that is to be effective within its environment. Despite this fact, various organizations have chosen different local environments to focus on, and have different product and service offerings, so it doesn’t make sense to compare effectiveness between organizations. It does make sense, however, to compare an organization’s present effectiveness to its past effectiveness.

Effectiveness operates through causal chains that are formulated for each product and service offering (or project and program offering). The overall effectiveness of the organization is derived by considering the effectiveness of the entire portfolio of causal chains. What is the effectiveness scale? The scale for effectiveness goes from essentially zero up to infinity. Like excellence, there is no upper limit to effectiveness. Because of this, it is more important to verify that effectiveness is occurring within relevant causal chains than it is to actually measure it. All measurements of effectiveness are relative with respect to historic performance.

The OFM offers a self-correcting model for management action, because if a demand-side behavior is being monitored with respect to each product and service offering, decreases in effectiveness will become quickly evident. Immediate actions can be taken to find out why, and to address the problem. That’s not so easy with the goal model.

You may recall that the US Army, back in 2001, changed its ad campaign and slogan, from the old slogan (“Be all you can be”) to the new slogan “Army of One”. In the new ad campaign, each soldier was to think of himself or herself as an army of one. We could envisage a similar approach under the OFM. Since the goal of every organization is to be effective within its environment, every employee is empowered to wake up each day and reinterpret what it means to “serve your environment” anew. It is clear, however, that “serve your environment and be rewarded in return” is not about extracting as much profit as possible from every customer. It’s about serving every customer and being sure that they receive the value that they are expecting. Potentially, this could create a very flat organization. Why do you need a highly-incentivized C-suite and a well-paid Board? The OFM gives clarity of purpose to every level of the organization. In fact, you could take much of the compensation that is being paid to the C-suite and the Board, and redistribute it to front-line staff.

In this episode, I have tried to contrast the goal model with the outcome-focused model (or OFM) and have described what it would be like to “think different” with respect to organizational effectiveness. In the goal model, the goals are set by management, and may or may not have anything to do with organizational effectiveness. In the outcome-focused model (OFM), on the other hand, goals are limited to a focus on expected external outcomes, which provides a clear view of what effectiveness is all about. In essence, it’s about getting expected demand-side responses through the causal chain for each product or service. The model also has predictive value, because unlike the goal model, the OFM is very clear about how effectiveness is increased and how it is decreased. Increased effectiveness under the OFM is win-win for both the organization and its environment. Of course, even drug cartels can be effective, so it is important that positive values such as honesty, transparency, and fair play be upheld within an organization in order to be sure that it is creating a future based on a strong foundation. It is safe to say that Enron (which went bankrupt in 2001 amidst scandal) did not follow this model.

I hope today’s episode provided a clear contrast between the goal model and the outcome-focused model. If you are already using the OFM, tell us about it by commenting on this episode (015) at our website (www.AgeofOE.com). I may showcase your efforts on an upcoming episode.

Charles G. Chandler, Ph.D.
cchandler@AssumptionAnalysis.com

014 Improving effectiveness in international development

In this episode I discuss a new way to think about effectiveness in development projects & programs that could allow international development to deliver on its original promises of development effectiveness.  I discuss Albert Hirschman’s ‘hiding hand’ that veils difficulties as well as the creativity available to solve problems as planner engage in the design process.  The goal model is still prominent in development organizations, although it presents difficulties in actually verifying project effectiveness.  Development agencies need to move toward the outcome-focused model (OFM, discussed in episode 009) to become more effective, due to its ability to verify success of the causal chain.  In addition, this offers a new way to improve the effectiveness of development organizations themselves.

Charles G. Chandler, Ph.D.
cchandler@AssumptionAnalysis.com

Reference:
Hirschman, A. O. 1967. Development Projects Observed. The Brookings Institution. Washington, DC.