Solutions For Building More Effective Market Systems

This blog post was originally published on the Website of CGAP, an independent policy and research center dedicated to advancing financial access for the world’s poor. The Blog post was part of the Systemic M&E initiative I worked on for the SEEP Network.

Screen Shot 2013-01-14 at 11.07.55There is a controversy brewing among systems and complexity thinkers. Is it useful to define a future goal towards which our initiatives strive? Or is it wiser instead to focus our attention on what we know we can change and trust that this will eventually lead us to a future that is better than any we could have anticipated? While the first feels intuitively right to many development practitioners, proponents of the latter argue that the absence of defined goals and targets may lead to future possibilities that are more sustainable and resilient (and that could not be fully anticipated). So the question is: can we know in advance what the best (or a good) outcome will be? Continue reading

Do we need a goal or is virtue sufficient purpose?

David Snowden has written on his blog about purpose and virtue (more specifically here, here, here and here). I find it a fascinating line of thought, but still cannot  wrap my head around it completely. The basic idea is that in contrast to systems thinking, where an idealized future is identified and interventions aim to close the gap to this future, complexity thinking (or at least the one advocated by Snowden) focuses on managing in the present and with that enabling possible futures to emerge or evolve that could not have been anticipated. Now the latter, the management without a specific goal, of course, asks for a purpose or motivation. Why should we bother, if we don’t have a goal? Continue reading

Systemic monitoring

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I have been very lucky to work for an initiative termed ‘Systemic M&E’ (although we talk more about the ‘M’ than the ‘E’), focusing on ways to move away from a linear and static understanding of the systems we work in and develop tools and approaches that let us monitor changes in the complexity of the real world. Continue reading

Knowledge Management in complex adaptive systems

How does systems thinking and complexity theory help us in designing a global knowledge management facility?

A global knowledge management facility has the goal to manage knowledge within a specific community of practice in order to improve the application of that knowledge in general or of a specific approach in particular. From a traditional point of view, important activities of such a facility would be to collect and codify knowledge, analyze good practices and there might even be a wish for standardization of the application of this particular knowledge or approach. In this sense, the facility can be seen as a custodian of the ‘right’ knowledge and oversee and certify the quality of its application. It would guard the rigor or ‘pureness’ of application of the specific approach with a view to preserve or improve its effectiveness and efficiency.

With this picture in mind I read a chapter in a knowledge management book that describes implications of systems thinking and complexity theory on knowledge management from an organizational perspectives (Bodhanya 2008). I would like to apply the conclusions of the article to the design of such a global knowledge management facility.

In his article, Bodhanya describes differences in characterizing knowledge that stem from a number of debates within the scientific community revolving around the interplay between ontology and epistemology or, to put it in simpler terms, between perspectives of knowledge as a thing and knowledge as a dynamic process. According to Bodhanya, the current debates in knowledge management, however, reduce this pluralism of the discussion around knowledge because the dominant discourse is based on what he calls a cognitive-possession perspective. He terms this ‘first order knowledge management’.

First order knowledge management is built on the following assumptions (Bodhanya 2008:7):

  • Knowledge is reified.
  • Knowledge is useful when it is objective and certain.
  • Distinction between tacit and explicit knowledge.
  • Knowledge may be managed through knowledge management.
  • Knowledge identification is a search process.
  • Knowledge construction is a process of configuration.
  • Knowledge management comprises knowledge processes such as identification, generation, codification, and transfer.
  • Business strategy may be formulated and implemented. This is a fundamental assumption across all strategic choice approaches to strategy and, at a minimum, will include the design, planning, positioning, and cultural schools of strategy.
  • Knowledge management strategy may be formulated and implemented.
  • Knowledge management strategy must be aligned to the business strategy.

The concept of first order knowledge management seems in line with the goals and traditional activities of a global knowledge management facility as described above: “Ultimately, first order KM relies on knowledge processes such as knowledge identification, generation (or more accurately configuration), codification, capture, and transfer in order to develop human and social capital, as these are considered as important in facilitating productive activity” (Bodhanya 2008:8).

In his paper, Bodhanya argues against the view of knowledge as a thing and criticizes current knowledge management of gross oversimplifications by relying on a view on knowledge as something that can be possessed. He suggests that knowledge is a much more dynamic phenomenon and suggests instead to shift the focus from knowledge to the act of knowing itself. “Knowledge is only generated in the act of knowing; everything else is information. In other words there is the perpetual potentiality for knowledge generation, but this is only transformed into actuality when information comes into contact with the human intellect. This happens in the act of knowing in the instant when there is sensemaking and interpretation. (…) [H]uman actors are constantly engaged in thought, and hence are engaged in sensemaking and interpretation at every instant, so knowledge is being regenerated afresh at every instant. This phenomenon of constant thought and action means that there is perpetual regenerating of knowledge” (Bodhanya 2008:10). Based on these insights, Bodhanya constructs a ‘second order knowledge management’ that takes into consideration the dynamic interplay between knowledge and the knower. In second order knowledge management, he points out, more attention needs to be paid to the social interactions between actors.

Bodhanya then details out how this view on knowledge and knowing is in line with systems thinking and complexity theory. An interesting debate he touches upon is the question who, from an organizational point of view, are the actors in a complex adaptive system of knowledge. The most obvious choice would be the individuals in an organization but another possibility is, for example, to see narrative themes as the actors. Bodhanya argues for a more nuanced view that includes the individuals as well as other forms of agents such as groups of individuals, departments, and human artifacts. He defines the systems of knowledge as ‘knowledge ecologies’: “A knowledge ecology is a dynamic system of heterogeneous agents that interact with each other according to their schemata. The schemata are inextricably linked to each agent’s propensity for interpretation and sensemaking on an on-going basis. Since interpretation and sensemaking are related to knowing in action, every act of interpretation and every act of sensemaking is in effect an actor creating knowledge. There are therefore multiple cognitive feedback loops being generated which in turn refresh the schemata according to which agents then act” (Bodhanya 2008:14). But he goes even further and looks for evolutionary tendencies in knowledge ecologies to an effect that knowledge structures become the primary agents that survive, vary, mutate, and are subject to retention and selection. There are, thus, various layers of interacting and interconnected complex adaptive systems with various types of actors at play, which makes the description – or prediction – of the system impossible.

Whereas first order knowledge management is based on a strategic choice view of business strategy, considerations of complexity and systems thinking show that the knowledge environment is far to complex for any one person to fully understand and, hence, to make strategic choices. This does not only change the view on knowledge management, but on business strategy itself; it shows the need for a more dynamic approach that is much more process oriented. “Alignment between business and knowledge management strategies may therefore not simply be designed and imposed, but may only be stimulated through managing organisational context and the interactions between actors within an outside the organisation. We may therefore also refer to business and knowledge management strategies as undergoing a process of co-evolution” (Bodhanya 2008:15).

What does this mean for knowledge management? First of all we have to realize that knowledge management does not have something to do with control over knowledge and its use. No single agent in a complex adaptive system can stand outside the system and direct it. “[M]anagerial orientations must shift from a preoccupation with the ordered, rational, analytical, and the fixed towards a tolerance of ambiguity, subjectivity, flux, and the transient nature of organisational life” (Bodhanya 2008:17). But this also means that there is no formula, recipe, or easy prescription on how to implement knowledge management. Rather, the conditions for the emergence of knowledge ecologies need to be developed. “The best that we can do is to facilitate rich interconnections between agents, increase agent diversity, and provide an enabling context for sensemaking and interpretation” (Bodhanya 2008:17). Bodhanya introduced an approach to second order knowledge management he calls strategic conversation, but he also points out that there is still a lot of research needed to fundamentally transform knowledge management into a systemic process co-evolving with other strategies within an organization.

One important piece of wisdom Bodhanya gives us for that journey: “As human actors and managers, we are in a sense deluded by the extent to which we think we are in control. It calls for increased humility on the part of all of us as human actors. In a systemic world, we control less than we think, because the effects of our actions are subject to many feedback loops and nonlinear responses that are outside our sphere of influence and control. (…) Our plans are merely artifacts, and to the extent that they contribute to co-evolution, they do have a valuable role. However, this may call into question our criteria for what the value of a plan is, and what constitutes a good or a bad plan” (Bodhanya 2008:19).

What does this all mean for a global knowledge management facility? Obviously, such a facility does not follow the same rules as an organization, which can be seen as complex adaptive system with a fairly obvious, if also penetrable, boundary. Knowledge sources are much more widespread and part of diverse organizations with their own agendas. One of the first insights, thus, must be that such a facility cannot exist on its own, observing, collecting knowledge, codifying it, and defining best practices, which it will then disseminate again into the system. Rather than a centralized secretarial-type entity, the facility should rather be a hub of a network of actors in the knowledge ecology with the aim to stimulate knowledge creation and exchange. As pointed out by Bodhanya, an essential step thereby is to “facilitate rich interconnections between agents, increase agent diversity, and provide an enabling context for sensemaking and interpretation” (Bodhanya 2008:17). So rather than to see the facility as a kind of library and custodian of the right kind of reified knowledge or the pure way of implementing an approach, it should much more be a place where discussions are stimulated and the knowledge is created while it is used. Thereby, diversity plays a big role. It is important to see that there is not one right way to implement an approach, but that knowledge is created from the diversity of its application.

This is just the beginning of a possible discussion and many things still need to be touched upon and many critical points in the assessment above need to be made visible and discussed. I hope, however, that this post provides some food for thought.

Reference: Shamim Bodhanya (2008): “Knowledge Management: From Management Fad to Systemic Change”. In: Abou-Zeid, El-Sayed: “Knowledge Management and Business Strategies: Theoretical Frameworks and Empirical Research.” Information Science Reference. Hershey, New York.

Owen Barder on Development and Complexity

 

Owen Barder, Senior Fellow and Director for Europe of the Center for Global Development last week posted a talk online, adapted from his Kapuściński Lecture of May 2012, in which he explores the implications of complexity theory for development policy (the talk is also available as audio-only version on the Development Drums podcast).

The talk tells a persuasive story of what has gone wrong in international development and in the various models of growth it used; that the adoption of the concepts of adaptation and co-evolution allow for much more accurate models; a brief description of complex adaptive systems and complexity theory; and what consequences these insights have for development policy. But these positive turns in development come for a price: we can no longer ignore that we – the developed nations – are also a part of the larger system and that our (policy) actions strongly influence the development potential of poor countries. It is no longer enough to ‘send money’ and experts and think that this will buy us out of our responsibilities towards those countries.

I want to quickly summarize what I think are the key points of Owen’s presentation, starting with what seems to me an obvious point:

Development is not an increase in output by an individual firm; it’s the emergence of a system of economic, financial, legal, social and political institutions, firms, products and technologies, which together provide the citizens with the capabilities to live happy, healthy and fulfilling lives.

Owen talks about various (economic) models and theories that have neglected this systemic perspective and, subsequently, failed to deliver successes in development. The focus of the economic models shifted over the years from providing capital and investment to technology.

Since this approach of ‘provision’ did not work out, the lack of favorable policies was blamed for hindering the market to achieve its theoretical potential. As a consequence, the Washington Consensus introduced which policies needed to be adopted by a country to be able to grow. As we know, this also did not work out, although the Washington Consensus did, according to Owen, have some positive impacts in developing countries.

After the Washington Consensus, development agencies focused on weak institutions and spent (and are still spending) huge amounts of money on institutional strengthening and capacity building initiatives. The results have been modest. Adding to the difficulties is the fact that it is still not clear which institutions are really important for development.

Most recently, a new book published by Daron Acemoglu and James A. Robinson (Why Nations Fail) promotes politics as culprit of failing development. According to them, the institutions are weak because it actually suits the elite that is in power to run them like this [what an insight …!!!]

All these models that were applied were actually based on traditional economic theory. After seeing all these approaches fail, Owen switches to a new way of describing economic development, based on adaptation and co-evolution in complex adaptive systems.

After making a compelling argument why complexity theory can actually better describe the real economy out there, Owen describes seven policy implications deducted from that insight.

  1. Resist engineering and avoid isomorphic mimicry. The first point mainly stems from the fact that solutions developed through evolution generally outperform design. The latter point mainly implicates that institutions that were mainly built after a blueprint following ‘best practices’ but do not connect to the local environment will have not much use.
  2. Resist fatalism. Development should not be seen as a pure Darwinian process. Smart interventions by us can accelerate and shape evolution.
  3. Promote innovation.
  4. Embrace creative destruction. Innovation without selection is no use. Feedback mechanisms to force performance in economic and social institutions are necessary.
  5. Shape development. The fitness function which the selective pressure enforces should represent the goals and values of a community.
  6. Embrace experimentation. Experimentation should become a part of a development process.
  7. Act global. We need to make a bigger effort to change processes that we can control, for example international trade, the selection of leadership in international organization, etc.

Owen is not telling any news in his presentation, but he succeeds to develop a compelling storyline on why complexity theory is relevant for development and why processes that are based on adaptation and co-evolution much better describe why some countries develop while other seem stuck in the poverty trap.

In my view this is an immensely important contribution to the discussion on how we can reform the international aid system to live up to our responsibility of enabling all people on this planet to live happy and fulfilled lives.

Is this the dilemma of complexity in development?

I have not been around for a while, so my blog has remained dormant. But I have not abandoned it! I will try to keep posting more often again.

This post is about a paragraph of a book that I have started reading recently. The book is called ‘Harnessing Complexity’ and the authors are Robert Axelrod and Michael D. Cohen. The paragraph says:

Analyzing complex systems within [our] framework does not assure the ability to produce specific outcomes but can foster an increase in the value of populations over time.

This statement made me thinking if this is actually the dilemma we face when we want to apply principles of complexity sciences to development – or other real-world cases, for that matter. In development, we need to specify outcomes we want to achieve within a given time frame and we need to build a system that enables us to measure and report about the achievement of these outcomes. Now if the use of frameworks informed by complexity sciences does not target the achievement of specific outcomes but more generally the increase in the value of populations over time (in the case of development that would be what we call ‘well-being’), than it will be hard to sell these projects to donors. We cannot go there and tell them ‘Our goal is to make the world a better place but we don’t have any specific outcomes nor a clear time frame to achieve that goal.’

I do not really have an answer to that dilemma right now. Any thoughts out there?

Help us support the MaFI-festo: changing the rules of international development

Dear readers, a while ago I wrote a post on the MaFI-festo, a discussion paper that makes some suggestions on how to make development more effective (Boosting development effectiveness: what would need to change?). The basic assumption of the paper is that if we facilitate the market systems to change from within rather than through a number of direct and distorting interventions, we have better and more sustainable results.

The challenge to unleash the power of markets to end poverty goes on. The MaFI-festo now entered the MIX, the annual Harvard Business Review/McKinsey M-Prize for Management Innovation.

We need your help to push the MaFI-festo up the ranks of this competition!

What you can do

To see the application go to http://www.managementexchange.com/node/62551

Find out more about the M-Prize go to: http://www.managementexchange.com/m-prize/long-term-capitalism-challenge

[Update] Unfortunately, the MaFI-festo contribution was not selected as a finalist for this years MIX. Nevertheless, we keep on promoting this initiative with a lot of enthusiasm.

‘Simplify and repeat’? Rather ‘simplify and evolve’

In a recent issue of the Economist, the Schumpeter column was titled “Simplify and repeat. The best way to deal with growing complexity may be to keep things simple.” The column reported on a new book by Chris Zook and James Allen, two consultants with Bain & Company, called “Repeatability”. The basic thesis of the book is that

most successful companies share three virtues. They have a highly distinctive core business. They make great efforts to keep their business model as simple as possible. And they apply it relentlessly to new opportunities.

The authors use examples such as Lego that lost it’s focus on their bricks and started expanding into so-called ‘adjacencies’ like theme parks, television programs, clothes, watches and learning labs. Only after hitting a wall (and getting a new boss), Lego returned to its core business and did better. Other cited examples are IKEA, McDonalds or Berkshire Hathaway. Or Apple, with its successful succession of iProducts.

The authors call this the ‘simplify and repeat’ formula with which the companies avoid complexity. The Schumpeter columnist notes, however, that

[c]omplexity is no easier to avoid than cholesterol. Companies need to keep hammering away at the simplicity mantra.

Well, I would say you cannot avoid complexity if you are acting in the global economy. It’s as simple as that, really. I am also a big fan of simplicity, I think that’s one reason I love my Apple products that much. Reduce to the max. Form follows function. And so on. Nevertheless, I think it is a false way to ‘avoid complexity’ by ‘simplifying’ ones activities.

It is probably easier to manage a company that has one core business or one business strategy than it is to manage a company like such as Samsung or Mitsubishi with their uncountable divisions (I am always surprised when I find out what things they are producing). This is, however, not the big secret why companies like Apple or Lego are so successful. It’s because they know how to evolve in an ever-changing dynamic global economy.

This is one of the fundamental theses in Eric Beinhocker’s book ‘The Origin of Wealth’, which I found a fascinating read. He writes in connection with the complexity and unpredictability of the economy and the subsequent search for the best strategy for companies:

We may not be able to predict or direct economic evolution, but we can design our institutions and societies to be better or worse evolvers.

The concept of repeatability is based on the assumption that there exists such a thing as a ‘sustainable competitive advantage’. Beinhocker is very clear in his book that such a thing does not exist and he uses many examples of successful and less successful companies to illustrate that.

Apple is a good example. If Apple had just stuck to its core business – simplified and repeated – it would still build only personal computers, improved versions of the Apple II (or most probably it would build nothing at all any more). But Apple evolved together with its clients and into new fields of business. It developed new products like the mentioned iProducts and was hugely successful with it. Indeed, Apple now makes more money with other products than the traditional personal computer. At the same time, Apple remains true to its fundamental values as the mentioned ‘form follows function’ principle and the search for the most elegant, most simple solution for a given problem.

‘Simplify and repeat’ is not the silver bullet in business strategies. Successful companies evolve and adapt. Simplicity does not hurt, though. Therefore I would rather say ‘simplify and evolve’.

Some observations on wisdom and intuition

Today I came across two texts, one was on wisdom and another one on intuition. I remembered a third text on intuition that I read some time ago. The observation of these three texts seem very interesting form a systems thinking perspective.

The first text is from The Economist magazine from April 7th. In the Science and Technology section one article writes on ‘Age and wisdom’ and asks the question ‘Older and Wiser?’ (the article is available online here). According to the study the article writes about, ‘Americans get wiser with age. Japanese are wise from the start.’ Not the differences between Americans and Japanese were what interested me, but the indicators the scientists choose to measure wisdom:

The assessors scored participants’ responses on a scale of one to three. This attempted to capture the degree to which they discussed what psychologists consider five crucial aspects of wise reasoning: willingness to seek opportunities to resolve conflict; recognition of the limits of personal knowledge; awareness that more than one perspective on a problem can exist; and appreciation of the fact that things may get worse before they get better.

For me it was interesting to read those criteria because they resonate pretty well with what we think is a smart way to work in systems. So, are systems thinker wise people?

The second text I want to quote here is from Donella Meadows’ book ‘Thinking in Systems’, which I finally opened today to start reading it. Donella wrote in her book:

Modern systems theory, bound up with computers and equations, hides the fact that it traffics in truths known at some level by everyone. It is often possible, therefore, to make a direct translation from systems jargon to traditional wisdom.

On the next page, she continues:

Ever since the Industrial Revolution, Western society has benefited from science, logic, and reductionism over intuition and holism. Psychologically and politically we would much rather assume that the cause of a problem is ‘out there’, rather than ‘in here.’ It’s almost irresistible to blame something or someone else, to shift responsibility away from ourselves, and to look for the control knob, the product, the pill, the technical fix that will make a problem go away.

Several problems, she continues, such as poverty, hunger, or environmental degradation have not gone away in spite of the analytical ability and technical brilliance we have developed.

This is because they are intrinsically systems problems – undesirable behaviors characteristic of the system structures that produce them. They will yield only as we reclaim our intuition, stop casting blame, see the system as the source of its own problems, and find the courage and wisdom to restructure it.

Intuition again. And wisdom.

Now the third text that came into my mind when reading the two texts above is a reflection by Steve Jobs about his journey to India in 1974/75, written down by Walter Isaacson in Steve Jobs’ biography:

Coming back to America was, for me, much more of a cultural shock than going to India. The people in the Indian countryside don’t use their intellect like we do, they use their intuition instead, and their intuition is far more developed than in the rest of the world. Intuition is a very powerful thing, more powerful than intellect, in my opinion. That’s had a big impact on my work.

Western rational thought is not an innate human characteristic; it is learned and is the great achievement of Western civilization. In the villages of India, they never learned it. They learned something else, which is in some ways just as valuable but in other ways is not. That’s the power of intuition and experiential wisdom.

I cannot really put any conclusions here. For me, it is interesting to think about such things as wisdom and intuition and how it helps us to shape systems. But I guess it is also difficult to put it down in writing. It should be intuitive, after all.