How do we plan for the future instead of planning for the past?

Economists, financial experts, politicians, bureaucrats, commentators, bloggers and others around the world are grappling with the question of how to respond to the current recession, acknowledged by many to be the biggest recession since the Great Depression. One approach common to many, if not most, of their analyses is to look at the past - the Great Depression itself, the Japanese lost decade, the Swedish bank crisis, to name a few of the most prominent examples - and draw inferences about what we should or should not do today to deal with the current recession. This approach of learning from the past is not restricted to economic analysis or economic policy, rather it is used in almost all instances when we have to plan for the future. Banks use it to set current interest rates on loans, insurance companies use it to set premiums, businesses use it to develop strategy, governments use it to set policy, and at an individual or family level, we use it to make personal decisions. While learning from the past is important in our decision-making, given that all knowledge is based on past experience (and our understanding and interpretation thereof), this approach of decision-making from extrapolation poses the pitfall of planning for the past rather than for the future. It is this issue that I address in this essay (and will address in ones to follow) - How do we plan for the future instead of planning for the past? In this essay, I set out the framework I will use to address this question, and in subsequent essays, I will try to answer this question by applying this framework to specific examples.

Planning is about decision-making - setting a course of action, allocating resources, prioritization, etc. The quality or effectiveness of decision-making in any area depends on the state of knowledge relevant to the area, and how the decision-maker responds to it. First, I will discuss the different possible states of knowledge, and then I will talk about the different possible responses to these states of knowledge that impact the decisions we make and how we make them.

As shown in Exhibit 1, there are four possible states of knowledge from the point of view of a decision-maker, which could be an individual, a group or an organization. We shall call this decision-maker the agent for the purposes of this essay. The vertical axis in the exhibit represents the state of knowledge in the world in general, and it divides this into two possibilities, either something is known, or it is not. The known here refers to any knowledge that exists in people's heads, computers, books or any other source that can contain knowledge that can be recovered by the agent, given sufficient interest, resources and effort. What is unknown is something that has not been discovered yet or something that was known but has been lost and cannot be recovered (it can of course, be discovered anew).

The horizontal axis represents the state of awareness of the agent about the knowledge of the thing or area in question. Either the agent knows the state of existence of the knowledge in question or it does not. Given this, there are four possible states of knowledge from the point of view of the agent, the known knowns, the known unknowns, the unknown knowns, and the unknown unknowns made famous by former US Defense Secretary Donald Rumsfeld.

Exhibit 1: Four states of knowledge

The bottom left hand quadrant represents the known known, and an example of this would be the knowledge that the US Treasury department (at least I would hope so) has about the Swedish banking crisis, the policy response and the shape of the post-response recovery from the banking crisis. The top left hand quadrant represents the known unknown, and to take our example further, this would represent the answer to the question - would the replication of the Swedish policy response work in the current crisis in the United States? The US Treasury Department does not definitively know the answer to this question, but they do know that they don't know the answer to this question (again I would hope so).

The bottom right hand quadrant represents the unknown known - knowledge which is known by someone or is captured somewhere, but the decision-maker it not aware of this. The example of this would be the knowledge of other bank crises in history or in other countries that exist in books, papers and in the heads of people in other countries, but of which the US treasury department is unaware. I would imagine that the size of knowledge in this box in this specific example has been shrinking with all the research and analysis already done and being done in the government and outside. This then points to the appropriate decision-making response to the knowledge in this quadrant - search and research that pushes the knowledge from this quadrant to the bottom left one. I will come back to this in more detail in a future essay on the details of how we can respond appropriately to the situations presented by the four different states of knowledge.

Finally, the top right quadrant consists of the unknown, unknown. The example of this would be the US Treasury department's or the Fed's knowledge in 2006 about how the economy would look like in 2009 (not variables like GDP growth, inflation, etc., which would be known unknowns, but questions like whether there would be a major crisis, and what shape this crisis would take - although keeping in mind that if they could frame this question in 2006, this would have become a known unknown).

Given these four states of knowledge, there are four possible decision-making responses. I describe these below in increasing order of complexity and sophistication.

The first most basic response is for the agent to make decisions based on what the agent already knows or the agent's direct experience. I guess that a lot of decision-making in the world is of this variety because of reasons of time, resources, laziness, discomfort with ambiguity, fundamentalist beliefs, etc. Examples of this type of decision-making include the following:

• Getting married to someone from your caste and religion because this is what has always been done in the past
• The annoying persistence of British companies and organizations to contact you by post rather than the speedier email
• New company executives making decisions based on their direct past experience in other companies (this may not be all bad, and if we think of the company rather than the executive as the agent, this then becomes an example of the second type of response)
• Deciding to build another 8 lane highway because this is what you did before to solve traffic problems
• Many religious, social and cultural practices that are based on doing things the way they have always been done
• Treating theory or ideology as gospel and always following it, no matter what - a good example is the Republican solution of tax cuts to all problems (although this may require a category of its own of I don't care what I know, but I will do it this way anyways)

The second response, like the first is based on learning from past experience. But it moves a step beyond and tries to learn not just from the agent's direct experience but also from the experiences of others. This essentially tries to increase the known known quadrant by reducing the unknown knowns. The tools used to do this are case studies, precedent studies, benchmarking, surveys, focus groups, etc. This form of decision-making is used by most of the smarter people and organizations, and it can often give a big leap in benefit over the previous response. Examples of this include the East Asians copying western technologies and then beating the west by using cheaper labour to produce the same tradeable goods and services. Or companies copying successful strategies from other companies, such as the copying of the Japanese just in time inventory strategy by US companies, the entry by US and European car companies into the hybrid car market space after the Japanese did so, and so on. There are big benefits to be had here, especially if the agent is the first or second follower. And it is an easier path to progress as you can build better products, services, institutions, practices, etc. based on what someone else has already done before. Or what someone else knows, as in the example given above of hiring executives from other companies to take advantage of their knowledge gained in other companies.

The third decision-making response deals with the known unknowns and it does it in two ways. First, it tries to move the knowledge from this box to the one below through focused research and analysis. Second, it tries to assess probabilities and consequences of different outcomes (scenario analysis, simulation, etc.) and prepares contingency plans for these. Let us understand this with the example of a marketing executive trying to predict the size of market for cars in the next two years. She can do this using the first decision-making method and extrapolate the past few years trend forward. Or she can incorporate the second method and look at what happened in other markets - geographies, products, times, etc. and prepare a more sophisticated analysis based on more variables (this may not necessarily be better, but more on this in subsequent essays). Or she can identify the variables that would affect the demand for cars, assign probability distributions around these and simulate the probabilities of potential market demand sizes. Based on these probabilities, she can work with other company executives to develop a business strategy with the necessary contingencies built in. This last would be an example of the third decision-making response. (Again, whether this is the right response is not automatically evident, and I will discuss this point in subsequent essays).

The last response addresses the unknown unknown quadrant. This is the most difficult response as the agent does not know what to plan for. Therefore, rather than planning for any specific outcome, the agent must focus on building the ability to innovate, to flexibly respond to uncertain scenarios, and a resilience that allows the agent to take hits and still survive and come back. Two examples of long term success based on innovation, flexibility and resilience are GE and IBM.

I conclude this essay here. In the next one, I will show how we can use this framework to better plan for the future by taking the specific example of how the United States should approach building competitiveness in the long run. This is especially pertinent today, as the United States is fundamentally rethinking the role of the government, it needs to adopt an approach that plans for the future instead of planning for the past.

© Raja Shankar: This essay may be copied or referred to freely, as long as it is sourced to the author