STRATEGY
THREE FORMS OF KNOWLEDGE Knowledge is more than information. It is the actionable understanding of a situation. Three kinds of knowledge enable action: Declarative knowledge, who or what something is. For example, we may or may not know the market shares in a therapy area or the organisational structure of a healthcare system Causal knowledge, what gives rise to a situation. For example, we may or may not know what causes the adoption of a new product to vary between accounts Procedural knowledge, how something happens. For example, we may or may not know how market access is achieved in a given situation. than other companies? My research has studied this for many years and, in the following paragraphs, I distil it down to a few, actionable lessons. First, admit ignorance
The journey to knowledge begins with agreeing what the firm does not know but needs to. That knowledge comes in three forms (see box 1) and learning begins with defining what kind of knowledge needs to be created. Is it declarative (e.g., What are the primary issues facing a clinical speciality?) or causal (e.g., Why do some patients not adhere to treatment?) or procedural (e.g. How do professionals choose between treatment options?). In practice, many firms collect information habitually but not reflectively, without thinking about what they are trying to learn. But, in my research, the ability to identify and admit to critical knowledge gaps is characteristic of learning organisations. To do so requires two component capabilities, 20
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first an analytical facility to spot the gap and second the cultural knack to avoid blaming. Firms in which admitting ignorance is a culturally unacceptable, blameworthy fault are very unlikely to learn or endure in a changing market. Choose your weapon
The task of creating knowledge has been usefully compared to cooking. There are many ways to cook a meal and the method you adopt depends on what ingredients you have and what it is you want to prepare. When organisations learn, their “recipe” is shaped by the kind of knowledge they want create and the data and information “ingredients” they have available. That said, there are three main ways — deduction, induction, and abduction — of turning those ingredients into either declarative, causal or procedural knowledge. Although different functions and professions tend to prefer one way of “cooking” information over the other, it is simplistic to judge them as better or worse approaches. Organisational learning is pragmatic, meaning the best approach is the one that works in a given situation. Deductive learning
When market change is clear and measurable, and the goal is to understand that change, then deductive learning is usually the best method. This involves proposing an explanation for the change and developing a hypothesis from that explanation. For example, if the market share of a premium-priced therapy is declining, one obvious explanation is that payers are switching to lower-priced options. This leads to the hypothesis that if price is the explanation, then the shares of lowerpriced equivalents should grow at the expense of high-price products. When the data supports that hypothesis, the putative explanation is upheld and becomes new, causal knowledge about how the market works. If, however, the data shows other patterns, such as shift to an equal-priced rival, then other, non-price explanations are needed and a new cycle of hypothesis testing is needed.
Deductive learning is the most obvious learning method. It is the basis of most scientific methodologies. But it is much less common in biomedical markets than you might expect. In part, this is because it is hard to isolate one variable and control for others. Just as often, however, deductive learning is feasible but managers are happier to have faith in their long-held, subjective beliefs rather than to risk them being proven false. Inductive learning
When market change is messy and hard data is unavailable, and the goal is to unravel what is happening, then inductive learning is the preferred method. Less structured than deductive learning, induction can appear structure-less when, in fact, its process is implicit. For example, prescriber behavioural issues such as adherence to patient pathways can be studied by exploring the experience of multiple prescribers. By structuring that exploration into episodes, such as when adherence persisted or failed, or into crosstherapy comparison matrices within the same group of prescribers, patterns are more likely to emerge. In this example, the research might induce that adherence is inversely proportional to experience and self-confidence, an example of new declarative knowledge. Induction can be a richer, more insightful method than deduction but it is vulnerable to cognitive biases and method design needs to guard against that. Inductive learning is the most common learning method amongst executives. But because it is pervasive and often implicit it is often not even recognised as a learning method. By recognising when they are inducing new knowledge, managers can make the process explicit, more structured and more effective. Abductive learning
Between deduction, which tests existing thinking, and induction, which draws out new ideas, lies abduction, which works well when multiple views of the world vie for acceptance. For example, why market access decisions vary between countries
