How real options reasoning and dynamic capabilities help

The strategic management literature has only a little to say about commercialisation strategy and business models in the biotech sector per se (Gans and Stern, 2003a; Pisano, 2006a, Sammut, 2005). Academics theorizing at an industry specific level have uncovered important industry and firm level strategic issues and some of the drivers of commercialisation strategy but have not brought these findings together in an actionable agenda that practitioners can capitalize on. Practitioners cannot easily seek solutions to the problem of poor industry performance from the literature. However, close

examination of the literature turned up two areas of theory that may be adapted and applied to the biotech setting in an actionable way. These are real options reasoning (ROR) and dynamic capabilities as discussed in the literature review.

Rather than coming up with a completely new theoretical framework for

commercialisation strategy in the biotech environment I have synthesized and extended theory related to ROR and dynamic capabilities utilizing the rich experience of

practitioners operating in the sector. The remainder of this chapter focuses on the integration of the academic concepts of ROR and dynamic capabilities with the

identified drivers of commercialisation strategy (and other observations) to propose an actionable model that may assist practitioners in developing commercialisation strategy.

Figure 6-1 captures the key drivers of commercialisation strategy at the firm level but does not address several key challenges that Pisano described – risk management (due to the profound uncertainty of science), integration across disciplines and functional areas and mechanisms for learning to keep up with rapid scientific progress. It also does not address the essential element of commercialisation strategy which is to build value. Addressing these issues is in the domain of dynamic capabilities – the organizational routines that enable a firm to reconfigure resources and act upon new opportunities (Eisenhardt and Martin, 2000; Teece, 1998).

Eisenhardt and Martin say that in stable industries dynamic capabilities are detailed analytic processes relying on existing knowledge and exercised and implemented in a linear fashion with the outcome being predictable. In stable industries dynamic

capabilities resemble the traditional concept of routines (Nelson and Winter, 1982). In highly dynamic industries such processes are exercised in an iterative, adaptive manner, and the outcome is unpredictable. The are simple or experimental processes, relying on new, quickly created knowledge (Brown and Eisenhardt, 1998). Most likely the biotech sector stands somewhere in between these two extremes. The high level of scientific uncertainty, and the fact that the sector is in its infancy, with best business models still evolving, means the traditional view of strategy as something first planned and then implemented does not provide flexibility to respond to the great unknown. Brown and Eisenhardt’s (1998) recommendation for a semicoherent strategic direction is appealing for competitive contexts that are in constant flux but it is too extreme for the biotech sector. However, Brown and Eisenhardt’s Competing on the Edge recommends

experimentation, which relies on small, fast and cheap probes to help gain insights to guide strategy for the future. Fast and cheap experiments are not always possible in the biotech sector but the concept is still valid and Brown and Eisenhardt have linked these probes to options, although they have not extrapolated this fully into a ROR framework. Dynamic capabilities closely support the concept of real options reasoning (ROR).

Under ROR entrepreneurial strategy making may be viewed as the development, exercise and possible termination of options over time. Some options may arise out of inspiration, some out of planning and analysis i.e. deliberate or intended strategy (Mintzberg, 1978) and others out of extemporized responses to events and serendipity i.e. emergent strategy (Mintzberg, 1985). Unexercised options resemble Mintzberg’s unrealized strategies.

The real options perspective helps to systematically identify the key variables that determine an option’s value – the present values of future income and expenditure streams, the degree of uncertainty in the project, the tie to expiration of the option (i.e. the time to a decision that can no longer be deferred) and the opportunity costs of preserving an option. In the biotech sector the real options framework has the

additional benefit of forcing the formulation of process milestones that have the effect of establishing decision criteria and the mitigation of financial risk by portioning the development process into predefined stages (Burns, 2005). Figure 6-2 summarises ROR into three stages.

Figure 6-2 Real options reasoning

To help conceptualise ROR I’ll be explaining this model by reference to a gardening metaphor, which is portrayed pictorially in figure 6-3

Garden Metaphor

Stage One

Plant Seeds _{Stage Two}

Nurture

Stage Three Harvest Stage Three

Weed

Figure 6-3 Garden metaphor

Stage one of the ROR model involves identifying the strategic options available to the firm at each stage of the commercialisation process and investing in selected options. In terms of the gardening metaphor it is about identifying all the possible plants (alias strategies) that can be grown in the garden and then planting the seeds of those selected. Stage two involves nurturing the ‘seedling’ options – fertilising (with further resources) and pruning as needed. The goal of stage two is to either reduce the risk or strategically amplify the value of the options. It is an ongoing process that may involve many cycles (or seasons). Stage three is where a firm either exercises or terminates options.

Exercise can be done either by selling the option in the market for ideas (e.g. through the sale of intellectual property or through out-licensing) or by making the full

investment commitment required to bring the product to market. Either way ‘exercise’ is about plugging into the value chain. In gardening terms this is the harvest. Stage three also involves the termination of options that are no longer viable. Termination can occur at any point in time and is the equivalent of ‘weeding out’ the plants / options no longer required, no longer affordable, or judged to have a low probability of future exercise.

The options available to a firm during commercialisation are very contextual, and path dependent, so MANY strategic choices made by biotech firms will affect their options for how and when they can plug into the value chain. I view commercialisation strategy as widely encompassing and incremental in nature. At the firm’s inception it includes issues such as defining company structure - both operational and ownership, choice of location, choice of technologies and products to commercialise (hence specifying aspects of R&D and certainly specifying the developing pipeline) and nurturing and creating demand for products. Commercialisation strategy may include seeking and ensuring finance to cash-flow operations, hiring and developing key management staff, and seeking and negotiating collaborations and alliances. It involves the development, acquisition or contracting of downstream functions such as sales, marketing and distribution and integrated support functions such as information technology. Commercialisation strategy involves investment decisions such as whether or not to patent, and ensuring that the costs of product development and commercialisation do not overwhelm revenue generating potential. And finally, commercialisation strategy may include collecting competitive intelligence on trends and developments in the environment to create an organizational awareness, particularly in terms of competition, technological innovation, and discontinuous change that could upset the firm’s

strategies.

What is apparent from this long list of activities associated with commercialisation strategy is that strategy is not formulated and then implemented. Rather, it is developed and modified over time. It is incremental as well as encompassing, and it is important to recognise that past actions shape future possibilities (Pettigrew, 1979). This is the true nature of commercialisation strategy in practice, as opposed to a more rationalistic view of commercialisation strategy as something that is formulated and then

implemented. The holy grail is to understand how lines of action related to these activities, and the options surrounding each, are knit into coherent strategies for the commercialisation of biotech innovations. This thesis raises the awareness of the complexity of commercialisation strategy and offers a ROR/dynamic capabilities approach as an actionable way of at least trying to deal with the complexity.

Drawing on ROR and dynamic capability theory, and melding this with the findings from the preceding chapter a prototype model for biotech commercialisation strategy is proposed in the following section. It is then refined and validated through discussion with experienced industry practitioners with their feedback and input described in the next chapter. The final model is presented in chapter eight as part of the continued discussion on how biotech firms could do strategy better.

6.3 How biotech firms ‘could’ do strategy better – a synthesis