There is increasing evidence that the failure of most ROI forecasting models springs from their linearized and simplified nature. The return of a project within a biotech value chain is usually calculated by determining its contribution to the company's equity value. This is achieved using in most cases a number of financial models that concentrate on R&D costing and cash flow generation, the measurement of which is based on in-house derived or externally acquired data.
However, these methods do not recognize that asset generation or disintegration within a company (produced by different co-interacting project teams) or within the industry (produced by alliance networks between innovators and licensees) can be a very complex process where a number of factors co-interact to derive the value of an intangible or tangible asset. Most importantly, even the value of each basic asset element is determined by a number of sub-elements that continuously interact with each other.
There is now need to:
move away from old two dimensional (risk/return) or conventional asset methods based on discounted cash flows and explore new asset valuation methods based on real option models that can be used to analyze the value hidden in highly uncertain and complex single assets or sets of projects comprised of both in-house and partnered programs;
understand the complex and dynamic nature of the biotech business and introduce novel strategies that will help industry players both in the innovative and fully-integrated sectors to evolve successful portfolio management strategies.
combine the knowledge extracted from both option-based models and the sector's complex nature to introduce hybrid multidimensional (multielement) real option based models that can describe the complexity hidden in business assets with high technological uncertainty.
This methodology brings a number of benefits that can improve the early bioresearch-driven
New product development decision-making process by:
offering a wider selection of investment decisions/ options related to the evolution or/and allocation of highly complex biotech assets;
showing how biotech managers can increase capital growth by exploiting a number of opportunities hidden in these uncertain risky projects. This can be accomplished by selecting the right time to exercise an option to invest in certain assets, wait or abandon plans for investment;
enhancing the degree of flexibility of the biotech innovators or their licensees in long-term asset allocation and more generally shaping R&D strategic planning by learning to continuously adapt or adjust their assets values.
In an attempt to unlock some of the mysteries hidden in biotech asset valuation and market behavior, our strategic development team has identified ten basic elements that could govern the success of each biotech project and determine its asset ROI-generating potential. Interestingly, the ten key elements can be found in every aspect of economic activity within the biotech/life sciences-oriented supply chain. In other words, market participants should utilize the structural model of the ten key elements (that attempts to lower the degree of complexity in the valued portfolio) even if attempting to determine the cumulative value of biotech projects participating in a total corporate business model or, when reaching more depth, to measure the value of assets that co-interact within a single biotech project.
These include 5 exogenous (exo) and 5 endogenous (endo) key elements:
Financial Health (exo): the economics of each project and its contribution to the company's key financial indicators.
In other words the financial contribution of each innovation asset to the company's stock/equity value. This can be a critical factor for the innovating side as the ability of an asset to offer a continuous wave of cash generation opportunities can improve the innovator's internal investment activity and help it to correct or abandon practices, acquire or relocate assets in order to evolve faster than its competitors. Equally important for the licensing/industrial partnering/investing party, is an asset's ability to contribute to its management efforts to implement cost- efficient practices. We suggest that asset owners or partners should evolve practices through good inter-departmental communication that will be able to monitor on a frequent basis the effect of macroeconomic factors on resource pricing related to new asset development.
Investor Confidence (exo): the ability of each biotech asset/project to influence investor/financier behavior.
This is a very sensitive area as investor/financier can be misled by failed financial projections. In this case the biotech innovator must launch a new policy of increasing transparency between its management and its investors/financiers. Companies should never forget that true investor/financier confidence can be only achieved and preserved in the long-term by establishing policies of trust and knowledge exchange. Communicating problems and technological difficulties early can help the investors/financiers refocus their activity on highly valued assets and save the company from the embarrassment of a devastating market exit.
To value Investor Confidence, two sub-elements have been identified. These include the level of growth or decline in equity or private funding directly related or linked to biotech asset development. Here, funding volume variations should correlate with the performance of each biotech project. In addition it is critical to estimate the economic value of the company's biotech partnering network (that is responsible for biotech asset accumulation and evolution during a horizontal or vertical project/program) and its contribution to the company's stock/equity value/wealth.
Technological Facilities/Tools (exo): the economic value and the technological depth and breadth of all basic technological platforms used to generate the biotech asset or complete the project.
Ideally a company would like to use the best facilities and technological equipment that is available at a specific period of time in order to beat its competitors or generate the highest possible ROI potential. However, although it is well accepted that technological superiority can generate strong competencies, it does not always guarantee the success of project. In other words, right technological equipment allocation (using the right tool the right time for the right project) can evolve in-house or partnered assets faster.
To value Technological Facilities/Tools three sub elements have been selected. The first includes the contribution of each biotech tool to the organization's productivity and return on capital employed. This is followed by the economic value and contribution to debt of each used facility or analytical tool, the level of technological adaptability to competition and the degree of technological diversification.
Regulation (exo): the degree of acceptance of the biotech asset by the regulatory agencies.
Newly evolved biotech assets should follow all regulatory rules that apply in modern industrial practice. Designing experiments, or projects that are using poorly regulated assets can in the longer term severely damage the project's value. Rergulation value is characterized by the level of harmonization with current global regulatory requirements employed during the product development process. In other words a manager should always assess how its evolving biotech asset fits with its fully integrated vertical value chain and the regulatory environment that controls the growth of its pipeline engine. In addition, it could be also important to determine the degree of litigation threat derived from co-evolving competition.
Social Impact (exo): the degree of biotechnology acceptance by governmental, industrial and consumer organizations.
This exogenous element is characterized by the degree of acceptance earned by key opinion leaders, governmental institutes and socioeconomic groups. In other words, the level of innovation and economic growth carried in every biotech asset must be in agreement with consumer behavior and social rising or dominant trends.
Innovation Value (endo): the contribution of the biotech project to the company's or partner's pipeline productivity.
Every biotech asset must have a direct or indirect effect on vertical activities otherwise its value is diminished. Players/partners should select groups of biotech assets that when blended could offer strong new molecules discovery and new product development capabilities. The key here is to select early developing biotech assets with clear market/industry area focus. A number of biotech business executives also believe that this is where their right selection of assets could have an enormous impact to wide range of industrial sectors in the near future by generating novel areas of business growth.
Innovation value is determined by five sub elements that focus on the degree of contribution of each biotech asset to product pipeline development and expansion, the number of successfully identified and validated biotech based new product/market targets followed by the level of accompanied knowledge in unveiling complex natural physiological mechanisms.
Human Capital (endo): the volume of tacit knowledge and human expertise hidden or carried in every biotech project or asset.
This is an important aspect both for the innovating and licensing side. Every asset carries up to a certain degree the knowledge, experience and talent of its creators. The tricky part here is to preserve and enhance the quality of human capital carried in each asset/project. In addition, continuous monitoring of scientific performance and knowledge creation and management within every asset of every project within the organization can help the biotech manager to determine the contribution of its human expertise to company value.
To determine the value of this element, it is critical to assess the ratio of the number of top-performing scientists over inexperienced workers that participate in a biotech project. More specifically, the quality of the researchers and scientists involved in every biotech asset is a decisive success factor. In addition, the level of diversification of scientific expertise can also determine, to a degree, the success of an asset. Two other crucial human capital sub-elements are related to the degree of patent productivity per scientist and the return on capital invested per scientist.
IP info/value (endo): the degree of protection and differentiation carried in the biotech asset intellectual property (IP) when compared to competitors.
This is a highly controversial issue especially when attempting to determine the value of patents that describe the role of complex biological molecules in physiological mechanisms and product development. Biotech assets with high IP value are the ones that not only provide general information on biochemical functionalities but also reveal specific and well-validated product/market targets. This of course means that current industrial players in order to increase the value of their patent portfolios have to continue adding new information that can link their patents with characteristic strategy maps, well defined product functionality mechanisms and potential market targets.
When looking at the amount of information that is carried in every biotech asset a manager should be able to determine the depth of protected IP related to specific market segments, followed by the number of well protected patents related to product functionality and well defined market segment targets.
Portfolio Management (endo): the ability of the company's executives to best evolve and manage the particular asset or complete the project achieving all key milestones.
It is our opinion that successful portfolio managers should work to understand the technological and economic uncertainties that lie in the heart of their assets. This can become a very complex process, and only the application of high transparency of horizontal knowledge exchange from asset to asset that can reveal early the main weaknesses and strengths can prevent rapid asset devaluation.
To determine the value of this element, four sub elements have been characterized. The volume of financial investment injected in every biotech asset compared to rivaling technologies and platforms can reflect the degree of management's ability to battle competition-driven threats. In addition, it could be also critical to look at the performance of each biotech asset manager in terms of partnering initiatives, experience and relevance to the particular project.
S&M Potential (endo): the contribution of the bioinnovation assets to the company's sales and marketing strategy.
For example certain biotech assets based on metabolomics can help a fully integrated industrial partner's marketed product to refocus on new consumer populations with more efficient regimes. This can have an immediate positive effect on the company's selling and marketing performance. In addition, biotech innovators can alternatively out-license or divest certain biotech assets that do not fit with its overall corporate strategy and use the cash to develop selling and marketing capabilities for the remaining offered services. Each biotech asset carries a specific contribution to the company's marketing strategies.
Although we showed above the role of structural multi-factorial modeling in unfolding the biotech' sector high degree of complexity and supporting better asset valuation, it is also important to show how innovators and their potential or current licensing industrial/financing partners can best evolve their highly complex biotech projects.
Recently there has been a growing interest in "evolutionary" ideas in describing modern economic theories. Based on Cambell's and Metcalfe's ideas on organizational evolution we apply three main strategies (Variation, Selection and Retention) that all biotech market participants should undertake in order to evolve highly successful assets that will be able to offer high ROI.
Diagram A: How we Apply Variation in Biotech Assets Evolution to achieve high ROI.
Diagram B: The dynamics of biotech innovation: from a tendency towards high-ROI asset clusters within the biotech business model to the formation of biotech company clusters
The economic returns associated with a successful biotech innovation are not stable by nature. They very often start weakening as soon as an emerging group of technological imitators (competitors with similar platforms) has successfully entered the newly developed market sector. However, as the figure above illustrates this continuous interaction between innovation and imitation can create areas or clusters of high ROI potential (inter-company level: where the main innovator and market leader occupies the center) and high asset value creation potential (intra-company level).
Diagram C: Evolving the "fittest" assets or identify your competitor's advantages
When looking at the evolution of biotech assets within the portfolio of an innovator the ultimate goal will be to use the previous evolutionary tools of variation, selection and retention to create a number of clusters of assets that can carry high ROI potential. The tricky part of this process is the right selection and restructuring of biotech assets in order to create highly valued clusters.
We believe that market players should use the lessons learned from complexity (e.g. the ten asset elements) and evolution (e.g. gene insertion, mutation and cross breeding) to restructure and refocus their portfolios. clusters of individual assets within a business model, or clusters of companies which are collection of organized assets, can play a significant role in knowledge-based, innovative areas such as the genomics sector. CorinGreening can promote the evolution towards successful asset formation strategies through the application of healthy competition or strong partnerships networks. It is a result of continuous interaction of biotech oriented companies fuelled by the exchange, creation or abandonment of assets.
Perlitz, Manfred & Peske, Thorsten & Schrank, Randolf, 1999. Real Options Valuation: the New Frontier in R&D Project Evaluation. R&D Management, 29:3, 255-269
Cambell, D. (1969) Variation and Selective Retention in Socio-Cultural Evolution. General Systems, 14, 69-85.
Metcalfe et al. (2000) Innovation growth and competition. Evolving complexity or complex evolution. Complexity and Complex Systems Industry Conference, University of Warwick.