Somewhat paradoxically, the complexity of key decisions in biotech continues to grow faster as the industry matures. Smaller
firms search for capacity while older players struggle under the weight of under-utilized capacity. Outsourcing drives work
around the globe and costs-per-mile soar. Maturing regulatory scrutiny and upstart innovation are cannibal cousins. New and
increasingly capable technology requires increasingly complex implementation. The proliferation of technical specialties spawns
whole teams with conflicting agendas. Gut instinct, vision, or turf protection, are no substitutes for the sophisticated methods
of decision science that have been developed precisely to apply to such increasingly complex environments.
Broad generation of alternatives: In biotech firms, complex decisions like build-or-buy usually cut across functions and disciplines and can have implications
that may not be obvious to the representative of any single function by itself. Having a single powerful individual dominate
the decision blinds the group to a broader view. Excluding the inputs of important constituencies leads to the risk of hiding
fatal flaws until it is too late to correct them. Further, critical functions and disciplines want their ideas and views considered.
The decision-making process should therefore be designed to generate as many reasonable alternatives as possible from all
interested parties. In our experience, the best mechanism for achieving those dual goals lies in a decision team broadly based
across functions.
More effective framing: Framing the decision means identifying the givens that must be taken into account and the level of detail at which the decision
will be made. For example, it might be a given that the company's fundamental production technology will remain the same—new
breakthrough technology is off the table. Lower-level details, such as whether to outsource administration, might be set aside
to focus on the key decision—whether to build a green-site plant in an optimal location or retrofit an existing plant. Framing
will also take into account the company's values—what it stands for and what it won't stand for. For example, if preserving
the workforce is a company value, alternatives that outsource jobs would be out of bounds.
Better information: The quality of a decision depends directly on the quality of the information on which it is based. The structured approach
to decision-making includes mechanisms for ensuring that all usable and relevant information is collected, quantified where
appropriate, and weighted accurately. A decision team should ask itself if better information about any of the alternatives
or the ability to pursue them might lead to a different conclusion. If the answer is yes, then the process needs work.
Rapid filtering of alternatives: The decision-making process should also be designed to quickly take the many possible alternatives and reduce them to the
few that have the potential to create the most value. Otherwise, the process is likely to drag out unproductively in endless
discussions of alternatives that don't merit such lengthy consideration.
Many alternatives are so similar that they are simply different settings on the same dial. The secret is to deeply understand
the bookend-alternatives—those at the two extremes of the range of plausible alternatives. For the firm looking to expand
capacity, those bookend alternatives might come down to only four: partnering with a CMO, buying an existing plant from another
company, upgrading several small existing plants, or building one big new plant. This approach enables the decision team to
focus on the most promising and genuinely different alternatives.
Strict comparability: To ensure the optimal business decision and to satisfy participants that the process of prioritization of alternatives is
fair and objective, a structured approach allows an apples-to-apples approach to comparability. Each promising and genuinely
different alternative is measured in terms of its likely financial performance under risk and uncertainty. Typically, that
measure is net present value (NPV) of cash flow. The final arbiter among alternatives is risk-adjusted profit, a language
that cuts across differences and gets to the heart of the matter.
Genuine alignment: In many ways, the ultimate advantage of a structured approach to decision-making is the alignment of the team. Soliciting
everyone's hypotheses and opinions and quickly prioritizing them through rigorous and objective methods of strict comparability
satisfies all participants in the process, no matter their initial positions. Resistance is converted into appreciation for
the most robust alternative. At the end of the process, the entire team is united behind the decision and ready to do their
part to implement it.
By contrast, the intuitive approach can degenerate into a contest between several powerful advocacy groups in the organization
and often results not only in poor decisions but also in triumphalist winners, resentful losers, and poor implementation.
More than once, we've seen build-or-buy decisions that were supposed to produce important new capacity flounder because the
decision-making process was short-circuited by favoritism and randomness. Or worse, the executive team simply announced a
decision with great fanfare—all the greater because they had made and unmade the same decision several times before.
In an industry where companies must repeatedly make high-value decisions in the face of increasing complexity in technical,
organizational, and regulatory developments, no biotech can afford to forgo the advantages of a rigorous decision-making process.
Clearly, this is a province where decision-making exceeds the powers of intuition and requires the same science that tames
the industry's other processes. In short, one of the most important decisions a biotech will make is what kind of decision-making
process it chooses in the first place.
James Bonine, is a managing consultant, Conrad J. Heilman, Jr., PhD, is a senior vice president, and Siddharth J. Advant, PhD, is a principal, all at Tunnell Consulting, King of Prussia, PA, 610.337.0820, heilman@tunnellconsulting.com
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