In general, few productivity improvements in sugarcane have occurred during the past three decades. At the same time, production costs have increased and production statistics reflect decreased yields globally. In comparison to the ‘golden years’ of new technology and improved germplasm in the second half of the previous century, little more than optimisation of existing practises has emerged from the past two decades. Given the slowdown in new technology delivery, it is not surprising that many industries have placed more scrutiny on how they manage their Research & Development institutions and investments. The result of this ‘slowdown’ has created a perception that poor management of research projects and programs by scientists is at the core of the problem. This has led to the introduction of ‘real’ managers with the subsequent management of R&D as if it is a ‘normal’ production and sales business through well established ‘business models’. Strong emphasis has been placed on project selection, project management and minimising risk. Research, especially in the discovery phase, is a very high-risk endeavour and a high proportion of all projects fail. Institutions that have a low appetite for risk quickly run out of new technology innovation. Because of the inability to predict, a discovery project cannot easily accommodate management issues such as budgeting, milestone definition and timeframes. Managers generally prefer D and Extension over R because of the higher predictability and lower perceived failure rate. The key to proper management of R&D is a recognition that researchers and managers operate under very different codes of conduct. If this is not properly managed, then conflict between researchers and the rest of the business follows. It has become customary to view RD&E as a unit following a ‘systems’ approach. Despite obvious advantages of this approach, it often fails to recognise the most significant shortfall(s) in the value chain. This practice can unnecessarily inflate the cost, slow project progress and is dependent on consensus that tends to favour the lowest common denominator or more vocal team members. Consensus and innovation tend to be opposing objectives, as innovation requires thinking with an ‘outside the box’ mindset. Consequently, innovation can be stifled using this approach. Peer review is a great tool to measure progress in projects and selecting projects for development. It is not suited for selection of new innovative ideas. With no obvious improvement in technology delivery and adoption, it is timely to ask whether the current approaches are achieving their objectives. In addressing this question it is important to look at the global evolution of R&D models and modern trends in highly innovative businesses. Instead of trying to ensure that every research project entering the technology funnel delivers a product, a greater emphasis is needed to create an innovative environment where all role players are focussed on key strategic objectives, and all research results are seen as key learnings for future deployment.
Models to inform neutralizing antibody therapy strategies during pandemics: the case of SARS-CoV-2
