Here's how you can enhance decision making in R&D teams.

Decision-making means to choose the best option by relying on decision-making knowledge, various methods and tools. In fact, the question that can be asked about making a decision is which of the options ahead should be chosen to achieve the goals? First, we must define the problem precisely and then consult with the experts, that is, instead of blaming, we should make a better decision by getting more information. Prepare a T-chart and examine the strengths and weaknesses to have a more valued decision.

Research & Development is the back bone of any of the organisation and without strengthening it , it would be difficult to have a grip on the cutting edge technologies across the globe. An organisation goals may be specific but ultimately reach to a common platform of strengthening students and faculty members. The R&D plays a pivotal role in overall growth of any organisation. It is very important to have clear vision about the organisation goals and each member must have a clear thought about it and infact every member must align their thoughts with the goal of the organisation and help for the overall growth and excellence in every aspects.

I believe it's crucial to encourage diverse perspectives and ensure everyone feels heard. Regular brainstorming sessions and workshops can help in generating innovative ideas. Implementing data-driven approaches and leveraging advanced analytics tools can provide valuable insights, leading to informed decisions. Additionally, fostering a continuous learning environment, where team members stay updated on the latest industry trends and technologies, significantly boosts the decision-making process.

El desarrollo de un producto de investigación puede ser extenso y riguroso si no se tienen objetivos delimitados. A pesar de que no existen tantos riesgos económicos como en un proyecto industrial, es importante clarificar y delimitar las bases a través de los objetivos. De esta manera el proyecto atraerá al inversionista o revisor del proyecto.

Example: When developing a new cancer immunotherapy drug, set a clear goal to achieve a specific milestone, such as reaching Phase I clinical trials within a specific timeframe. This goal should align with the company’s vision of advancing innovative cancer treatments. By establishing this target, the team can prioritize tasks, allocate resources effectively, and measure progress. This clarity ensures that every decision, from research directions to budget allocations, directly contributes to reaching this milestone.

It is very crucial to engage all the team members in giving their valuable ideas , no matter who they are and from where (means other departments) belong. It is always recommended that one must give their valuable inputs in making the strong R& D team. As a matter of fact it is sometimes found that people choose team by cast, gender or community which is strictly wrong and not acceptable in any mode .

En la investigación comúnmente se exponen ideas para el trabajo futuro desde diversas fuentes: tesis, artículos científicos de congreso, simposiums, seminarios, etc. Dadas estas fuentes nos surgirán ideas y aportes para innovar nuestro proyecto. La constante actualización y las nuevas ideas fortalecen el transcurso de cada proyecto de investigación.

Example: During the early stages of developing a new drug for colorectal cancer, involve team members from various departments such as pharmacology, clinical research, regulatory affairs, and marketing. This diversity brings different perspectives to the table, ensuring comprehensive evaluation of the drug’s potential impacts. For instance, the marketing team might provide ideas into patient needs and market demand, while regulatory experts can highlight compliance requirements. This cross-functional collaboration leads to more robust and innovative solutions, avoiding the pitfalls of groupthink.

As a matter of fact R&D is based mainly on one major thing which is Data..no one can think of any sort of research without having valid data.. either we talk about IT work or research analysis the major role is played by Data and due to which we must realise the importance of it and must work genuinely.

Según Andrew NG, uno de los expertos según la revista TIME en el área de la inteligencia artificial, los datos son la nueva electricidad del mundo actual. Gracias a los datos es posible tomar decisiones de forma más inteligente y desarrollar mejoras en el producto de investigación. La experimentación y la simulación son las fuentes principales de datos a considerar.

To consult the statistician after an experiment is finished is often merely to ask him to conduct a post mortem examination. He can perhaps say what the experiment died of. - R. A. Fisher Basic statistics proficiency is vital in R&D. Considering the structure and depth of data required to answer your question will help you not just to set up an experimental plan, but also to asses your experimental procedures. Experiments which could never yield significant results, e.g. due to sample size, measurement precision/repeatability, are a waste of resources and a source of frustration. Consider systematic approaches (DoE) if you suspect complex correlations. Representative sampling is key!

Example: When deciding on the optimal formulation for a new prostate cancer drug, utilize data from preclinical studies, patient demographics, and competitor analysis. Equip the team with advanced analytics tools to interpret this data. For instance, data from previous trials may indicate which formulation had the best efficacy with the fewest side effects. By focising on decisions on this empirical evidence, the team can objectively choose the formulation most likely to succeed in clinical trials, rather than relying solely on intuition or experiences.

Example: Before advancing a new monoclonal antibody therapy into clinical trials, conduct a thorough risk analysis. Assess potential risks such as adverse reactions, production scalability, and regulatory hurdles. For instance, evaluate the likelihood of side effects based on preclinical toxicity data and their potential impact on trial success. This systematic approach helps the team identify acceptable risks, such as manageable side effects, versus high-impact risks that require mitigation strategies, such as developing new plans for manufacturing challenges. This informed decision-making ensures that the team is prepared for various scenarios, balancing innovation with caution.

To play big, you have to find ways to create maximum impact – that means doing something different…but it doesn’t mean doing it on your own! In fact, it’s SO MUCH easier – and a lot more fun – when you do it with other people. And when you learn from others on feedback loops, it means you don’t have to forge your own path – which can be difficult and lonely.