Research and development (R&D) professionals face complex and challenging problems every day. How do they decide which ones to focus on and which ones to postpone or ignore? In this article, you will learn about some common strategies that R&D professionals use to prioritize problems and achieve their goals.
One strategy is to evaluate the value and urgency of each problem. Value refers to how much the problem affects the customer, the market, or the organization. Urgency refers to how soon the problem needs to be solved or how much it will worsen over time. By ranking the problems according to these criteria, R&D professionals can identify the most important and time-sensitive ones and allocate their resources accordingly.
My guiding start would be the risk assessment, and how identified risks would be affected by a new problem would be affected. Then I try to keep things simple and quick: Is the problem a potential show-stopper? If so, who needs to know this immediately to start risk mitigation on every level affected. If not, enroll experts as needed to get their opinion and advice. In general, a wise and focussed way of communication helps to reach the most goal for now: Try to calm down the team and the leaders by building confidence and refocus on the issue itself. If there is a cluster of issues, I analyze any dependencies among them. A root cause analysis is helpful here to focus effectively and allocate resources properly.
When it comes to value and urgency, within the R&D realm, one of the biggest challenges is quantification. It is very difficult to quantify potential value and urgency. If it is about prioritization, not necessarily a final go/no-go decision, I’d recommend simpler ranking view. Bucket the ideas in a 2x2 with “high/low” or in a 3x3 with “high/med/low” criteria.
In a previous project, we prioritized problems based on their value to the project goals and the urgency they posed. We allocated resources to address critical issues with immediate impact on project milestones, ensuring our efforts aligned with the project's overarching objectives.
Na minha experiência, uma maneira fácil e clara de definir prioridade em uma lista de problemas é: busque aval da diretoria para essa defini??o. Caso n?o obtenha sucesso, indico construir uma matriz GUT (Gravidade x Urgência x Tendência). A matriz é construída atribuindo notas para cada uma das variáveis, e depois essas notas s?o multiplicadas (ou somadas) e, listando em ordem decrescente, você obterá uma lista de prioridades do que ser feito. Obs.: importante que essa constru??o seja em equipe, com pessoas que possuam uma vis?o diferente.
In my view, the prioritization of problems within research and development is not merely a matter of scientific or technical merit, but rather a reflection of the prevailing power dynamics and knowledge paradigms. The problems deemed valuable or urgent are often those that align with the interests and agendas of dominant institutional forces - be it funding bodies, corporate interests, or governmental policies. The discourse within the scientific community, a crucial determinant in this process, guides what is considered known, unknown, urgent, or valuable. It is shaped by historical and social contexts, which can shift the perception of urgency in response to societal needs or crises.
Another strategy is to assess the impact and effort of each problem. Impact refers to how much the problem contributes to the desired outcome or the overall objective. Effort refers to how much time, money, or resources are required to solve the problem. By plotting the problems on a matrix of impact and effort, R&D professionals can prioritize the ones that have high impact and low effort, and avoid the ones that have low impact and high effort.
When faced with multiple problems, evaluating their potential impact on the project's success versus the effort required for resolution was crucial. We identified high-impact issues that could be resolved with relatively lower effort, optimizing our resources for maximum impact.
Bei Wirkung und Aufwand f?llt mir gerne das Pareto-Prinzip ein. Wie schon oft hier auf LinkedIn habe ich Zweifel an der Methode, da diese m.E. nur funktionieren kann, wenn die restlichen 20% delegiert werden k?nnen. Wir in der Medizintechnik sind sehr streng reguliert. "Mut zur Lücke" f?hrt irgendwann sehr schmerzhaft vor die Wand. Daher ist es effizienter, die Verschwendung eines jeden Prozesses zu minimieren und Zeit für die eigentliche Wertsch?pfung zu haben.
The Impact-Effort Matrix is a visual tool that categorizes problems based on their potential impact and the effort required to solve them. By plotting challenges on a matrix, R&D teams can strategically focus on those with high impact and low effort, optimizing the allocation of time, money, and resources. 1. Strategic Decision-Making: The matrix aids in strategic decision-making by offering a clear overview of each problem's potential impact. R&D professionals can align their efforts with overarching goals, ensuring that the solutions pursued contribute significantly to desired outcomes.
A third strategy is to consider the stakeholder and risk of each problem. Stakeholder refers to who is affected by or interested in the problem, such as customers, managers, or partners. Risk refers to how uncertain or unpredictable the problem or its solution is, and how much it can affect the project or the organization. By weighing the stakeholder and risk of each problem, R&D professionals can prioritize the ones that have high stakeholder and low risk, and manage the ones that have high risk and high stakeholder.
Considering stakeholder needs and risk factors influenced our prioritization strategy. We assessed problems that significantly affected stakeholders or posed substantial risks to the project's success. Addressing these problems gained priority to maintain stakeholder confidence and mitigate potential setbacks.
A fourth strategy is to explore the creativity and feasibility of each problem. Creativity refers to how novel or innovative the problem or its solution is, and how much it can generate new value or opportunities. Feasibility refers to how realistic or practical the problem or its solution is, and how much it can be implemented or tested. By comparing the creativity and feasibility of each problem, R&D professionals can prioritize the ones that have high creativity and high feasibility, and experiment with the ones that have high creativity and low feasibility.
I’d propose a 2x2. Feasibility on the horizontal axis (the higher, the more feasible), creativity on the vertical axis (the higher, the more creative). Once the ideas are mapped on this 2x2, prioritize the ones in the top right quadrant. With a few caveats (there are always caveats! ??): 1) “creativity” should include both uniqueness and size of prize. Just because something is unique would not warrant success. 2) Sometimes, in R&D, we tend to evaluate technically complex ideas as “creative or unique” (I call this ‘the scientist’s dilemma’) creative ideas do not need to be always the technically complex ones 3) “size of prize” is not only about economic or business gain, how much of a big problem are we solving here?
In some instances, prioritizing problems involved assessing their creative solutions and feasibility. We weighed innovative approaches against their practicality to solve complex issues. This approach allowed us to focus on problems where innovative solutions were both plausible and beneficial.
A fifth strategy is to check the alignment and learning of each problem. Alignment refers to how well the problem or its solution matches the vision, mission, or strategy of the project or the organization. Learning refers to how much the problem or its solution can provide new knowledge, insights, or feedback. By verifying the alignment and learning of each problem, R&D professionals can prioritize the ones that have high alignment and high learning, and adapt the ones that have low alignment and high learning.
These are some of the strategies that R&D professionals use to prioritize problems. However, there is no one-size-fits-all approach, and different situations may require different combinations of strategies. The key is to be flexible, adaptable, and data-driven, and to communicate clearly and effectively with the stakeholders and the team.
Prioritizing problems aligned with our organizational learning goals was crucial. We focused on issues that not only solved immediate challenges but also contributed to the team's learning curve or enhanced our R&D capabilities in the long term.
Regularly re-evaluating problem priorities ensures alignment with evolving project needs. Incorporating data analytics to prioritize problems based on empirical evidence enhances the objectivity of the decision-making process.
Firstly, they conduct thorough risk assessments to identify critical issues. For example, in pharmaceuticals, potential safety concerns might take precedence. Secondly, they leverage data-driven approaches, utilizing tools like decision matrices to objectively rank problems based on factors such as impact and feasibility. Unconventionally, fostering a culture of open communication and cross-functional collaboration can lead to innovative problem-solving. Encouraging diverse perspectives often yields unexpected solutions. Lastly, embracing a fail-fast mentality allows teams to quickly discard unviable ideas, accelerating the focus on more promising challenges.