Striving for efficient process design?

Cutting costs should not be a goal, I would recomment to reformulate this goal to increase profitability instead. There are many ways to calculate production costs, it is a very biased indicator. It is possible to reduce the unit cost while increasing overall expenses, the way fixed costs are distributed over the different products may have to be modified with a new process design (which can artifically increase or decrease the calculated cost, making it different from the actual cost). Profitability is less vulnerable to formula manipulations, and more straightforward... After all, if the end goal is really to reduce costs, we can close shop, thus bring the expenses to zero. That's not the best business model 😉

By using advanced technologies and data insights, we can streamline workflows, cut costs, and boost productivity. Working together and focusing on continuous improvement are vital for creating processes that meet and surpass industry standards.

In process design, it’s important to remember that striving for perfection can often hinder progress, as “perfect is the enemy of the good.” While having clear and measurable goals is crucial, there comes a point when refining every detail can delay the entire process. Focusing on creating a “good enough” solution and freezing assumptions at key points allows you to move forward, iterate, and improve over time. This approach keeps momentum and ensures that the process design progresses without being paralyzed by the pursuit of an unattainable perfect state. Ultimately, it’s better to implement practical, functional designs that meet the core objectives than to endlessly chase perfection.

One of the most delicate phases of process design is the goal definition which people undermine because we are too quick to believe that we know the problem, bottlenecks and the goal. It takes deliberate brainstorming sessions to dive into understanding the critical problems that demand the process design.

Clarify Objectives: Start by identifying what you want to achieve. These goals should be specific, measurable, attainable, relevant, and time-bound (SMART). For example, if your process is related to renewable energy, a goal might be "Reduce energy waste by 15% within six months." Align with Organizational Strategy: Ensure that these goals align with the broader strategic objectives of your organization. This alignment will help secure stakeholder buy-in and ensure the process changes are seen as valuable. Stakeholder Engagement: Involve key stakeholders in the goal-setting process. Their input can provide valuable insights and help you gain early support.

Involving other disciplines early in the process design is essential for setting accurate constraints and refining assumptions. Each discipline brings a unique perspective that can identify potential issues or opportunities that might be overlooked by process engineers alone. Since not everyone is familiar with the intricacies of process engineering, creating simple, easy-to-understand sketches or diagrams helps communicate key concepts clearly across all teams. This approach ensures that everyone can contribute meaningfully to discussions, making the decision-making process smoother and more collaborative. By fostering cross-functional engagement, the design becomes more robust, with better-aligned goals and fewer surprises in the project.

Identify Current Processes: Document existing processes as they are, using tools like flowcharts, SIPOC diagrams (Suppliers, Inputs, Process, Outputs, Customers), or value stream mapping. This will give you a clear picture of the current state. Involve Key Participants: Include those who are directly involved in the process. Their hands-on experience will help in accurately mapping out the steps and identifying potential gaps or inefficiencies. Analyze the Flow: Look for bottlenecks, redundancies, or unnecessary steps. Understanding these will be crucial for streamlining later.

Es de suma importancia conocer la situación actual del proceso, por lo que se requiere generar una representación de la forma en la que opera. Como un primer acercamiento se puede definir su diagrama SIPOC (Proveedores, Entradas, Proceso, Salidas, Clientes) y después su diagrama de flujo. Para el caso en donde intervengan varias personas o áreas de la empresa, es importante definir responsables para cada etapa, paso o actividad del proceso y dejar claras las interacciones entre las áreas involucradas. Por último es importante identificar en qué parte del proceso se localiza la situación a resolver para lograr el objetivo planteado. Es crucial vivir o recorrer el proceso para hablar con el responsable y operadores del mismo para conocerlo.

Collect Relevant Data: Gather quantitative and qualitative data related to the process. This might include time metrics, error rates, resource usage, and feedback from employees or customers. Identify Patterns and Trends: Use statistical tools or software to analyze the data. Identify where the process is underperforming or where improvements can be made. Benchmarking: Compare your data against industry standards or best practices. This will give you a reference point to measure your process's effectiveness.

However, the fundamental need to collect information from the process and subsequent decisions is even more impactful, since it is the interpretation of this data that will really allow fine, punctual, precise and timely adjustment within a process. In the same way, the data collection mechanism must guarantee veracity, protection and integrity, otherwise there will not be a complete scenario to address future problems or adequately address current ones.

Good data analysis starts from data acquisition. Defining the acquisition parameters ( amount, frequency, type of data) defines the analysis you do. The tipping points between a simple regression and a PCA is 1 parameter, not much but when you consider scaling a digital solution into production quality we are talking magnitudes difference in processing costs. So my tips are: 1. Concise Factorial selection 2. Frugal parameter tracking 3. Combine factors if possible 4. Break down analytics into multiple stages. Might seem a lot of work but the decentralisation of data processing is a sure and direct path to an efficient process.

Es importante definir cuáles indicadores necesito de mi proceso, lo cual me lleva a definir lo siguiente: tipo de datos (cualitativos o cuantitativos), cuáles datos se requieren tomar o medir, cómo se realizaran las tomas de esos datos (instrumento de medición y validez del mismo), cada cuándo se realizaran las mediciones, analizar el comportamiento de las mediciones (histórico si aplica) y definir cuál será el tipo de análisis estadístico más adecuado para interpretar los datos obtenidos y tomar mejores decisiones para actuar. También es de suma importancia hablar con los dueños y operadores del proceso, los cuales al compartir sus experiencias y percepciones del día a día, ayudarán a tener una mejor interpretación de los datos recabados.

Design the New Process: Based on your analysis, create a new process design that addresses the identified issues. Make sure to include input from those who will be affected by the changes. Pilot Testing: Before full-scale implementation, conduct a pilot test to evaluate the impact of the changes in a controlled environment. This allows you to make adjustments before wider roll-out. Training and Communication: Ensure that everyone involved in the new process is trained and informed about the changes. Effective communication is key to a smooth transition.

Having a process design software is crucial when implementing changes because it allows for accurate modeling and simulation of the impact of adjustments before they are applied on a larger scale. By using software, you can capture data and visualize how different modifications will affect the overall workflow, reducing the risk of unforeseen complications. Additionally, it enables you to conduct sensitivity analysis, helping identify which variables or changes have the most significant impact on performance. This analytical approach allows for better-informed decision-making and ensures that adjustments are optimized before full-scale implementation, ultimately enhancing the efficiency and adaptability of your process design.

La implementación de los cambios debe ser gradual y de forma controlada, una vez realizado el plan de acción también se debe contar con un plan de control para asignar tareas y responsables a cada una de las etapas de la implementación y registrar su avance. Es importante dar seguimiento continuo y cercano a la implementación, así como seguir aplicando el proceso PDCA.

Set Key Performance Indicators (KPIs): Establish KPIs that will help you measure the success of the new process. These should be directly tied to the goals defined in step one. Regular Review: Continuously monitor the process using these KPIs. Regularly review the data to ensure the process is performing as expected. Feedback Loop: Create a mechanism for ongoing feedback from those involved in the process. This will help you quickly identify any issues and adjust as needed.

Una vez implementado el cambio se deben realizar las mediciones y el análisis de los indicadores definidos para el proceso y corroborar que realmente ha habido una mejora después de la implementación del cambio. Además, permitirá seguir monitorizando el proceso y tomar decisiones futuras sobre qué otra mejora se puede realizar para incrementar su desempeño o adaptarlo a nuevos requerimientos, ya sean internos o para cumplir con los requerimientos de los clientes de la organización.

Promote a Culture of Continuous Improvement: Encourage a mindset that values ongoing improvement. This can be done through regular training, workshops, and by recognizing and rewarding those who contribute to process enhancements. Flexible Processes: Design processes with flexibility in mind. This will allow your organization to quickly adapt to changes in the market, technology, or regulations. Monitor External Factors: Stay aware of changes in industry trends, customer needs, or regulations that may necessitate further changes to your processes.

Culture of Continuous Improvement Encourage ongoing feedback and make process improvement a regular part of your operations. Lean and Six Sigma methodologies can be particularly useful here.

Fostering adaptablity comes from setting a range of objectives rather than firm goals. Anticipate steering from early on, communicate the need for a steer co, and always recalculate and re-communicate change of outcomes (...in line with business strategies) after every pivot.