You're striving for efficient decision-making. How can you align data analysis with Lean principles?

Alinho a análise de dados com princípios Lean identificando desperdícios e priorizando informações essenciais para decisões ágeis e eficientes, sempre focando na otimização de recursos

Align data analysis with lean principles by focusing on value-added insights and eliminating waste. Use real-time data to identify bottlenecks and streamline processes. For example, applying predictive analytics can prevent downtime, reducing unnecessary breakdown losses. By prioritizing actionable data, decision-making becomes faster and more efficient, directly supporting lean goals of continuous improvement and resource optimization.

El enfoque principal de la metodologia lean es trabajar e intentar reducir los tiempos de ciclo de la manufactura de productos asi como los tiempos estandares de la manufactura de los productos, una herramienta muy valiosa para lograr esto es elaborar un value stream mapping de todo el proceso de fabricacion para poder establecer que le da valor al proceso y cuales no y de ahi establecer la estrategia para mejorar el proceso.

Focus on the data that are meaningful and related to the decision making, value-added to think and take your resources. The over-process waste is a common issue need to avoid.

To align data analysis with Lean principles for efficient decision-making, I focus on collecting relevant data that directly impacts key value streams. I use Lean tools like Value Stream Mapping and Root Cause Analysis to identify where data insights can reduce waste and improve processes. Prioritizing real-time data and visual management tools, such as dashboards and Kanban boards, supports quick and informed decisions. I ensure that data analysis remains actionable and aligned with continuous improvement goals, empowering the team to make decisions that drive efficiency and eliminate non-value-added activities.

Utilizando correctamente un value stream mapping podemos definir que es lo que le da valor al proceso entendiendo que esto es todo lo que cambia al producto en su proceso de manufactura y todo lo que no genera un valor podemos considerarlo como desperdicio y eso es lo que se debe eliminar en la medida que se pueda.

When starting a lean project, I usually recommend starting with value stream mapping. VSM has a comprehensive approach to the product manufacturing process. VSM evaluates your suppliers, you as a manufacturer and your customer. The initial stage in VSM is recording the current state (current times). Based on that recording, we make projections of where we want to be in six months or a year, and the necessary corrective measures are implemented. Corrective measures can be of a wide range. For example, you may need to revise your layout or request a supplier to shorten the delivery time of raw materials or semi-finished products. Once you've identified what actions need to be taken, I also recommend setting up KPIs to track progress.

Os 3 M's do Lean Manufacturing – Muda (desperdício), Mura (variação) e Muri (sobrecarga) – podem otimizar a análise de dados: - **Muda:** Elimine dados irrelevantes para focar nos que agregam valor. - **Mura:** Minimize variações nos dados para garantir consistência e precisão. - **Muri:** Evite sobrecarga, utilizando ferramentas adequadas e mantendo o fluxo de dados equilibrado. Essa abordagem torna a análise de dados mais eficiente e precisa.

To begin with, let's define what process losses are. Simply put, waste is any activity that does not add value to your process. Your customer is not ready to pay for such activities. A common mistake is to think of losses solely as waste or interruptions. The eight basic losses include losses due to unnecessary transportation, unnecessary inventory, unnecessary movement, all types of waiting, overproduction, overprocessing, and scrap. The eighth loss is unused talent in your company. Methods based on lean management are solutions for numerous challenges in the process. With this way of doing business, the company reduces costs, improves the value of its products and ultimately increases customer satisfaction.

To align data analysis with Lean principles and improve decision-making, we need to build a data-driven culture that supports Lean values. This means integrating Lean practices into how we use data, setting an example of making decisions based on data, and making sure everyone in the organization can easily access and understand the data they need. By creating clear metrics that align with Lean goals and increasing data literacy, we can more effectively spot inefficiencies, eliminate waste, and focus on activities that add value. Providing timely training and creating a consistent approach to data across the organization will help streamline operations, drive ongoing improvements, and deliver more value to both our customers and employees.

Digital technology and lean management are not "enemies". Indeed. Real-time data will only improve the performance of lean systems. However, if you have real-time data but do not use a lean management strategy, the company may not achieve the desired results.

To inform decision making Consider and prioritize metrics in their Lean order of Importance; 1. Safety 2. Quality 3. Efficiency 4. Cost