[MUSIC] In this lesson, we'll discuss some concepts from ISO 9001:2015 international standard for business quality management system. We will discover an internationally recognized framework to implement data driven decisions. Okay, so what is the ISO 9001:2015? ISO, stands for international standardization organization. It is based at Geneva Switzerland, over 160 countries are part of ISO, including the United States. ISO develops all kinds of standards such as traffic symbols, material standards, inspection, practices, and more. Quality Management System(QMS) is a data driven framework to manage quality and ultimately your business. Quality means meeting customer requirements, which could be the fit form or function of a product or service. Management is a set of activities to ensure we met customer requirements based on data, acquired from inspection, customer feedback etc. The system is a set of processes and organization uses to execute its quality management activities. These processes could be customer, support or management oriented. The benefits of best practices from ISO are simple. It talks about data driven methods to improve business performance. The ISOs process versus person mindset helps manage risks better. Here's an overview of the ISO 9001:2015 business quality management system. We will walk talk about seven tools from ISO that will help accomplish two goals. One, to drive data driven decisions. Two, as a bonus, map out a business case for the appropriate Internet of Things implementation. The seven tools are in business context, leadership, or top management, operational planning, operational support, operations who's an output could be a product service, performance management, and improvement activities. As we have previously discussed throughout the series of courses for any data-driven decision, recommend the business context first. A tactic to do so is to start by understanding the internal and external factors surrounding the business. Consider both positive and negative factors or conditions. Internal factors could be organization values, culture, mission, vision, core competency, etc. External factors could be economics, market share, local, legal, finance, supply chain, etc. Interested parties are stakeholders in an organization. These parties could be customers, suppliers, employees, regulatory bodies, etc. Document your organization's scope. The scope should indicate the boundaries and applicability of your business quality management system. An example is company A designs and manufacturer widgets for the automotive industry. Once you've determined your internal and external factors, interested parties and scope, leverage this knowledge to map out all your business process. These processes could range from sales, accounting, legal, finance, supply chain, production, quality, inspection, receiving, delivery, and many more. Some process mapping tools, are process flowcharts, turtle diagrams, etc. A process should typically comprise the source of inputs, activities, outputs, and receiver of outputs. Refer to course one in this series for more information on process mapping. As a team raise strong key performance indicators (KPIs) associated with each of your These KPIs indicate the health off your processes and business as a whole. For sales, KPIs could be revenue and profitability. For production KPIs could be quality and on time delivery. The purchasing KPIs could be associate with vendor quality pricing and on time delivery. Another tool IO also talks about is gaining buying from the leadership for a data driven organization. Top management must demonstrate a commitment by ensuring the business process KPIs align with the strategic direction off the organization. Management must promote data driven decisions by engaging, directing and supporting persons to contribute to the effectiveness off your business quality management system. With the focus on enhancing customer satisfaction, top management must determine, maintain and review the KPIs, such as quality pricing and on time delivery. Senior management must ensure the customer and applicable statutory or regulatory requirements are consistently met using data. Management must also implement a data policy that provides the framework for setting KPIs and improvement projects. This data policy must be communicated, understood and applied within the organization. This policy should also be available toe all the interested parties we discussed. Lastly, management should assign roles responsibilities and authorities within the organization to ensure the organization conforms to its state of standards and uses it to inform data driven decisions. Now that we've established your organization context and gain buying from your senior management, leverage data to identify and mitigate risks and opportunities. Risks are the negative outcome off uncertainty and could result in financial laws, safety hazards, etc. Opportunities are positive, outcome off uncertainty and could result in financial gains, improved customer satisfaction, etc. There are numerous tools to use data to conduct risks and opportunities assessment such as FEMA, Failure, Modes and Effects Analysis. SWOT, Strength, Weaknesses, Opportunities and Threats, and PEST, Political, Economical, Social and Technological. Quantify the risks and opportunities associated with each off your business processes. Prioritize them based on their likelihood and impact of Akron's. Plan any organization changes accordingly. Support wise, consider identifying the hardware and software assets or infrastructure in the organization. This repository would be paramount while you determine improvement activities. Another valuable tip is to create a central database for all your monitoring and measuring resource is an example, is the calibration status of the equipment. Leverage databases to document the current calibration statuses, intervals, responsibilities etc. As you can imagine, organizations generate and acquire lot of knowledge over the years. Consider setting a framework to capture and processes knowledge. A few example tools are rapid learning curves, process work instructions or standard operating procedures of business manual etc. As with any documented information, consider implementing a robust version control process to control any changes, and ensure you have the most up to date information to dry decisions. Operation wise, be it a product or service, consider implementing a design and development process. This process should include its supplier, inputs, process steps, output and customers. Assigned metrics during every step of the process. Embrace the iOT to enable traceability throughout the supply chain. Identify the status off your outputs using monitoring and measurement tools, including data from sensors, manual entry, equipment, Accounting customer relationship management, et cetera. This traceability will help identify outputs in real time, such as if it is conforming output or not associated KPIs and gain visibility on analytics. Leverage the state architecture to identify and control non-conforming products or services. Take actions based on nonconfirmation nature. Which could be scrap, rework, weight grade, concession, etc.. Retain additional records of any corrections or corrective actions and of deep KPI's accordingly. As good business practice gauge customer satisfaction periodically using surveys, feedback of products and services, customer meetings, return materials etcetera. This data point is an excellent indicator of the degree to which we met or customer needs and expectations. Another useful tool is to conduct an internal audit off your data at planned intervals to ensure we're leveraging it to make decisions. This audit should also surface if you're effectively implementing and maintaining a data culture plan. Establish, implement and manage this data audit program, including the frequency methods, responsibilities, reporting, etc. Lastly, I'd highly encourage the senior management to review this whole business quality management infrastructure. Periodically, to ensure its continuing suitability, adequacy and effectiveness in making data driven decisions. Implementing this data driven system will generate a lot of opportunities for improvement. You can classify them into two parts. Continual and continuous improvement. Continual improvement improves the current business process for a better outcome. It is long term and conducted in phases. They improve a portion of your processes, measure and sustain it and execute the next improvement face. Continuous improvement is a subset or chain link in the continual improvement. It is short term and conducted in a constant straits old fashion. These are typically small wins and need to sustain over time
