What are the best ways to analyze supplier performance data?

In logistics one of the key KPIs is on time performance. Of course you should also take SLAs and general service offering under consideration as well as if you have an aligned strategy with your supplier.

Antes de analisar os dados de desempenho dos fornecedores, é essencial ter clareza sobre o que esperamos alcan?ar e quais critérios s?o mais relevantes para nossa opera??o. Isso nos permite focar na coleta e organiza??o dos dados mais pertinentes, evitando dispers?o e garantindo que nossa análise seja direcionada e eficaz. Ao definir objetivos claros e critérios específicos, podemos avaliar o desempenho dos fornecedores de forma mais precisa e tomar decis?es embasadas para otimizar nossa cadeia de suprimentos.

To analyze supplier performance data effectively, start by defining your objectives and criteria. Determine what specific aspects of supplier performance you want to evaluate, such as on-time delivery, product quality, or cost-effectiveness. Establish clear metrics and benchmarks against which you will measure supplier performance to ensure alignment with your organization's goals and priorities.

Defining your objectives is a very important step that you should take. Since there are some common metrics in the industry, you have to define which metrics you have to measure to be fully aligned with the Company strategy and goals. What as I think you should avoid is wasting resources for industry-common metrics which have no value in the particular business model.

Identify and define the key metrics that are most relevant to your organization's goals and objectives. Common KPIs for supplier performance analysis include on-time delivery, quality of goods or services, lead times, cost savings, and responsiveness to issues or concerns.

Collecting and organizing your data is crucial for comprehensive supplier performance analysis. Gather relevant data points from various sources such as purchase orders, delivery records, quality control reports, and feedback from internal stakeholders. Organize this data systematically, ensuring it is accurate, complete, and up-to-date. Centralizing data in a structured format facilitates easier analysis and comparison across different suppliers and time periods.

The collection of crucial data may take work. You have to be sure that your data is accurate and complete; that's why automation brings much value here. Several solutions exist for organizing your data. In my experience, PowerBI is an efficient and flexible instrument for organizing and visualizing data.

Supplier and vendor are key to the success of your business, but as your network grows, managing it with multiple technologies can lead to in efficiencies. Five keys use cases that supplier can help solve, 1.automating the onboarding process 2.providing a simple location for communication and collaboration 3.empowing suppliers with self service capabilities 4.digitizing suppliers processes 5.monitoring and improving supplier performance

This can be the challenging part. From step one, you know what you want to measure and why. You also know where this information (or not) is available within your organisation. Any information not available can be collected in a survey questionnaire. Typically non conformance reporting, spend data and feedback from buyers are a great first step. You can use ‘pillars’ to visualise and organise your data feeds(e.g quality, customer service,innovation,speed to market, competitiveness,honesty and integrity etc). You can pick pillars that fit into 2 cores;feedback from internal teams and buyers around suppliers and the other; feedback from suppliers about your organisation. Also consider Ai tools to help both gather and analyse results.

Analyzing and visualizing supplier performance data allows you to uncover insights and trends that may not be immediately apparent. Utilize statistical techniques, such as variance analysis or trend analysis, to identify patterns and deviations in supplier performance metrics. Visual tools like charts, graphs, and dashboards can help you visualize the data effectively, making it easier to spot trends, anomalies, and areas for improvement.

As per my previous contribution, I used to work mainly (but not limited to) Power BI, especially when you need to visualize the data. Data analysis is a huge, complex process that you should be very cautious with. There are a lot of cases in worldwide corporations when the wrong interpretation of data causes big losses.

I think analyzing data after collecting data is the key element of performance measurement , particularly when it comes to supplier data and in the regard, professional competences of supply and procurements staff are vital for accurate and meaningful analysis , for analyzing data visualization and illustration it would be helpful remedy in order to attain our goal in performance measurement

Develop performance scorecards or dashboards that provide a visual representation of supplier performance metrics. These tools can help quickly identify trends, areas of improvement, and potential risks or issues.

Once you have collected all the relevant data (you need to be mindful of the original question) "why do you need to measure your supplier". You need to ensure that you have three clear types of data, the billing information, the delivering information and the customer systematic information (IE the order placed on the customer ERP before the carrier gets the data). With these three sources you can be sure to be able to provide amazing details. What you need to do is go beyond simply reporting what the data is telling you, it's what the data is not telling you that is important. Sure you can measure the usual suspects, OTIF, POD, Claims etc but can you tell if your customers ordering pattern means your DC is incorrectly located?

Once you have analyzed the supplier performance data, it's essential to interpret your findings and report them in a clear and actionable manner. Identify strengths and weaknesses in supplier performance relative to your objectives and criteria. Highlight areas where suppliers are excelling or underperforming, and provide recommendations for improvement or corrective action. Communicate your findings to relevant stakeholders, such as procurement teams or supplier managers, to facilitate informed decision-making and drive continuous improvement initiatives.

Collecting and visualizing the data is only the first step of the journey. Reporting and taking specific correcting actions seems to be a time-consuming process that you should pay attention to. It's extremely important to communicate your findings to stakeholders and launch enhancements.

Good communication and collaboration with your partners is essential. Once you have the data, once you have interpreted your data and once you have been able to evaluate all relevant information areas you can then begin to decide how to manage your supplier. I have been working with a reporting tool that has developed over the last 15 years which now enables us to provide the supplier with data and avoids them using their own statistics because they trust what we produce as it is one source of truth. Remember suppliers will give you a focused performance from their perspective not yours. If you have a baseline they trust then implementing change based on the agreement of the areas of concern (root causes) becomes a lot easier to implement.

In my experience the vast amount of data you collect in setting this up brings to life strategies and actions. Done correctly, you will have baseline scores for each pillar or segment of ratings. These can be blended to create targets. You now know ‘what good looks like’. Coaching suppliers becomes easier. Add these metrics to your category plans-different categories and even country of supplier may give different baselines. Make sure you always set targets. Doing this in the past I have seen high spend suppliers underperform against emerging or lower tiered vendors when viewing data. Focus in. Finally coaching is key. You can incentivise good and bad performers but you need structure. Feedback feedback feedback. You have the data!