From Spend Analysis to Supplier Performance with Data Analytics

Dariusz Pielach
procurement analytics solutions

This article is the second in our series on how modern data analytics can provide procurement professionals solutions with insights into their operations.

In the first article, we covered spend analysis. One of the most important reasons organizations analyze their spend is so that they can accurately rank suppliers by spend allocated to different categories, materials, products and services delivered, as well as by the manufacturing sites that the suppliers deliver to.

With good spend analysis data, an organization can clearly see how important each supplier is and focus supplier performance monitoring accordingly. But this is only a starting point. To build a solid analytical foundation for supplier relationship management (SRM) processes – which in turn support risk and cost management processes – data on spend and supplier performance from all relevant sites or locations should be unified and integrated. Proper analysis of this data creates enormous opportunities.

Every company has different strategies and objectives for its supplier performance management program. No company, therefore, measures and monitors data in the exact same way. One thing most companies do share, however, is the challenge with extracting and integrating loads of data from numerous disparate data sources.

There are many ways to measure supplier performance, but the three main data-abundant dimensions are quality, service, and competitiveness. Let us look at each one in terms of data and its sources:

  • Quality is a crucial supplier performance measurement dimension. It can help an enterprise detect, estimate, or avoid potential costly damages caused by returns or defects.
    Here, the fundamental thing to measure is delivery quality. Depending on the industry, there are about thirty different metrics used for this purpose, but not all of them can be tracked in ERP systems when registering the receipt of goods. Some records, e.g. regarding claims or corrective actions, are often kept in separate files. Moreover, ERP systems often restrict the variety of formulas able to be used to measure the quality of goods or services received. Different ERP systems often use different approaches to track these metrics depending on the system’s version, location, and way of implementation. All this variety often complicates the comparison and analysis of supplier quality data.
  • Service is another dimension in which suppliers are typically measured. An ERP is often the key data source. Analysts can extract data about Lead Times calculated based on purchase orders (PO) and Goods Received timing data as well as track supplier reliability using On-Time Delivery (OTD) metrics.
    This is a standard approach, but tracking service quality has historically been challenging due to the same factors mentioned earlier regarding supplier quality. Also, today’s procurement professionals increasingly wish to enhance their supplier service measurement systems by including metrics on supplier availability, flexibility, and resilience. That often means collecting and managing more data only partially available in databases powering ERP systems.
  • Competitiveness is just as important as quality and service. Understanding supplier competitiveness can help a company identify good opportunities and stay on track with market changes, offerings, and prices. Achieving good visibility of supplier competitiveness requires processing data on internal and external benchmarks. Analyzing internal benchmarks can help procurement professionals analyze spend, especially with a focus on prices and payment terms.

Here the challenges are similar to those encountered when tracking quality and service. Data from multiple sources, e.g. ERP systems and procurement platforms, must be managed. This data is often structured in different ways and written in various languages and alphabets. Prices are often expressed in different currencies and payment terms are not always defined in the same way. Adding benchmarking data from external sources (if available) and additional integration with should-cost analysis are possible only with modern data analytics technologies.

Clearly, measuring and reporting supplier performance on a daily basis involves a great deal of data of different types from multiple sources. Is it possible to turn it all into readable and easy-to-analyze business reports?

YES!

Thanks to the development of modern, cloud-based data management and business reporting technologies, supplier performance can be measured and reported so as to meet the needs of procurement professionals.

Today, companies have the opportunity to implement comprehensive, automated management dashboards with integrated real-time supplier performance data that supports highly effective supplier relationship management.

Thanks to this technology, professionals procurement analytics solutions have a range of new capabilities, including:

  • Monitoring integrated supplier performance in all locations
  • Communicating indicators to suppliers in real-time
  • Instantly responding to alerts and notifications of drops in supplier performance
  • Observing trends and making projections
  • Monitoring up-to-date results of long-term and short-term supplier performance improvement initiatives (including internal and collaborative ones)

The benefits for supplier relationship management cannot be overestimated.

Stay tuned for our next article on how modern procurement analytics solutions help with risk management.

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Dariusz Pielach
Procurement Analytics Subject Matter Expert

Procurement expert with extensive experience in management consulting (including big4). Dariusz managed a number of strategic sourcing projects as well as transformations of procurement organizations along with deployment of e-procurement solutions and optimization of P2P processes for companies in manufacturing, banking, and energy sectors. Currently responsible for the development of Procurement Analytics business line and providing procurement expertise to data science, data management, and business reporting projects.

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