Assessment of Your Supply Chain Analytics Programme

A structured approach to assessing the maturity of your own supply chain analytics and its impact on the relationship with stakeholders.


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When assessing your analytics, the key question is always what kind of data should you collect and how should you use it. This video introduces four approaches to analytics and provides examples to help you.

Most, if not all, of your analytics may be thought of as descriptive. That is it describes what has happened - in the past. In today’s uncertain and fast changing world however, Procurement should also include appropriate diagnostic analytics to help understand why the data is as it is; predictive analytics to guide you on what might happen in the future and prescriptive analytics to guide you on what to do to improve performance. This video will describe a comprehensive framework of supply chain analytics and help you decide what kind of analytics might be suitable for your reports and data.



Supply chain analytics is a powerful tool to help you manage your work and to help improve performance and relationships with your internal stakeholders. Data analysis can be understood as the process of examining data to draw conclusions for future actions. Data analytics can, for example, help to improve suppliers’ performance, reduce supply chain risks and help you respond more quickly to internal and external changes.

Both quantitative and qualitative data needs to be considered in a balanced programme. A quantitative data analysis focuses on numerical data with quantifiable variables that can be compared or measured statistically. Typical examples for this would be spend reports, savings performance and supplier performance measurements. A qualitative data analysis is more interpretive. It focuses on the understanding of non-numerical data like surveys or other feedback from internal and external stakeholders.

There are four types of supply chain analytics:

1. Descriptive analytics

Descriptive analytics tells you what happened in the past. How did a supplier perform in the last weeks or how has the exchange rate fluctuated over the past week?

2. Diagnostic analytics

Diagnostic analytics interprets the historic data to help you understand why something happened. For example, why a developed sourcing strategy didn’t work out as expected.

3. Predictive analytics

Predictive analytics provides guidance on what might happen next as a result of a given set of circumstances or performance. For example, what will happen to commodity prices or the price of labour?

4. Prescriptive analytics

Prescriptive analytics guides us on what to do next. Do we buy a scarce commodity ahead or book more air freight capacity?

Procurement cannot rely on Descriptive or Diagnostic analytics alone. We also need to be prepared to manage future events and incidents. A well thought out analytics programme which not only looks backwards with Descriptive and Diagnostic analytics but also includes Predictive and Prescriptive analytics is an essential tool to drive improved Procurement performance and increase stakeholder satisfaction.

Faculty name: Eric Larson
Duration: 17:49 Min.
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