This guide outlines how businesses can use procurement analytics for profitable data-driven decision-making.

Procurement decisions are hugely important. A forward-looking approach is needed for businesses to minimise the risk of supply chain disruptions. This is particularly evident in the food industry, given how the market can fluctuate based on global agriculture, seasonal consumer trends and a dynamic regulatory environment. This guide will show how businesses such as food manufacturers and retailers can use analytics to make informed purchasing decisions that align with their needs and strategic priorities. 

What are some of the different types of procurement analysis? 

Procurement analytics allow for an overview of procurement from different perspectives. This type of holistic approach can give businesses confidence in their data-driven decision-making. 

  • Descriptive analytics helps us to see what has happened in procurement in the past. This was the traditional focus of procurement analysis.
  • Diagnostic analytics supplements descriptive insights by uncovering the reasons why certain things occurred with procurement in the past
  • Predictive analytics allows decision-makers to see trends and patterns and determine future performance.  
  • Prescriptive analytics shows likely future outcomes and makes recommendations, helping businesses to make smarter decisions.  

What types of metrics are used in procurement analytics? 

Supplier analytics 

This procurement metric covers a wide range of key performance indicators (KPIs) to determine whether suppliers are performing as promised when contracted. Positive indicators in the food industry include: 

  • The amount of procured inputs received within the required timeframe
  • The extent to which invoices reflect agreed prices and discount structures
  • A reduction in pricing disputes or mismanaged expectations about costs
  • High levels of compliance with risk assessments and audits to maintain regulatory requirements and minimise the risk of food fraud.
  • An increase in markers of quality such as ingredient quality and freshness, with only a negligible amount of goods considered defective or substandard 
  • Overall, a particular supplier compares well with others in terms of price, reliability, quality, and sustainability. 

Supplier performance in these areas indicates whether your business can save on procurement costs and boost efficiencies by focusing on relationships with existing suppliers or by choosing new ones.  

Spend analytics & cost per invoice 

Procurement costs involve much more than the price of goods purchased. Your employees’ time and other resources are employed in placing and tracking orders, receiving goods, performing administrative tasks and settling invoices.  

These expenses should remain within acceptable limits when compared with invoice totals. Maintaining a clear overview of where resources are being expended is particularly crucial for food industries such as manufacturing. This is because profit margins have traditionally been lower when compared to other industries.

The results of your analysis can point toward a need for your business to make things more efficient. For example, you might attempt to automate more resource-intensive invoice processing tasks. Alternatively, an unusually high cost per invoice may indicate that a costly procurement choice is open for reconsideration. Related metrics include procurement return on investment and emergency purchase ratios. 

Purchase order analytics 

Purchase order analytics allows your business to determine whether procurement aligns with internal policies and procedures and agreements with suppliers. For example, you can see if you have been paying more than necessary for goods. This could be because you are placing rush orders that don’t qualify for beneficial pricing or suppliers are not compliant with agreements.  

This data also indicates the time taken between order placement and delivery so that you can calculate the inventory level at which repeat orders must be placed. This helps you to optimise storage costs without the risk of stock shortages, which is particularly important in the food industry given the abundance of perishable stock. Analysis of purchase order data facilitates accurate forecasting and budgeting. It can also indicate opportunities for enhancing efficiency in procurement and financial planning.  

Payment term analytics 

Analysing payment terms and performance can reveal opportunities to negotiate favourable supplier agreements. For example, extended payment periods can enhance liquidity, and prompt payment can motivate suppliers to offer early settlement discounts. It also allows you to determine whether your payments align with supplier expectations and helps your business avoid penalties associated with late payments.  

Sustainability analytics 

By evaluating suppliers and their supply chains, it is possible to determine the sustainability profiles of the goods your company procures and how they impact your sustainable procurement targets. This could incorporate, for example, insights from animal welfare audits and questionnaires, as well as metrics related to environmental impact such as packaging consumption and food waste management.  

Supplier risk analytics 

By examining the risk profiles of individual suppliers, including product delivery consistency and adherence to standards such as HACCP, you can map out potential contingency plans for maintaining profits, regulatory compliance and customer satisfaction. 

Supply chain dependencies should also be examined. For example, reliance on a single source carries a high level of risk - particularly in the event of a safety breach or a product recall. Additionally, otherwise reliable suppliers may present risk owing to vulnerabilities in their own supply chains. Once you know what the risks are and where they lie, you can work to reduce them, but without data-driven risk analysis, it’s easy to miss crucial supplier vulnerabilities.  

What are the main benefits of procurement analytics? 

Cost savings & quality control  

Every business strives to enhance its profitability without compromising on quality. Use analytics to examine spending patterns and look for areas where your business might be able to save costs without compromising on product quality.  

Procurement analytics can also indicate areas where your business might improve its own efficiency and save costs. You may notice that there are errors in purchase orders that lead to an additional administrative burden or that there are rushed orders to rectify shortfalls.  

While taking advantage of opportunities uncovered in your procurement analytics results, you can measure the success of your strategies and optimise them based on ongoing analysis of historical data, current results, and market forecasts.   

Negotiations & improved supplier relations 

When negotiating contracts with suppliers, analytics can indicate where it would be reasonable to request more favourable terms. This could be achieved by comparing not only pricing but also contract and payment terms.  

As an illustration of how analytics might aid negotiations, you might notice that a supplier has fallen short in certain facets of an audit but outperforms in certain areas such as food safety and risk management. This could indicate an ideal opportunity for mutually beneficial negotiation. 

An analysis of your procurement patterns and trends further benefits supplier relations through collaborative planning. Your analytics offer information that you and your suppliers can use to plan for seasonal demand fluctuations, efficient deliveries, and quality enhancements.  

Manage supplier & market risks 

By using analytics to identify and assess supplier and market risks, you’re better able to prioritise areas where there’s a need for strong risk mitigation strategies. Trend analysis based on historical data can help you to identify emerging risks and address them before they become critical.    

Your analytics indicate the types and levels of risk you face - such as the risk of a product recall due to contamination. Use analytics to create models of specific scenarios and test them so that you can be prepared for any eventuality. As for the thinking that goes into this, prescriptive data analytics can even suggest possible risk reduction strategies and solutions for you to model.  

Addressing the challenges of procurement analytics 

Procurement analytics offers opportunities for continuous improvement on several fronts. Nevertheless, there are challenges to be alert for and to address if you encounter them. These include: 

Data quality challenges & integration issues 

Analytics are only as accurate as the data on which their conclusions are based. Inconsistencies can be introduced through incorrect data collection methods or a lack of uniformity in data formats. While there has been a push for data-driven decision-making across the food industry, if the data is low-quality certain choices can drastically impact supply chain management and product delivery. 

Your business can address this by implementing a data governance strategy. Define the required standards to be met and allocate responsibility for completeness and accuracy. Implement standardised formats, set validation and verification rules, use tools for data integration and cleaning and conduct regular audits.  

Although this sounds labour intensive, AI is capable of doing much of the legwork involved in evaluating datasets and preparing them for analysis. To achieve all this, your procurement analytics software must be chosen for compatibility and integration with data sources across your organisation.  

Accessing external data 

To deliver the best results possible, procurement data analytics should have access to data from external sources. This could include information on supplier compliance and sustainability, supply chain risks and market trends. 

It’s not an insurmountable challenge, but rising to it requires analytics software that can extract data from external sources without investing heavily in manual processes for capturing and gathering data. 

Skills gaps 

Your business may not have access to skilled data analysis professionals or have staff who are able to use analytical tools effectively. There are simple solutions, however. Choose a procurement data analytics provider who is willing to handle the technical aspects, offers user-friendly analytics software, and is willing to offer training, help and support when needed.  

Data security 

No matter what type of data you store and process, data security is a current issue that no business can afford to ignore. Although this challenge is not unique to procurement data, your organisation should ensure that it is stored and accessed securely with authorisations granted on a need-to-know basis. Procurement data is sensitive information, and unauthorised access could be used to perpetrate food fraud by falsifying information such as finished product specifications.  

Cost constraints 

The initial investment in analytics software is only one of the costs your business will incur. It may be necessary to implement additional changes. For example, a renewed focus on data governance may be needed, and employee training will be necessary.  

Nevertheless, the investment has a high potential for profit. McKinsey reports 10 to 40% growth in value delivery, better risk management, and accelerated innovation for businesses that implement procurement data analytics.  

What are the main types of data analysed for procurement? 

Spend data 

Spend data is the most obvious starting point. Expenditure, invoice and payment data are analysed, cross-referencing product categories and prices, indicating suppliers, and identifying the business units where expenditure occurred. 

Supplier data  

This includes supplier performance metrics like lead and delivery times, price, quality performance, and contractual compliance. Additionally, the financial stability and credit rating of supplier organisations goes toward evaluating risk. Other questions to consider include regulatory compliance and sustainability profiles.  

Contract data  

The terms under which you do business with suppliers form part of the analysis. For example, pricing and payment terms as well as any quality assurance clauses are of importance.  

Market & business environment data 

Procurement occurs within the broader market, and information on commodity prices and market trends inform most procurement decisions. Economic indicators help with forecasting, and benchmarking allows you to evaluate your purchasing performance. Much of the information needed to evaluate supplier risk owing to external factors falls under this category.  

Demand data & trend data 

Sales and consumption data contribute to procurement analytics by providing the information needed to forecast market demand and procurement needs. Trend data indicates whether your business should expect growth, consistent sales, or plan for reduced demand. That said, it is important to proactively identify new trends and patterns in consumer behaviour, especially those impacted by the launch of new products or an unforeseen demand for certain ingredients. 

Operational data & supplier relationship data 

The procurement cycle time is the time taken from order placement to delivery and payment. Additionally, the accuracy with which orders are fulfilled is of importance. A record of interactions with suppliers indicates the frequency and nature of interactions and can also form part of the analysis.  

Compliance & sustainability data 

For ethical and effective procurement, data analytics should incorporate metrics regarding suppliers’ regulatory compliance and ability to meet requirements for food safety, quality, traceability and sustainability. The need for this data also illustrates the importance of a clear audit trail across various facets of the supply chain. 

What are the main use cases of procurement analytics? 

Optimise spend, streamline purchasing decisions and forecast demand 

Using generative AI, it's possible to draw relevant data together for analysis, often without human intervention. Thanks to this technology, demand forecasts are more accurate than ever before. And, it’s possible to interrogate AI. For example, a procurement manager can ask analytics software to evaluate the spend on suppliers impacted by a geopolitical event or seek sources to replace a supplier who cannot meet demand. Standardised purchases, negotiations, and contract management activities can be automated, and a variety of sourcing scenarios can be simulated for testing purposes.  

Manage & evaluate external drivers of profitability 

Machine learning algorithms can examine market reports to identify patterns and pricing trends. When price volatility is present, procurement managers can determine what commodities should cost in the current market environment, using this information to choose new suppliers or negotiate with existing ones.  

At the same time, analytics make it possible to model a variety of scenarios that can help reduce the impact of price volatility on profits and suggest solutions. Apart from passing on costs to customers through price changes, one might consider using alternative inputs or adjusting stock levels to ride out volatility. In the longer term, you might decide to change your approach to supplier contracting, look for suppliers in different geographical regions, or consider strategic agreements with key suppliers including partial acquisition.  

Manage supplier performance 

From automating negotiation templates to contracts and routine emails, AI makes dealing with suppliers less labour intensive. You can also get up-to-date supplier performance reports, indicating where they deviate from your agreed KPIs. This allows for rapid intervention and improved collaboration with suppliers. The analysis extends to pricing since AI not only examines what commodities are costing you, but what they should cost.

Identify & manage supply chain risks 

The ongoing wars in the Ukraine and the Middle East continue to impact food prices and global food security. The food industry is directly impacted and this upheaval demonstrates why evaluating supply chain risks is so important, regardless of the industry you are in.  

Analytics can evaluate and predict supply chain risks such as this, and digital twinning allows you to prepare alternative sourcing scenarios and test them. You can set up virtual models that compare your current procurement to the results you’d achieve if you made changes to your procurement practices. Because your digital twinning exercise is theoretical, your exposure to risk is reduced. From its results, you would be able to see how implementing alternatives would impact operations and profits, and determine what new risks are associated with a hypothetical alternative.  

Planning based on real-time data and accurate predictions allows for timely reactions. It grants your business an opportunity to lead on products, pricing, distribution and sustainability despite changes in the procurement environment.  

Optimise sustainability 

For your products to be ethical, your supply chain must uphold the principles you support. The promotion of animal welfare, fair labour practices and the minimisation of negative environmental impacts begins with your procurement choices. Your procurement analytics offer the answers you’re looking for, providing sustainability metrics, monitoring progress, and helping you to meet your sustainability goals through informed procurement choices.  

Measuring the ROI of procurement analytics software 

With so many factors contributing to the potential ROI of procurement analytics software, your calculations would include short-term, direct benefits like efficiencies realised, labour saved, and acquiring better quality goods at lower prices. For a more holistic view, indirect savings like better decision-making, improved supplier relationships, reduced exposure to risk, and stronger strategic alignment can be difficult to quantify but are nonetheless significant.  

The ROI of procurement analytics varies, depending on factors ranging from the nature and size of your business to the analytics software you choose to use. At Foods Connected, companies can realise between 2 and 10% direct cost savings from using our intelligent procurement software. Our procurement analytics software includes: 

  • E-negotiations and contracts that enhance supplier relationships
  • Demand forecasting and order management systems to keep our clients’ procurement activities aligned with their needs
  • Open book supplier cost modules that offer data-driven cost management insights
  • Finished product cost models that allow our clients to see the cost makeup of their products

  • Measurements of market trends and sentiments that keep them informed and responsive, and forecasts that enable the development of proactive procurement strategies.  

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