Top 5 ways analytics optimize the procurement process

17 June 2024 By Heidi Humphries

Procurement analytics in manufacturing is a critical area that leverages data analysis to optimize various aspects of the procurement process, including cost reduction, process efficiency, supplier performance, inventory management and risk mitigation. This article aims to provide procurement leaders with insights into what procurement analytics are and how they can be best utilized to enhance the procurement process in manufacturing.

1 - Procurement analytics reduces costs

Procurement analytics play a pivotal role in identifying cost-saving opportunities by analyzing spending patterns, supplier pricing and contract terms. By leveraging data, procurement teams can negotiate better deals, identify alternative suppliers offering competitive pricing, or switch to more cost-effective materials without compromising quality. This strategic approach to spending can significantly reduce procurement costs and improve the bottom line.

For instance, procurement spend analytics can help organizations understand their spend data from internal or external sources, enabling them to identify savings opportunities and measure the impact of savings projects on the financial bottom line. A real world example of this was when we helped one industrial products manufacturer save 16% on their tail end spend items.

2 - Procurement analytics improve process efficiency

Analyzing procurement processes through data can highlight inefficiencies and bottlenecks within the procurement cycle. For instance, procurement analytics can identify delays in the approval process, inefficiencies in purchase order processing, or repetitive tasks that could be automated.

By streamlining these processes, organizations can reduce cycle times, improve responsiveness, and enhance overall procurement efficiency. The integration of AI and Robotic Process Automation (RPA) into Procure-to-pay (P2P) and, even better, Source-to-pay (S2P) systems, is revolutionizing procurement by automating manual tasks such as requisitioning, purchase orders, invoice processing and supplier onboarding, thus freeing up procurement professionals to focus on more strategic initiatives.

3 - Procurement analytics boosts supplier performance

Maintaining a high-performing supplier base is crucial for manufacturing success. Procurement analytics enables organizations to monitor and evaluate supplier performance based on various criteria such as delivery times, quality of goods, compliance with contracts and responsiveness.

This data-driven approach allows procurement leaders to make informed decisions about which suppliers to continue working with, which to develop further, and which to phase out. Supplier analytics can provide insights into individual suppliers’ performance, risk, sustainability and diversity.

4 - Procurement analytics optimizes inventory management

Effective inventory management is essential to avoid overstocking or stockouts, both of which can be costly for manufacturing companies. Procurement analytics can forecast demand more accurately, optimize reorder points and determine optimal inventory levels for different products. This ensures that the right amount of inventory is available when needed, reducing holding costs and minimizing the risk of production delays. Demand forecasting, leveraging historical data or machine learning techniques, can help predict consumer demand and optimize inventory levels.

5 - Procurement risk mitigation

In today's volatile market, managing procurement risks is more important than ever. Procurement analytics can identify potential risks in the supply chain, such as supplier financial instability, geopolitical risks affecting supply routes, or the risk of material shortages.

By analyzing these risks, procurement teams can develop strategies to mitigate them, such as diversifying the supplier base, increasing inventory levels for critical components, or establishing contingency plans for supply chain disruptions. Supplier risk analytics can help identify and act on external risk factors that negatively impact the supply chain.

Implementing procurement analytics

To effectively implement procurement analytics, manufacturing companies should consider the following four steps:

Data collection and integration: Collect and integrate data from various sources, including ERP systems, supplier databases and market data. Ensuring data consistency and accuracy is crucial for reliable analysis.
Analytics tools and technologies: Invest in analytics tools and technologies that can process large volumes of data and provide actionable insights. Skills in Excel, Python, or R for data analysis, as well as knowledge in statistical methods, are beneficial. AI-powered tools can enhance spend analytics and benchmarking, providing quick and actionable market insights.
Cross-functional collaboration: Foster collaboration between procurement, finance, operations, and IT departments to ensure a holistic approach to data analysis and decision-making. This collaboration can help in leveraging diverse datasets for comprehensive insights. This is a critical skill needed from today’s procurement leader, allowing them to position themselves as trusted advisors and value creators, ensuring procurement's voice is heard in critical decision-making processes.
Continuous improvement: Use insights gained from analytics to continuously improve procurement processes, supplier relationships and inventory management practices. Regularly updating and refining analytics strategies can help maintain efficiency and effectiveness in procurement operations.

Key metrics for leveraging procurement analytics in 2024

To effectively leverage procurement analytics, procurement leaders should focus on implementing a range of key performance indicators (KPIs) and metrics that provide comprehensive insights into their procurement processes. Here are the essential metrics to consider:

Spend under management: This metric measures the portion of an organization's total spend that is actively managed by the procurement team. Increasing this percentage can lead to significant cost savings and better control over procurement activities.
Supplier performance scorecard: A comprehensive assessment of suppliers' performance based on criteria such as quality, delivery speed, compliance and responsiveness. This helps in maintaining high-performing supplier bases and making informed decisions about supplier relationships.
Contract compliance rate: This metric indicates the percentage of purchases made under existing contracts, reflecting the procurement team's adherence to guidelines and procedures. High compliance rates ensure better control over procurement activities and cost savings.
Procurement ROI: Procurement Return on Investment (ROI) measures the cost savings from procurement activities relative to the cost of those activities. This metric highlights the effectiveness of procurement strategies and their impact on the organization's bottom line.
Purchase Order cycle time: This KPI tracks the time taken from creating a purchase order to receiving the goods. Shorter cycle times contribute to more efficient operations and faster response rates, enhancing overall procurement efficiency.
Cost of Purchase Order (CPO): This metric reflects the total expenses incurred in processing each purchase order. Reducing these costs through automation and better vendor management practices can significantly lower operational expenses.
Maverick spend: Maverick spending refers to purchases made outside of established procurement procedures. Monitoring and reducing maverick spend helps in maintaining control over procurement activities and reducing unnecessary costs.
Total Cost of Ownership (TCO): TCO analysis assesses all associated costs throughout the lifecycle of a product or service, not just the purchase price. This comprehensive view helps in making procurement decisions that impact long-term profitability.
Inventory carrying costs: This metric includes all expenses related to storing inventory, such as warehouse rent, salaries and losses due to theft or natural calamities. Optimizing inventory levels while keeping carrying costs low is crucial for efficient inventory management.
Supplier defect rate: This KPI measures the frequency of defects in goods supplied by vendors. A lower defect rate indicates higher supplier quality and reliability, which is essential for maintaining smooth operations.
On-time delivery performance: This metric tracks the percentage of orders delivered on time by suppliers. High on-time delivery rates are critical for maintaining production schedules and meeting customer demands.
Savings achieved: This KPI measures the cost savings achieved through procurement activities, such as negotiating better deals or finding more cost-effective suppliers. It is a direct indicator of the procurement team's effectiveness in reducing costs.
Procure-to-Pay cycle efficiency: This metric evaluates the efficiency of the entire procure-to-pay process, from purchase requisition to payment. Streamlining this cycle through digital solutions can enhance accuracy and reduce processing times.
Supplier availability: This KPI measures the availability of suppliers to meet the organization's needs. High supplier availability ensures that procurement activities are not disrupted due to supplier shortages.
Spend vs. budget: This operational KPI compares the budgeted procurement costs with the actual spend. A smaller gap indicates higher accuracy in budgeting and better financial control.

By implementing these metrics, procurement leaders can gain valuable insights into their procurement processes, identify areas for improvement and make data-driven decisions that enhance efficiency, reduce costs and improve supplier performance.

The biggest hurdles to implementing procurement analytics

Data quality and integration

Challenge: Poor data quality and integration issues are major hurdles. Inaccurate, incomplete, or inconsistent data can lead to flawed insights and poor decision-making. Data is often scattered across multiple systems, making it difficult to consolidate and analyze effectively. Furthermore, procurement tends to only look at spend data, which is a mistake.

According to McKinsey, “To generate true, actionable insights, it is crucial to develop a single source of truth that incorporates all sources of relevant data, along the entire supply chain, and from all relevant functions—including sales, finance, product development, R&D, and operations When these sources are not linked to each other, executives are hard-pressed to form an accurate understanding of the entire data situation.”

Strategy:

Data cleansing: Regularly clean and standardize data to ensure accuracy and completeness.
Integration tools: Use advanced integration tools to consolidate data from various sources into a single, unified system.
Data governance: Implement strong data governance policies to maintain data quality and consistency across the organization.

Choosing the right technology

Challenge: Selecting the appropriate procurement analytics tools that fit the organization’s needs can be daunting. The wrong choice can lead to sub-par outcomes and wasted resources.

Strategy:

Needs assessment: Conduct a thorough needs assessment to understand the specific requirements of the organization.
Vendor evaluation: Evaluate multiple vendors and solutions through demonstrations and trials to ensure alignment with organizational needs.
IT partnership: Involve the IT department early in the process to facilitate smooth integration and address technical challenges.

Customizing data analysis

Challenge: Customizing data analysis to generate meaningful insights requires specialized skills and knowledge, which may be lacking in the procurement team.

Strategy:

Hiring data experts: Hire data analysts or data scientists to handle complex data analysis.
Training procurement professionals: Train procurement professionals in basic data analysis skills and tools to bridge the gap between procurement and data analysis. This is the new procurement function - upskilling will be the only way forward.

In conclusion, procurement analytics offers a powerful tool for manufacturing companies to optimize their procurement processes, reduce costs, improve efficiency, manage suppliers effectively and mitigate risks. By leveraging data-driven insights, procurement leaders can make informed decisions that contribute to the overall success and competitiveness of their organizations.

If you’re exploring procurement analytics options, check out how we can help or chat with the DSSI team for more information.