Procurement analytics is the process of using data and analytics to develop meaningful insights into procurement processes, spend, performance, and risk. The appearance of digital procurement platforms and e-sourcing systems has brought about vast amounts of procurement data available to organizations.
Through analytics, they can identify the ones that will allow them to make major cost savings, process improvements, supplier risk reduction and overall procurement performance improvement. Here is the article that looks at some of the key gains that can be made through the appropriate application of analytics in procurement.
Enhanced visibility into spending
One of the most important, yet significant, advantages of procurement analytics is that it gives a clear picture of the spend. Through the process of the consolidation, cleansing, and categorization of the spend data coming from different sources like ERPs, e-invoicing, payment systems etc.
Analytics gives a single source of truth. Data visualization is the backbone of drill-downs that can be used to get deeper understanding of the spending patterns, maverick spend, tail spend distribution, seasonal variations, etc. This visibility is the foundation of identifying saving opportunities, rationalization of suppliers, and informing sourcing strategies.
Identification of savings opportunities
Analytics makes it possible to find cost-cutting options in both direct and indirect spend categories through its analysis. Through the use of historical spend data, price benchmarking, should-cost modelling, and other methods, a high-value savings opportunities can be pointed out. Such as predictive analytics that can be used to forecast future demand to obtain information on volume-based discounts for direct materials.
Besides the direct procurement categories, analytics can uncover opportunities like network optimization, load consolidation, etc. in the indirect categories. This prompts the procurement department to take specific actions such as consolidation of spend, strategic negotiations, etc. to achieve savings.
Supplier base optimization
Analytics can also enable optimization of the supplier base by providing clarity on spend concentration, supplier performance, risks, and segmenting best-in-class suppliers. Spend analysis will reveal instances of maverick buying and opportunities for supplier consolidation. Performance metrics derived through analytics help rate, rank, and differentiate suppliers.
Risk analysis provides insights into issues like single-source dependencies, the financial health of suppliers, etc. These inputs help procurement organizations rationalize their supplier ecosystem, avoiding both over- and under-utilization of suppliers.
Data-driven category management
Category management involves defining strategies for sourcing different spend categories. Analytics augments traditional category management processes with data-driven insights on spend clusters, pricing trends, market intelligence, etc.
This enables fact-based prioritization of categories, the identification of new sourcing mechanisms, and the development of category-specific procurement strategies for optimal value. Analytics also facilitates continuous monitoring to identify category shifts necessitating strategy changes.
Improved sourcing outcomes
Analytics boosts the outcomes of sourcing initiatives like RFPs, e-auctions, and strategic negotiations. Demand forecasting, price benchmarking, and market intelligence reports generated through analytics allow buyers to make sourcing decisions from a position of strength. Analytics also enables sourcing mechanics like should-cost modelling for negotiations and optimization algorithms to get the best bids in auctions. This improves the price, terms, and overall value derived from sourcing events.
Enhanced compliance
By providing spend visibility and analysing transaction-level data, analytics enables organizations to monitor procurement processes for compliance. Analytics can quickly highlight maverick or non-compliant spending compared to contracts and policies. Continuous monitoring and auditing of procurement activities is possible through analytics. This improves compliance, policy adherence, and adoption of preferred buying channels across the enterprise.
Improved supplier relationships
Analytics provides insights to improve relationships with strategic suppliers through fact-based performance reviews, collaboration on forecasting and planning, risk monitoring, etc. It enables a data-driven view of supplier performance on parameters like pricing, quality, delivery, etc., minimizing subjectivity. Joint forecasting, demand planning, and inventory optimization can also be enabled through analytical models. This leads to a mutually beneficial buyer-supplier relationship.
Enhanced agility
With the insights derived from analytics, procurement can sense and respond better to changes in the business environment. Trends in commodity prices, supply risks, changes in business demand, etc. can be continuously monitored through analytics models to balance cost, risk, and continuity of supply. Scenario analysis enables the assessment of optimal responses to various situations. This analytical agility makes procurement more proactive and responsive to dynamic business needs.
Promoting fact-based decision-making
Analytics brings objectivity to procurement by promoting data-driven decision-making. For example, supplier selection and contract awards can be biased by subjective factors like personal rapport, brand perception, etc.
Analytics provides objective data on pricing, performance, and total cost, which makes the overall process impartial. Dashboards also make procurement performance visible across the enterprise to multiple stakeholders. This transparency and fact-based decision-making enhance procurement’s credibility.
Boosting automation
Analytics also enables higher levels of automation in procurement processes, which can yield significant efficiency improvements. Through techniques like supervised learning, procurement tasks like purchase order creation, invoicing, and payments can be automated based on systems trained on historical data patterns.
Chatbots can handle supplier and stakeholder queries based on analytical insights. Cognitive automation yields productivity benefits by enabling procurement staff to focus on high-value decision-making.
Enabling continuous improvement
The insights from analytics provide input for the continuous improvement of policies, procedures, organizational structures, and skills in the procurement function. By benchmarking performance metrics like process cycle times, transaction touch points, and compliance levels, areas for improvement can be identified. Analytics provides an objective baseline to measure the impact of change initiatives. It enables regular monitoring of progress on improvement programs aimed at procurement excellence.
Improved cash flow management
Through analysing payment flows and current working capital requirements analytics can then help in the optimization of cash flows in the procurement process. Data on the extent of invoice processing time, dispute resolution, and delay can be used for improving payment cycles and terms. It will be ensured that procurement does not occupy more working capital and hence this will improve cash flow for the organization.
Conclusion
Digital supply chain analytics uses the digital data footprint of procurement to produce valuable information in the fields of expenditure, suppliers, performance, risks, and market dynamics. Employing models like predictive modelling, benchmarking, forecasting and optimization analytics enable the exposure of value delivery enhancement possibilities. It is used for decision making and guides automation to increase efficiency.
Through the use of analytics, managers are enabled to make decisions based on facts from procurement function which brings in sustained value and continuous improvement. With the expanding adoption of esourcing platforms, analytics is poised to disrupt traditional procurement and cement its position as an indispensable business capability.
