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Elevating Your Procurement Organization from Knee-Jerk Reactions to Predictive Analytics

by Henner Schliebs | SAPinsider

October 1, 2011

Procurement analytics — which encompass traditional spend analytics and key procurement measures — provide the key to identifying areas of low performance, optimizing procurement functions, and reducing costs. But what's the best way to configure and deploy a procurement analytics program? This article will walk you through the 4-step process.

For most companies, the CPO’s list of top goals includes tasks like: maximize savings, focus on sustainability, manage supplier performance, and minimize supplier risk to ensure supply chain continuity. To do all this, CPOs are turning to procurement analytics.

The term “procurement analytics” encompasses traditional spend analytics, along with other key procurement measures, like supplier performance and risk and market trending. This discipline provides insight that helps identify areas of low performance, optimize procurement functions, and reduce costs (see sidebar).

Benchmark findings prove that a 5% reduction in spending can drive upwards of a 45% increase in net income,1 and migrating to automated spend analytics can capture a 30% higher rate of cost savings, a 27% higher rate of spend under management, and a 10% increase in contract compliance over peers that use manual processes.2

To start reaping these rewards, we’ll walk through a four-step process to help you deploy and configure a procurement analytics program.

Step #1: Aggregate Procurement Data

Today, your relevant data likely resides in disparate systems and formats across one or more ERP systems, in data warehouses and data marts, and on servers across your enterprise, for example. To truly analyze your spending and procurement performance, you need to deploy a solution that automates and facilitates data extraction, transformation, and load (ETL) processes from your internal sources, as well as from third-party data providers, RSS feeds, and web services. The best-case scenario is a native integration that helps avoid the traps of costly and error-prone interface development and maintenance.

Once all relevant spend data is in a single, structured environment, you next need to ensure that you are basing your analyses on valid data by addressing the issue of data quality and reliability.

Step #2: Ensure Data Reliability

Consider some of the factors that contribute to unreliable procurement data: Data may be incomplete, spend categories may not be fully defined, or the linkages between suppliers may not be identified. If these scenarios sound familiar, you are likely missing significant opportunities to make informed decisions.

To realize the full potential of procurement analytics, you must incorporate data quality and reliability into your data transformation process. A good way to start is to leverage packaged services to cleanse, classify, and enrich your transaction data. Experts in your organization can also work with those from your service provider to ensure accurate data classifications on the first pass. Thereafter, internal data stewards can monitor the now automated process.

By choosing an analytics solution that supports streamlined workflows and intuitive user interfaces, you can readily manage the transformation of your raw data into enriched, actionable, and properly classified information to drive your procurement initiatives. But before you start applying analytics to this information, you must make sure that your key systems and processes are available for analysis.

Step #3: Incorporate Sourcing, Contract Management, and Operational Procurement in Your Spend Analysis

Integrating your sourcing, contract lifecycle management, and operational procurement processes and systems with your procurement analytics functionality is critical to realize savings. To enable effective analytics, you need a solution that allows you to monitor supplier performance and spending against supplier contracts to ensure compliance. The right solution can also feed everyday operational measures, such as percentage of on-time delivery and volume of back orders, into your analytics engine and automatically measure this data against KPIs. Dashboard reporting and alerts can then provide immediate notifications when suppliers fall out of tolerance, allowing for prompt intervention.

Market-leading analytics software systems provide these capabilities by integrating sourcing, contract lifecycle management, and operational procurement systems as part of their core functionality so that, when it’s time to consider a contract renewal or reevaluate a spend category, you can make your decision from a fully informed, data-rich position.

With a solid data foundation and aligned processes and systems, you’re ready to put analytics to work in your organization. But not all analytics solutions are created equal — so be sure you’re using the right kind.

Step #4: Move Ahead of the Curve with Predictive Analytics

All too often, we look behind us to define the road ahead, and we miss the warning signs of potential issues. When a tragic earthquake struck Japan, for example, US automotive manufacturers reported steep profit losses because they relied on analysis of historical data for their procurement planning rather than real-time and multi-tier information. If those manufacturers were alerted that their tier-1 suppliers were sourcing goods from tier-2 suppliers in Japan, they could have secured new supply channels and avoided millions in lost revenue.

To help avoid such scenarios, emerging technologies are introducing innovative ways to gain greater insights into world events, market activities, and supplier performance that can empower your organization with predictive, forward-looking analytics. These solutions aggregate collective intelligence from industry peers’ systems and market research sources across key industries and supply bases. Incorporating these powerful data points into your procurement analytics can expose potential risks in your daily operations and your supply base, positioning you to proactively mitigate potential issues.

Real analytics start with the future. Analysis and performance management are key, but analytical decision support with predictive and simulative approaches catapults you from knee-jerk reactions to a competitive advantage.

Achieve Your Procurement Analytics Goals with SAP Solutions

A fully integrated source-to-pay and procurement analytics environment is key to driving more spend under management — the ultimate measure of procurement success. SAP Business­Objects Spend Performance Management, SAP Business-Objects Data Enrichment and Classification OnDemand, and SAP Supplier InfoNet cover the spectrum of data optimization, spend management, and predictive supplier analytics. Tightly coupled with SAP’s procurement portfolio, these solutions empower organizations of all sizes with the strategic tools to turn procurement analytics into a competitive advantage. For more information, visit

Henner Schliebs ( is a Global Director of Business Analytics Solutions Marketing at SAP. In this role, Henner contributes to the strategic direction and market awareness of the analytic applications portfolio to ensure customer value and business growth.

1 ASUG and SAP Benchmarking and Best Practices 2011 report. [back]

2 Aberdeen Group, “Unearthing the True Value of Spend Analysis” (2010). [back]

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