Article Preview
Top1. Introduction
Over the last decade, Big Data and Supply Chain Management are key trends that have influenced the procurement process (Anderson & Rask, 2003). Procurement is the key driving function for strategic sourcing (Nair, Jayaram & Das 2015) (Barney 2012).
Furthermore, globalization through mergers and acquisitions, has led to supplier proliferation and, as the number of suppliers increase and become more complex, procurement requires elevated capabilities and advanced technologies to manage complexity and identify strategic levers gaining leverage in supplier negotiations.
Visibility of cost and spend analysis are key to find opportunities to reduce procurement costs. A detailed spend and contract analysis tends to reveal many opportunities that can lead to cost reduction.
This paper has the objective to discuss the business architecture required to collect, process and understand how a firm spends its funds on various goods and services to either manufacture and sell goods and services (i.e. direct spend) or to support its operations (i.e. indirect spend). This will be our starting point as without a clear understanding of where costs occur, cost reduction activities can become very limiting. We will then discuss the importance of process integration in order centralize, monitor and assess the impact of decisions from an end-to-end perspective.
The literature review will introduce emerging concepts in Computer Science (i.e. analytics, business-rules, etc.) and their adaptability to Procurement Operations. This paper’s contributions aim at expanding current technological breakthroughs to functional areas where impact has not been explored nor fully leveraged – in this case Procurement.
To achieving spend visibility, companies can profit from data mining technologies and business intelligence. Table 1 outlines some spend analytics, in the form on business intelligence organizations can perform to generate cost reduction opportunities. The greatest challenge many companies face today lies in their ability to aggregate data from different instances (i.e., ERP) and related systems (i.e... e-Procurement systems).
Table 1. Potential spend and contract analyses to generate cost-reduction insight
| Spend & Contract Analytics – Potential Analyses for Insight Generation |
| Spend by Supplier | Total spend by Business Unit |
| Spend by Category | Number of Stock Keeping Units (SKU) |
| Operational Spend (Open) | Number of SKU’s by Category |
| Capital Spend (Capex) | Average Invoice dollar amount by Category |
| Number of Invoices per year | Average invoice dollar amount by subcategory |
| Number of Invoices per supplier | Average dollar amount by purchase order (PO) |
| Number of transactions by category | Pareto Analysis (top suppliers representing a large percentage of the spend) |
| Year overview of spend history (aggregated) | Tail Spend Analysis (Large percentage of suppliers representing a low percentage of remaining spend) |
| % of spend purchased under contract | Days Payable Outstanding by supplier |
| Price by SKU | |