The Important Role and Process of Procurement Analytics

The Important Role and Process of Procurement Analytics

Any company that focuses on manufacturing business operations (lean manufacturing or direct manufacturing) will certainly manage the procurement process by purchasing certain raw materials, goods, or services. However, before that, the company must carry out a series of business analysis procedures in terms of procurement which is commonly called procurement analytics.

This practice is very important in efforts to manage the company’s supply chain or supply chain management where business owners and stakeholders are involved in several steps of market analysis and strategic business management (strategic management) to streamline the company’s team workflow (workflow management).

Thus, the process of business analytics in terms of procurement can help companies gain a more realistic and holistic perspective on their business operational expenses (business costs). As well as at the same time being able to improve their business strategy approach to decision-making in all procurement procedures.

However, procurement analytics is not a one-time process but must be implemented and monitored continuously. Thus, companies will later have alternatives to manage business processes (business process management) and understand exactly what business competitiveness is like in their industry niche.

What is Procurement Analytics

What is Procurement Analytics?

Adapting from the Analytics Steps site page, procurement analytics is the process of identifying, collecting, compiling, reporting, and analyzing procurement information for the purpose of making business decisions.

This concept first appeared due to the increasing demand for business operational management (demand management) in forming a consolidated, impartial, accurate, timely, and realistic perspective on expenses.

As a result, in implementing procurement analytics, companies only need to extract budget data and statistics, purchase history, and expense reports which consist of the company’s cash flow to suppliers or vendors. Where this analytics requires an end-to-end process to analyze (data analysis), divide, perfect (data wrangling), and enrich data (data enrichment) which will add business value (brand value).

That way, companies can optimize total fixed costs and increase business operational expenses to make the right purchasing decisions. Where these conditions make the procurement analytics process better than data visualization.

Kinds of Procurement Analytics Process

Procurement analytics generally requires data collection procedures (data mining) that use a variety of internal and external sources, ranging from:

  • Enterprise resource planning (ERP) and financial modeling systems.
  • Invoice and purchase order management software.
  • Platform customer relationship management (CRM) dan vendor relationship management (VRM). 
  • External information regarding companies and suppliers.
  • Procurement benchmarking service.
  • Sistem competitive intelligence.

With these data, the procurement team will run several business data analysis techniques. Among others are:

1. Descriptive Analytics

Descriptive analytics or descriptive analysis is the initial stage in data analysis which is useful for providing a complete description or picture of data based on variables that have been collected in the past to improve procurement prospects in the future (demand forecasting). For example, a company’s procurement management team analyzes procurement expenditures to determine historical purchase costs for a particular vendor.

Generally, the results of the descriptive analysis can be displayed in the form of frequency distribution tables, mean values, histogram tables, standard deviation values, and so on. Later, the results of this analysis will provide a summary of data that the company can process into useful information for business procurement.

2. Diagnostic Analytics

The concept of diagnostic analytics or diagnostic analysis is almost the same as descriptive analysis. However, diagnostic analysis is specifically meant to explain “why something might have happened in the past”.

For example, if the descriptive analysis identifies product price increases or price skimming in the past. The diagnostic analysis then helps the procurement management team understand why or why the price increase occurred. Then, the company may be able to overcome these problems to change the pricing policy (pricing strategy).

3. Predictive Analytics

Launching from Investopedia, predictive analysis or predictive analytics is a form of advanced analytics that uses current data and historical data to estimate business performance, behavior, and business trends in the future (business forecasting).

Generally, the predictive analytics process will also combine historical data with statistical modeling, data mining techniques, machine learning, deep learning algorithms, and even artificial intelligence (AI). Thus, this form of analysis will answer the question “What might happen in the future?”.

For example, trends in customer purchase history can be used by company management to understand buying cycles or patterns of repeat purchases in the future. This information will be useful in visualizing pricing strategies, including reasonable price bargaining points or thresholds.

4. Prescriptive Analytics

The analysis stage in procurement analytics is a prescriptive analysis or the process of making business procurement decisions based on the analysis of information from raw data. That is, prescriptive analysis assists companies in analyzing data and provides suggestions on the best course of action that companies should take in certain scenarios.

In the concept of procurement analysis, this stage will use patterns from data collected from various sources (data warehouse). Then, companies need to carry out data mining and data visualization to study targeted procurement management. So, the company can find the best solution or step that will benefit the company based on CBA (cost-benefit analysis).

The Important Role of Procurement Analytics

Based on the explanations above, it can be seen that the procurement analytics process is not only related to the amount of organizational expenditure. But it also deals with everything that includes demand generation, purchase orders, category management, contract management, and business compliance.

Procurement analysis is an end-to-end process to create a robust procurement platform and align procurement activities to create efficient procurement. Therefore, procurement analytics will bring benefits in terms the following of:

  • Help category management transform and revolutionize enterprise projects (project management).
  • Enables category managers to facilitate innovation, develop relationships with vendors, address risks in the supply chain, and increase visibility in product category utilization (product classification).
  • Providessentialant data to classify, compare and report supplier output results (data mapping).
  • Facilitates contract lifecycle management as procurement analysis can provide data and notifications about when contracts should be signed.
  • Help uncover issues, trends, and patterns in environmental and corporate social responsibility.
  • Facilitate the process of identification (risk analysis) and prevention of all business risks (risk management).

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