Regression Analysis in Procurement

Regression Analysis in Procurement

Few days ago I came across this terminology called Regression Analysis and I was wondering to know how it can be used in data analysis useful for negotiation or deciding strategy for Procurement.

Few people in Procurement fraternity including me always gets scared when such heavy words like regression analysis is used in conversation or decision making and always believe that this terminology is not for procurement and may be used by data science people or people in Manufacturing industry.

My curiosity pushed me to understand where this type of analysis can be used in Procurement. I believe few large procurement organization must be using it for their key analysis as a technique.

So here are my views about Regression analysis and it’s usage in Procurement domain. I have used few of google definitions and wordings as it is to express my views.

Regression analysis is?a statistical method that shows the relationship between two or more variables. Usually it is expressed in a graph. This gives us the relationship between a dependent variable against independent variables. Typically, the independent variable(s) changes with the dependent variable(s) and the regression analysis attempts to answer which factors matter most to that change.

Formulating a regression analysis?helps you predict the effects of the independent variable on the dependent one.?

The main uses of regression analysis are?forecasting, time series modelling and finding the cause and effect relationship between variables.

We know that most of time we need to make data driven decisions in Procurement and in other domain too, but when there’s literally millions, or trillions of data points, where do you even begin?

Fortunately, artificial intelligence (AI) and?machine learning?(ML) can take enormous amounts of data and analyze it in a matter of hours to make it more digestible. It is then up to the analyst to examine the relationship more closely.

In the current era of globalization, global procurement and supply chain management have become critical operations. They require quick solutions and enhanced decision-making while handling large and complex data.

The regression analysis (Linear Performance Pricing) technique can be applied in situations where a combination of product variants, manufacturing volumes, and price points present themselves, for each of which large data is available.

These situations could arise due to various scenarios and factors, such as part characteristics, globally diverse operating units, supply chain management complexities related to multiple vendors, and price points thereof.

In the regression analysis applied to this scenario, a mathematical equation between cost-affecting parameters and the price of the parts is established.?

Sometimes, procurement and its extended cross-functional team will not have enough knowledge or power over suppliers to build a detailed bottom-up cost model as described under cost-based price modelling.

Many suppliers will not be willing to provide a cost breakdown, or they will manipulate the data. In addition, the procurement team may be under time constraints to negotiate a final price and may not have enough time to develop a detailed model. In this case, cost -regression analysis is the right method because it uses data that already exists within the company to assess suppliers' cost positions.

Procurement will typically have access to two sets of information about each part or service:

• Commercial data such as price, volume rebates, and delivery and payment terms
• Specifications for parts (technical parameters such as weight, volume, material type, tolerances, and other technical parameters that define the part) or services (element of service level agreements, such as frequency, scope, technical knowledge, and the capability level of the people delivering the service)

This data can often be found in past requests for proposals. A method is needed to help understand the dependency of the price from the respective (mostly technical) specifications. Cost-regression uses statistical tool regression analysis to help estimate the relationship between many variables. In particular, it describes how the dependent variable—the price (p) —will change when the independent variables—the specifications (x) —change.

For application in daily procurement practice, need to verify the availability of the data within the organization upfront. Procurement usually has all commercial data, including prices, supplier names, and volumes etc from the ERP systems. Nonetheless, technical specifications often need to be collected from the user department in a structured format. The team will have to evaluate how much effort will be required to collect these parameters.?

Regression analysis is done in four phases.

1. First phase: beginning with collecting and preparing data. In this phase, it is essential to define the right set of parameters that are expected to drive costs.?The collected data needs to be checked for completeness and plausibility, and qualitative information has to be quantified.
2. Second Phase: During the second phase, the regression model will be built and tested for its statistical relevance. In several iterations, the model will be adjusted to optimize the quality of the regression by potentially removing parameters that show mutual dependencies (such as weight and density or volume), and linearizing some parameters to better fit the linear regression model.?
3. Third Phase:?After the model has been optimized, the results will be validated within procurement and with engineering or other departments that provided technical parameters. Here, outliers will be discussed to understand a potential rationale and see if any parameters have been omitted that should instead be included to explain the difference.
4. Final Phase: Finally, data will be extracted from the model to aggregate the results and prepare a negotiation strategy. Renegotiating with suppliers based on target price identification is the ultimate aim of the cost-regression analysis within procurement.?

With this model, procurement can quickly analyze the cost position of a particular supplier or of selected parts and identify opportunities to reduce costs.?

Having said that in the agile era where everything is quickly required, we hardly get time to collate the data to analyze it whether thru regression analysis or any other tool for that matter.

During dealing for any large requirement, if Procurement has to really bring value to the table, it’s imperative to say that they should be given sufficient time to understand, study/analyze the data with all available resources to derive right proposal for the deal of the company.