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Evolution of Spend Analysis and the Rise of Big Data: Part 1

Spend Analysis and the Rise of Big Data
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Spend analysis for an organization has always attracted attention of the top management as it directly has an impact on the productivity of the organization, cost of finished product, quality of product/services and competitiveness of the organization.

Starting today, we will embark on journey that will cover many facets of Spend analysis and big data.

The business model has changed to a global model. Although globalization of the business has opened up new opportunities for greater sales and increasing the profits of the companies, it has also brought in many challenges not experienced earlier.

The most potential area yet to be tapped to increase profits or to remain competitive is Spend analysis. Spend analysis encompasses all the possible activities where savings could be effected. Each activity is examined to see: Where are the possibilities of making savings? And, what should be done to improve the savings? Spend analysis comprise three core areas: the process, analysis and visibility.

Let’s look at the evolution of Spend analysis.

Procurement spend analysis is not a very old concept. Till 1980, the concept was not known to the business. The practice in procurement decision making was to favor the firm with lowest quotation. In many cases, initially it was felt that company has negotiated an excellent deal but soon it was realized that there are many areas where adequate visibility was not there and money was drained through various hidden costs which did not form part of the deal. The results were not encouraging and beneficial.

The shift from this was seen in 1980 with the initiatives taken by automotive industry in US, especially by General Motors (GM) and Ford in applying spend analysis in key commodities. The approach adopted was to rationalize the supplier base in the key commodities. Since 1980, the approach of spend analysis has become increasingly popular and is expanding its domain day by day.

Stay tuned as we delve into Big Data in the next blog.


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