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Insights into the Should-Cost Analysis of Tank Cleaning Services

May 3, 2017

The expense involved in cleaning tanks is a rather vague area to venture into. And therefore, companies are looking for avenues through which they can gain an accurate and in-depth analysis of the market. This analysis is not only to get a clear picture on the leading suppliers, but also to figure out the most optimal resources and hidden ‘cost out’ opportunities embedded in the endeavor. One of the best ways in which this goal can be achieved is by resorting to should-cost analysis (should costing).

Role of should-cost analysis in tank cleaning services

Category managers would agree how unlike strategic sourcing, should costing begins with an internal assessment of the potential costs involved in the project. Through the process of benchmarking, value analysis, tear down, and strategic sourcing, should costing provides an optimized strategy to improve product value and boost profit margins.

Though there is a popular conception that should costing is a rather complex process, the fact remains that it is one of the best procurement practices available at present. As it takes every minute cost into picture, the cost model provided by should costing is far more accurate than other methodologies.

When it comes to tanks, the major procurement pain points which have been noticed by our procurement specialists are:

  • Gaining actionable insights into best cleaning methods
  • Assessing average cleaning cost per cubic foot of solids in the tank
  • Eliminating the chances of ambiguous billing

Thus, by taking applicable economic and physical attributes into consideration, should-cost analysis predicts the cost involved in a system or a product.

Tank cleaning services and the SpendEdge advantage

Tank cleaning services is an integral cost component for many companies. Getting a realistic picture on its potential cost to the company is one of the primary steps towards building a foolproof financial strategy. The procurement team at SpendEdge can build a comprehensive should-cost model by blending primary and secondary data, and backing it with data analysis. This model clearly chalks out the primary costs involved in the cleaning process, along with detailed assessment of region specific labor costs. The model is customized depending on the varying cost components and different locations that are taken into consideration.

To know more about should-cost analysis

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