How Should-Cost Modelling can be a Powerful Tool for Utilities

How Should-Cost Modelling can be a Powerful Tool for Utilities

  • To increase resilience and meet sustainability goals, companies, especially utilities, need to invest in new infrastructure
  • Should-cost modelling helps control the costs of those investments by granting visibility into cost drivers and increasing leverage in negotiations
  • Technology solutions allow enterprises to track material prices in real time and predict future costs
October 08, 2021 | Supply Chain Software Blogs

After a tumultuous 18 months due to a pandemic, natural disasters, blackouts and other disruptions, sustainability has become a pressing concern for different industries, particularly utilities.

Roughly a quarter of greenhouse gas emissions stem from electricity generation. Investing in renewable energy and updating aging infrastructure are now priorities for utilities.

Investments into projects like high-voltage transmission lines will help companies make electric grids more resilient and tap more into renewable energy sources like wind and solar. And the $1-trillion infrastructure bill under consideration in the U.S. House of Representatives will spur those investments by providing $27 billion for the electric grid.

To ensure those outlays are profitable, though, there is a greater need on the part of utility companies for effective, real-time should-cost modelling. This will help their sourcing teams understand cost drivers and improve supplier negotiations to reduce long-term costs.

Should-cost modelling enables enterprise teams to unlock valuable cost savings

Should-cost modelling can provide a significant advantage for companies in the sourcing process by giving them an advanced understanding of the costs required to deliver a product or service. Components that go into these models include material, labor, facility and production costs.

The goal is to understand and predict all the material and manufacturing cost drivers to inform negotiations. By better understanding the drivers of price, companies have more leverage in discussions with suppliers.

But rather than being a weapon for companies to use against suppliers to drive the price down, should-cost modelling is an essential tool for building strong, mutually beneficial relationships with suppliers.

Obtaining an accurate view of cost drivers and the pressures a supplier is facing can lead to more productive discussions about how enterprises can collaborate strategically in the long term.

Given the value that should-cost modelling can provide, companies are more and more looking to technological solutions to leverage it, particularly because it helps manage the complexities involved.

Technology makes should-cost modelling easier and more effective

Should-cost modelling is extremely complex for several reasons:

Volatility of cost drivers

The number of components that go into producing a detailed, accurate should-cost model can be significant, especially for complex products or services. And those prices are variable as the market changes in real time. Price volatility means that having live market indices, in addition to forecasts and historical data, is essential to reducing the potential for error in should-cost models.

Siloed information

Should-cost modelling draws information from a variety of sources. However, that information too often exists in functional silos that do not communicate with each other, making good collaboration necessary to developing an accurate model.

Manual processes

The need to get information on costs from real-time market indices makes manual processes a hindrance to conducting should-cost analyses efficiently, not only with regard to speed but in terms of avoiding errors as well.

AI-powered should-cost analysis tools use machine learning algorithms to predict item costs and integrate live market indices to track commodity prices in real time. With the capability to analyze existing prices, assess market trends and compare against historical data, artificial intelligence can not only provide cost estimates, but achieve more accurate estimates over time.

As part of a unified platform, should-cost modelling software connects supply chain with sourcing to create a comprehensive cost estimation workbench for comparing prices with historical data.

Moreover, cost-modelling software makes it possible to automate the time-consuming manual processes, enabling teams to develop dynamic cost models that update automatically as price drivers change.

Should-cost modelling helps companies act as part of a larger supply ecosystem

Enabled by technology, should-cost modelling is a precision instrument for gaining visibility into the real drivers of material and manufacturing costs. For companies beset by supply shortages, transportation issues and other disruptions, getting that visibility is crucial.

By facilitating stronger negotiations between buyers and suppliers, should-cost modelling actually encourages the development of the strategic collaboration that is essential. For utilities that need to continue driving value while achieving sustainability goals in a disruptive new normal, it’s a powerful tool.

Turn ideas into action. Talk to GEP.

GEP helps enterprise procurement and supply chain teams at hundreds of Fortune 500 and Global 2000 companies rapidly achieve more efficient, more effective operations, with greater reach, improved performance, and increased impact. To learn more about how we can help you, contact us today.

Alex Zhong

Director, Product Marketing

Alex has more than 20 years of practical experience in supply chain operations and has advised many Fortune 500 companies on their digital transformation. At GEP, he leads product marketing for the company’s AI-enabled supply chain solution. He is passionate about the role technologies play in driving supply chain excellence and business growth.



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