Data-based cost control in purchasing


Cost optimization is a significant concern for organizations of all sizes. Companies constantly look for ways to streamline processes, increase efficiency and maximize profitability. One of the most effective ways to achieve these goals is through big data.

With the advent of big data, companies have access to vast amounts of information. Data-driven strategies analyze data to identify areas in the business where costs can be optimized. Traditional approaches to cost optimization are often based on intuition and experience but are rarely accurate or comprehensive. You can create accurate forecasts and budgets using historical data and predictive analytics. This allows you to allocate resources efficiently, identify potential cost overruns, and make informed decisions about where to invest or cut costs.



Cost reduction vs. cost optimization

Cost reduction and cost optimization are two different company expense management approaches. Although both aim to reduce costs, their strategies and outcomes differ significantly. Cost reduction focuses on overall cost reduction without considering the broader impact on value or performance. Cost optimization takes a more strategic approach and aims to optimize costs by ensuring that resources are used efficiently and that investments provide the greatest possible return.


There are a variety of ongoing operating costs that are worth taking a closer look at:

  • Utility services: Electricity, water, gas, garbage collection
  • Office supplies
  • Technology and equipment
  • Rents
  • Insurance costs
  • Legal and accounting costs
  • Marketing/advertising
  • Transportation costs
  • Wages and salaries
  • Fees for licenses and permits


Challenges of implementing data-supported cost optimization

Your company’s software and tools are essential in effective cost optimization, as they determine how accessible and accurate your data is. Having easy access to accurate information in one centralized location can make all the difference. For example, Financial Planning and Analysis (FP&A) software can integrate data from various sources, such as ERP systems, cost management tools, and cloud platforms. It provides a centralized and automated solution for aggregating and visualizing data, making it easier to analyze and identify cost-optimization opportunities.


Implementing data-driven cost optimization is challenging but offers many benefits. Ensuring data privacy in the digital age is critical, and companies must take appropriate measures to protect sensitive information. Data quality can also significantly impact the effectiveness of data-driven strategies, so robust data validation and cleansing processes are essential. Employees need to be trained to improve their data literacy and enable them to interpret and use data effectively. It is also vital to foster a data-driven culture within the organization, where data is valued as an important business resource and decision-making is based on data-driven insights.

While implementation can be complex, those who invest in sound data management and effective integration strategies will reap the benefits. As predictive analytics evolves, your impact on controlling costs, increasing efficiency, and shaping the future of business processes will reach new dimensions.

We are happy to support you.

Get in touch