A major portion of any government organization’s budget goes towards procurement, acquiring the goods and services needed to support operational needs and complete construction projects.
While many procurement decisions are planned, there is a great deal of activity that is also reactive – responding to an emergency, unexpected repairs, newly passed legislation, or changing operational needs. To be more strategic in the future, procurement should review and analyze spending patterns to streamline and improve decision making processes.
Procurement analytics is the systematic method of gathering, organizing, and interpreting data related to procurement activities. Through analytics, patterns, supplier performance, and trends can be identified, which can be crucial to driving savings, negotiating better terms with suppliers, minimizing risk, and allocating limited resources towards more strategic initiatives.
Benefits of Data-Driven Analysis
Data-driven analysis can provide a granular view of spending patterns, historical data and market conditions. It can also result in several benefits:
Streamlined Processes
Documenting and analyzing the costs – personnel and non-personnel – across the entire procurement solicitation process can create a better understanding of each step and the roles involved to result in an awarded contract. It can also identify possible inefficiencies or high-cost steps to further study and possibly address, potentially reducing cycle times, streamlining workflow, and automating manual tasks.
Cost Reduction and Rogue Spend Management
Comparing pricing, understanding the costs of procuring, and identifying off-contract spending can offer opportunities to save money. Leveraging spending patterns into more advantageous contract offerings or limiting off-contract spending can drive budgetary savings.
Better Contract Management
Once a contract is awarded, management of that agreement over the contract period of 3-5 years can be inconsistent. Managing paper contracts stored in a file cabinet is a cumbersome process. It’s important to ensure that the price paid was the price that was negotiated and to asses supplier performance across the life of the contract.
Minimized Risk
Analytics help identify, assess, and minimize potential risks such as pricing fluctuations, supply chain disruptions, and legal implications. Better management of supplier contracts can also ensure adherence to legal requirements and best practices.
Anticipation of Trends
Using AI in procurement analytics to review historical data and market trends can help proactively address pricing escalations in certain industries or mitigate supply chain disruptions.
As a crucial part of the organization, procurement must bring forward possible strategies and problem solving to offer solutions, as well as to add value to the process. Using data is a strategic tool to help with that role, demonstrating procurement’s capabilities and leadership.
A few examples of where analytics can be strategic include:
- Pulling all high-value commodity contracts to perform a mini-audit of pricing paid versus negotiated pricing, then taking those contracts and comparing them with other contracting solutions (i.e. cooperative contracts) to determine whether the best pricing is being obtained.
- A comprehensive analysis of spending and supplier data to give procurement teams insights for better negotiation when renewing a contract for additional option years.
- Analyzing the procurement cycle to identify roadblocks or slow points that can be adjusted or eliminated to improve the process.
- Calculating and identifying areas of cost, such as advertising, that might be eliminated by moving towards automation.
- Implementing analytics to introduce performance metrics that lay the groundwork for ongoing improvement.
There are numerous benefits of utilizing procurement data to strive for efficiencies and savings. It can be leveraged to improve overall operations while uncovering opportunities to further demonstrate procurement’s value and leadership within the organization.
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