Good practice contract management (CM) in line with the government framework requires knowledge, know-how, experience, and a whole range of soft skills. Professional CM resources are scarce and in ever-increasing demand.
CM skills deliver the greatest value when they are focused on keeping a contract on track, liaising with stakeholders and suppliers to deal with risk or poor performance early, and keeping relationships positive and focused on the end goals. They handle issues when they are small and before they become disentangleable knots.
The CM lead and their team must also keep track of contract and regulatory changes, monitor risk and compliance, and report regularly. A high overhead of administration and data extraction is necessary to support this active relationship and performance management.
The Procurement Act, in force later this year, expands the contracts for which KPIs are published and reported and increases the potential impact on the vendor with the new debarment regime. The mandated increase in transparency is expected to increase supplier challenge of performance ratings and further absorb buyer contract management resources.
Given the wide scope of the Procurement Act across the public sector, contracting authorities will be looking for ways to fulfil the requirements of the new Act in the most efficient and consistent way.
Proxima spoke to Ian Makgill of Spend Network, an advocate of greater transparency, to imagine how AI can support and amplify excellent contract management—carrying some of the weight and freeing up resources to focus on what adds value. He stresses that there are real opportunities to reduce time spent on manual tasks and to gain a broader view of all the events and documents relating to a complex system in one place.
Examples of how AI can be used in contract management include:
- Scanning contracts to extract critical data at the start and then regularly scan your systems to collate different data sources to create a full picture of supplier performance
- Evaluate outputs and timings to review quality and spot performance trends or potential issues
- Analyse communications to look for non-compliance or potential risks
- Analyse all change notices or remedies to ensure they do not conflict with the contract
- Compiling monthly reports to support meetings and provide MI to central systems, particularly valuable if a contract requires input from multiple suppliers
But Makgill has words of caution, too. AI takes skill to use. Throwing data into a chatbot and expecting a perfect response is likely to fail. Instead, buyers must learn how to use these tools—for example, building chains of prompts that deliver more accurate analysis. Care must be taken to ensure that the contextual data is appropriate for your analysis and that the context is up to date.
If your contract terms have changed, the model must be informed before you ask if the supplier complies with the contract. Of course, security is also an issue. The data you upload to any AI service must be suitably secure, and the model must not retain the data you upload for fear that it may be republished later.
The opportunity for contract managers is to let the machine do the tedious, repetitive work of reviewing communications and outputs before creating a first draft analysis, which can then be checked and reviewed by a human.
With robust, well-validated analysis, CMs can spot poor performance early, empowering them to work with suppliers on remedies before problems become entrenched or endemic.
Buyers can safely use AI when properly configured and hosted on the right services.