An AI strategy provides orientation
Secure the future of purchasing with algorithms
Even though AI promises huge benefits in purchasing, there is hesitance over its implementation. An AI strategy that can support you in selecting and implementing 44 suitable intelligent purchasing tools can be helpful.
Whether automation of routine tasks, real-time analyses or precise needs and price development forecasts – the use of AI can help purchasers to save time and money, reduce error and risk, improve decision making and boost productivity. Nevertheless, many companies are still reluctant about introducing AI. In terms of in-house
expertise, concerns can be overcome by creating an AI roadmap that is tailored to the specific tasks of each
procurement organisation and that incorporates different milestones.
Start with an analysis of the current situation
This starts with analysing the existing operational (Request-to-Order) and strategic (Source-to-Contract) purchasing processes to determine whether there is an opportunity for their optimisation with intelligent tools. To this end, apsolut operates an ever growing library, currently consisting of around 80 AI use cases
covering topics from the automation of recurring manual tasks such as order processing, supplier qualification and simple negotiation to AI-supported data analyses for risk management, contract management and supplier evaluation. In addition, there are also use cases for supplier development and complex negotiation strategies. Different types of AI are available according to the use case, including Machine Learning (ML), Deep Learning (DL) and Large Language Models (LLMS), such as GPT-4.
PoC: cost versus benefit
Whether or not implementing AI for certain process steps will actually pay for itself can be determined by performing a cost-benefit analysis based on predefined goals and KPIs. An example is the introduction of LLM negotiation bots for tail-spend orders, i.e. for non-strategic transactions of low value or for a company’s rare
purchases whose overall volume can accumulate quite considerably. In order to achieve the Return on Investment (ROI), LLM negotiation bots should enable cost savings of at least three per cent in tail spend.
To keep the effort as low as possible, the cost-benefit analyses are performed as part of a Proof of Concept (PoC). In the case of a negotiation bot, the purchasing organisation is given with the corresponding app by the provider, which can be quickly used for selected example requirements without the need for integration into existing systems. If the PoC is a success and evidences the anticipated costs savings, the LLM negotiation bot can be implemented across the purchasing division.
New uses cases, mature tools
Even if AI in purchasing is, in many ways, still in its infancy, continuous technological progress means that intelligent solutions are gaining in importance in this area too. New areas are emerging in which AI can be implemented, bringing with them ever more sophisticated AI tools which offer increasing advantages and relieve purchasers of tiresome routine tasks so that they can turn more of their focus to strategic activities that add value. SAP-based purchasing organisations should quickly set their reservations about AI to one side and start laying the groundwork for the future by putting together a clear AI roadmap and amassing the right AI tools.
* By Sergen Batman, SAP BTP Architect, apsolut
