AI in Procurement Summary:
1. Using AI in Demand Forecasting
Chipotle Real Life Example for Using AI in Demand Planning!
2. Using AI When Doing Spend Analysis!
IBM’s Real Life Example in Using AI in Spend Analysis
3. Using AI in Supplier Onboarding
Real Life Example: SAP Ariba
Artificial Intelligence (AI) has transformed various industries across the globe– and procurement is not different. Artificial intelligence in procurement helps automate repetitive tasks, analyze large amounts of data, and enhance strategic sourcing.
As artificial intelligence in procurement continues to gain traction globally, procurement professionals are seeking innovative ways to leverage AI and unlock unprecedented value for their businesses.
Did You Know? According to Market Research Biz "Global Generative AI In Procurement Market Report" Global Generative AI in procurement market size is expected to be worth more than $2 billion by 2032.
Here are 3 areas where you can implement artificial intelligence in procurement this year:
Demand Forecasting basically refers to the process of predicting future demand for a particular product or service. Traditionally, this process has been performed manually using historical data and expert opinions.
However, the use of AI in demand forecasting has made this process more efficient and accurate. You can now use artificial intelligence in procurement to analyze vast amounts of data– both structured and unstructured– much faster than human experts.
By employing an AI-driven demand forecasting solution, you can quickly analyze sales data, market trends, and customer behavior to gain valuable insights. You can subsequently use these insights to make more informed decision-making to optimize your overall procurement processes.
Also read: The 7 Step Strategic Sourcing Process
A prime example of artificial intelligence in procurement with regards to demand forecasting is the restaurant chain Chipotle, which has implemented AI-powered demand forecasting to optimize its inventory management. The solution uses POS data, forecasting models, and AI algorithms to predict demand at each restaurant location.
Moreover, artificial intelligence (AI) also predicts inventory needs, which helps in ensuring that all the necessary supplies are ordered, and there is no understocking or overstocking of crucial materials for Chipotle.
Here’s what you can learn from this:
Spending analysis involves gathering, organizing, and examining an organization's spending data. Implementing artificial Intelligence in procurement can significantly enhance spend analysis by leveraging natural language processing (NLP) and computer vision.
These technologies enable the extraction and classification of data from a wide range of sources, including invoices, contracts, purchase orders, receipts, and more.
AI also utilizes machine learning and deep learning techniques to detect patterns and irregularities in spending data, including instances of fraud, duplicate payments, overcharges, and more– all of which are critical in preventing financial losses before they occur.
A real-life example of AI in spend analysis is of IBM’s Watsonx. The technology giant uses AI to analyze its $57 billion annual spend across 150 countries and 15,000 suppliers.
IBM's AI system can process millions of documents in multiple languages and formats, and provide insights into spending trends, risks, opportunities, and best practices.
Here’s what you can learn from IBM’s example:
Supplier onboarding involves the registration of new suppliers into an organization's procurement system. When it comes to supplier onboarding, it's important to thoroughly verify the supplier's identity, compliance, and performance.
Supplier onboarding is crucial as it plays a vital role in guaranteeing the quality of the supply chain. Artificial intelligence in procurement makes supplier onboarding more efficient by utilising NLP and optical character recognition (OCR) to scan and verify important supplier documents like certificates, licences, tax forms, and more.
In addition, artificial intelligence in procurement in the form of supplier onboarding also utilizes machine learning and sentiment analysis to evaluate the supplier's reputation, reviews, ratings, and more.
Also read: Selecting A Vendor: Your Vendor Selection Criteria
An excellent illustration of AI in supplier onboarding is SAP Ariba. The cloud-based procurement platform uses AI to streamline and simplify the supplier onboarding process for its customers.
The AI system of SAP Ariba is capable of verifying supplier information, conducting compliance checks, matching suppliers with relevant opportunities, and offering feedback and support to the suppliers.
Here are the key takeaways you can take from this real life example:
AI is certainly a game-changer in procurement if implemented effectively. It can optimize operations, enhance performance, and ultimately deliver more value to organizations and stakeholders.
The three areas discussed in the article– demand forecasting, spend analysis, and supplier onboarding offer great opportunities for businesses to start their AI adoption journey.
With AI-powered solutions, businesses will continue to streamline their procurement processes and create significant value in the next few years.
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