Businesses are flourishing across the globe, and this invites third-party interventions and collaborations. While these collaborations bring in strategic advantages, it also involves significant risks. Be it 10 or 100; managing vendors isn’t an easy task. In a business ecosystem, third-party vendors play an important role in today’s competitive market. A small mistake by a Vendor can cost significant businesses losses. Traditional checklist methods are not sufficient anymore to manage multiple vendors. Natural Language Interface (NLI) can help in providing effective and efficient vendor management solutions.
AI-driven vendor management system goes a long way in eliminating risks associated with vendors. Most organizations follow traditional methods for vendor management. However, for improved risk management, companies need to have advanced systems and tools that allow them to be prepared for any third-party vendor risks.
How can AI be used in effective and efficient vendor management?
Companies that heavily depend on third-party vendors do not have clear visibility into their entire vendor network that can put them into high risk. Any vendor that has access to internal systems or data is vulnerable to a company. The AI-based system will allow companies to have a clear picture of the entire vendor network and will enable them to be prepared well-before a risk happens. Moreover, it will allow the companies to analyze the vendors properly and help them achieve business goals cost-effectively.
Centralizes the Vendor Information
The AI-powered tool helps to assign different roles and access rights to users based on their respective responsibilities. It allows all the information like contracts, vendor details, pricing etc. to be stored in one place, thus, centralizing all the information under one tab. Further, it helps in monitoring and tracking all the vendor documents and related information.
Automated Vendor Segmentation & Selection
These AI-based systems simplify the process of selecting vendors as it automates the process of requesting quotes, defining rates and pricing, track spending, segregating different vendors, managing deadlines, and monitoring costs and billing information. It allows Project Managers to have deeper insights into the Vendor profiles and aids for better vendor selection.
Cuts down on the total number of resources required
AI based tools help in minimizing the involvement of large workforce, thus, performing all the different functions that can be easily managed without human intervention.
Bots for Voice and better user interaction
AI-based bots provide a more conversational approach towards vendors. Through these chatbots, companies can speak to vendors as and when required and vice-versa. Chatbots can also help in sending documents relating to compliance and SOPs. Vendors can place purchasing requests. The chatbots can also perform internal searches regarding procurement queries asked by the vendors and at the same also complete research on the vendor itself.
Natural Language Processing (NLP) for Data Management
NLP allows deciphering large chunks of data in various languages and segregating them in a streamlined manner. It will enable categorizing data into different sets and collects all the untapped information into meaningful data. It simplifies audit and compliance actions that previously occurred due to language barriers between vendors and organizations.
AI allows Predictive Analytics
Sourcing the right vendor can be a daunting task for many organizations as vendor related risks are increasing. With the help of AI and Machine Learning (ML) combined with intelligent algorithms collecting passive data about various vendors will become easy. Vendor selection would be more predictive, creating valuable long-term relationships. With AI implementation and automation, companies can have ‘better vendor scenarios’ based on several parameters the company desires to have.
AI and NLP tools aid in Metadata tagging
Wonder how? AI tools combined with NLP help in extracting existing contracts from the database and promote automatic tagging of the data. Earlier, manual process was followed to import contracts information, and Meta tags were applied only to specific contracts which had any changes. But with the help of AI and NLP Vendors can now quickly search contracts and apply metadata easily.
AI and ML approximate the conclusions
AI has the ability for computer algorithms to approximate the conclusions by processing vendor invoices accurately without human intervention creating more effective productivity, better cash flows and vendor relations, thereby generating better reports. This way, companies can monitor trends, bring in relevant policies for vendor management.
AI can be leveraged to automate purchase orders as it automatically reviews and approves orders.
Intelligent workflow through AI
There is a lot of time wasted in streamlining the workflow while analyzing and integrating data. AI-powered systems allow intelligent workflows that further initiate tasks performance monitoring. So, now the managers know how much time an employee takes to finish certain tasks assigned to him/her. It also increases visibility on the workflows as there are visual representations of the workflows available, allowing the project managers to remove bottlenecks if any.
AI-based tools help in extracting real-time and accurate spend data and gives you granular insights into the data and later automatically aggregates, classifies, and reports the data across the enterprise.
Some benefits AI offers in vendor management:
- Helps in better decision-making
- Identifies new revenue opportunities
- Allows better Vendor selection
- Enhances operations & workflows
- Automates manual tasks
- Saves time by avoiding repetitive tasks
- Captures and Analyzes bits of data
- Optimizes vendor-company relationships.
AI is proving to be the most modern technology that is driving the entire vendor management process. We would be witnessing days where AI will be used in every organization for effective and efficient vendor management as it promises to speed-up the conventional processes, offer vendor intelligence, and provide real-time performance insights.