In the past two years, procurement teams across industries have played a critical role in enabling businesses to tackle COVID-19 challenges. However, this has not been easy as there are several factors that have made procurement all the more challenging.
Identifying and onboarding stable strategic suppliers with a low-risk profile, redesigning procurement to meet volatile demand and supply mismatch, managing the increasing input cost, and insulating the business from supply chain disruptions caused by political issues are a few challenges that have increased the complexity of procurement.
This has brought about a paradigm shift in the way sourcing and procurement have been done since time immemorial. Strategic sourcing is no longer restricted to only critical and high-value categories but is being adopted across all categories. The key to strategic sourcing is effective optimization considering dynamic market variables and minimizing risk, aka sourcing optimization. However, since the process of sourcing optimization is complex and time-consuming, there has been resistance from sourcing teams for its widespread use especially when the requirements are critical and procurement needs to be done at the earliest.
Artificial intelligence-powered autonomous procurement platforms have stepped in to completely redefine sourcing by dramatically reducing the time and effort taken. This has unlocked a huge potential for cost savings and as they are addressing the need of the hour, they are getting great traction.
Contents
- What is Sourcing Optimization?
- Scenario Modelling: Backbone of Sourcing Optimization
- Benefits of Sourcing Optimization
- What is the cause of the low adoption of sourcing optimization?
- How can AI simplify sourcing optimization?
- Conclusion
What is Sourcing Optimization?
In strategic sourcing, apart from primary factors like account price, lead time, and quality, more and more data points are considered to evaluate the total cost of ownership. Hence, suppliers are chosen not only on the lowest purchase price but a multitude of data points that ultimately will have an impact on the business. Supplier performance, risk profile, diversity, and incumbency are evaluated to avoid supply chain disruptions.
Factors like supplier production capacity, locations they can service, financial stability, and ESG need to be checked to ensure alignment with corporate policies.
In order to carry out strategic sourcing efficiently, procurement professionals use sourcing optimization. It is a process used to evaluate and design the optimum strategy for supplier selection and award. Sourcing optimization tools use complex algorithms, mathematics, and machine learning models to analyze large amounts of bid data from several vendors on various criteria used in the bid event.
Scenario Modeling: Backbone of Sourcing Optimization
Some of the common scenarios used are maximum number of suppliers, preference for incumbent suppliers, splitting the award in the desired optimum ratios, financial stability, etc. Additionally, sourcing professionals try to optimize total cost, ESG practices, and diversity.
Benefits of Sourcing Optimization
Cost Savings
In sourcing optimization, the cost impact of all the parameters is considered in addition to the actual purchase price. Hence, there is a huge scope for overall cost savings.
Reduced Risk
As sourcing optimization takes into account multiple factors such as supplier performance, capacity, financial stability, and related parameters, risk can be minimized.
Better supplier relationships
With sourcing optimization, buying is not done on a transactional basis but rather taking long-term success into account. This makes the suppliers more invested in keeping up higher service levels and extending support in times of unforeseen disruptions.
What are the causes of the low adoption of sourcing optimization?
Although sourcing optimization seems to be the clear direction forward for all enterprise procurement teams, there seems to be an issue with adoption. Here are the possible reasons for sourcing optimization resistance from sourcing and procurement teams:
Tedious processes
Designing a bid event considering various data points that affect the cost and the subsequent supplier selection is a time-consuming process. Each stakeholder who is involved in the sourcing process brings their own set of needs and requirements to be considered.
Insufficient data
Even after multiple back-and-forth conversations with internal stakeholders and suppliers, the data is often incomplete to run a full-fledged analysis. Often there is data leakage due to the inefficient systems used for collaborating and sharing files.
Time-consuming analysis
Analyzing bids and evaluating the optimum award scenarios is a time-consuming process. Comparing different scenarios with minute changes in business rules can lead to delays.
Complicated systems with ambiguous data can push sourcing teams to resort to traditional excel sheets leading to disconnected data and manual errors creeping in.
Low adoption
Due to the complexity involved in multiple stakeholder participation and the usage of disconnected systems, sourcing professionals often resort to traditional buying processes using multiple discrete and disconnected tools.
How can AI Simplify Sourcing Optimization?
A simple intuitive tool to eliminate cumbersome activities is necessary to make procurement teams incorporate sourcing optimization for all projects and not just the complex ones. Today’s next-generation AI-powered sourcing automation software will help achieve just that.
Automated Bid Creation
Artificial intelligence (AI) simplifies the bid creation process to a great extent. It enables RFIs and RFQs to be converted into a comprehensive bid event with just a single click. It can also intelligently understand complex requirements from a purchase requisition and suggest predefined templates to work on. The computing power of AI also makes it deeply configurable with an infinite number of fields and suppliers.
Easing Out Buyer Work / Supplier Response
The easiest way to obtain information from suppliers is to make them share it through tools that they use on a daily basis. This could be through their regular emails, WhatsApp, or simple web-based chatbots. AI synthesizes the documents provided in these media and processes them for bid analysis.
The process can be simplified for buyers by providing them with simple user interfaces like being able to copy-paste from Excel and providing them bots to automate non-value added tasks.
Eliminates coordination and follow-ups
New-age bots have enabled better coordination between internal and external stakeholders. From sending automated reminders for task completion to answering queries, bots completely eliminate the delay caused by the incessant back and forth between teams.
Intelligently recommends alternative award scenario
Keeping in consideration the rules and business constraints set by the sourcing professional, AI can recommend an alternative scenario that has not been considered yet but could unlock greater cost savings. It also continuously learns user preferences and modifies the next award scenario suggestion accordingly.
Conclusion
Businesses have been relying on archaic tools and engaging in inefficient practices for ages. However, with the advent of AI-powered tools, sourcing and its optimization will be a different ball game. Sourcing optimization is quickly gaining traction across industries and geographies. Enterprise procurement teams need to adopt and implement these effective sourcing practices to improve cost-savings and efficiency with these next-generation AI-powered tools.
