How to improve visibility with AI-powered spend analytics software

As businesses strive to stay competitive and efficient, the adoption of spend analytics software powered by AI has become a critical component of modern spend management. While the potential of this technology to uncover hidden insights and improve operations is well recognized, the journey from understanding this potential to leveraging it can be daunting. This transition requires not only a strategic vision but also meticulous planning and execution.

Below we walk you through the step-by-step process of leveraging AI-powered spend analysis software, from assessing your current capabilities to achieving seamless operational improvements. By following these guidelines, your organization can move confidently towards a future where complete spend visibility is not just a goal but a reality.

Introduction to AI-driven spend management

Modern businesses often manage various degrees of chaos, often with multiple finance platforms and a reactive approach to spending. Transitioning from traditional spend management to a unified AI-driven approach offers numerous advantages, including enhanced visibility, deeper insights, improved operational efficiency, and cost savings. Businesses can subsequently control spending proactively, even when dealing with large volumes of data. However, achieving these benefits requires a strategic approach that involves understanding the technology, aligning it with organizational goals, and executing a detailed plan to wield it seamlessly with existing processes.

How to implement spend analytics software

Assess your current capabilities

The first step in leveraging AI-powered spend analytics software is to evaluate your current data infrastructure and spend management processes. This assessment helps identify gaps and areas for improvement, providing a clear picture of your starting point. Key activities in this phase include:

• Reviewing existing data systems and processes to understand their strengths and limitations.
• Identifying data silos and inconsistencies that need to be addressed.
• Mapping out current spend patterns and management workflows to pinpoint inefficiencies.

Define objectives and key metrics

Setting clear goals is crucial for success. Define what you want to achieve with a new spend analytics solution and determine the key performance indicators (KPIs) that will measure your success. Objectives might include:

• Improving spend visibility across the organization.
• Identifying cost-saving opportunities.
• Enhancing supplier management and risk mitigation.

KPIs could include metrics such as the percentage of spend under management, cost savings realized, and supplier performance ratings.

Choosing the right solution partner

Selecting the right spend analytics software and a technology partner is a critical decision. Consider the following factors when evaluating potential solutions and partners:

• Previous expertise: Review the provider’s experience and the maturity of their AI modeling capabilities.
• Information Security: Ensure the solution has the appropriate Information Security protocols
• Pricing and ROI: Assess the cost of the solution and the potential return on investment. Look for a solution that offers significant value for the price.

Data preparation and categorization

Having clean and organized data is essential for the success of spend analytics software. This phase involves:

• Data consolidation: Bringing together data from various sources in a structured format allows AI to make accurate predictions, identify patterns, and give you actionable insights to facilitate efficient management of your business.
• Data classification and categorization: Likewise, organizing data into an industry-standard or custom taxonomy, such as the United Nations Standard Products and Services Code (UNSPSC), helps you get the most out of AI-powered software. An added benefit is that once you have classified your data, AI-driven tech will drastically improve the speed and accuracy of the process so it can be done on an ongoing basis instead of ad hoc.

Initial testing phase

Testing spend analysis software in a controlled environment can help identify and resolve potential issues. This phase involves:

• Running pilot tests with a subset of data to evaluate the software’s performance.
• Adjusting configurations and addressing any challenges that arise during testing.

Post-deployment training and change management

Successfully leveraging spend analytics software requires training staff on how to use the new software solution effectively. Additionally, a supportive partner will assist with adoption and ensure the software provides ongoing value. Key activities include:

• Training: Providing comprehensive training sessions for users at all levels.
• Support: Offering ongoing support and resources to help staff adapt to the new system.

Coca-Cola Amatil successfully leveraged AI-powered spend analytics software in partnership with RobobAI. The company’s experience showcases the advantages and transformative impact of using this technology. They were able to aggregate large volumes of disparate data quickly, providing visibility into spend and actionable insights. Simon Ellis, Chief Sales Officer at RobobAI, highlights the benefits:

“We see the challenges that procurement leaders are facing in today's competitive business landscape. They are constantly navigating the challenges of doing more with less. Our customers choose us for our ability to aggregate large volumes of disparate data quickly, which gives them visibility of spend and the ability to act on it.”

Upgrade to powerful spend analytics software

Implementing AI-powered spend analytics software is a strategic move that can significantly improve your spend management. By assessing your current capabilities, defining clear objectives, choosing the right solution and partner, preparing your data, and conducting thorough testing, you can achieve a seamless transition. Post-deployment, training and change management are crucial for ensuring adoption and realizing the full benefits of the technology. With AI-driven insights, your organization can achieve complete spend visibility, streamline operations, and drive smarter decision-making.

Is your supply chain leaking millions in unknown costs?

Without knowing it, your supply chain could be costing you billions in expenditures. RobobAI’s AI-powered supply chain visibility software allows you to aggregate data and gain unparalleled insights into your spending patterns and supplier risk. Get in touch with us or book a personalized demo.