Information is a Critical Need for Procurement Decisions.

The procurement industry faces several challenges that hinge on access and analysis of  good quality, timely and complete data.

Managing supplier risks, controlling costs, and achieving supply chain visibility, as well as accurately forecasting demand has historically been a costly exercise. The industry also grapples with ensuring sustainable and ethical sourcing practices as well as ensuring compliance with regulatory requirements.

Verodat has paved the way for the Procurement industry to address these challenges with a Lean Data Management for AI framework, improving operational efficiencies and maintaining a competitive edge.

 

Identifing The Business Problem Publishing The Data Need Establishing Data Suppliers Enriched Data Layer Activating AI The Future
Identifying The Business Problem

Reporting Delays Impact Procurement Team Responsiveness.

For procurement teams, identifying the business problem inevitably comes down to data. Reaching a level of business understanding that allows them to rapidly react to both internal and external forces is the key goal of our procurement clients. In many cases they have identified AI tools that they want to use to help them achieve this goal but their data is not AI ready, meaning they cannot trust AI outcomes in the way they need to.

The Problems:

  • Complicated workflows to extract data from multiple systems.
  • ERP is tracking orders and sales, but the system doesn’t provide reports that fit with their procurement process
  • Difficulties to build procurement analytics.
  • Time Delays in responding to business and market demands.
  • Decision making based on misinformation.
  • Over reliance on personal experience and ‘instinct’ for decisions and planning.
  • Late of Inaccurate ordering because of wrong or missing information.
  • Delays in ordering leading to unavailable stock.
  • Not having a quick and simple way to get good business understanding.

By using the Lean Data for AI framework, our procurement clients document both the business context and key questions in a qualitative context. Once this initial business context and problem have been characterised these details can be shared with a generative AI tool to define the data needed for the business problem.

For procurement teams, this might be key data sets from right across their business and supply network or even public data like weather, travel or market fluctuations. AI has helped speed up this documentation stage but this is where traditional data management process either spirals into a long arduous projects or simply fail completely. Verodat supports a different path.

Publish The Data Need

AI Readiness by Design

Having identified clear business objectives, our procurement users then published the data model and the requirements to the Verodat platform. As a data supply chain platform, Verodat facilitated the sharing of these requirements with the information owners and opened a seamless workflow between the procurement team and all the data suppliers.

The Process:

  • Each data supplier was given explicit instructions regarding the format, type, and precision of the data required.
  • Suppliers could easily understand and meet these requirements using their existing tools and processes.
  • Easy collaboration and cooperation in the data sourcing as gaps or missing data were quickly identified and either rectified or the data model was easily adjusted.
  • All adjustments and agreements were documented within Verodat to maintain the context and integrity of the final data, which is vital for supporting AI implementation.
  • This process instilled an ‘AI ready’ by design mentality. Verodat ensured the data flow adhered to the defined data context, a critical element in AI interpretation of data.

“ This has transformed how we operate day-to-day, we are finally in tune with what’s going on in the market. ”

Establish Data Suppliers

Automated and Accurate

The procurement team rely on a myriad of internal and external data suppliers which was causing a roadblock in many of their previous data management projects. Verodat allowed the procurement team to easily define who they needed the data from, what data they needed and how often they needed it. This allowed them to completely eliminate the manual back and forth of chasing data suppliers, the task now automated and managed securely within the platform.

Ultimately, this automation and defined supply cadence created a data supply maintained with full information on the supply status- another vital element in the enablement of downstream AI.

Automated Supply:

  • Automated connector to ERP systems like Oracle NetSuite or SAP
  • Automated connector to CRM systems like Salesforce, Hubspot or Zoho
  • Automated connector to Warehouse Management Systems
  • Load data from suppliers and manufacturers via Excel Attachment

A by-product of this step in the process has been vastly improved relationships between the team and the data suppliers, with the data supply chain offering a more seamless collaboration with clear expectations and schedules. It also allowed the business teams to take more control of the process without the high dependency on the technical teams.

 

 

Enriched Data Layer

From Two Months to Two Days

As data flowed through the data supply chain, the procurement team could easily identify, and instantly remedy, missing data, anomalies and errors. With data that was filtered, mapped, validated and transformed and any error handling along the process logged and tracked, enabling AI became a simple and fast project.

Used to conducting much of their reporting in Microsoft Excel, the procurement team instantly switched on the Verodat Excel add-in which provided them with access to clean, consolidated and reliable data in a familiar environment where they can independently perform data analysis.

A previous attempt to roll out Excel Co-Pilot within the procurement team had stalled, with the quality of the data resulting in too many errors to fully trust the outcome. With the new data layer in place, it is ready for use with Microsoft Co-Pilot, which enabled the team to utilise the Co-Pilot assistant to write and apply formulas, create pivot tables and chart views. This allowed the team to quickly create the dashboard and drill-down views needed to make decisions, and to automatically update them in a single click to pull down the latest data from Verodat and refresh analysis views.

Reports and information about the business that previously took teams weeks to prepare, were accessed in an application of their preference, saving 60% of the teams time in delivery, enabling the team to respond to market demands in near-real time.
Activating AI

Accessible AI for the Whole Team

Reiterating the goal of reaching a level of business understanding that allows them to rapidly react to both internal and market external forces, further embracing AI was the next logical step for the procurement team.

Using ChatGPT built by Verodat, the Procurement Team were able to get instant information on current sales trends like best selling products or product categories, enabling them to more accurately predict and respond to demand. ChatGPT was also able to provide real-time insights on the status of product stock in the warehouse, alerting when popular items are running low, and to get updates on the status of in-transit orders across their supply chain. 

The GPT’s data analytics capabilities also simplified the process to perform more powerful analysis like forecasting, by providing instant answers on trends from previous years and seasons. 

Overall, the GPT provided a signficant improvement in the usability and accessibility of data insights for the Procurement Team, making it easier and faster to get key insights to power responsive ordering that ensures the organisation is managing their inventory efficiently.