Master Data Management in SAP Ariba: The Key to a Successful, On-Time Implementation
Master Data Management may not make headlines, but it’s the backbone of SAP Ariba's success. Imagine this: A company invests millions in a digital transformation project, only to face delays and cost overruns because their Master Data isn’t ready. Sound familiar? That’s where Groupsoft steps in, turning months of manual work across millions of records and data fields into seconds with our AI-driven solutions.
However, MDM is the customer’s responsibility when it comes to Ariba, not the responsibility of the systems implementation consultant. Unless the customer already has a robust MDM team and process (Master Data Governance, or MDG for short), the accurate master data required for implementation testing, systems integration, and Ariba go-live will delay the project and result in significant budget overruns. But who knows any new Ariba customer that wasn’t (or is) delayed by MDM issues? That’s why when implementing Ariba, MDM is often referred to as “the longest pole in the tent.” Everything depends on it, but it takes the most time, effort, and resources to set it up.
Master Data Management (MDM) for Ariba is driven by the ERP’s Material Master (MM) and Ariba’s Vendor Master (VM) on the SAP Business Network (SBN). Nearly every S2P transaction requires some sort of MDM. Therefore, data accuracy and completeness are paramount to buying the right goods and services on time, receiving the correct quantities, and paying the amount agreed to with suppliers.
In addition to helping achieve high customer service levels and operational efficiencies, MDM also drives financial and tax reporting. For example, assigning the wrong material code to a good or service can be the difference between it being tax-free versus being fully taxable across multiple tax jurisdictions.?
At Groupsoft, we’ve seen countless customers wrestle with managing and standardizing millions of master data records spanning suppliers, catalogs, bills of materials, and more. With the launch of our SAP Ariba Center of Excellence (COE), we’re introducing cutting-edge AI to automate, standardize, and enrich MDM processes. The result? Higher value for customers and their stakeholders. With the introduction of our SAP Ariba Center of Excellence (COE), we are bringing together the latest in AI to not only automate MDM but also to standardize and enrich it, thereby increasing its value to the customer and their customers as follows:
Traditional Approach: Typically 82% after manual attempts
Groupsoft AI-Driven MDM: Typically around 95% without manual intervention
Traditional Approach: Weeks or months
Groupsoft AI-Driven MDM: Seconds
Traditional Approach: Low due to labor-intensive processes and poor standards
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Groupsoft AI-Driven MDM: Significant savings per record
Traditional Approach: Frequent delays, manual interventions, project overruns
Groupsoft AI-Driven MDM: Streamlined processes and enriched data, on time and on budget
Case Study:?
After a 14-month effort across categories and business units, a customer with just over 500 strategic items could not correctly determine the correct material codes for more than 90% of these records for tax reporting purposes. Unlike Ariba, their legacy systems did not require high-quality MDM, and much of the historical data that was there was poorly managed and maintained. It wasn’t until late in the implementation during integration testing (where other systems and databases are impacted) that this MDM problem surfaced. This issue delayed implementation by 3 months so that all these records could be manually reviewed, standardized, enriched, and retested. In simple terms, if a typical Ariba implementation takes on average 12 months, then this MDM-related delay resulted in a 25% overrun on a multimillion-dollar project budget.
The “quick fix” was to hire a team of accounting consultants for a month to fix just the most critical of these 500 records, yet they only achieved 82% accuracy. Running out of time and budget, they went live with incomplete, inaccurate, and unstructured data elements that resulted in every order and payment being blocked and then manually unblocked.
As a comparison, we ran similar data through our COE’s Master Data AI solution. The result was 98% accuracy in just 3.8 seconds of processing time. Imagine how much unplanned time and cost could have been saved by using AI!?
In addition, every record with less than 100% accuracy was flagged by the AI solution; it also suggested how to quickly close every master data “gap” and all similar gaps across the entire material master database.?
So, how can the COE’s Master Data AI do in seconds what humans need weeks or months to do manually? Without going into the technical workings, the solution works by teaching itself what worked before and by humans teaching it how to close those data gaps when the solution is unable to or doesn’t “feel confident” in its recommendations. Once the AI “learns” how to correctly standardize and populate each field of each record, it also “remembers” how it did it and then applies that learning to similar data gaps elsewhere across the master data.
If you are like most customers implementing Ariba, and if your master data isn’t already keeping you up at night, it eventually will. But MDM is also the one major aspect of your Ariba implementation that can never be started early enough. Our COE can guide you through how to review your master data as part of your implementation fit-gap sessions to help you identify where your data needs help and how we can work together with our AI solutions to fill those gaps.
And, because the Groupsoft COE uses AI models for MDG, we can offer these services at a significantly lower cost on a per-record basis compared to traditional time & materials pricing. This pricing will literally save millions of project and operational dollars and months of manual data tent building.?