When my wife looks at my closet she complains that I have 5 identical white shirts from Brooks Brothers, three Panamas exactly the same, and many many black socks some matched some not. This problem appears in most large enterprises when they look at their Master Data for Parts, Suppliers and Customers. The answer to a messy closet is the “Queen of Clean”, Marie Kondo.

Marie Kondo says to only keep possessions that “spark joy”. Similarly, master data clean-up focuses on keeping only the true master records that accurately reflect the business.

• A core part of Marie Kondo’s method is removing duplicate items. Master data clean-up also involves consolidating duplicate records into single master files.

• Marie Kondo emphasizes neat and intuitive storage using boxes, files, and folders. Master data requires proper organization in a well-designed system

• Marie Kondo’s rules for keeping tidy must be followed constantly. Master data hygiene also requires ongoing discipline to prevent new duplicate records.

For Master Data, the old ways of writing complex scripts don’t scale. Steve Curtis of Mars has a new way, as he recently explained on this podcast.

Why Master Data is so crucial in an Enterprise

Master data governance is a critical but often overlooked area for many enterprises. Master data encompasses business-critical entities like customers, materials, suppliers – the core data needed to run operations. Keeping this data consistent and correct across complex IT landscapes is incredibly challenging. However, poor master data quality can severely impact business performance.

At Mars, master data governance in their SAP MDG system was a pain point. Making updates to master data was cumbersome, requiring IT tickets and waiting days for changes. SAP screen complexity also meant intensive training for business users.

Introducing the Chatbot embedded in MS-Teams

To transform their process, Mars’ MDM team developed an intelligent chatbot that allows business users to rapidly make mass updates to master data themselves. They simply start a chat to initiate requests in plain business language. The chatbot guides users through the process, hiding technical complexity and providing real-time status.

For example, to update payment terms for customers, a user can just tell the chatbot they want to “change payment terms” and provide a list of IDs. The chatbot looks up the relevant field, generates a template for changes, and submits the updates into SAP MDG with no user knowledge needed of the backend.

The chatbot is integrated directly into Microsoft Teams, allowing users to initiate conversations and requests through Teams chat. Users can start a chat with the bot in Teams and walk through the master data change process in a conversational way. Teams provides the front-end user interface and allows capabilities like file sharing to upload templates back and forth. People are already using Teams for collaboration and communication, so having the bot embedded in Teams chat makes it easily accessible rather than having to go to a separate portal or interface.

Since going live in May, adoption has steadily increased. Over 300 updates have been made to general ledger data alone, with hundreds more for other master data. Feedback has been overwhelmingly positive from business teams.

Updates reduced from taking days to mere minutes

Previously, making master data changes took up to 5 days due to the need for creating tickets and having the IT team handle them. Now with the chatbot, there are near real-time updates, doing them in seconds/minutes rather than days. Steve says that Mars can process 1000+ changes to general ledger data in about 15 seconds through APIs.

By using intelligent automation and conversational interfaces, Mars has made managing master data in complex ERPs simple and accessible for business users. Tedious requests are handled instantly by the chatbot. This boosts productivity, drives efficiency gains, and enables a responsive digital enterprise.

Mars continues to expand the capabilities of their intelligent chatbot and explore use cases like complex mass processing workflows. The chatbot has unlocked hidden potential in their master data management process. It provides a model other SAP customers may wish to evaluate as they transform critical business processes. Adding a friendly conversational interface makes imposing enterprise software more usable for business teams.

To here more from Steve, listen to this podcast: SAP on Azure Podcast, Episode 164