Is it John, Jon, or Jonathon?

Ever given any thought as to why you receive two to three of the same advertising mailer from the same company on the same day?  You most likely have multiple identifiers in their system (or across multiple systems) and look like different “prospects.”  And while this seems like an inconsequential example, consider that this inaccurate data has a direct cost – postage, advertising fees, environmental impacts like paper production and transportation, data storage, etc – impacting revenue, product price, and more. No matter how good your systems and processes are, with bad data, you risk negative financial impacts.

The Role of Technology

Today, many companies are looking to move to SAP S/4 HANA, the next generation of ERP from SAP which provides end-to-end solutions from procure-to-pay, order-to-cash, request-to-service, plan-to-product, and hire-to-retire through global networks for spend, asset intelligence, and more.  And while this extensive network will enable the platform to streamline processes delivering competitive advantage to your company, having inaccurate data from multiple source systems can significantly reduce its value.  Similar to the mailer example, duplicate or incorrectly mastered source information can lead to missed cross-sell or up-sell opportunities, additional shipping costs, restocking fees, loss of purchasing discounts, or increased inventory carrying costs. And these are exactly the problems Tamr helps address.

In the example depicted below, using the raw data, a single customer looks like three entities with limited spend.  However, once you harmonize and enrich the data, a clearer picture surfaces, enabling better decision-making.  This graphic is representative of other scenarios we see in most organizations. Simply replace the customer name with duplicate part numbers or vendors, and you can see how companies miss out on purchase discounts or carry more inventory than needed.

 

Data and Technology is Key

As a next-generation data mastering platform, Tamr uses patented processes to integrate machine learning with human feedback to continuously clean and deliver accurate data across your business.  

Southwire is an SAP customer using Tamr to harmonize and master customer data across multiple acquisitions.  Edgar Garcia, senior vice president of digital transformation at Southwire, stated “We’ve been using SAP solutions since 2012 and, as we are trying to get these acquired companies onto our existing SAP technologies, there’s a lag in data consistency. By using Tamr, by the time the companies we’ve acquired are ready to migrate to the solutions, a big portion of the data cleanup will be done and that’s a huge win for us.”  

This is a great collaborative example highlighting how an organization can manage its customers across multiple legacy systems, providing visibility into spend and service history while, in parallel, cleansing and mastering data for the ultimate migration into SAP S/4 HANA.

Toyota Motors Europe, as another example, benefits from Tamr by aggregating data from multiple country-oriented source systems. As a result, not only can they enable a better consumer experience but they also gain marketing and sales efficiency across the region. Regardless of location, a customer now has a seamless relationship for sales and service. With centrally-enriched data, companies can now enhance their source SAP systems while driving direct customer applications and services in parallel.   

So What’s Next?

Two things are clear:

  • Better systems, like SAP S/4 HANA, enable more effective and efficient processes, and
  • Processes utilizing accurate and harmonized data with Tamr provide more impactful outcomes 

As we’ve seen with Southwire, Toyota, and scores of others, it is the combination of the technology and data that have the most significant influence on your business.  Now is the time to consider how your processes and data are impacting your customer’s experience and your bottom line.  And as an SAP customer, you can benefit from the “Intelligent Enterprise” while you address your data quality in parallel. 

Ask yourself these questions: is your most valuable asset (customer, supplier, and material data) being used effectively by your operational systems? Or more specifically, is your company one that is sending me two to three mailers this week?

Stay tuned for upcoming posts where I’ll highlight specific customer success stories.