Second of a two-part Guest Contributor series.
In an earlier article, Allan Coulter of IBM explained the rationale for clean core and the approach enabled through IBM, SAP, and ecosystem solutions like Syniti. Here Coulter is joined by Rex Ahlstrom, Syniti Chief Technology Officer, to dig deeper into the role of data as an integral part of clean core solution and how to rethink its value to the overall intelligent transformation journey.
Historically, data has been seen largely as a technical consideration with a focus on object-based data quality, technical “lift-and-shift” migration for aligning the target attributes to support the transactional execution in SAP, or transactional integrity through master data management (MDM) solutions.
The reality, however, is that data is a business problem.
The critical nature of this can’t be underestimated. As most organizations have experienced, many post-go-live migration challenges result from data integrity issues. That’s why companies like IBM trust Syniti solutions to turn this problem into an opportunity for growth.
Fast forward to today, where we constantly hear that data is the “new oil,” the most important commodity in our client organizations. As a result, we see a new focus on transforming data from a by-product of transactional excellence into one that powers the shift to the intelligent enterprise. The IBM Clean Core offering emphasizes code and data modernization to make SAP solutions simpler and smarter through data-driven AI insights. Embedded in our philosophy and approach—backed up by IBM and Syniti software solutions—is the ability to solve data quality and relevance challenges as part of the Clean Core approach for SAP implementations.
The Shift to Intelligence
As a leader in AI and advanced analytics, IBM has seen the benefits of moving from traditional ERP approaches to Intelligent Enterprise solutions–redefining the user experience in the shift from manual to digital (intelligent workflow) processes.
Identifying data catalogues and knowledge graphs are foundational to enabling this AI transformation. However, one of the biggest hurdles in this shift is that the insights aren’t trusted because of low-quality data.
To achieve optimal insights, we needed a higher emphasis on both data quality and data standardization across the data footprint, shifting to a more unified data model approach.
Data quality isn’t just about data deduplication. Instead, focus on data consistency, true data quality, and what’s needed to help improve business outcomes. There’s tremendous value in getting the data right. It’s not just for migration processes; it’s key to achieving actual business benefits and goals.
Getting It Right Matters
Accelerating intelligent enterprise transformation, driving continuous innovation, and achieving business outcomes must start with a clean and quality data foundation. Understanding the quality state and completeness of data prior to the move to, say, SAP S/4HANA® is key to a successful transformation effort. In addition, rightsizing data will help optimize performance and potentially reduce spend on needed cloud infrastructure.
Typically, if the project is approached as a technical exercise, you get potentially a team focused on a technical solution. They may use an Extract, Transform and Load (ETL) tool. The problem is that all the knowledge and learning is buried in the ETL. It’s not reusable in any way; there’s no documentation for it. You’re basically in the same state as you were before you migrated–and none of that investment is being carried forward.
It’s a missed opportunity. Even if you are not ready for AI just yet, this is the best time to prepare your data for the future.
Transform Digital Transformation
Syniti and IBM recently announced the IBM Data Readiness Assessment with Syniti Knowledge Platform to help accelerate digital transformation for their joint customers preparing to transition to SAP S/4HANA. Through better data quality assessment, conversion, process optimization, and code/infrastructure modernization, this solution helps advance the goal of accelerating digital transformations and driving continuous innovation by beginning with a clean and quality data foundation.
The offering enables joint customers to size the services and time required and assist with right-sizing data to optimize performance and possibly lower the budget spent on needed cloud infrastructure. Joint customers benefit from one platform that helps accelerate projects, even those already in process, and that reduces project risk.
The IBM Data Readiness Assessment with Syniti Knowledge Platform[1] is an end-to-end, comprehensive solution that reuses all the content and rules generated within the platform to help accelerate and automate the migration. This unique solution connects data quality to true business outcomes using hundreds of pre-built data quality reports and dashboards that identify cost savings, cash flow, and P&L improvements.
Next Steps
The clean core philosophy is now accepted. IBM has been leading the charge in extending this from Code to Data and Process Modernization. By working in collaboration with ecosystem partners like Syniti, insights be achieved while executing data modernization. Whether starting or amid an Intelligent Enterprise journey, exploring the opportunities provided in modernization of your data will set the right foundation for the shift to intelligence.
Rex Ahlstrom is Chief Technology Officer at Syniti and Allan Coulter is IBM Consulting Global Chief Technology Officer for SAP Services.